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Yu X, Xiang J, Zhang Q, Chen S, Tang W, Li X, Sui Y, Liu W, Kong Q, Guo Y. Corrigendum to Triple-negative breast cancer: predictive model of early recurrence based on MRI features [78 (11) e798-e807]. Clin Radiol 2024; 79:e640. [PMID: 38316571 DOI: 10.1016/j.crad.2024.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Affiliation(s)
- X Yu
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - J Xiang
- Guangdong Women and Children Hospital, No. 13 West Guangyuan Road, Guangzhou, Guangdong, 510010, China
| | - Q Zhang
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - S Chen
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - W Tang
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - X Li
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - Y Sui
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - W Liu
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China.
| | - Q Kong
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510630, China.
| | - Y Guo
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China.
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Tang W, Li L, Li XB, Qiu XT, Ger DL. [The accuracy and feasibility study of freehand pedicle screw insertion for subaxial cervical spine assisted with safe core-referred technique]. Zhonghua Wai Ke Za Zhi 2024; 62:202-209. [PMID: 38291665 DOI: 10.3760/cma.j.cn112139-20230820-00052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Objectives: To construct the "safe core" of the pedicle screw trajectory using CT imaging data of the subaxial cervical spine in adults, and to assess the accuracy and feasibility of the pedicle screw insertion assisted with the "safe core-referred technique" for subaxial cervical spine with a cadaver specimen study. Methods: This is an experimental study. From January 2015 to March 2020,60 adults' CT images data of the cervical spine were collected from the database of the First Affiliated Hospital of Gannan Medical University,and were imported into Mimics 20.0 software. Virtual cervical pedicle trajectory and safe core were constructed according to the self-designed "virtual construction method of pedicle in the subaxial cervical spine". The success rate of the construction and the spatial position data of the virtual safe core of was recorded,including the distance between the safe core and the tangent line of the upper and lower outer edge of Luschka's joint on coronal plane,and the distance between the safe core and the posterior edge of the vertebral body on sagittal plane.The 3.5 mm column was used to simulate the pedicle screw placement,using the safe core as the only hub in pedicle screw trajectory.The length of the anterior pedicle screw trajectory,the interval of the abductive angle of the pedicle screw in axial plane, and the projection area of the entry area on periapical radiograph was calculated.In addition,8 adult cervical cadaver specimens were collected for the pedicle screw insertion experiment.The left side group used the "safe core-referred technique" for pedicle screw insertion,while the right side group used the Abumi method for pedicle screw insertion.The accuracy of pedicle screw placement was verified by CT scan.The difference between the accuracy of subjective judgment based on X-ray monitoring of operator and the actual accuracy of pedicle screw insertion verified by CT scan was compared between the two groups.The chi-square test was used to compare the intergroup data. Results: The total success rate of the virtual construction method for the safe core of the subaxial cervical spine was 97.0% (291/300); The distance between the safe core and the tangent line of the upper and lower outer edge of Luschka's joint on coronal plane was (M(IQR)) 0.91 (0.98) mm (range: 0 to 1.85 mm);The distance between the safe core and the posterior wall on the sagittal plane of the vertebral body was (2.01±0.86) mm (range: 0.67 to 3.53 mm). The distance (anterior pedicle screw trajectory) from the posterior cortex to the central point of the safe core was (11.58±1.00)mm (range: 8.27 to 14.93 mm).The projection area of the entry point on the coronal plane was (36.18±11.67) mm2 (range: 13.38 to 83.11 mm2). Pedicle screw insertion experiment in cervical cadaver specimen showed the rate of intraoperative correction of the pedicle screw trajectory was 7.5% (3/40) in the experimental group and 12.5% (5/40) in the control group (χ2=0.139,P=0.709). The operator 's correct rate of subjective judgment on CT in the stage of pedicle screw trajectory preparation was 100% (40/40) in the experimental group and 82.5% (33/40) in the control group, the difference was statistically significant (χ2=5.638,P=0.018). The actual correct rate of CT verification in the stage of pedicle screw insertion was 100% (40/40) in the experimental group and 90.0% (36/40) in the control group, the difference was statistically significant (χ2=2.368,P=0.124); The operator 's correct rate of subjective judgment in the stage of pedicle screw insertion completion was 100% (83/83) in the experimental group and 92.9% (79/85) in the control group (χ2=4.199,P=0.040). Conclusions: The virtual safe-core of subaxial cervical spine can be use as a reliable anatomical fluoroscopy landmark for freehand pedicle screw insertion."Safe core-referred technique" can improve the accuracy rate of the operator's subjective judgment on the intraoperative fluoroscopy monitoring,and hence improve the accuracy of freehand pedicle screw insertion technology for subaxial cervical spine. And it still needs to be further verified in clinical practice.
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Affiliation(s)
- W Tang
- Department of Orthopaedics,Trauma Center, the First Affiliated Hospital of Gannan Medical University,Ganzhou 341000,China
| | - L Li
- Department of Spine Surgery, 903 Hospital,Jiangyou 621700,China
| | - X B Li
- Center for Information Technology and Network Management,Gannan Medical University,Ganzhou 341000,China
| | - X T Qiu
- Department of Medical Imaging,the First Affiliated Hospital of Gannan Medical University,Ganzhou 341000,China
| | - D L Ger
- Gannan Medical University, Ganzhou 341000, China
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Yau YK, Su Q, Xu Z, Tang W, Ching JYL, Cheung CP, Fung M, Ip M, Chan PKS, Chan FKL, Ng SC. Faecal microbiota transplantation for patients with irritable bowel syndrome: abridged secondary publication. Hong Kong Med J 2024; 30 Suppl 1:34-38. [PMID: 38413211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/29/2024] Open
Affiliation(s)
- Y K Yau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Microbiota I-Center (MagIC), Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, State Key Laboratory of Digestive Disease, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Q Su
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Microbiota I-Center (MagIC), Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, State Key Laboratory of Digestive Disease, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Z Xu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Microbiota I-Center (MagIC), Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, State Key Laboratory of Digestive Disease, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - W Tang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Microbiota I-Center (MagIC), Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, State Key Laboratory of Digestive Disease, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - J Y L Ching
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Microbiota I-Center (MagIC), Hong Kong SAR, China
| | - C P Cheung
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Microbiota I-Center (MagIC), Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, State Key Laboratory of Digestive Disease, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - M Fung
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Microbiota I-Center (MagIC), Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, State Key Laboratory of Digestive Disease, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - M Ip
- Department of Microbiology, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - P K S Chan
- Department of Microbiology, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - F K L Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Microbiota I-Center (MagIC), Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, State Key Laboratory of Digestive Disease, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - S C Ng
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Microbiota I-Center (MagIC), Hong Kong SAR, China
- Li Ka Shing Institute of Health Sciences, State Key Laboratory of Digestive Disease, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR, China
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Abratenko P, Alterkait O, Andrade Aldana D, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barr G, Barrow D, Barrow J, Basque V, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhat A, Bhattacharya M, Bishai M, Blake A, Bogart B, Bolton T, Book JY, Brunetti MB, Camilleri L, Cao Y, Caratelli D, Cavanna F, Cerati G, Chappell A, Chen Y, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Cross R, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Djurcic Z, Dorrill R, Duffy K, Dytman S, Eberly B, Englezos P, Ereditato A, Evans JJ, Fine R, Finnerud OG, Foreman W, Fleming BT, Franco D, Furmanski AP, Gao F, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Gramellini E, Green P, Greenlee H, Gu L, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hilgenberg C, Horton-Smith GA, Imani Z, Irwin B, Ismail M, James C, Ji X, Jo JH, Johnson RA, Jwa YJ, Kalra D, Kamp N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, Leibovitch MB, Lepetic I, Li JY, Li K, Li Y, Lin K, Littlejohn BR, Liu H, Louis WC, Luo X, Mariani C, Marsden D, Marshall J, Martinez N, Martinez Caicedo DA, Martynenko S, Mastbaum A, Mawby I, McConkey N, Meddage V, Micallef J, Miller K, Mogan A, Mohayai T, Mooney M, Moor AF, Moore CD, Mora Lepin L, Moudgalya MM, Mulleriababu S, Naples D, Navrer-Agasson A, Nayak N, Nebot-Guinot M, Nowak J, Oza N, Palamara O, Pallat N, Paolone V, Papadopoulou A, Papavassiliou V, Parkinson HB, Pate SF, Patel N, Pavlovic Z, Piasetzky E, Pophale I, Qian X, Raaf JL, Radeka V, Rafique A, Reggiani-Guzzo M, Ren L, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Rudolf von Rohr C, Safa I, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Snider EL, Soderberg M, Söldner-Rembold S, Spitz J, Stancari M, St John J, Strauss T, Szelc AM, Tang W, Taniuchi N, Terao K, Thorpe C, Torbunov D, Totani D, Toups M, Tsai YT, Tyler J, Uchida MA, Usher T, Viren B, Weber M, Wei H, White AJ, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wu W, Yandel E, Yang T, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. Search for Heavy Neutral Leptons in Electron-Positron and Neutral-Pion Final States with the MicroBooNE Detector. Phys Rev Lett 2024; 132:041801. [PMID: 38335355 DOI: 10.1103/physrevlett.132.041801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 11/30/2023] [Indexed: 02/12/2024]
Abstract
We present the first search for heavy neutral leptons (HNLs) decaying into νe^{+}e^{-} or νπ^{0} final states in a liquid-argon time projection chamber using data collected with the MicroBooNE detector. The data were recorded synchronously with the NuMI neutrino beam from Fermilab's main injector corresponding to a total exposure of 7.01×10^{20} protons on target. We set upper limits at the 90% confidence level on the mixing parameter |U_{μ4}|^{2} in the mass ranges 10≤m_{HNL}≤150 MeV for the νe^{+}e^{-} channel and 150≤m_{HNL}≤245 MeV for the νπ^{0} channel, assuming |U_{e4}|^{2}=|U_{τ4}|^{2}=0. These limits represent the most stringent constraints in the mass range 35
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - O Alterkait
- Tufts University, Medford, Massachusetts 02155, USA
| | - D Andrade Aldana
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | - A Ashkenazi
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - D Barrow
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - J Barrow
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - V Basque
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | | | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
- Michigan State University, East Lansing, Michigan 48824, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - A Bhat
- University of Chicago, Chicago, Illinois 60637, USA
| | - M Bhattacharya
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - B Bogart
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - M B Brunetti
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - Y Cao
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - D Caratelli
- University of California, Santa Barbara, California 93106, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Chappell
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - Y Chen
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | | | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - R Cross
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- Universität Bern, Bern CH-3012, Switzerland
| | - Z Djurcic
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | - P Englezos
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - A Ereditato
- University of Chicago, Chicago, Illinois 60637, USA
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O G Finnerud
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - W Foreman
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - B T Fleming
- University of Chicago, Chicago, Illinois 60637, USA
| | - D Franco
- University of Chicago, Chicago, Illinois 60637, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - F Gao
- University of California, Santa Barbara, California 93106, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - E Gramellini
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Green
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Gu
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- University of Chicago, Chicago, Illinois 60637, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - Z Imani
- Tufts University, Medford, Massachusetts 02155, USA
| | - B Irwin
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - M Ismail
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Nankai University, Nankai District, Tianjin 300071, China
| | - J H Jo
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - M B Leibovitch
- University of California, Santa Barbara, California 93106, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - J-Y Li
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - H Liu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Viriginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N Martinez
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - S Martynenko
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - I Mawby
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N McConkey
- University College London, London WC1E 6BT, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Micallef
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tufts University, Medford, Massachusetts 02155, USA
| | - K Miller
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Mogan
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
- Indiana University, Bloomington, Indiana 47405, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - M M Moudgalya
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | | | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - N Nayak
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - N Oza
- Columbia University, New York, New York 10027, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - N Pallat
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - H B Parkinson
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Piasetzky
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - I Pophale
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Rafique
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - M Reggiani-Guzzo
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Ross-Lonergan
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | | | - I Safa
- Columbia University, New York, New York 10027, USA
| | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - N Taniuchi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - D Torbunov
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Tyler
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - A J White
- University of Chicago, Chicago, Illinois 60637, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - W Wu
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L E Yates
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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Tang W, Zhou LJ, Zhang WQ, Jia YJ, Ge MW, Hu FH, Chen HL. Association of radiotherapy for prostate cancer and second primary colorectal cancer: a US population-based analysis. Tech Coloproctol 2023; 28:14. [PMID: 38095784 DOI: 10.1007/s10151-023-02883-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 11/17/2023] [Indexed: 12/18/2023]
Abstract
BACKGROUND Radiotherapy (RT) is a common treatment for prostate cancer, yet the risk of second primary colorectal cancer (SPCRC) in patients with prostate cancer undergoing RT has not been adequately studied. METHODS This study employed a population-based cohort design using the US Surveillance, Epidemiology, and End Results (SEER) database to identify individuals diagnosed between January 1975 and December 2015. The cumulative incidence of SPCRC was estimated using Fine-Gray competing risk regression. Poisson regression analysis was used to estimate the risk associated with RT. Survival outcomes of patients with SPCRC were evaluated using the Kaplan-Meier method. RESULTS A total of 287,607 patients diagnosed with prostate cancer were identified. The cumulative incidences were higher in patients who did not receive RT (2.00%) compared to those who underwent RT (2.47%) after 25 years. After adjustment for multiple variables, RT was associated with an increased risk of developing combined SPCRC (adjusted HR 1.590). Additionally, the overall survival was significantly lower in patients who developed colorectal cancer after receiving RT as compared to those who did not receive RT. CONCLUSION These findings underscore the need for diligent long-term monitoring and effective management strategies to detect SPCRC in patients treated with RT for prostate cancer.
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Affiliation(s)
- W Tang
- Medical School, Nantong University, Nantong, China
| | - L-J Zhou
- Nursing Department, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, China
| | - W-Q Zhang
- Medical School, Nantong University, Nantong, China
| | - Y-J Jia
- Medical School, Nantong University, Nantong, China
| | - M-W Ge
- Medical School, Nantong University, Nantong, China
| | - F-H Hu
- Medical School, Nantong University, Nantong, China
| | - H-L Chen
- School of Public Health, Nantong University, 9#Seyuan Road, Nantong, 226000, Jiangsu, China.
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Chen S, Sui Y, Ding S, Chen C, Liu C, Zhong Z, Liang Y, Kong Q, Tang W, Guo Y. A simple and convenient model combining multiparametric MRI and clinical features to predict tumour-infiltrating lymphocytes in breast cancer. Clin Radiol 2023; 78:e1065-e1074. [PMID: 37813758 DOI: 10.1016/j.crad.2023.08.029] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 08/30/2023] [Accepted: 08/31/2023] [Indexed: 10/11/2023]
Abstract
AIM To develop a simple and convenient method based on multiparametric magnetic resonance imaging (MRI) and clinical features to non-invasively predict tumour-infiltrating lymphocytes (TILs) in breast cancer (BC) and to explore the relationship between TIL levels and disease-free survival (DFS). MATERIALS AND METHODS A total of 172 BC patients were enrolled between November 2017 and June 2021 in this retrospective study. The patients were divided into high (≥10%) and low (<10%) TIL groups. Clinicopathological data were collected. MRI features were reviewed by two radiologists. Predictors associated with TILs were determined by using multivariable logistic regression analyses. Kaplan-Meier survival curves based on TIL levels were used to estimate DFS. RESULTS A total of 102 patients with low TILs and 70 patients with high TILs were included in the study. Tumour size (odds ratio [OR], 1.040; 95% confidence interval [CI]: 1.006, 1.075; p=0.020), apparent diffusion coefficient (ADC; OR, 1.003; 95% CI: 1.001, 1.005; p=0.015), clinical axillary lymph node status (CALNS; OR, 3.222; 95% CI: 1.372,7.568; p=0.007), and enhancement pattern (OR, 0.284; 95% CI: 0.143, 0.563; p<0.001) were independently associated with TIL levels. These features were used in the ALSE model (where A is ADC, L is CALNS, S is size, and E is enhancement pattern). High TILs were associated with better DFS (p=0.016). CONCLUSION The ALSE model derived from multiparametric MRI and clinical features could non-invasively predict TIL levels in BC, and high TILs were associated with longer DFS, especially in human epidermal growth factor receptor 2 (HER2)-positive BC and triple-negative BC (TNBC).
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Affiliation(s)
- S Chen
- Department of Radiology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, 510180, China
| | - Y Sui
- Department of Radiology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, 510180, China; Department of Radiology, Guangzhou Women and Children's Medical Center, Guangzhou, 510005, China
| | - S Ding
- Department of Radiology, Liuzhou People's Hospital, Guangxi Medical University, Liuzhou, 545006, China
| | - C Chen
- Department of Pathology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, 510180, China
| | - C Liu
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China
| | - Z Zhong
- Department of Radiology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, 510180, China
| | - Y Liang
- Department of Pathology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, 510180, China
| | - Q Kong
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510630, China.
| | - W Tang
- Department of Radiology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, 510180, China.
| | - Y Guo
- Department of Radiology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, 510180, China.
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Peng Q, Wu N, Huang Y, Zhao SJ, Tang W, Liang M, Ran YL, Xiao T, Yang L, Liang X. [Diagnostic values of conventional tumor markers and their combination with chest CT for patients with stageⅠA lung cancer]. Zhonghua Zhong Liu Za Zhi 2023; 45:934-941. [PMID: 37968078 DOI: 10.3760/cma.j.cn112152-20220208-00082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 11/17/2023]
Abstract
Objective: To investigate the diagnostic efficiency of conventional serum tumor markers and their combination with chest CT for stage ⅠA lung cancer. Methods: A total of 1 155 patients with stage ⅠA lung cancer and 200 patients with benign lung lesions (confirmed by surgery) treated at the Cancer Hospital, Chinese Academy of Medical Sciences from January 2016 to October 2020 were retrospectively enrolled in this study. Six conventional serum tumor markers [carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA125), squamous cell carcinoma associated antigen (SCCA), cytokeratin 19 fragment (CYFRA21-1), neuron-specific enolase (NSE), and gastrin-releasing peptide precursor (ProGRP)] and chest thin-slice CT were performed on all patients one month before surgery. Pathology was taken as the gold standard to analyze the difference of positivity rates of tumor markers between the lung cancer group and the benign group, the moderate/poor differentiation group and the well differentiation group, the adenocarcinoma group and the squamous cell carcinoma group, the lepidic and non-lepidic predominant adenocarcinoma groups, the solid nodule group and the subsolid nodule group based on thin-slice CT, and subgroups of ⅠA1 to ⅠA3 lung cancers. The diagnostic performance of tumor markers and tumor markers combined with chest CT was analyzed using the receiver operating characteristic curve. Results: The positivity rates of six serum tumor markers in the lung cancer group and the benign group were 2.32%-20.08% and 0-13.64%, respectively; only the SCCA positivity rate in the lung cancer group was higher than that in the benign group (10.81% and 0, P=0.022). There were no significant differences in the positivity rates of other serum tumor markers between the two groups (all P>0.05). The combined detection of six tumor markers showed that the positivity rate of the lung cancer group was higher than that of the benign group (40.93% and 18.18%, P=0.004), and the positivity rate of the adenocarcinoma group was lower than that of the squamous cell carcinoma group (35.66% and 47.41%, P=0.045). The positivity rates in the poorly differentiated group and moderately differentiated group were higher than that in the well differentiated group (46.48%, 43.75% and 22.73%, P=0.025). The positivity rate in the non-lepidic adenocarcinoma group was higher than that in lepidic adenocarcinoma group (39.51% and 21.74%, P=0.001). The positivity rate of subsolid nodules was lower than that of solid nodules (30.01% vs 58.71%, P=0.038), and the positivity rates of stageⅠA1, ⅠA2 and ⅠA3 lung cancers were 33.33%, 48.96% and 69.23%, respectively, showing an increasing trend (P=0.005). The sensitivity and specificity of the combined detection of six tumor markers in the diagnosis of stage ⅠA lung cancer were 74.00% and 56.30%, respectively, and the area under the curve (AUC) was 0.541. The sensitivity and specificity of the combined detection of six serum tumor markers with CT in the diagnosis of stage ⅠA lung cancer were 83.0% and 78.3%, respectively, and the AUC was 0.721. Conclusions: For stage ⅠA lung cancer, the positivity rates of commonly used clinical tumor markers are generally low. The combined detection of six markers can increase the positivity rate. The positivity rate of markers tends to be higher in poorly differentiated lung cancer, squamous cell carcinoma, or solid nodules. Tumor markers combined with thin-slice CT showed limited improvement in diagnostic efficiency for early lung cancer.
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Affiliation(s)
- Q Peng
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - N Wu
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Y Huang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - S J Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - W Tang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - M Liang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Y L Ran
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - T Xiao
- State Key Laboratory of Molecular Oncology, Beijing Key Laboratory for Carcinogenesis and Cancer Prevention, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - L Yang
- Department of Pathology Diagnosis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - X Liang
- Medical Statistics Office, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
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Yu X, Xiang J, Zhang Q, Chen S, Tang W, Li X, Sui Y, Liu W, Kong Q, Guo Y. Triple-negative breast cancer: predictive model of early recurrence based on MRI features. Clin Radiol 2023; 78:e798-e807. [PMID: 37596179 DOI: 10.1016/j.crad.2023.07.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 07/13/2023] [Accepted: 07/18/2023] [Indexed: 08/20/2023]
Abstract
AIM To develop an integrated model based on preoperative magnetic resonance imaging (MRI) features for predicting early recurrence in patients with triple-negative breast cancer (TNBC). MATERIALS AND METHODS Women with TNBC who underwent breast MRI and surgery between 2009 and 2019 were evaluated retrospectively. Two breast radiologists reviewed MRI images independently based on the Breast Imaging Reporting and Data System Lexicon (BI-RADS), and classified the breast oedema scores on T2-weighted imaging (WI) as no oedema, peritumoural oedema, prepectoral oedema, or subcutaneous oedema. The relationship between disease-free survival (DFS) and MRI features was analysed by Cox regression, and a nomogram model was generated based on the results. RESULTS 150 patients with TNBC were included and divided into a training cohort (n=78) and validation cohort (n=72). MRI features including subcutaneous oedema and rim enhancement showed a tendency to worsen DFS in univariate analysis. Multivariate analysis showed that subcutaneous oedema (p=0.049, HR [95% confidence interval {CI} = 8.24 [1.01-67.52]) and rim enhancement (p=0.016, HR [95% CI] = 4.38 [1.32-14.54]) were independent predictors for DFS. In the nomogram, the areas under the curves (AUCs) of the training cohort was 0.808, and that of the validation cohort was 0.875. CONCLUSION The presence of subcutaneous oedema or rim enhancement on preoperative breast MRI was shown to be a good predictor of poor survival outcomes in patients with TNBC.
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Affiliation(s)
- X Yu
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - J Xiang
- Guangdong Women and Children Hospital, No. 13 West Guangyuan Road, Guangzhou, Guangdong, 510010, China
| | - Q Zhang
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - S Chen
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - W Tang
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - X Li
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - Y Sui
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - W Liu
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China.
| | - Q Kong
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510630, China.
| | - Y Guo
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China.
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Tang W, Guo Q, Chen J, Wu Q, Zhang T, Wang Q, Zhang X, Xie P. The Predictive Value of Circulating Exosomal PD-L1 in Cervical Cancer Immunotherapy. Int J Radiat Oncol Biol Phys 2023; 117:e548-e549. [PMID: 37785688 DOI: 10.1016/j.ijrobp.2023.06.1851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Programmed death ligand 1 (PD-L1) expression was wildly used as a predictor of immune Check-Point Inhibitors (ICIs) efficiency. However, emerging results showed that PD-L1 was of great heterogeneity in sampling time and site. Recently, some studies found that exosomal PD-L1(ExoPD-L1) was related to ICIs response. In this study, we aimed to explore the predictive value of ExoPD-L1 in ICIs treatment of cervical cancer (CC) for the first time. MATERIALS/METHODS A total of 40 primarily diagnosed CC patients who accepted radical radiotherapy (RT) from March 2021 to October 2022 were included. The consecutive tumor sample were collected before and during RT. Another 37 advanced CC patients who accepted ICIs combination therapy from June 2020 to October 2022 were enrolled in this study. Blood samples were collected from each participant before and during treatment. Exosomes were derived by differential centrifugation, which was further identified by Western blot (WB) (CD9/TSG101/Calnexin), transmission electron microscope analysis and nanoparticle tracking analysis. ExoPD-L1 detection was conducted by enzyme-linked immuno-sorbent assay (ELISA). The knockout of PD-L1 was conducted via CRISPR/Cas9 assay and the overexpress of PD-L1 was conducted by lentiviral transfection. CD8+ T cells were extracted from murine spleen by CD8+ T Cell Isolation Kit. Immune cells and cytokines markers were detected by multicolor flow cytometry. RESULTS The consecutive detection of PD-L1 showed a dynamic change during RT. Compared with the level before RT, PD-L1 expression elevated in most patients (87.5%, 35/40) after RT. And the responders (n = 18) had elevated ExoPD-L1 level at the first two circles in the ICIs combination therapy (P<0.001). Whereas the level of pre-treatment ExoPD-L1 couldn't stratified clinical responders and non-responders (P = 0.181). The median follow-up time was 14.13 months. The mPFS in increased group vs. decreased group: not reach vs.11.02 months (P = 0.025, HR: 0.218, 0.052-0.913). Continuous blood sampling of mice models also found that effective therapeutic intervention could increase ExoPD-L1 in the early stage. The combination of exosome inhibitor GW4869 and anti-PD-1 further inhibited tumor growth. Mice were injected with external ExoPD-L1OE and ExoPD-L1KO. The results showed that ExoPD-L1OE suppressed body immunity and promoted tumor growth. The results of flow cytometry showed that ExoPD-L1OE inhibited CD8+ T cells from releasing interferon-and granzyme B. And ExoPD-L1OE also suppressed the CD8+ T cells proliferation in murine spleen. The coculture of CD8+ T cells and exosomes in vitro also confirmed the above conclusion. CONCLUSION Compared with unstable and impressionable tumoral PD-L1, ExoPD-L1 seems to be better predictor for the efficacy of immunotherapy in CC, which was with easy accessibility and continuation. Exosome PD-L1 played an immunosuppressive role by inhibiting the proliferation and functional factor release of CD8+ T cell.
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Affiliation(s)
- W Tang
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Q Guo
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - J Chen
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Q Wu
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - T Zhang
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Q Wang
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - X Zhang
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - P Xie
- Shandong Cancer Hospital and Institute, Jinan, Shandong, China
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Wang S, Tang W, Luo H, Jin F. Incidence and Risk Factors for Brain Metastases in Patients with Lung Cancer: A Systematic Review and Meta-Analysis. Int J Radiat Oncol Biol Phys 2023; 117:e71-e72. [PMID: 37786078 DOI: 10.1016/j.ijrobp.2023.06.804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Brain metastases (BM) are a very common metastatic site in lung cancer, but the exact rate of metastasis is still controversial. Risk factors for BM development are also largely lacking, hampering personalized treatment strategies. This study aimed to identify the incidence and possible risk factors for BM in lung cancer. MATERIALS/METHODS A systematic review, based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guide-lines, was conducted using PubMed, Medline databases and Cochrane Library databases from inception until February 2023. Two investigators independently searched and selected literature, included in randomized controlled trials and cohort studies. Heterogeneity was assessed using the χ2 test and the I2 statistic. Significant heterogeneity was indicated by P <0.05 in Cochrane Q tests and a ratio greater than 40% in I2 statistics. The review is registered on PROSPERO, number: CRD42022370173. RESULTS Forty-nine studies were included in the meta-analysis. The results showed that the incidence rate of BM in non-small cell lung cancer (NSCLC) was 0.24 (95% confidence interval [CI]: 0.23-0.25; I2 = 97.1%). The incidence rate in early NSCLC was 0.11 (95% CI: 0.10-0.13), locally advanced NSCLC was 0.32 (95% CI: 0.29-0.34), and advanced NSCLC was 0.37 (95% CI: 0.35-0.38). Lung adenocarcinoma was more prone to BM in NSCLC (risk ratio [RR] = 3.59, 95% CI: 1.97-6.54; P<0.001). The BM rate of NSCLC with EGFR mutation was also higher (hazard ratio [HR] = 1.49, 95% CI: 1.14-1.94; P = 0.004). Sex and smoking had no significant effect on the incidence of BM in NSCLC. Prophylactic Cranial Irradiation (PCI) could significantly reduce BM in NSCLC (HR = 0.36, 95% CI: 0.23-0.56; P<0.001), but chemotherapy had no obvious effect on decreasing the rate of BM (HR = 0.91, 95% CI: 0.54-1.54; P = 0.73). The incidence rate of BM in small cell lung cancer (SCLC) was 0.28 (95% CI: 0.27-0.30; I2 = 95.9%), and 0.23 (95% CI: 0.20-0.25) in the limited-stage SCLC. Older age (≥65) (HR = 0.70, 95% CI: 0.54-0.92; P = 0.01) were associated with less BM in SCLC. A higher T stage (≥T3) (HR = 1.72, 95% CI: 1.16-2.56; P = 0.007) was a significant risk factor for BM, while sex, smoking dose were not. PCI could also significantly decreased BM in SCLC (HR = 0.47, 95% CI: 0.38-0.58; P<0.001). CONCLUSION This study is the first meta-analysis of BM incidence rate in lung cancer, and further explores the factors affecting BM, providing some suggestions for clinical decision-making of BM prevention in patients with lung cancer.
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Affiliation(s)
- S Wang
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - W Tang
- Department of Rehabilitation, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - H Luo
- Department of Radiation Oncology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, China
| | - F Jin
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
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Abratenko P, Alterkait O, Andrade Aldana D, Anthony J, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barr G, Barrow J, Basque V, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhattacharya M, Bishai M, Blake A, Bogart B, Bolton T, Book JY, Camilleri L, Caratelli D, Caro Terrazas I, Cavanna F, Cerati G, Chen Y, Cohen EO, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Djurcic Z, Dorrill R, Duffy K, Dytman S, Eberly B, Ereditato A, Evans JJ, Fine R, Finnerud OG, Foreman W, Fleming BT, Foppiani N, Franco D, Furmanski AP, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Goodwin O, Gramellini E, Green P, Greenlee H, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hicks R, Hilgenberg C, Horton-Smith GA, Irwin B, Itay R, James C, Ji X, Jiang L, Jo JH, Johnson RA, Jwa YJ, Kalra D, Kamp N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, Leibovitch MB, Lepetic I, Li JY, Li K, Li Y, Lin K, Littlejohn BR, Louis WC, Luo X, Mariani C, Marsden D, Marshall J, Martinez N, Martinez Caicedo DA, Mason K, Mastbaum A, McConkey N, Meddage V, Miller K, Mills J, Mogan A, Mohayai T, Mooney M, Moor AF, Moore CD, Mora Lepin L, Mousseau J, Mulleriababu S, Naples D, Navrer-Agasson A, Nayak N, Nebot-Guinot M, Nowak J, Oza N, Palamara O, Pallat N, Paolone V, Papadopoulou A, Papavassiliou V, Parkinson HB, Pate SF, Patel N, Pavlovic Z, Piasetzky E, Ponce-Pinto ID, Pophale I, Prince S, Qian X, Raaf JL, Radeka V, Rafique A, Reggiani-Guzzo M, Ren L, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Rudolf von Rohr C, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Snider EL, Soderberg M, Söldner-Rembold S, Spitz J, Stancari M, John JS, Strauss T, Sword-Fehlberg S, Szelc AM, Tang W, Taniuchi N, Terao K, Thorpe C, Torbunov D, Totani D, Toups M, Tsai YT, Tyler J, Uchida MA, Usher T, Viren B, Weber M, Wei H, White AJ, Williams Z, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wright N, Wu W, Yandel E, Yang T, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. First Double-Differential Measurement of Kinematic Imbalance in Neutrino Interactions with the MicroBooNE Detector. Phys Rev Lett 2023; 131:101802. [PMID: 37739352 DOI: 10.1103/physrevlett.131.101802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 05/09/2023] [Accepted: 07/14/2023] [Indexed: 09/24/2023]
Abstract
We report the first measurement of flux-integrated double-differential quasielasticlike neutrino-argon cross sections, which have been made using the Booster Neutrino Beam and the MicroBooNE detector at Fermi National Accelerator Laboratory. The data are presented as a function of kinematic imbalance variables which are sensitive to nuclear ground-state distributions and hadronic reinteraction processes. We find that the measured cross sections in different phase-space regions are sensitive to different nuclear effects. Therefore, they enable the impact of specific nuclear effects on the neutrino-nucleus interaction to be isolated more completely than was possible using previous single-differential cross section measurements. Our results provide precision data to help test and improve neutrino-nucleus interaction models. They further support ongoing neutrino-oscillation studies by establishing phase-space regions where precise reaction modeling has already been achieved.
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - O Alterkait
- Tufts University, Medford, Massachusetts 02155, USA
| | - D Andrade Aldana
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - J Anthony
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | - A Ashkenazi
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - J Barrow
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - V Basque
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - O Benevides Rodrigues
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
- Syracuse University, Syracuse, New York 13244, USA
| | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - M Bhattacharya
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - B Bogart
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - D Caratelli
- University of California, Santa Barbara, California 93106, USA
| | - I Caro Terrazas
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y Chen
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - E O Cohen
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - L Cooper-Troendle
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- Universität Bern, Bern CH-3012, Switzerland
| | - Z Djurcic
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | | | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O G Finnerud
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - W Foreman
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - B T Fleming
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - N Foppiani
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - D Franco
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - O Goodwin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - E Gramellini
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - P Green
- The University of Manchester, Manchester M13 9PL, United Kingdom
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - R Hicks
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - B Irwin
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - R Itay
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - L Jiang
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - J H Jo
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - M B Leibovitch
- University of California, Santa Barbara, California 93106, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - J-Y Li
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N Martinez
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - K Mason
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - N McConkey
- The University of Manchester, Manchester M13 9PL, United Kingdom
- University College London, London WC1E 6BT, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - K Miller
- University of Chicago, Chicago, Illinois 60637, USA
| | - J Mills
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mogan
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Mousseau
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | | | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - N Nayak
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - N Oza
- Columbia University, New York, New York 10027, USA
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - N Pallat
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - H B Parkinson
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Piasetzky
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - I D Ponce-Pinto
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - I Pophale
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - S Prince
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Rafique
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - M Reggiani-Guzzo
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Ross-Lonergan
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | | | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S Sword-Fehlberg
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - N Taniuchi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - D Torbunov
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Tyler
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - A J White
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Z Williams
- University of Texas, Arlington, Texas 76019, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - N Wright
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - W Wu
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L E Yates
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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Tang W, Xie G, Li J, Tan W, Yi R, Yang L, Zhang L, Deng J, Zhang Y, Li K. Body composition parameters correlate with the endoscopic severity in Crohn's disease patients treated with infliximab. Front Nutr 2023; 10:1251448. [PMID: 37674885 PMCID: PMC10478258 DOI: 10.3389/fnut.2023.1251448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Accepted: 08/07/2023] [Indexed: 09/08/2023] Open
Abstract
Background The disease activity status and behavior of Crohn's disease (CD) can reflect the severity of the disease, and changes in body composition are common in CD patients. Aims The aim of this study was to investigate the relationship between body composition parameters and disease severity in CD patients treated with infliximab (IFX). Methods Patients with CD assessed with the simple endoscopic score (SES-CD) and were treated with IFX were retrospectively collected, and body composition parameters at the level of the 3rd lumbar vertebrae were calculated from computed tomography (CT) scans of the patients. The correlation of patients' body composition parameters with disease activity status and disease behavior was analyzed, and the diagnostic value of the relevant parameters was assessed using receiver operating characteristic (ROC) curves. Results A total of 106 patients were included in this study. There were significant differences in the subcutaneous adiposity index (SAI) (p = 0.010), the visceral adiposity index (VAI) (p < 0.001), the skeletal muscle mass index (SMI) (p < 0.001), and decreased skeletal muscle mass (p < 0.001) among patients with different activity status. After Spearman and multivariate regression analysis, SAI (p = 0.006 and p = 0.001), VAI (p < 0.001 and p < 0.001), and SMI (p < 0.001and p = 0.007) were identified as independent correlates of disease activity status (both disease activity and moderate-to-severe activity), with disease activity status independently positively correlated with SAI and SMI and independently negatively correlated with VAI. In determining the disease activity and moderate-to-severe activity status, SMI performed best relative to SAI and VAI, with areas under the ROC curve of 0.865 and 0.801, respectively. SAI (p = 0.015), SMI (p = 0.011) and decreased skeletal muscle mass (p = 0.027) were significantly different between different disease behavior groups (inflammatory disease behavior group, complex disease behavior group) but were not independent correlates (p > 0.05). Conclusion Body composition parameters of CD patients treated with IFX correlate with the endoscopic disease severity, and SMI can be used as a reliable indicator of disease activity status.
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Affiliation(s)
- Wuli Tang
- Chongqing Medical University, Chongqing, China
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China
- Chongqing School, University of Chinese Academy of Science, Chongqing, China
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Gang Xie
- Department of Radiology, The Third People’s Hospital of Chengdu, Chengdu, China
| | - Junlin Li
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Wei Tan
- Department of Gastroenterology, Chongqing General Hospital, Chongqing, China
| | - Rongqi Yi
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Ling Yang
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Lingqin Zhang
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Jiaxing Deng
- Department of General Medicine, Chongqing General Hospital, Chongqing, China
| | - Yue Zhang
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Kang Li
- Chongqing Medical University, Chongqing, China
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China
- Chongqing School, University of Chinese Academy of Science, Chongqing, China
- Department of Radiology, Chongqing General Hospital, Chongqing, China
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Abratenko P, Andrade Aldana D, Anthony J, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barr G, Barrow J, Basque V, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhattacharya M, Bishai M, Blake A, Bogart B, Bolton T, Book JY, Camilleri L, Caratelli D, Caro Terrazas I, Cavanna F, Cerati G, Chen Y, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Djurcic Z, Dorrill R, Duffy K, Dytman S, Eberly B, Ereditato A, Evans JJ, Fine R, Finnerud OG, Foreman W, Fleming BT, Foppiani N, Franco D, Furmanski AP, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Goodwin O, Gramellini E, Green P, Greenlee H, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hicks R, Hilgenberg C, Horton-Smith GA, Irwin B, Itay R, James C, Ji X, Jiang L, Jo JH, Johnson RA, Jwa YJ, Kalra D, Kamp N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, Leibovitch MB, Lepetic I, Li JY, Li K, Li Y, Lin K, Littlejohn BR, Louis WC, Luo X, Mariani C, Marsden D, Marshall J, Martinez N, Martinez Caicedo DA, Mason K, Mastbaum A, McConkey N, Meddage V, Miller K, Mills J, Mogan A, Mohayai T, Mooney M, Moor AF, Moore CD, Mora Lepin L, Mousseau J, Mulleriababu S, Naples D, Navrer-Agasson A, Nayak N, Nebot-Guinot M, Nowak J, Nunes M, Oza N, Palamara O, Pallat N, Paolone V, Papadopoulou A, Papavassiliou V, Parkinson HB, Pate SF, Patel N, Pavlovic Z, Piasetzky E, Ponce-Pinto ID, Pophale I, Prince S, Qian X, Raaf JL, Radeka V, Rafique A, Reggiani-Guzzo M, Ren L, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Rudolf von Rohr C, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Snider EL, Soderberg M, Söldner-Rembold S, Spitz J, Stancari M, John JS, Strauss T, Sword-Fehlberg S, Szelc AM, Tang W, Taniuchi N, Terao K, Thorpe C, Torbunov D, Totani D, Toups M, Tsai YT, Tyler J, Uchida MA, Usher T, Viren B, Weber M, Wei H, White AJ, Williams Z, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wright N, Wu W, Yandel E, Yang T, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. First Measurement of Quasielastic Λ Baryon Production in Muon Antineutrino Interactions in the MicroBooNE Detector. Phys Rev Lett 2023; 130:231802. [PMID: 37354393 DOI: 10.1103/physrevlett.130.231802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 04/07/2023] [Accepted: 04/28/2023] [Indexed: 06/26/2023]
Abstract
We present the first measurement of the cross section of Cabibbo-suppressed Λ baryon production, using data collected with the MicroBooNE detector when exposed to the neutrinos from the main injector beam at the Fermi National Accelerator Laboratory. The data analyzed correspond to 2.2×10^{20} protons on target running in neutrino mode, and 4.9×10^{20} protons on target running in anti-neutrino mode. An automated selection is combined with hand scanning, with the former identifying five candidate Λ production events when the signal was unblinded, consistent with the GENIE prediction of 5.3±1.1 events. Several scanners were employed, selecting between three and five events, compared with a prediction from a blinded Monte Carlo simulation study of 3.7±1.0 events. Restricting the phase space to only include Λ baryons that decay above MicroBooNE's detection thresholds, we obtain a flux averaged cross section of 2.0_{-1.7}^{+2.2}×10^{-40} cm^{2}/Ar, where statistical and systematic uncertainties are combined.
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - D Andrade Aldana
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - J Anthony
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | - A Ashkenazi
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - J Barrow
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - V Basque
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | | | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - M Bhattacharya
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - B Bogart
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - D Caratelli
- University of California, Santa Barbara, California 93106, USA
| | - I Caro Terrazas
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y Chen
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - L Cooper-Troendle
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- Universität Bern, Bern CH-3012, Switzerland
| | - Z Djurcic
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | | | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O G Finnerud
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - W Foreman
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - B T Fleming
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - N Foppiani
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - D Franco
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - O Goodwin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - E Gramellini
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - P Green
- The University of Manchester, Manchester M13 9PL, United Kingdom
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - R Hicks
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - B Irwin
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - R Itay
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - L Jiang
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - J H Jo
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - M B Leibovitch
- University of California, Santa Barbara, California 93106, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - J-Y Li
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N Martinez
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - K Mason
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - N McConkey
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - K Miller
- University of Chicago, Chicago, Illinois 60637, USA
| | - J Mills
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mogan
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Mousseau
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | | | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - N Nayak
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - M Nunes
- Syracuse University, Syracuse, New York 13244, USA
| | - N Oza
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - N Pallat
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - H B Parkinson
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Piasetzky
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - I D Ponce-Pinto
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - I Pophale
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - S Prince
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Rafique
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - M Reggiani-Guzzo
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Ross-Lonergan
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | | | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S Sword-Fehlberg
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - N Taniuchi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - D Torbunov
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Tyler
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - A J White
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Z Williams
- University of Texas, Arlington, Texas 76019, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - N Wright
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - W Wu
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L E Yates
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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Zeng W, Zhou SL, Guo JX, Tang W. [Metal artifact reduction and clinical verification in oral and maxillofacial region based on deep learning]. Zhonghua Kou Qiang Yi Xue Za Zhi 2023; 58:542-548. [PMID: 37271998 DOI: 10.3760/cma.j.cn112144-20230302-00067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Objective: To construct a kind of neural network for eliminating the metal artifacts in CT images by training the generative adversarial networks (GAN) model, so as to provide reference for clinical practice. Methods: The CT data of patients treated in the Department of Radiology, West China Hospital of Stomatology, Sichuan University from January 2017 to June 2022 were collected. A total of 1 000 cases of artifact-free CT data and 620 cases of metal artifact CT data were obtained, including 5 types of metal restorative materials, namely, fillings, crowns, titanium plates and screws, orthodontic brackets and metal foreign bodies. Four hundred metal artifact CT data and 1 000 artifact-free CT data were utilized for simulation synthesis, and 1 000 pairs of simulated artifacts and metal images and simulated metal images (200 pairs of each type) were constructed. Under the condition that the data of the five metal artifacts were equal, the entire data set was randomly (computer random) divided into a training set (800 pairs) and a test set (200 pairs). The former was used to train the GAN model, and the latter was used to evaluate the performance of the GAN model. The test set was evaluated quantitatively and the quantitative indexes were root-mean-square error (RMSE) and structural similarity index measure (SSIM). The trained GAN model was employed to eliminate the metal artifacts from the CT data of the remaining 220 clinical cases of metal artifact CT data, and the elimination results were evaluated by two senior attending doctors using the modified LiKert scale. Results: The RMSE values for artifact elimination of fillings, crowns, titanium plates and screws, orthodontic brackets and metal foreign bodies in test set were 0.018±0.004, 0.023±0.007, 0.015±0.003, 0.019±0.004, 0.024±0.008, respectively (F=1.29, P=0.274). The SSIM values were 0.963±0.023, 0.961±0.023, 0.965±0.013, 0.958±0.022, 0.957±0.026, respectively (F=2.22, P=0.069). The intra-group correlation coefficient of 2 evaluators was 0.972. For 220 clinical cases, the overall score of the modified LiKert scale was (3.73±1.13), indicating a satisfactory performance. The scores of modified LiKert scale for fillings, crowns, titanium plates and screws, orthodontic brackets and metal foreign bodies were (3.68±1.13), (3.67±1.16), (3.97±1.03), (3.83±1.14), (3.33±1.12), respectively (F=1.44, P=0.145). Conclusions: The metal artifact reduction GAN model constructed in this study can effectively remove the interference of metal artifacts and improve the image quality.
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Affiliation(s)
- W Zeng
- Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
| | - S L Zhou
- Department of Oral and Maxillofacial Surgery, School of Stomatology, The Fourth Military Medical University & State Key Laboratory of Military Stomatology & National Clinical Research Center for Oral Diseases & Shaanxi Clinical Research Center for Oral Diseases, Xi'an 710032, China
| | - J X Guo
- Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu 610041, China
| | - W Tang
- Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
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Tang W, Zhu D, Wu F, Xu JF, Yang JP, Deng ZP, Chen XB, Papi A, Qu JM. Intravenous N-acetylcysteine in respiratory disease with abnormal mucus secretion. Eur Rev Med Pharmacol Sci 2023; 27:5119-5127. [PMID: 37318485 DOI: 10.26355/eurrev_202306_32628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
OBJECTIVE Evidence for the mucolytic and expectorant efficacy of intravenous (IV) N-acetylcysteine (NAC) is limited. This study aimed to evaluate in a large, multicenter, randomized, controlled, subject, and rater-blinded study whether IV NAC is superior to placebo and non-inferior to ambroxol in improving sputum viscosity and expectoration difficulty. PATIENTS AND METHODS A total of 333 hospitalized subjects from 28 centers in China with respiratory disease (such as acute bronchitis, chronic bronchitis and exacerbations, emphysema, mucoviscidosis, and bronchiectasis) and abnormal mucus secretion were randomly allocated in a 1:1:1 ratio to receive NAC 600 mg, ambroxol hydrochloride 30 mg, or placebo as an IV infusion twice daily for 7 days. Mucolytic and expectorant efficacy was assessed by ordinal categorical 4-point scales and analyzed by stratified and modified Mann-Whitney U statistics. RESULTS NAC showed consistent and statistically significant superiority to placebo and non-inferiority to ambroxol in change from baseline to day 7 in both sputum viscosity scores [mean (SD) difference 0.24 (0.763), p<0.001 vs. placebo] and expectoration difficulty score [mean (SD) difference 0.29 (0.783), p=0.002 vs. placebo]. Safety findings confirm the good tolerability profile of IV NAC reported from previous small studies, and no new safety concerns were identified. CONCLUSIONS This is the first large, robust study of the efficacy of IV NAC in respiratory diseases with abnormal mucus secretion. It provides new evidence for IV NAC administration in this indication in clinical situations where the IV route is preferred.
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Affiliation(s)
- W Tang
- Department of Pulmonary and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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Tang W, Xie G, Wang D, Li T, Ren Y, Li J, Deng J, Li K. Imaging-based assessment of body composition in patients with Crohn's disease: a systematic review. Int J Colorectal Dis 2023; 38:126. [PMID: 37171498 DOI: 10.1007/s00384-023-04413-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/25/2023] [Indexed: 05/13/2023]
Abstract
BACKGROUND AND AIMS Body composition changes in patients with Crohn's disease (CD) have received increasing attention in recent years. This review aims to describe the changes in body composition in patients with CD on imaging and to analyze and summarize the prognostic value of body composition. METHODS We systematically searched Web of Science, PubMed, Embase, Cochrane Library, and Medline via OVID for literature published before November 2022, and two researchers independently evaluated the quality of the retrieved literature. RESULTS A total of 39 publications (32 cohort studies and 7 cross-sectional studies) involving 4219 patients with CD were retrieved. Imaging methods for body composition assessment, including dual-energy X-ray absorptiometry (DXA), computed tomography (CT) and magnetic resonance imaging (MRI), were included in this review. The study found that patients with CD typically have more visceral adipose tissue and less skeletal muscle mass, and the prevalence of sarcopenia and visceral obesity was significantly different in different studies (sarcopenia: 16-100%; visceral obesity: 5.3-30.5%). Available studies suggest that changes in the body composition of CD patients are significantly related to inflammatory status, disease behavior, poor outcomes, and drug efficacy. CONCLUSION Altered body composition can be a significant predictor of poor outcomes for CD patients. Therefore, the body composition of CD patients may serve as a potential therapeutic target to help optimize disease management strategies in clinical practice.
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Affiliation(s)
- Wuli Tang
- Chongqing Medical University, Chongqing, China
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China
- Chongqing School, University of Chinese Academy of Science, Chongqing, China
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Gang Xie
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Danni Wang
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Ting Li
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Yitao Ren
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Junlin Li
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Jiaxing Deng
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Kang Li
- Chongqing Medical University, Chongqing, China.
- Department of Radiology, Chongqing General Hospital, Chongqing, China.
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17
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Hofmeyer M, Haas G, Kransdorf E, Ewald G, Morris A, Owens A, Lowes B, Stoller D, Tang W, Garg S, Trachtenberg B, Shah P, Pamboukian S, Sweitzer N, Wheeler M, Wilcox J, Katz S, Pan S, Jimenez J, Smart F, Wang J, Gottlieb S, Judge D, Moore C, Huggins G, Jordan E, Kinnamon D, Ni H, Hershberger R. Genetic Signature of Dilated Cardiomyopathy Severity: The DCM Precision Medicine Study. J Heart Lung Transplant 2023. [DOI: 10.1016/j.healun.2023.02.1674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2023] Open
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18
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Longinow J, Il'Giovine Z, Martens P, Higgins A, Soltesz E, Tong M, Estep J, Starling R, Tang W, Hanna M, Lee R. Hemodynamic Response after Intra-Aortic Balloon Counter-Pulsation in Cardiac Amyloidosis and Cardiogenic Shock. J Heart Lung Transplant 2023. [DOI: 10.1016/j.healun.2023.02.821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2023] Open
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19
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Jiang DH, Tang W. [The theory of unresponsive pulse by Wang Ji : The historical position of his Yun Qi Yi Lan]. Zhonghua Yi Shi Za Zhi 2023; 53:67-73. [PMID: 37183619 DOI: 10.3760/cma.j.cn112155-20221025-00153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
Wang Ji (1463-1539) was a well-known doctor of the Xin An Medical School in the Ming Dynasty. He and his representative masterpiece Yun Qi Yi Lan are particularly important in the medical history of Yunqi, which refers to the principles of Air (Qi) regulation, influencing almost all life in nature. In terms of the theory "nonresponsive pulse matching the South and the North in the ten Stem years" (Nan Bei Zheng Bu Ying Mai), Wang Ji differentiated and analysed the changes of this theory after the Jin and Yuan Dynasties and traced it back to the classics the Inner canon of Huangdi (Huang Di Nei Jing), based on Su Wen Ru Shi Yun Qi Lun Ao, Huang Di Nei Jing and other relevant reference materials. This paper examined the evolution of the theory of unresponsive pulse in the ancient and modern literature. It was found that after the Song Dynasty, the theory of nonresponsive pulse in the South-North in the ten Stem years was developed into two main schools. One was represented by Cheng Wuji and Liu Wansu, followed with Zhang Jingyue, Li Yanshi, Yao Zhian, Lu Guanquan, Wu Qian, Huang Yuanyu, Xue Fuchen and Zhou Xuehai, who argued that the nonresponsive pulse was determined by the position of Shaoyin. Another was represented by Liu Wenshu, followed with Wang Ji, Li Zhongzi, Zhang Zhicong and Ren Yingqiu, who believed that Shaoyin always stands in the middle, Jueyin and Taiyin are always on the two sides of Shaoyin.
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Affiliation(s)
- D H Jiang
- College of Acupuncture and Moxibustion, Anhui University of Chinese Medicine, Hefei 230038, China
| | - W Tang
- College of Acupuncture and Moxibustion, Anhui University of Chinese Medicine, Hefei 230038, China
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20
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Liang M, Zhao SJ, Zhou LN, Xu XJ, Wang YW, Niu L, Wang HH, Tang W, Wu N. [The performance of digital chest radiographs in the detection and diagnosis of pulmonary nodules and the consistency among readers]. Zhonghua Zhong Liu Za Zhi 2023; 45:265-272. [PMID: 36944548 DOI: 10.3760/cma.j.cn112152-20220304-00150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/23/2023]
Abstract
Objective: To investigate the detection and diagnostic efficacy of chest radiographs for ≤30 mm pulmonary nodules and the factors affecting them, and to compare the level of consistency among readers. Methods: A total of 43 patients with asymptomatic pulmonary nodules who consulted in Cancer Hospital, Chinese Academy of Medical Sciences from 2012 to 2014 and had chest CT and X-ray chest radiographs during the same period were retrospectively selected, and one nodule ≤30 mm was visible on chest CT images in the whole group (total 43 nodules in the whole group). One senior radiologist with more than 20 years of experience in imaging diagnosis reviewed CT images and recording the size, morphology, location, and density of nodules was selected retrospectively. Six radiologists with different levels of experience (2 residents, 2 attending physicians and 2 associate chief physicians independently reviewed the chest images and recorded the time of review, nodule detection, and diagnostic opinion. The CT imaging characteristics of detected and undetected nodules on X images were compared, and the factors affecting the detection of nodules on X-ray images were analyzed. Detection sensitivity and diagnosis accuracy rate of 6 radiologists were calculated, and the level of consistency among them was compared to analyze the influence of radiologists' seniority and reading time on the diagnosis results. Results: The number of nodules detected by all 6 radiologists was 17, with a sensitivity of detection of 39.5%(17/43). The number of nodules detected by ≥5, ≥4, ≥3, ≥2, and ≥1 physicians was 20, 21, 23, 25, and 28 nodules, respectively, with detection sensitivities of 46.5%, 48.8%, 53.5%, 58.1%, and 65.1%, respectively. Reasons for false-negative result of detection on X-ray images included the size, location, density, and morphology of the nodule. The sensitivity of detecting ≤30 mm, ≤20 mm, ≤15 mm, and ≤10 mm nodules was 46.5%-58.1%, 45.9%-54.1%, 36.0%-44.0%, and 36.4% for the 6 radiologists, respectively; the diagnosis accuracy rate was 19.0%-85.0%, 16.7%-6.5%, 18.2%-80.0%, and 0%-75.0%, respectively. The consistency of nodule detection among 6 doctors was good (Kappa value: 0.629-0.907) and the consistency of diagnostic results among them was moderate or poor (Kappa value: 0.350-0.653). The higher the radiologist's seniority, the shorter the time required to read the images. The reading time and the seniority of the radiologists had no significant influence on the detection and diagnosis results (P>0.05). Conclusions: The ability of radiographs to detect lung nodules ≤30 mm is limited, and the ability to determine the nature of the nodules is not sufficient, and the increase in reading time and seniority of the radiologists will not improve the diagnostic accuracy. X-ray film exam alone is not suitable for lung cancer diagnosis.
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Affiliation(s)
- M Liang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - S J Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - L N Zhou
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - X J Xu
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Y W Wang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - L Niu
- Radiology Department, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
| | - H H Wang
- Radiology Department, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
| | - W Tang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - N Wu
- Department of Nuclear Medicine (PET-CT Center), National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Hebei Cancer Hospital, Chinese Academy of Medical Sciences, Langfang 065001, China
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21
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Jiang C, Tang W, Hou X, Li H. Recurrent syncope in an 84-year-old man. J Postgrad Med 2023; 69:111-113. [PMID: 36861546 DOI: 10.4103/jpgm.jpgm_414_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2023] Open
Abstract
An 84-year-old man with hypertension and type 2 diabetes presented with recurrent transient loss of consciousness within 2 hours after dinner at home. Physical examination, electrocardiogram, and laboratory studies were unremarkable except hypotension. Blood pressures were measured in different postures and within 2 hours after meal, but neither orthostatic hypotension nor postprandial hypotension was detected. Further, history taking revealed that the patient was tube-fed with a fluid food pump with an inappropriate rapid infusion rate of 1500 mL per minute at home. He was eventually diagnosed as having syncope due to postprandial hypotension, which was caused by the inappropriate way of tube feeding. The family was educated about appropriate way of tube-feeding and the patient did not develop any episode of syncope during a two-year follow-up. This case highlights the importance of careful history taking in the diagnostic evaluation of syncope and the increased risk of syncope due to postprandial hypotension in the elderly.
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Affiliation(s)
- C Jiang
- Department of Internal Medicine and Geriatrics, Beijing Friendship Hospital, Capital Medical University, Beijing, India
| | - W Tang
- Department of Internal Medicine and Geriatrics, Beijing Friendship Hospital, Capital Medical University, Beijing, India
| | - X Hou
- Department of Internal Medicine and Geriatrics, Beijing Friendship Hospital, Capital Medical University, Beijing, India
| | - H Li
- Department of Internal Medicine and Geriatrics, Beijing Friendship Hospital, Capital Medical University, Beijing, India
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22
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Yu YX, Wu ZJ, Tang W, Liao R. [A comparison of current guidelines for the management of intrahepatic cholangiocarcinoma worldwide]. Zhonghua Wai Ke Za Zhi 2023; 61:297-304. [PMID: 36822586 DOI: 10.3760/cma.j.cn112139-20221125-00495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
Abstract
Intrahepatic cholangiocarcinoma (ICC) is the second most common human liver malignancy and its incidence rate has been gradually increasing worldwide over the past decades. Surgical resection (R0 resection) is the preferred potentially curative treatment for ICC patients. However, due to its conceal clinical features and high invasiveness, most patients have lost the opportunity for surgical resection at the time of diagnosis. In recent years, with the rapid development of targeted therapy and immunotherapy, which is represented by immune checkpoint inhibitors, clinicians are expected to provide more effective treatment options for patients with mid-stage or advanced ICC. At present, there are still controversial opinions on different guidelines regarding preoperative biliary drainage, the extent of hepatectomy, the definition of R0 resection, the width of the resection margin, lymph node dissection, postoperative recurrence, adjuvant therapy, etc. In this review, 12 guidelines or expert consensus published worldwide from 2012 to 2022 (including 4 Chinese guidelines, 4 European guidelines, 2 American guidelines and 2 Japanese guidelines) were retrieved. Focusing on sorting and comparing the current views on clinical management of ICC in different guidelines, this review aims to provide reference information for ICC clinical management and decision-making.
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Affiliation(s)
- Y X Yu
- Department of Hepatobiliary Surgery, the First Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Z J Wu
- Department of Hepatobiliary Surgery, the First Hospital of Chongqing Medical University, Chongqing 400016, China
| | - W Tang
- National Center for Global Health and Medicine, Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, the University of Tokyo Hospital, Tokyo 162-8655, Japan
| | - R Liao
- Department of Hepatobiliary Surgery, the First Hospital of Chongqing Medical University, Chongqing 400016, China
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23
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Ji MM, Shen YG, Gong JC, Tang W, Xu XQ, Zheng Z, Chen SY, He Y, Zheng X, Zhao LD, Zhao WL, Wu W. [Efficiency and safety analysis of Plerixafor combined with granulocyte colony-stimulating factor on autologous hematopoietic stem cell mobilization in lymphoma]. Zhonghua Xue Ye Xue Za Zhi 2023; 44:112-117. [PMID: 36948864 PMCID: PMC10033277 DOI: 10.3760/cma.j.issn.0253-2727.2023.02.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/24/2023]
Abstract
Objective: To evaluate the advantages and safety of Plerixafor in combination with granulocyte colony-stimulating factor (G-CSF) in autologous hematopoietic stem cell mobilization of lymphoma. Methods: Lymphoma patients who received autologous hematopoietic stem cell mobilization with Plerixafor in combination with G-CSF or G-CSF alone were obtained. The clinical data, the success rate of stem cell collection, hematopoietic reconstitution, and treatment-related adverse reactions between the two groups were evaluated retrospectively. Results: A total of 184 lymphoma patients were included in this analysis, including 115 cases of diffuse large B-cell lymphoma (62.5%) , 16 cases of classical Hodgkin's lymphoma (8.7%) , 11 cases of follicular non-Hodgkin's lymphoma (6.0%) , 10 cases of angioimmunoblastic T-cell lymphoma (5.4%) , 6 cases of mantle cell lymphoma (3.3%) , and 6 cases of anaplastic large cell lymphoma (3.3%) , 6 cases of NK/T-cell lymphoma (3.3%) , 4 cases of Burkitt's lymphoma (2.2%) , 8 cases of other types of B-cell lymphoma (4.3%) , and 2 cases of other types of T-cell lymphoma (1.1%) ; 31 patients had received radiotherapy (16.8%) . The patients in the two groups were recruited with Plerixafor in combination with G-CSF or G-CSF alone. The baseline clinical characteristics of the two groups were basically similar. The patients in the Plerixafor in combination with the G-CSF mobilization group were older, and the number of recurrences and third-line chemotherapy was higher. 100 patients were mobilized with G-CSF alone. The success rate of the collection was 74.0% for one day and 89.0% for two days. 84 patients in the group of Plerixafor combined with G-CSF were recruited successfully with 85.7% for one day and 97.6% for two days. The success rate of mobilization in the group of Plerixafor combined with G-CSF was substantially higher than that in the group of G-CSF alone (P=0.023) . The median number of CD34(+) cells obtained in the mobilization group of Plerixafor combined with G-CSF was 3.9×10(6)/kg. The median number of CD34(+) cells obtained in the G-CSF Mobilization group alone was 3.2×10(6)/kg. The number of CD34(+) cells collected by Plerixafor combined with G-CSF was considerably higher than that in G-CSF alone (P=0.001) . The prevalent adverse reactions in the group of Plerixafor combined with G-CSF were grade 1-2 gastrointestinal reactions (31.2%) and local skin redness (2.4%) . Conclusion: The success rate of autologous hematopoietic stem cell mobilization in lymphoma patients treated with Plerixafor combined with G-CSF is significantly high. The success rate of collection and the absolute count of CD34(+) stem cells were substantially higher than those in the group treated with G-CSF alone. Even in older patients, second-line collection, recurrence, or multiple chemotherapies, the combined mobilization method also has a high success rate of mobilization.
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Affiliation(s)
- M M Ji
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Y G Shen
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - J C Gong
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - W Tang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - X Q Xu
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Z Zheng
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - S Y Chen
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Y He
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - X Zheng
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - L D Zhao
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - W L Zhao
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - W Wu
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
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24
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Abratenko P, Andrade Aldana D, Anthony J, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barr G, Barrow J, Basque V, Bathe-Peters L, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhattacharya M, Bishai M, Blake A, Bogart B, Bolton T, Book JY, Camilleri L, Caratelli D, Caro Terrazas I, Cavanna F, Cerati G, Chen Y, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Dorrill R, Duffy K, Dytman S, Eberly B, Ereditato A, Evans JJ, Fine R, Finnerud OG, Foreman W, Fleming BT, Foppiani N, Franco D, Furmanski AP, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Goodwin O, Gramellini E, Green P, Greenlee H, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hicks R, Hilgenberg C, Horton-Smith GA, Irwin B, Itay R, James C, Ji X, Jiang L, Jo JH, Johnson RA, Jwa YJ, Kalra D, Kamp N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, Leibovitch MB, Lepetic I, Li JY, Li K, Li Y, Lin K, Littlejohn BR, Louis WC, Luo X, Manivannan K, Mariani C, Marsden D, Marshall J, Martinez N, Martinez Caicedo DA, Mason K, Mastbaum A, McConkey N, Meddage V, Miller K, Mills J, Mogan A, Mohayai T, Mooney M, Moor AF, Moore CD, Mora Lepin L, Mousseau J, Mulleriababu S, Naples D, Navrer-Agasson A, Nayak N, Nebot-Guinot M, Nowak J, Nunes M, Oza N, Palamara O, Pallat N, Paolone V, Papadopoulou A, Papavassiliou V, Parkinson HB, Pate SF, Patel N, Pavlovic Z, Piasetzky E, Ponce-Pinto ID, Pophale I, Prince S, Qian X, Raaf JL, Radeka V, Reggiani-Guzzo M, Ren L, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Rudolf von Rohr C, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Smith A, Snider EL, Soderberg M, Söldner-Rembold S, Spitz J, Stancari M, St John J, Strauss T, Sword-Fehlberg S, Szelc AM, Tang W, Taniuchi N, Terao K, Thorpe C, Torbunov D, Totani D, Toups M, Tsai YT, Tyler J, Uchida MA, Usher T, Viren B, Weber M, Wei H, White AJ, Williams Z, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wright N, Wu W, Yandel E, Yang T, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. First Constraints on Light Sterile Neutrino Oscillations from Combined Appearance and Disappearance Searches with the MicroBooNE Detector. Phys Rev Lett 2023; 130:011801. [PMID: 36669216 DOI: 10.1103/physrevlett.130.011801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 12/08/2022] [Indexed: 06/17/2023]
Abstract
We present a search for eV-scale sterile neutrino oscillations in the MicroBooNE liquid argon detector, simultaneously considering all possible appearance and disappearance effects within the 3+1 active-to-sterile neutrino oscillation framework. We analyze the neutrino candidate events for the recent measurements of charged-current ν_{e} and ν_{μ} interactions in the MicroBooNE detector, using data corresponding to an exposure of 6.37×10^{20} protons on target from the Fermilab booster neutrino beam. We observe no evidence of light sterile neutrino oscillations and derive exclusion contours at the 95% confidence level in the plane of the mass-squared splitting Δm_{41}^{2} and the sterile neutrino mixing angles θ_{μe} and θ_{ee}, excluding part of the parameter space allowed by experimental anomalies. Cancellation of ν_{e} appearance and ν_{e} disappearance effects due to the full 3+1 treatment of the analysis leads to a degeneracy when determining the oscillation parameters, which is discussed in this Letter and will be addressed by future analyses.
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - D Andrade Aldana
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - J Anthony
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | - A Ashkenazi
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - J Barrow
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - V Basque
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | | | | | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - M Bhattacharya
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - B Bogart
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - D Caratelli
- University of California, Santa Barbara, California 93106, USA
| | - I Caro Terrazas
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y Chen
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - L Cooper-Troendle
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- Universität Bern, Bern CH-3012, Switzerland
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | | | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O G Finnerud
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - W Foreman
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - B T Fleming
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - N Foppiani
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - D Franco
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - O Goodwin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - E Gramellini
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - P Green
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - R Hicks
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - B Irwin
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - R Itay
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - L Jiang
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - J H Jo
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - M B Leibovitch
- University of California, Santa Barbara, California 93106, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - J-Y Li
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - K Manivannan
- Syracuse University, Syracuse, New York 13244, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N Martinez
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - K Mason
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - N McConkey
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - K Miller
- University of Chicago, Chicago, Illinois 60637, USA
| | - J Mills
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mogan
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Mousseau
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | | | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - N Nayak
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - M Nunes
- Syracuse University, Syracuse, New York 13244, USA
| | - N Oza
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - N Pallat
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - H B Parkinson
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Piasetzky
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - I D Ponce-Pinto
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - I Pophale
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - S Prince
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Reggiani-Guzzo
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Ross-Lonergan
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | | | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Smith
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S Sword-Fehlberg
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - N Taniuchi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - D Torbunov
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Tyler
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - A J White
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Z Williams
- University of Texas, Arlington, Texas 76019, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - N Wright
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - W Wu
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L E Yates
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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25
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Tang W. Doctor's bag belonging to Dr Wai-cheung Chau. Hong Kong Med J 2022; 28:504-505. [PMID: 36523126 DOI: 10.12809/hkmj202212-hkmms] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Affiliation(s)
- W Tang
- Member, Educational and Research Committee, Hong Kong Museum of Medical Sciences Society
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Chang W, Zhou S, Sun D, Liu Y, Mao W, Cen W, Tang W, Ye L, Wang L, Xu J. 53P Baseline PET/CT deep radiomics signature apply for identifying bevacizumab sensitivity of RAS-mutant colorectal cancer liver metastases patients. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.10.085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2022] Open
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Xing J, Fu YH, Song Z, Wang Q, Ma T, Li M, Zhuang Y, Li Z, Zhu YJ, Tang W, Wang SG, Yang N, Wang PF, Zhang K. Predictive model for deep venous thrombosis caused by closed lower limb fracture after thromboprophylactic treatment. Eur Rev Med Pharmacol Sci 2022; 26:8508-8522. [PMID: 36459032 DOI: 10.26355/eurrev_202211_30387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
OBJECTIVE Currently, there are still no convincing clinical models predicting closed lower extremity fracture-associated deep vein thrombosis in patients treated through thromboprophylactic methods. We aimed at using two retrospective cohorts to develop and externally verify a clinical prediction model for deep vein thrombosis in patients treated with anticoagulants after suffering closed lower extremity fractures. PATIENTS AND METHODS We evaluated the patients' pre- and post-operatively, to accurately determine the predictive power of the biomarkers and clinical risk factors. Two retrospective cohorts were used for the development and external verification of a pre-operative clinical prediction model (development: n = 2,253; verification: n = 833) and post-operative clinical prediction model (development: n = 1,422; verification: n = 449), respectively. RESULTS The C-indices were used to show the predicted incidence of objective thrombosis at the pre- and post-operative stage, which were then compared with the observed incidence of thrombosis in both cohorts. Biomarkers and clinical indicators were included in pre- and post-operative nomograms, which were adequately calibrated in both cohorts. The cross-validated C-indices of the pre- and post-operative clinical prediction models in the verification cohort were 0.706 (95% Cl, 0.67-0.74) and 0.875 (95% Cl, 0.84-0.91), respectively. CONCLUSIONS We present our findings of novel pre- and post-operative nomograms for the prediction of deep venous thrombosis in patients who received thromboprophylaxis after suffering closed lower extremity fractures.
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Affiliation(s)
- J Xing
- Department of Orthopedics and Traumatology, Honghui Hospital, Xi'an Jiaotong University, Shaanxi, China.
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28
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Lin Q, Ding K, Zhao R, Wang H, Ren L, Wei Y, Ye Q, Cui Y, He G, Tang W, Feng Q, Zhu D, Chang W, Lv Y, Mao Y, Wang X, Liang L, Zhou G, Liang F, Xu J. 43O Preoperative chemotherapy prior to primary tumor resection for colorectal cancer patients with asymptomatic resectable primary lesion and synchronous unresectable liver-limited metastases (RECUT): A prospective, randomized, controlled, multicenter clinical trial. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.10.075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2022] Open
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29
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Zhang ZW, Jin YJ, Zhao SJ, Zhou LN, Huang Y, Wang JW, Tang W, Wu N. [Prevalence and risk factors of coronary artery calcification on lung cancer screening with low-dose CT]. Zhonghua Zhong Liu Za Zhi 2022; 44:1112-1118. [PMID: 36319457 DOI: 10.3760/cma.j.cn112152-20201114-00986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Objective: To investigate the prevalence and risk factors of coronary artery calcification (CAC) on lung cancer screening with low-dose computed tomography (LDCT). Methods: A total of 4 989 asymptomatic subjects (2 542 males and 2 447 females) who underwent LDCT lung cancer screening were recruited at Cancer Hospital, Chinese Academy of Medical Sciences from 2014 to 2017. The visual scoring method was used to assess coronary artery calcification score. χ(2) test or independent t-test was used to compare the difference of CAC positive rate among different groups. Multivariate logistic regression was used to analyze risk factors associated with CAC in the study. Results: Of the 4 989 asymptomatic subjects, CAC occurred in 1 018 cases. The positive rate was 20.4%, of which mild, moderate and severe calcification accounted for 86.3%, 11.4% and 2.3%, respectively. Gender, age, BMI, education level, occupation, smoking history, diabetes, hypertension and hyperlipidemia had statistically significant differences in CAC positive rates among groups. Multivariate logistic regression analysis showed that gender, age, diabetes, hypertension, hyperlipidemia and smoking history were risk factors for CAC. Age, diabetes, hypertension and smoking history were statistically significant risk factors between the mild and moderate CAC group. A total of 1 730 coronary arteries in 1 018 CAC positive cases had calcification, CAC positive rate of left anterior descending was the highest(51.3%); 568 cases (55.8%) were single vessel calcification, 450 cases (44.2%) were multiple vessel calcification. Conclusions: LDCT can be used for the 'one-stop' early detection of lung cancer and coronary atherosclerosis. Gender, age, diabetes, hypertension, hyperlipidemia and smoking are related risk factors for coronary atherosclerosis.
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Affiliation(s)
- Z W Zhang
- Department of Nuclear Medicine, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021 China
| | - Y J Jin
- Department of Nuclear Medicine, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021 China
| | - S J Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - L N Zhou
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Y Huang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - J W Wang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - W Tang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - N Wu
- Department of Nuclear Medicine, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021 China
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Xiong YT, Xu L, Zeng W, Liu C, Guo JX, Tang W. [Virtual reconstruction and clinical verification of maxillary defect based on deep learning]. Zhonghua Kou Qiang Yi Xue Za Zhi 2022; 57:1029-1035. [PMID: 36266076 DOI: 10.3760/cma.j.cn112144-20220714-00384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Objective: To construct a virtual reconstruction method including midspan maxillary defects and provide clinical reference by training a generative adversarial network (GAN) model. Methods: The CT data of middle-aged Han patients with oral diseases who visited the Department of Radiology, West China Hospital of Stomatology, Sichuan University from June 2015 to June 2022 were collected, where the CT data of 100 healthy maxilla and 15 maxillary defects (5 simple unilateral defects, 5 unilateral defects involving zygomatic bone, 5 midspan defects) were selected. Mimics was used to create spherical phantom and simulate bone defects around the healthy maxillas, including simple unilateral defects, unilateral defects involving zygomatic bone and midspan defects. The original image was set as the correct reference for the reconstruction: artificial defects paired with the correct reference were divided into training set (n=70), validation set (n=20) and test set (n=10), where the first two were used to train the GAN model, and the test set was used to evaluate the GAN performance. Data from 15 clinical defects were imported into the trained GAN model for reconstruction, with mirroring and GAN-based virtual reconstruction for unilateral clinical defects, and only the latter method was adopted for midspan defects. The reconstruction results were divided into mirror reconstruction group (n=10), unilateral defect GAN reconstruction group (n=10) and midspan defect GAN reconstruction group (n=5). The test set, mirror reconstruction group, and unilateral defect GAN reconstruction group were quantitatively evaluated, whose quantitative indicators were Dice similarity coefficient (DSC) and 95% Hausdorff distance (HD95), and the group results were subjected to one-way ANOVA and Tukey test. The test set, mirror reconstruction group, unilateral defect GAN reconstruction group and midspan defect GAN reconstruction group were qualitatively scored, and Kruskal-Wallis test and Bonferroni correction were used for the total score of each group. Results: The total differences in the test set, mirror reconstruction group, unilateral defect GAN reconstruction group DCS (0.891±0.049, 0.721±0.047, 0.778±0.057, respectively) and HD95 [(3.58±1.51), (5.19±1.38), (4.51±1.10) mm, respectively] were statistically significant (F=28.08, P<0.001; F=3.62, P=0.041); among them, the test set DSC was significantly larger than the mirror reconstruction group (P<0.05), and the test set HD95 was significantly less than the mirror reconstruction group (P<0.05). Overall difference in qualitative total scores [8 (1), 6 (2), 6 (2), and 4 (2) points, respectively] in the test set, mirror reconstruction group, unilateral defect GAN reconstruction group, and midspan defect GAN reconstruction group were statistical significance (H=18.13, P<0.001); pairwise comparison showed that the total score of the test set was significantly higher than that of the mirror reconstruction group (P<0.05). Conclusions: The virtual reconstruction method based on GAN proposed in this study has better virtual reconstruction effect of unilateral defect than mirror technique, and can also realize virtual reconstruction of maxillary midspan defect.
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Affiliation(s)
- Y T Xiong
- Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
| | - L Xu
- Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu 610041, China
| | - W Zeng
- Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
| | - C Liu
- Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
| | - J X Guo
- Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu 610041, China
| | - W Tang
- Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
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Greene S, Spertus JA, Tang W, Kang A, Zhong Y, Myers M, Shen S, Jiang J, Liu X, Steffen DR, Viola M, Felker GM. Heart failure across the range of preserved ejection fraction in United States clinical practice. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Introduction
Recent clinical trials of heart failure with preserved ejection fraction (HFpEF) have observed varying patient profiles by ejection fraction (EF), with attenuation of treatment benefits as EF increases. In routine clinical practice, the degree to which patients hospitalized for HF with EF≥60% may differ from those with lower EF is unknown.
Purpose
To compare patient characteristics, treatment patterns, and clinical outcomes across the range of EF among patients hospitalized for HFpEF.
Methods
Using the Humedica electronic medical records database between Jan 2010 and Dec 2020, patients hospitalized for a primary diagnosis of HF with EF>40% and who were haemodynamically stable at admission, without concurrent acute coronary syndrome or end-stage renal disease, and treated with intravenous (IV) diuretic agents within 48 h of admission were identified. Patient characteristics, treatment patterns, and clinical outcomes were compared by EF ranges of 41–49%, 50–59%, and ≥60%.
Results
Of 47,026 patients hospitalized with HFpEF, 6,335 (13%) had EF 41–49%, 18,603 (40%) had EF 50–59%, and 22,088 (47%) had EF≥60%. Across all 3 groups, patients were similar with respect to age (median 77 years for each group), race (83–84% White, 12–13% Black), systolic blood pressure (137–138 mmHg at admission), and eGFR (63–64 mL/min/1.73 m2 at admission). With progressively higher EF group, the proportion of women increased (45% vs 54% vs 65%) and median NT-proBNP decreased (4,221 vs 2,945 vs 2,234 pg/mL). Patients with EF ≥60% had the lowest rates of coronary artery disease and atrial fibrillation, and the highest rates of chronic pulmonary disease (Figure 1, Panel A). Discharge medications were generally similar, with exception of less beta-blocker use and more calcium channel blocker use among those with EF ≥60% (Figure 1, Panel B). Discharge use of angiotensin receptor-neprilysin inhibitor and sodium glucose cotransporter-2 inhibitor therapies were each <1% in all groups. Hospital length of stay (median 4 days for each group) and in-hospital mortality (1.1–1.3%) were similar across groups, but rates of in-hospital acute respiratory failure were higher among patients with EF ≥60% (27% vs 230-25% for lower EF groups). Rates of 30-day and 12-month post-discharge clinical events were high irrespective of EF, without meaningful differences between groups (Figure 2).
Conclusion
In a contemporary real-world population of US patients hospitalized for HF with EF >40%, nearly half had an EF≥60%. While clinical profiles and discharge medications varied, post-discharge outcomes were similarly poor irrespective of EF. There remain important opportunities to improve the care and outcomes for patients with HF across the range of preserved ejection fraction.
Funding Acknowledgement
Type of funding sources: Private company. Main funding source(s): MyoKardia, Inc., a wholly owned subsidiary of Bristol Myers Squibb
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Affiliation(s)
- S Greene
- Duke Clinical Research Institute , Durham , United States of America
| | - J A Spertus
- St. Luke's Mid America Heart Institute , Kansas City , United States of America
| | - W Tang
- Duke Clinical Research Institute , Durham , United States of America
| | - A Kang
- Bristol-Myers Squibb Company , Lawrenceville , United States of America
| | - Y Zhong
- Bristol-Myers Squibb Company , Lawrenceville , United States of America
| | - M Myers
- Bristol-Myers Squibb Company , Lawrenceville , United States of America
| | - S Shen
- Bristol-Myers Squibb Company , Lawrenceville , United States of America
| | - J Jiang
- Bristol-Myers Squibb Company , Lawrenceville , United States of America
| | - X Liu
- Bristol-Myers Squibb Company , Lawrenceville , United States of America
| | - D R Steffen
- Analysis Group Inc. , New York , United States of America
| | - M Viola
- Analysis Group Inc. , New York , United States of America
| | - G M Felker
- Duke Clinical Research Institute , Durham , United States of America
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Hughes D, Wilson R, Saijo Y, Chan N, Kumar A, Grimm R, Griffin B, Tang W, Nissen S, Aminian A, Xu B. Impact of weight loss on cardiac function: improvement in left ventricular global longitudinal strain following metabolic surgery. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Introduction
Obesity leads to an increased risk of cardiovascular disease (CVD) morbidity and mortality and is associated with the metabolic risk factors such as hypertension, diabetes mellitus, hyperlipidemia [1]. Metabolic surgery has been proven to be the most effective long term weight management tool and has known benefits in CVD prevention [2]. Global longitudinal strain (GLS) is an effective quantitative measurement of left ventricular (LV) function that is also a powerful predictor of future CVD events and mortality [3]. The impact of metabolic surgery on LV structure and function is unknown.
Purpose
This study investigated the changes in cardiac structure and function after metabolic surgery, including GLS. To our knowledge there has not been a study investigating this relationship previously reported.
Methods
Consecutive patients undergoing metabolic surgery at our center between March 2005 and February 2019 were recruited. Patients with transthoracic echocardiographic imaging (TTE) pre and post metabolic surgery (May 2005 to January 2019) were included. Electronic medical records were searched to obtain demographic, surgical and clinical data. GLS was calculated with Velocity Vector Imaging (VVI, Siemens, v2.0, Pennsylvania, USA). Averaged GLS values were derived from 4 chamber, 2 chamber and 3 chamber calculations.
Results
398 patients with pre- and post-operative cardiac imaging were included. Please see Table 1 for the baseline demographics of our study population. The mean age was 60.0 years with 70% being female. There were significant rates of CVD risk factors such as: hypertension (76.4%), diabetes mellitus (58.8%) and hyperlipidemia (76.4%).
The clinical and echocardiographic changes noted post metabolic surgery are detailed in Table 2. Along with decreases in weight post operatively, there were significant improvements in the markers of CVD risk factors such as mean blood pressure (134/75 to 129/72 mmHg, p value <0.001), mean gylcated hemoglobin levels (7.0 to 6.1%, p value <0.001) and mean low density lipoprotein (LDL) levels (97.7 to 88.2 mg/dl, p value <0.001).
There were a number of statistically significant positive changes in the left ventricular structure and function. The mean LV ejection fraction increased from 56.3% to 57.4% (p=0.008); left ventricular mass decreased from 238.2 g to 179.3 g (p value <0.001), and both septal and posterior wall thicknesses decreased significantly (p value <0.001). The LV mass indexed to body surface area (BSA) also decreased from 93.5 g/m2 to 83.1 g/m2.
The average global LV GLS was −15.7% pre-operatively, improving significantly to −17.9% post-operatively (p<0.001).
Conclusion
Our study has shown for the first time the impact of metabolic surgery on ventricular structure and function, with reduction in LV mass and improvement in LV GLS. These novel findings lends further support to the cardiovascular benefits of metabolic surgery.
Funding Acknowledgement
Type of funding sources: None.
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Affiliation(s)
- D Hughes
- Cleveland Clinic, Heart and Vascular Institute , Cleveland , United States of America
| | - R Wilson
- Cleveland Clinic, Bariatric and Metabolic Institute , Cleveland , United States of America
| | - Y Saijo
- Cleveland Clinic, Heart and Vascular Institute , Cleveland , United States of America
| | - N Chan
- Cleveland Clinic, Heart and Vascular Institute , Cleveland , United States of America
| | - A Kumar
- Cleveland Clinic, Heart and Vascular Institute , Cleveland , United States of America
| | - R Grimm
- Cleveland Clinic, Heart and Vascular Institute , Cleveland , United States of America
| | - B Griffin
- Cleveland Clinic, Heart and Vascular Institute , Cleveland , United States of America
| | - W Tang
- Cleveland Clinic, Heart and Vascular Institute , Cleveland , United States of America
| | - S Nissen
- Cleveland Clinic, Heart and Vascular Institute , Cleveland , United States of America
| | - A Aminian
- Cleveland Clinic, Bariatric and Metabolic Institute , Cleveland , United States of America
| | - B Xu
- Cleveland Clinic, Heart and Vascular Institute , Cleveland , United States of America
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Hutt E, Vega Brizneda M, Aguilera J, Wang TKM, Taimeh Z, Culver D, Callahan T, Tang W, Jaber WA, Cremer P, Ribeiro M, Jellis C. Multimodality imaging predictors of appropriate ICD shock and mortality in adults with cardiac sarcoidosis. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background
Identifying patients with cardiac sarcoidosis (CS) who are at increased risk of sudden cardiac death (SCD) is imperative. Current guideline recommendations for implantable cardioverter-defibrillator (ICD) implantation in patients with CS are based on small observational studies and have not been validated in contemporary cohorts using multimodality cardiac imaging.
Purpose
The aim of this study was to characterize a cohort of patients with tissue-proven cardiac sarcoidosis who underwent multimodality cardiac imaging and identify predictors of appropriate ICD shock and mortality.
Methods
We retrospectively identified subjects with a diagnosis of CS established by clinical/imaging criteria, and tissue biopsy (N=273) seen at our tertiary care center between 2001 and 2021. Clinical characteristics and outcomes were collected from electronic medical records. The primary endpoint of interest was a composite of appropriate ICD shock and all-cause mortality. Secondary endpoints were individual rates of appropriate ICD shock and all-cause mortality. Cox proportional hazard regression analysis was used to identify independent predictors of the outcomes.
Results
Mean age was 59±11 years and 40% were female. Isolated CS was found in 49 subjects (17.9%). The prevalence of traditional cardiovascular risk factors was low. Atrial fibrillation prevalence was high (41%). After a median follow-up of 7.9 years, the rate of appropriate ICD shock and all-cause mortality was 29% (N=79). The 5-year overall survival rate of 97.5%. Age, left ventricular ejection fraction (LVEF), and delayed gadolinium enhancement (DGE) in cardiac magnetic resonance (CMR) were independent predictors of the primary composite endpoint; LVEF and DGE in CMR were independent predictors of appropriate ICD-shock; and LVEF and baseline serum NT proBNP were independent predictors of overall mortality. An LVEF of 47% was identified as the optimal cutoff in predicting the primary composite endpoint. Presence of scar, inflammation or mismatch pattern in positron emission tomography were not significant predictors of the outcomes.
Conclusion
In this large cohort of subjects with CS, we found that the presence of DGE in CMR was the strongest independent predictor of the composite endpoint of appropriate ICD-shock and mortality and of appropriate ICD-shock individually; LVEF by echocardiogram was an independent predictor of the primary and secondary endpoints with an optimal LVEF cutoff for predicting the composite endpoint of 47%.
Funding Acknowledgement
Type of funding sources: None.
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Affiliation(s)
- E Hutt
- Cleveland Clinic , Cleveland , United States of America
| | | | - J Aguilera
- Cleveland Clinic , Cleveland , United States of America
| | - T K M Wang
- Cleveland Clinic , Cleveland , United States of America
| | - Z Taimeh
- Cleveland Clinic , Cleveland , United States of America
| | - D Culver
- Cleveland Clinic , Cleveland , United States of America
| | - T Callahan
- Cleveland Clinic , Cleveland , United States of America
| | - W Tang
- Cleveland Clinic , Cleveland , United States of America
| | - W A Jaber
- Cleveland Clinic , Cleveland , United States of America
| | - P Cremer
- Cleveland Clinic , Cleveland , United States of America
| | - M Ribeiro
- Cleveland Clinic , Cleveland , United States of America
| | - C Jellis
- Cleveland Clinic , Cleveland , United States of America
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Xie G, Li T, Ren Y, Wang D, Tang W, Li J, Li K. Radiomics-based infarct features on CT predict hemorrhagic transformation in patients with acute ischemic stroke. Front Neurosci 2022; 16:1002717. [PMID: 36213752 PMCID: PMC9533555 DOI: 10.3389/fnins.2022.1002717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 09/02/2022] [Indexed: 11/15/2022] Open
Abstract
Objective To develop and validate a model based on the radiomics features of the infarct areas on non-contrast-enhanced CT to predict hemorrhagic transformation (HT) in acute ischemic stroke. Materials and methods A total of 118 patients diagnosed with acute ischemic stroke in two centers from January 2019 to February 2022 were included. The radiomics features of infarcted areas on non-contrast-enhanced CT were extracted using 3D-Slicer. A univariate analysis and the least absolute shrinkage and selection operator (LASSO) were used to select features, and the radiomics score (Rad-score) was then constructed. The predictive model of HT was constructed by analyzing the Rad-score and clinical and imaging features in the training cohort, and it was verified in the validation cohort. The model was evaluated with the receiver operating characteristic curve, calibration curve and decision curve, and the prediction performance of the model in different scenarios was further discussed hierarchically. Results Of the 118 patients, 52 developed HT, including 21 cases of hemorrhagic infarct (HI) and 31 cases of parenchymal hematoma (PH). The Rad-score was constructed from five radiomics features and was the only independent predictor for HT. The predictive model was constructed from the Rad-score. The area under the curve (AUCs) of the model for predicting HT in the training and validation cohorts were 0.845 and 0.750, respectively. Calibration curve and decision curve analyses showed that the model performed well. Further analysis found that the model predicted HT for different infarct sizes or treatment methods in the training and validation cohorts with 78.3 and 71.4% accuracy, respectively. For all samples, the model predicted an AUC of 0.754 for HT in patients within 4.5 h since stroke onset, and predicted an AUC of 0.648 for PH. Conclusion This model, which was based on CT radiomics features, could help to predict HT in the setting of acute ischemic stroke for any infarct size and provide guiding suggestions for clinical treatment and prognosis evaluation.
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Affiliation(s)
- Gang Xie
- North Sichuan Medical College, Nanchong, China
| | - Ting Li
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Yitao Ren
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Danni Wang
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Wuli Tang
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Junlin Li
- Department of Radiology, Chongqing General Hospital, Chongqing, China
| | - Kang Li
- Department of Radiology, Chongqing General Hospital, Chongqing, China
- *Correspondence: Kang Li,
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Haringa C, Tang W, Noorman H. Analyzing bioprocess heterogeneity from the microbial viewpoint: Recent developments. CHEM-ING-TECH 2022. [DOI: 10.1002/cite.202255018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- C. Haringa
- Delft University of Technology Biotechnology Van der Maasweg 9 2629HZ Delft The Netherlands
| | - W. Tang
- Delft University of Technology Biotechnology Van der Maasweg 9 2629HZ Delft The Netherlands
- Royal DSM Alexander Fleminglaan 1 2613AX Delft The Netherlands
| | - H. J. Noorman
- Delft University of Technology Biotechnology Van der Maasweg 9 2629HZ Delft The Netherlands
- Royal DSM Alexander Fleminglaan 1 2613AX Delft The Netherlands
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Yang YY, Tang SW, Tang W, Fan JL, Li Z, Yang JW, Ren J, Li CS. [Antibody levels of measles, rubella and mumps viruses in healthy population in Shanghai from 2010 to 2020]. Zhonghua Yu Fang Yi Xue Za Zhi 2022; 56:1095-1100. [PMID: 35922237 DOI: 10.3760/cma.j.cn112150-20211116-01057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To determine IgG antibody levels of measles, rubella, mumps in healthy population in Shanghai from 2010 to 2020 and analyze the trend of antibody changes in different age groups. Methods: 10 828 healthy people without measles, rubella and mumps in Shanghai were included in the study from 2010 to 2020. Serum samples were collected from 12 age groups, and the serum IgG antibody of measles, rubella and mumps were detected by ELISA. The difference of antibody positive rates and antibody levels were analyzed. Results: The median age M (Q1, Q3) of 10 828 objects were 8 years old (9 months old, 20 years old). Males accounted for 48.34% (5 234/10 828) and females accounted for 50.92% (5 514/10 828). Unknown gender information accounted for 0.74% (80/10 828), and 27.03% (2 927/10 828) of participants had unknown MMR immunization history. The total positive rates of measles, rubella and mumps IgG antibody were 76.78%, 64.46% and 64.29% and their GMCs were 541.45 mIU/ml, 31.76 IU/ml and 133.73 U/ml respectively. There were significant differences in serum IgG antibody GMC of measles, rubella and mumps in each year (Fmeasles=180.74, P<0.001; Frubella=189.95, P<0.001; Fmumps=122.40, P<0.001). The positive rate of measles antibody was higher than that of rubella and mumps, and the difference was statistically significant (χ²=518.09, P<0.001). Conclusion: The level of measles IgG antibody in healthy people in Shanghai is higher, while the level of rubella and mumps IgG antibody is slightly lower.
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Affiliation(s)
- Y Y Yang
- Department of Pathogen Biological Detection, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - S W Tang
- Department of Pathogen Biological Detection, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - W Tang
- Department of Pathogen Biological Detection, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - J L Fan
- Department of Infectious Disease Prevention and Control, Shanghai Minhang District Municipal Center for Disease Control and Prevention, Shanghai 201101, China
| | - Z Li
- Department of Pathogen Biological Detection, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - J W Yang
- Department of Pathogen Biological Detection, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - J Ren
- Department of Pathogen Biological Detection, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - C S Li
- Shanghai Institute of Infectious Disease and Biosecurity, Shanghai 200032, China
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Abratenko P, An R, Anthony J, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barnes C, Barr G, Basque V, Bathe-Peters L, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhat A, Bishai M, Blake A, Bolton T, Book JY, Camilleri L, Caratelli D, Caro Terrazas I, Cavanna F, Cerati G, Chen Y, Cianci D, Collin GH, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Dorrill R, Duffy K, Dytman S, Eberly B, Ereditato A, Escudero Sanchez L, Evans JJ, Fine R, Fiorentini Aguirre GA, Fitzpatrick RS, Fleming BT, Foppiani N, Franco D, Furmanski AP, Garcia-Gamez D, Gardiner S, Ge G, Genty V, Gollapinni S, Goodwin O, Gramellini E, Green P, Greenlee H, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hilgenberg C, Horton-Smith GA, Hourlier A, Itay R, James C, Ji X, Jiang L, Jo JH, Johnson RA, Jwa YJ, Kaleko D, Kalra D, Kamp N, Kaneshige N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, LaZur R, Lepetic I, Li K, Li Y, Lin K, Lister A, Littlejohn BR, Louis WC, Luo X, Manivannan K, Mariani C, Marsden D, Marshall J, Martinez Caicedo DA, Mason K, Mastbaum A, McConkey N, Meddage V, Mettler T, Miller K, Mills J, Mistry K, Mogan A, Mohayai T, Moon J, Mooney M, Moor AF, Moore CD, Mora Lepin L, Mousseau J, Murphy M, Naples D, Navrer-Agasson A, Nebot-Guinot M, Neely RK, Newmark DA, Nowak J, Nunes M, Palamara O, Paolone V, Papadopoulou A, Papavassiliou V, Pate SF, Patel N, Paudel A, Pavlovic Z, Piasetzky E, Ponce-Pinto ID, Prince S, Qian X, Raaf JL, Radeka V, Rafique A, Reggiani-Guzzo M, Ren L, Rice LCJ, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Russell B, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Sinclair J, Smith A, Snider EL, Soderberg M, Söldner-Rembold S, Soleti SR, Spentzouris P, Spitz J, Stancari M, John JS, Strauss T, Sutton K, Sword-Fehlberg S, Szelc AM, Tang W, Terao K, Thomson M, Thorpe C, Totani D, Toups M, Tsai YT, Uchida MA, Usher T, Van De Pontseele W, Viren B, Weber M, Wei H, Williams Z, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wright N, Wu W, Yandel E, Yang T, Yarbrough G, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. Search for an Excess of Electron Neutrino Interactions in MicroBooNE Using Multiple Final-State Topologies. Phys Rev Lett 2022; 128:241801. [PMID: 35776450 DOI: 10.1103/physrevlett.128.241801] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 04/13/2022] [Indexed: 06/15/2023]
Abstract
We present a measurement of ν_{e} interactions from the Fermilab Booster Neutrino Beam using the MicroBooNE liquid argon time projection chamber to address the nature of the excess of low energy interactions observed by the MiniBooNE Collaboration. Three independent ν_{e} searches are performed across multiple single electron final states, including an exclusive search for two-body scattering events with a single proton, a semi-inclusive search for pionless events, and a fully inclusive search for events containing all hadronic final states. With differing signal topologies, statistics, backgrounds, reconstruction algorithms, and analysis approaches, the results are found to be either consistent with or modestly lower than the nominal ν_{e} rate expectations from the Booster Neutrino Beam and no excess of ν_{e} events is observed.
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - R An
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - J Anthony
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | - A Ashkenazi
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Barnes
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - V Basque
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | | | | | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - A Bhat
- Syracuse University, Syracuse, New York 13244, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - D Caratelli
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Caro Terrazas
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y Chen
- Universität Bern, Bern CH-3012, Switzerland
| | - D Cianci
- Columbia University, New York, New York 10027, USA
| | - G H Collin
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - L Cooper-Troendle
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | | | | | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - G A Fiorentini Aguirre
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | | | - B T Fleming
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - N Foppiani
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - D Franco
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - V Genty
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - O Goodwin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - E Gramellini
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - P Green
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - A Hourlier
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - R Itay
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - L Jiang
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - J H Jo
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kaleko
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - N Kaneshige
- University of California, Santa Barbara, California 93106, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - R LaZur
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - A Lister
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - K Manivannan
- Syracuse University, Syracuse, New York 13244, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - K Mason
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - N McConkey
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - T Mettler
- Universität Bern, Bern CH-3012, Switzerland
| | - K Miller
- University of Chicago, Chicago, Illinois 60637, USA
| | - J Mills
- Tufts University, Medford, Massachusetts 02155, USA
| | - K Mistry
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - A Mogan
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Moon
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Mousseau
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Murphy
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - R K Neely
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Newmark
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - M Nunes
- Syracuse University, Syracuse, New York 13244, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - A Paudel
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Piasetzky
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - I D Ponce-Pinto
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - S Prince
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Rafique
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M Reggiani-Guzzo
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L C J Rice
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | | | - B Russell
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Tufts University, Medford, Massachusetts 02155, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - J Sinclair
- Universität Bern, Bern CH-3012, Switzerland
| | - A Smith
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - S R Soleti
- Harvard University, Cambridge, Massachusetts 02138, USA
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - P Spentzouris
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Sutton
- Columbia University, New York, New York 10027, USA
| | - S Sword-Fehlberg
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - M Thomson
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - W Van De Pontseele
- Harvard University, Cambridge, Massachusetts 02138, USA
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - Z Williams
- University of Texas, Arlington, Texas 76019, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - N Wright
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - W Wu
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Yarbrough
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - L E Yates
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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Dale DC, Alsina L, Azar A, Badolato R, Bertrand Y, Deya A, Dickerson KE, Ezra N, Hasle H, Kang HJ, Kiani-Alikhan S, Kuijpers T, Kulagin A, Langguth D, Levin C, Neth O, Peake J, Rutten CE, Shcherbina A, Tarrant TK, Vossen MG, Wysocki CA, Belschner A, Cadavid D, Hu Y, Jiang H, MacLeod R, Tang W, Tillinger M, Donadieu J. PB1938: 4WHIM: EVALUATING MAVORIXAFOR, AN ORAL CXCR4 ANTAGONIST, IN PATIENTS WITH WHIM SYNDROME VIA A GLOBAL PHASE 3, RANDOMIZED, PLACEBO-CONTROLLED TRIAL WITH OPEN-LABEL EXTENSION. Hemasphere 2022. [PMCID: PMC9431515 DOI: 10.1097/01.hs9.0000850592.82147.9b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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Ma B, Guo J, Chu H, De Biase A, Sourlos N, Tang W, Langendijk J, M P, van Ooijen A, Both S, Sijtsema N. PO-1777 Self-supervised image feature extraction for outcomes prediction in oropharyngeal cancer. Radiother Oncol 2022. [DOI: 10.1016/s0167-8140(22)03741-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Abratenko P, An R, Anthony J, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barnes C, Barr G, Basque V, Bathe-Peters L, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhat A, Bishai M, Blake A, Bolton T, Book JY, Camilleri L, Caratelli D, Caro Terrazas I, Cavanna F, Cerati G, Chen Y, Cianci D, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Dorrill R, Duffy K, Dytman S, Eberly B, Ereditato A, Evans JJ, Fine R, Fiorentini Aguirre GA, Fitzpatrick RS, Fleming BT, Foppiani N, Franco D, Furmanski AP, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Goodwin O, Gramellini E, Green P, Greenlee H, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hilgenberg C, Horton-Smith GA, Hourlier A, Itay R, James C, Ji X, Jiang L, Jo JH, Johnson RA, Jwa YJ, Kalra D, Kamp N, Kaneshige N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, Lepetic I, Li K, Li Y, Lin K, Littlejohn BR, Louis WC, Luo X, Manivannan K, Mariani C, Marsden D, Marshall J, Martinez Caicedo DA, Mason K, Mastbaum A, McConkey N, Meddage V, Mettler T, Miller K, Mills J, Mistry K, Mogan A, Mohayai T, Moon J, Mooney M, Moor AF, Moore CD, Mora Lepin L, Mousseau J, Murphy M, Naples D, Navrer-Agasson A, Nebot-Guinot M, Neely RK, Newmark DA, Nowak J, Nunes M, Palamara O, Paolone V, Papadopoulou A, Papavassiliou V, Pate SF, Patel N, Paudel A, Pavlovic Z, Piasetzky E, Ponce-Pinto ID, Prince S, Qian X, Raaf JL, Radeka V, Rafique A, Reggiani-Guzzo M, Ren L, Rice LCJ, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Sinclair J, Smith A, Snider EL, Soderberg M, Söldner-Rembold S, Spentzouris P, Spitz J, Stancari M, John JS, Strauss T, Sutton K, Sword-Fehlberg S, Szelc AM, Tang W, Terao K, Thorpe C, Totani D, Toups M, Tsai YT, Uchida MA, Usher T, Van De Pontseele W, Viren B, Weber M, Wei H, Williams Z, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wright N, Wu W, Yandel E, Yang T, Yarbrough G, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. First Measurement of Energy-Dependent Inclusive Muon Neutrino Charged-Current Cross Sections on Argon with the MicroBooNE Detector. Phys Rev Lett 2022; 128:151801. [PMID: 35499871 DOI: 10.1103/physrevlett.128.151801] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Accepted: 03/09/2022] [Indexed: 06/14/2023]
Abstract
We report a measurement of the energy-dependent total charged-current cross section σ(E_{ν}) for inclusive muon neutrinos scattering on argon, as well as measurements of flux-averaged differential cross sections as a function of muon energy and hadronic energy transfer (ν). Data corresponding to 5.3×10^{19} protons on target of exposure were collected using the MicroBooNE liquid argon time projection chamber located in the Fermilab booster neutrino beam with a mean neutrino energy of approximately 0.8 GeV. The mapping between the true neutrino energy E_{ν} and reconstructed neutrino energy E_{ν}^{rec} and between the energy transfer ν and reconstructed hadronic energy E_{had}^{rec} are validated by comparing the data and Monte Carlo (MC) predictions. In particular, the modeling of the missing hadronic energy and its associated uncertainties are verified by a new method that compares the E_{had}^{rec} distributions between data and a MC prediction after constraining the reconstructed muon kinematic distributions, energy, and polar angle to those of data. The success of this validation gives confidence that the missing energy in the MicroBooNE detector is well modeled and underpins first-time measurements of both the total cross section σ(E_{ν}) and the differential cross section dσ/dν on argon.
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - R An
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - J Anthony
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | | | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Barnes
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - V Basque
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | | | | | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - A Bhat
- Syracuse University, Syracuse, New York 13244, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - D Caratelli
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Caro Terrazas
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y Chen
- Universität Bern, Bern CH-3012, Switzerland
| | - D Cianci
- Columbia University, New York, New York 10027, USA
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - L Cooper-Troendle
- Department of Physics, Wright Laboratory, Yale University, New Haven, Connecticut 06520, USA
| | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | | | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - G A Fiorentini Aguirre
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | | | - B T Fleming
- Department of Physics, Wright Laboratory, Yale University, New Haven, Connecticut 06520, USA
| | - N Foppiani
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - D Franco
- Department of Physics, Wright Laboratory, Yale University, New Haven, Connecticut 06520, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - O Goodwin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - E Gramellini
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - P Green
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- Department of Physics, Wright Laboratory, Yale University, New Haven, Connecticut 06520, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - A Hourlier
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - R Itay
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - L Jiang
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - J H Jo
- Department of Physics, Wright Laboratory, Yale University, New Haven, Connecticut 06520, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - N Kaneshige
- University of California, Santa Barbara, California 93106, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - K Li
- Department of Physics, Wright Laboratory, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - K Manivannan
- Syracuse University, Syracuse, New York 13244, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - K Mason
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - N McConkey
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - T Mettler
- Universität Bern, Bern CH-3012, Switzerland
| | - K Miller
- University of Chicago, Chicago, Illinois 60637, USA
| | - J Mills
- Tufts University, Medford, Massachusetts 02155, USA
| | - K Mistry
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - A Mogan
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Moon
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Mousseau
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Murphy
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - R K Neely
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Newmark
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - M Nunes
- Syracuse University, Syracuse, New York 13244, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - A Paudel
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | | | - I D Ponce-Pinto
- Department of Physics, Wright Laboratory, Yale University, New Haven, Connecticut 06520, USA
| | - S Prince
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Rafique
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M Reggiani-Guzzo
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L C J Rice
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | | | - G Scanavini
- Department of Physics, Wright Laboratory, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Tufts University, Medford, Massachusetts 02155, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - J Sinclair
- Universität Bern, Bern CH-3012, Switzerland
| | - A Smith
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - P Spentzouris
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Sutton
- Columbia University, New York, New York 10027, USA
| | - S Sword-Fehlberg
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - W Van De Pontseele
- Harvard University, Cambridge, Massachusetts 02138, USA
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - Z Williams
- University of Texas, Arlington, Texas 76019, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - N Wright
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - W Wu
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Yarbrough
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - L E Yates
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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Abratenko P, An R, Anthony J, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barnes C, Barr G, Basque V, Bathe-Peters L, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhat A, Bishai M, Blake A, Bolton T, Book JY, Camilleri L, Caratelli D, Caro Terrazas I, Castillo Fernandez R, Cavanna F, Cerati G, Chen Y, Cianci D, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Dorrill R, Duffy K, Dytman S, Eberly B, Ereditato A, Evans JJ, Fine R, Fiorentini Aguirre GA, Fitzpatrick RS, Fleming BT, Foppiani N, Franco D, Furmanski AP, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Goodwin O, Gramellini E, Green P, Greenlee H, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hilgenberg C, Horton-Smith GA, Hourlier A, Itay R, James C, Ji X, Jiang L, Jo JH, Johnson RA, Jwa YJ, Kalra D, Kamp N, Kaneshige N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, LaZur R, Lepetic I, Li K, Li Y, Lin K, Littlejohn BR, Louis WC, Luo X, Manivannan K, Mariani C, Marsden D, Marshall J, Martinez Caicedo DA, Mason K, Mastbaum A, McConkey N, Meddage V, Mettler T, Miller K, Mills J, Mistry K, Mogan A, Mohayai T, Moon J, Mooney M, Moor AF, Moore CD, Mora Lepin L, Mousseau J, Murphy M, Murrells R, Naples D, Navrer-Agasson A, Nebot-Guinot M, Neely RK, Newmark DA, Nowak J, Nunes M, Palamara O, Paolone V, Papadopoulou A, Papavassiliou V, Pate SF, Patel N, Paudel A, Pavlovic Z, Piasetzky E, Ponce-Pinto ID, Prince S, Qian X, Raaf JL, Radeka V, Rafique A, Reggiani-Guzzo M, Ren L, Rice LCJ, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Sinclair J, Smith A, Snider EL, Soderberg M, Söldner-Rembold S, Spentzouris P, Spitz J, Stancari M, John JS, Strauss T, Sutton K, Sword-Fehlberg S, Szelc AM, Tang W, Terao K, Thorpe C, Totani D, Toups M, Tsai YT, Uchida MA, Usher T, Van De Pontseele W, Viren B, Weber M, Wei H, Williams Z, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wright N, Wu W, Yandel E, Yang T, Yarbrough G, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. Search for Neutrino-Induced Neutral-Current Δ Radiative Decay in MicroBooNE and a First Test of the MiniBooNE Low Energy Excess under a Single-Photon Hypothesis. Phys Rev Lett 2022; 128:111801. [PMID: 35363017 DOI: 10.1103/physrevlett.128.111801] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 02/10/2022] [Indexed: 06/14/2023]
Abstract
We report results from a search for neutrino-induced neutral current (NC) resonant Δ(1232) baryon production followed by Δ radiative decay, with a ⟨0.8⟩ GeV neutrino beam. Data corresponding to MicroBooNE's first three years of operations (6.80×10^{20} protons on target) are used to select single-photon events with one or zero protons and without charged leptons in the final state (1γ1p and 1γ0p, respectively). The background is constrained via an in situ high-purity measurement of NC π^{0} events, made possible via dedicated 2γ1p and 2γ0p selections. A total of 16 and 153 events are observed for the 1γ1p and 1γ0p selections, respectively, compared to a constrained background prediction of 20.5±3.65(syst) and 145.1±13.8(syst) events. The data lead to a bound on an anomalous enhancement of the normalization of NC Δ radiative decay of less than 2.3 times the predicted nominal rate for this process at the 90% confidence level (C.L.). The measurement disfavors a candidate photon interpretation of the MiniBooNE low-energy excess as a factor of 3.18 times the nominal NC Δ radiative decay rate at the 94.8% C.L., in favor of the nominal prediction, and represents a greater than 50-fold improvement over the world's best limit on single-photon production in NC interactions in the sub-GeV neutrino energy range.
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - R An
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - J Anthony
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | | | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Barnes
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - V Basque
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | | | | | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - A Bhat
- Syracuse University, Syracuse, New York 13244, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - D Caratelli
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Caro Terrazas
- Colorado State University, Fort Collins, Colorado 80523, USA
| | | | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y Chen
- Universität Bern, Bern CH-3012, Switzerland
| | - D Cianci
- Columbia University, New York, New York 10027, USA
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - L Cooper-Troendle
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | | | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - G A Fiorentini Aguirre
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | | | - B T Fleming
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - N Foppiani
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - D Franco
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - O Goodwin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - E Gramellini
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - P Green
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - A Hourlier
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - R Itay
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - L Jiang
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - J H Jo
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - N Kaneshige
- University of California, Santa Barbara, California 93106, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - R LaZur
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - K Manivannan
- Syracuse University, Syracuse, New York 13244, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - K Mason
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - N McConkey
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - T Mettler
- Universität Bern, Bern CH-3012, Switzerland
| | - K Miller
- University of Chicago, Chicago, Illinois 60637, USA
| | - J Mills
- Tufts University, Medford, Massachusetts 02155, USA
| | - K Mistry
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - A Mogan
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Moon
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Mousseau
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Murphy
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - R Murrells
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - R K Neely
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Newmark
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - M Nunes
- Syracuse University, Syracuse, New York 13244, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - A Paudel
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | | | - I D Ponce-Pinto
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - S Prince
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Rafique
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M Reggiani-Guzzo
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L C J Rice
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | | | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Tufts University, Medford, Massachusetts 02155, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - J Sinclair
- Universität Bern, Bern CH-3012, Switzerland
| | - A Smith
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - P Spentzouris
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Sutton
- Columbia University, New York, New York 10027, USA
| | - S Sword-Fehlberg
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - W Van De Pontseele
- Harvard University, Cambridge, Massachusetts 02138, USA
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - Z Williams
- University of Texas, Arlington, Texas 76019, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - N Wright
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - W Wu
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Yarbrough
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - L E Yates
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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Yang Q, Wang A, Luo J, Tang W. Improving ionic conductivity of polymer-based solid electrolytes for lithium metal batteries. Chin J Chem Eng 2022. [DOI: 10.1016/j.cjche.2021.07.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Chen S, Du Y, Hu Y, Ling R, Huang D, Xiang J, Liang Y, Wei X, Tang W, Guo Y. Preoperative MRI of breast squamous cell carcinoma: diagnostic value of distinguishing between two subtypes. Clin Radiol 2022; 77:e321-e328. [PMID: 35093233 DOI: 10.1016/j.crad.2021.12.018] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 12/03/2021] [Indexed: 11/03/2022]
Abstract
AIM To retrospectively analyse the clinical and MRI data of primary squamous cell carcinoma (SCC), particularly pure squamous cell carcinoma (PSCC) and mixed squamous cell carcinoma (MSCC). MATERIALS AND METHODS The MRI data and clinicopathological characteristics of 20 patients with histopathologically confirmed SCC of the breast, including eight PSCC patients and 12 MSCC patients, from multiple centres between January 2013 and December 2020 were analysed retrospectively. RESULTS Nine of 12 patients in the MSCC group showed hyperintensity on T1-weighted imaging (WI), while this feature was not observed in the PSCC group (p=0.001). Most of the PSCC group showed rim enhancement, whereas most of the MSCC group showed heterogeneous enhancement (p=0.007). In addition, there was no significant difference in the thickness of the rim enhancement and the percentage of necrotic components in the tumours between the two types of SCCs of the breast (p=0.545 and p=0.662, respectively). Four patients (4/12) in the MSCC group had sentinel lymph node metastasis, while only one patient (1/8) in the PSCC group showed lymph node metastasis (p=0.603). Metastatic disease occurred in 25% of patients with PSCC and in approximately 41.7% of patients with MSCC. CONCLUSION The signal on T1WI and internal enhancement characteristics were the key features for differentiating PSCC and MSCC. Therefore, MRI phenotypes may provide additional information for the pathological classification of breast SCC.
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Affiliation(s)
- S Chen
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - Y Du
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - Y Hu
- Breast Tumour Centre, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China
| | - R Ling
- Department of Radiology, Shenzhen People's Hospital, 2nd Clinical Medical College of Jinan University, 1st Affiliated Hospital of Southern University of Science and Technology, Shenzhen 518020, China
| | - D Huang
- Department of Breast Surgery, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - J Xiang
- Department of Radiology, Guangdong Women and Children Hospital, Guangzhou, Guangdong, 510010, China
| | - Y Liang
- Department of Pathology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - X Wei
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China.
| | - W Tang
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China.
| | - Y Guo
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China.
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Li L, Tang W, Zhao M, Gong B, Cao M, Li J. Study on the regulation mechanism of lipopolysaccharide on oxidative stress and lipid metabolism of bovine mammary epithelial cells. Physiol Res 2021; 70:777-785. [PMID: 34505530 DOI: 10.33549/physiolres.934682] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
The long-term feeding of a high-concentrate diet (the concentrate ratio is greater than 60 %) leads to mammary gland inflammatory response in ruminants and decreased quality in dairy cows and affects the robust development of the dairy industry. The main reason is closely related to elevated lipopolysaccharide (LPS) in the body. In this experiment, a bovine mammary epithelial cell line (MAC-T) was used as a model, and LPS at different concentrations (0 ng/ml, 1 ng/ml, 10 ng/ml, 100 ng/ml, 1000 ng/ml, 10000 ng/ml) was added to the cells. The cell survival rate, oxidative stress indicators, total lipid droplet area, triglyceride content and key genes regulating lipid metabolism were detected by 3-(4,5)-dimethylthiahiazo(-z-y1)-3,5-di-phenytetrazoliumromide (MTT), assay kit, microscope observation and RT-PCR methods to explore the regulatory mechanism of mammary health and milk fat synthesis. The results showed that compared with those of the control group, the survival rates of cells were significantly decreased after 9 h of stimulation with 1000 ng/ml and 10000 ng/ml LPS (P<0.01). The contents of superoxide dismutase (SOD), catalase (CAT) and total antioxidant capacity (T-AOC) in cells were significantly decreased (P<0.05). Compared with that of the control group, the content of malondialdehyde (MDA) in cells was significantly increased (P<0.05) after stimulation with 10000 ng/ml LPS for 9 h. After 9 h of stimulation with 100 ng/ml, 1000 ng/ml and 10000 ng/ml LPS, the total lipid drop area and triglyceride (TG) content of MAC-T cells were significantly decreased (P<0.05). The expression levels of fatty acid synthesis-related genes Acetyl-CoA carboxylase (ACC) and Stearoyl-CoA desaturase 1 (SCD-1) were significantly decreased after 9 h of stimulation with 100 ng/ml, 1000 ng/ml and 10000 ng/ml LPS (P<0.05), while the expression levels of Fatty Acid synthetase (FAS) were significantly decreased after stimulation with 1000 ng/ml and 10000 ng/ml LPS (P<0.05). TG synthesis by the related gene Diacylglycerol acyltransferase-1 (DGAT1) was significantly lower than that of the control group after stimulation with 1000 ng/ml and 10000 ng/ml LPS for 9 h (P<0.05), and Diacylglycerol acyltransferase-2 (DGAT2) also showed a significant decrease after 10000 ng/ml LPS stimulation (P<0.05). In conclusion, adding different concentrations of LPS to MAC-T cells not only led to a decrease in cell activity, resulting in oxidative damage, but also affected fatty acid and TG synthesis, which may ultimately be closely related to the decrease in milk fat synthesis.
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Affiliation(s)
- L Li
- School of Biological Science and Engineering, Xingtai University, Xingtai, China.
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Abratenko P, An R, Anthony J, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barnes C, Barr G, Basque V, Bathe-Peters L, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhat A, Bishai M, Blake A, Bolton T, Book JY, Camilleri L, Caratelli D, Caro Terrazas I, Castillo Fernandez R, Cavanna F, Cerati G, Chen Y, Cianci D, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Del Tutto M, Dennis SR, Devitt D, Diurba R, Dorrill R, Duffy K, Dytman S, Eberly B, Ereditato A, Evans JJ, Fine R, Fiorentini Aguirre GA, Fitzpatrick RS, Fleming BT, Foppiani N, Franco D, Furmanski AP, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Goodwin O, Gramellini E, Green P, Greenlee H, Gu W, Guenette R, Guzowski P, Hagaman L, Hall E, Hen O, Horton-Smith GA, Hourlier A, Itay R, James C, Ji X, Jiang L, Jo JH, Johnson RA, Jwa YJ, Kamp N, Kaneshige N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, LaZur R, Lepetic I, Li K, Li Y, Lin K, Littlejohn BR, Louis WC, Luo X, Manivannan K, Mariani C, Marsden D, Marshall J, Martinez Caicedo DA, Mason K, Mastbaum A, McConkey N, Meddage V, Mettler T, Miller K, Mills J, Mistry K, Mogan A, Mohayai T, Moon J, Mooney M, Moor AF, Moore CD, Mora Lepin L, Mousseau J, Murphy M, Naples D, Navrer-Agasson A, Neely RK, Nowak J, Nunes M, Palamara O, Paolone V, Papadopoulou A, Papavassiliou V, Pate SF, Paudel A, Pavlovic Z, Piasetzky E, Ponce-Pinto ID, Prince S, Qian X, Raaf JL, Radeka V, Rafique A, Reggiani-Guzzo M, Ren L, Rice LCJ, Rochester L, Rodriguez Rondon J, Rogers HE, Rosenberg M, Ross-Lonergan M, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Siegel H, Sinclair J, Smith A, Snider EL, Soderberg M, Söldner-Rembold S, Spentzouris P, Spitz J, Stancari M, John JS, Strauss T, Sutton K, Sword-Fehlberg S, Szelc AM, Tagg N, Tang W, Terao K, Thorpe C, Totani D, Toups M, Tsai YT, Uchida MA, Usher T, Van De Pontseele W, Viren B, Weber M, Wei H, Williams Z, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wright N, Wu W, Yandel E, Yang T, Yarbrough G, Yates LE, Zeller GP, Zennamo J, Zhang C. Search for a Higgs Portal Scalar Decaying to Electron-Positron Pairs in the MicroBooNE Detector. Phys Rev Lett 2021; 127:151803. [PMID: 34678031 DOI: 10.1103/physrevlett.127.151803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 08/11/2021] [Accepted: 09/10/2021] [Indexed: 06/13/2023]
Abstract
We present a search for the decays of a neutral scalar boson produced by kaons decaying at rest, in the context of the Higgs portal model, using the MicroBooNE detector. We analyze data triggered in time with the Fermilab NuMI neutrino beam spill, with an exposure of 1.93×10^{20} protons on target. We look for monoenergetic scalars that come from the direction of the NuMI hadron absorber, at a distance of 100 m from the detector, and decay to electron-positron pairs. We observe one candidate event, with a standard model background prediction of 1.9±0.8. We set an upper limit on the scalar-Higgs mixing angle of θ<(3.3-4.6)×10^{-4} at the 95% confidence level for scalar boson masses in the range (100-200) MeV/c^{2}. We exclude, at the 95% confidence level, the remaining model parameters required to explain the central value of a possible excess of K_{L}^{0}→π^{0}νν[over ¯] decays reported by the KOTO collaboration. We also provide a model-independent limit on a new boson X produced in K→πX decays and decaying to e^{+}e^{-}.
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - R An
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - J Anthony
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | - A Ashkenazi
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tel Aviv University, Tel Aviv 69978, Israel
| | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Barnes
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - V Basque
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | | | | | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - A Bhat
- Syracuse University, Syracuse, New York 13244, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - D Caratelli
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Caro Terrazas
- Colorado State University, Fort Collins, Colorado 80523, USA
| | | | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y Chen
- Universität Bern, Bern CH-3012, Switzerland
| | - D Cianci
- Columbia University, New York, New York 10027, USA
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - L Cooper-Troendle
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - D Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | | | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - G A Fiorentini Aguirre
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | | | - B T Fleming
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - N Foppiani
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - D Franco
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - O Goodwin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - E Gramellini
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - P Green
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - E Hall
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | | | - A Hourlier
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - R Itay
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - L Jiang
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - J H Jo
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - N Kaneshige
- University of California, Santa Barbara, California 93106, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - R LaZur
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - K Manivannan
- Syracuse University, Syracuse, New York 13244, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - K Mason
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - N McConkey
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - T Mettler
- Universität Bern, Bern CH-3012, Switzerland
| | - K Miller
- University of Chicago, Chicago, Illinois 60637, USA
| | - J Mills
- Tufts University, Medford, Massachusetts 02155, USA
| | - K Mistry
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - A Mogan
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Moon
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Mousseau
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Murphy
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R K Neely
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - M Nunes
- Syracuse University, Syracuse, New York 13244, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - A Paudel
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | | | - I D Ponce-Pinto
- Columbia University, New York, New York 10027, USA
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - S Prince
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Rafique
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M Reggiani-Guzzo
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L C J Rice
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - H E Rogers
- St. Catherine University, Saint Paul, Minnesota 55105, USA
| | - M Rosenberg
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | | | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Tufts University, Medford, Massachusetts 02155, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - H Siegel
- Columbia University, New York, New York 10027, USA
| | - J Sinclair
- Universität Bern, Bern CH-3012, Switzerland
| | - A Smith
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - P Spentzouris
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Sutton
- Columbia University, New York, New York 10027, USA
| | - S Sword-Fehlberg
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - N Tagg
- Otterbein University, Westerville, Ohio 43081, USA
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - W Van De Pontseele
- Harvard University, Cambridge, Massachusetts 02138, USA
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - Z Williams
- University of Texas, Arlington, Texas 76019, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - N Wright
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - W Wu
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Yarbrough
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - L E Yates
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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Abratenko P, Alrashed M, An R, Anthony J, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barnes C, Barr G, Basque V, Bathe-Peters L, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhat A, Bishai M, Blake A, Bolton T, Camilleri L, Caratelli D, Caro Terrazas I, Castillo Fernandez R, Cavanna F, Cerati G, Chen Y, Church E, Cianci D, Conrad J, Convery M, Cooper-Troendle L, Crespo-Anadón J, Del Tutto M, Dennis S, Devitt D, Diurba R, Domine L, Dorrill R, Duffy K, Dytman S, Eberly B, Ereditato A, Escudero Sanchez L, Evans J, Fiorentini Aguirre G, Fitzpatrick R, Fleming B, Foppiani N, Franco D, Furmanski A, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Goodwin O, Gramellini E, Green P, Greenlee H, Gu W, Guenette R, Guzowski P, Hagaman L, Hall E, Hamilton P, Hen O, Hill C, Horton-Smith G, Hourlier A, Itay R, James C, Jan de Vries J, Ji X, Jiang L, Jo J, Johnson R, Jwa YJ, Kamp N, Kaneshige N, Karagiorgi G, Ketchum W, Kirby B, Kirby M, Kobilarcik T, Kreslo I, LaZur R, Lepetic I, Li K, Li Y, Littlejohn B, Lorca D, Louis W, Luo X, Marchionni A, Mariani C, Marsden D, Marshall J, Martin-Albo J, Martinez Caicedo D, Mason K, Mastbaum A, McConkey N, Meddage V, Mettler T, Miller K, Mills J, Mistry K, Mogan A, Mohayai T, Moon J, Mooney M, Moor A, Moore C, Mora Lepin L, Mousseau J, Murphy M, Naples D, Navrer-Agasson A, Neely R, Nienaber P, Nowak J, Palamara O, Paolone V, Papadopoulou A, Papavassiliou V, Pate S, Paudel A, Pavlovic Z, Piasetzky E, Ponce-Pinto I, Porzio D, Prince S, Qian X, Raaf J, Radeka V, Rafique A, Reggiani-Guzzo M, Ren L, Rochester L, Rodriguez Rondon J, Rogers H, Rosenberg M, Ross-Lonergan M, Russell B, Scanavini G, Schmitz D, Schukraft A, Seligman W, Shaevitz M, Sharankova R, Sinclair J, Smith A, Snider E, Soderberg M, Söldner-Rembold S, Soleti S, Spentzouris P, Spitz J, Stancari M, John J, Strauss T, Sutton K, Sword-Fehlberg S, Szelc A, Tagg N, Tang W, Terao K, Thorpe C, Toups M, Tsai YT, Uchida M, Usher T, Van De Pontseele W, Viren B, Weber M, Wei H, Williams Z, Wolbers S, Wongjirad T, Wospakrik M, Wu W, Yandel E, Yang T, Yarbrough G, Yates L, Zeller G, Zennamo J, Zhang C. Measurement of the flux-averaged inclusive charged-current electron neutrino and antineutrino cross section on argon using the NuMI beam and the MicroBooNE detector. Int J Clin Exp Med 2021. [DOI: 10.1103/physrevd.104.052002] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Qiu M, Guo Y, Guo W, Nian W, Liao W, Xu Z, Zhang W, Zhang Y, Wei X, Xue L, Tang W, Wu Y, Ren G, Wang L, Xi J, Wang Y, Li M, Hausheer F, Hu C, Xu R. 905P FIH phase I dose escalation and dose expansion study of anti-EGFR ADC MRG003 in patients with advanced solid tumors. Ann Oncol 2021. [DOI: 10.1016/j.annonc.2021.08.1315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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Zhang X, Wang Z, Wang X, Tang W, Liu R, Bao H, Chen X, Wu S, Wu X, Shao Y, Fan J, Zhou J. 950P Ultra-sensitive and cost-effective method for early stage hepatocellular carcinoma and intrahepatic cholangiocarcinoma detection using plasma cfDNA fragmentomic profiles. Ann Oncol 2021. [DOI: 10.1016/j.annonc.2021.08.170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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Guo Y, Xue J, Peng W, Xue L, Ge X, Zhao W, Tang W, Nian W, Li Q, Zhang S, Sun J, Li M, Hausheer F, Hu C, Li J. 271P First-in-human, phase I dose escalation and expansion study of anti-HER2 ADC MRG002 in patients with HER2 positive solid tumors. Ann Oncol 2021. [DOI: 10.1016/j.annonc.2021.08.554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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Acciarri R, Adams C, Andreopoulos C, Asaadi J, Babicz M, Backhouse C, Badgett W, Bagby L, Barker D, Basque V, Bazetto MCQ, Betancourt M, Bhanderi A, Bhat A, Bonifazi C, Brailsford D, Brandt AG, Brooks T, Carneiro MF, Chen Y, Chen H, Chisnall G, Crespo-Anadón JI, Cristaldo E, Cuesta C, de Icaza Astiz IL, De Roeck A, de Sá Pereira G, Del Tutto M, Di Benedetto V, Ereditato A, Evans JJ, Ezeribe AC, Fitzpatrick RS, Fleming BT, Foreman W, Franco D, Furic I, Furmanski AP, Gao S, Garcia-Gamez D, Frandini H, Ge G, Gil-Botella I, Gollapinni S, Goodwin O, Green P, Griffith WC, Guenette R, Guzowski P, Ham T, Henzerling J, Holin A, Howard B, Jones RS, Kalra D, Karagiorgi G, Kashur L, Ketchum W, Kim MJ, Kudryavtsev VA, Larkin J, Lay H, Lepetic I, Littlejohn BR, Louis WC, Machado AA, Malek M, Mardsen D, Mariani C, Marinho F, Mastbaum A, Mavrokoridis K, McConkey N, Meddage V, Méndez DP, Mettler T, Mistry K, Mogan A, Molina J, Mooney M, Mora L, Moura CA, Mousseau J, Navrer-Agasson A, Nicolas-Arnaldos FJ, Nowak JA, Palamara O, Pandey V, Pater J, Paulucci L, Pimentel VL, Psihas F, Putnam G, Qian X, Raguzin E, Ray H, Reggiani-Guzzo M, Rivera D, Roda M, Ross-Lonergan M, Scanavini G, Scarff A, Schmitz DW, Schukraft A, Segreto E, Soares Nunes M, Soderberg M, Söldner-Rembold S, Spitz J, Spooner NJC, Stancari M, Stenico GV, Szelc A, Tang W, Tena Vidal J, Torretta D, Toups M, Touramanis C, Tripathi M, Tufanli S, Tyley E, Valdiviesso GA, Worcester E, Worcester M, Yarbrough G, Yu J, Zamorano B, Zennamo J, Zglam A. Cosmic Ray Background Removal With Deep Neural Networks in SBND. Front Artif Intell 2021; 4:649917. [PMID: 34505055 PMCID: PMC8421797 DOI: 10.3389/frai.2021.649917] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 03/23/2021] [Indexed: 11/13/2022] Open
Abstract
In liquid argon time projection chambers exposed to neutrino beams and running on or near surface levels, cosmic muons, and other cosmic particles are incident on the detectors while a single neutrino-induced event is being recorded. In practice, this means that data from surface liquid argon time projection chambers will be dominated by cosmic particles, both as a source of event triggers and as the majority of the particle count in true neutrino-triggered events. In this work, we demonstrate a novel application of deep learning techniques to remove these background particles by applying deep learning on full detector images from the SBND detector, the near detector in the Fermilab Short-Baseline Neutrino Program. We use this technique to identify, on a pixel-by-pixel level, whether recorded activity originated from cosmic particles or neutrino interactions.
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Affiliation(s)
- R. Acciarri
- Fermi National Accelerator Laboratory, Batavia, IL, United States
| | - C. Adams
- Argonne National Laboratory, Lemont, IL, United States
| | - C. Andreopoulos
- University of Liverpool, Liverpool, United Kingdom
- STFC, Rutherford Appleton Laboratory, Harwell, United Kingdom
| | - J. Asaadi
- University of Texas at Arlington, Arlington, TX, United States
| | - M. Babicz
- CERN, European Organization for Nuclear Research, Geneva, Switzerland
| | - C. Backhouse
- University College London, London, United Kingdom
| | - W. Badgett
- Fermi National Accelerator Laboratory, Batavia, IL, United States
| | - L. Bagby
- Fermi National Accelerator Laboratory, Batavia, IL, United States
| | - D. Barker
- Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom
| | - V. Basque
- University of Manchester, Manchester, United Kingdom
| | - M. C. Q. Bazetto
- Universidade Estadual de Campinas, Campinas, Brazil
- Center for Information Technology Renato Archer Campinas, Campinas, Brazil
| | - M. Betancourt
- Fermi National Accelerator Laboratory, Batavia, IL, United States
| | - A. Bhanderi
- University of Manchester, Manchester, United Kingdom
| | - A. Bhat
- Syracuse University, Syracuse, NY, United States
| | - C. Bonifazi
- Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | | | - A. G. Brandt
- University of Texas at Arlington, Arlington, TX, United States
| | - T. Brooks
- Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom
| | - M. F. Carneiro
- Brookhaven National Laboratory, Upton, NY, United States
| | - Y. Chen
- Universität Bern, Bern, Switzerland
| | - H. Chen
- Brookhaven National Laboratory, Upton, NY, United States
| | - G. Chisnall
- University of Sussex, Brighton, United Kingdom
| | - J. I. Crespo-Anadón
- CIEMAT, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, Madrid, Spain
| | - E. Cristaldo
- FIUNA Facultad de Ingeniería, Universidad Nacional de Asunción, San Lorenzo, Paraguay
| | - C. Cuesta
- CIEMAT, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, Madrid, Spain
| | | | - A. De Roeck
- CERN, European Organization for Nuclear Research, Geneva, Switzerland
| | - G. de Sá Pereira
- University of Liverpool, Liverpool, United Kingdom
- STFC, Rutherford Appleton Laboratory, Harwell, United Kingdom
| | - M. Del Tutto
- Fermi National Accelerator Laboratory, Batavia, IL, United States
| | - V. Di Benedetto
- Fermi National Accelerator Laboratory, Batavia, IL, United States
| | | | - J. J. Evans
- University of Manchester, Manchester, United Kingdom
| | - A. C. Ezeribe
- Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom
| | | | - B. T. Fleming
- Wright Laboratory, Department of Physics, Yale University, New Haven, CT, United States
| | - W. Foreman
- Illinois Institute of Technology, Chicago, IL, United States
| | - D. Franco
- Wright Laboratory, Department of Physics, Yale University, New Haven, CT, United States
| | - I. Furic
- University of Florida, Gainesville, FL, United States
| | | | - S. Gao
- Brookhaven National Laboratory, Upton, NY, United States
| | | | - H. Frandini
- Universidade Estadual de Campinas, Campinas, Brazil
| | - G. Ge
- Columbia University, New York, NY, United States
| | - I. Gil-Botella
- CIEMAT, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, Madrid, Spain
| | - S. Gollapinni
- Los Alamos National Laboratory, Los Alamos, NM, United States
- University of Tennessee, Knoxville, TN, United States
| | - O. Goodwin
- University of Manchester, Manchester, United Kingdom
| | - P. Green
- University of Manchester, Manchester, United Kingdom
| | | | - R. Guenette
- Harvard University, Cambridge, MA, United States
| | - P. Guzowski
- University of Manchester, Manchester, United Kingdom
| | - T. Ham
- University of Liverpool, Liverpool, United Kingdom
| | | | - A. Holin
- University College London, London, United Kingdom
| | - B. Howard
- Fermi National Accelerator Laboratory, Batavia, IL, United States
| | - R. S. Jones
- University of Liverpool, Liverpool, United Kingdom
| | - D. Kalra
- Columbia University, New York, NY, United States
| | | | - L. Kashur
- Colorado State University, Fort Collins, CO, United States
| | - W. Ketchum
- Fermi National Accelerator Laboratory, Batavia, IL, United States
| | - M. J. Kim
- Fermi National Accelerator Laboratory, Batavia, IL, United States
| | - V. A. Kudryavtsev
- Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom
| | - J. Larkin
- Brookhaven National Laboratory, Upton, NY, United States
| | - H. Lay
- Lancaster University, Lancaster, United Kingdom
| | - I. Lepetic
- Rutgers University, Piscataway, NJ, United States
| | | | - W. C. Louis
- Los Alamos National Laboratory, Los Alamos, NM, United States
| | | | - M. Malek
- Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom
| | - D. Mardsen
- University of Manchester, Manchester, United Kingdom
| | - C. Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, VA, United States
| | - F. Marinho
- Universidade Federal de São Carlos, Araras, Brazil
| | - A. Mastbaum
- Rutgers University, Piscataway, NJ, United States
| | | | - N. McConkey
- University of Manchester, Manchester, United Kingdom
| | - V. Meddage
- University of Florida, Gainesville, FL, United States
| | - D. P. Méndez
- Brookhaven National Laboratory, Upton, NY, United States
| | | | - K. Mistry
- University of Manchester, Manchester, United Kingdom
| | - A. Mogan
- University of Tennessee, Knoxville, TN, United States
| | - J. Molina
- FIUNA Facultad de Ingeniería, Universidad Nacional de Asunción, San Lorenzo, Paraguay
| | - M. Mooney
- Colorado State University, Fort Collins, CO, United States
| | - L. Mora
- University of Manchester, Manchester, United Kingdom
| | - C. A. Moura
- Universidade Federal do ABC, Santo André, Brazil
| | - J. Mousseau
- University of Michigan, Ann Arbor, MI, United States
| | | | | | - J. A. Nowak
- Lancaster University, Lancaster, United Kingdom
| | - O. Palamara
- Fermi National Accelerator Laboratory, Batavia, IL, United States
| | - V. Pandey
- University of Florida, Gainesville, FL, United States
| | - J. Pater
- University of Manchester, Manchester, United Kingdom
| | - L. Paulucci
- Universidade Federal do ABC, Santo André, Brazil
| | - V. L. Pimentel
- Universidade Estadual de Campinas, Campinas, Brazil
- Center for Information Technology Renato Archer Campinas, Campinas, Brazil
| | - F. Psihas
- Fermi National Accelerator Laboratory, Batavia, IL, United States
| | - G. Putnam
- Enrico Fermi Institute, University of Chicago, Chicago, IL, United States
| | - X. Qian
- Brookhaven National Laboratory, Upton, NY, United States
| | - E. Raguzin
- Brookhaven National Laboratory, Upton, NY, United States
| | - H. Ray
- University of Florida, Gainesville, FL, United States
| | | | - D. Rivera
- University of Pennsylvania, Philadelphia, PA, United States
| | - M. Roda
- University of Liverpool, Liverpool, United Kingdom
| | | | - G. Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, CT, United States
| | - A. Scarff
- Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom
| | - D. W. Schmitz
- Enrico Fermi Institute, University of Chicago, Chicago, IL, United States
| | - A. Schukraft
- Fermi National Accelerator Laboratory, Batavia, IL, United States
| | - E. Segreto
- Universidade Estadual de Campinas, Campinas, Brazil
| | | | - M. Soderberg
- Syracuse University, Syracuse, NY, United States
| | | | - J. Spitz
- University of Michigan, Ann Arbor, MI, United States
| | - N. J. C. Spooner
- Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom
| | - M. Stancari
- Fermi National Accelerator Laboratory, Batavia, IL, United States
| | | | - A. Szelc
- University of Manchester, Manchester, United Kingdom
| | - W. Tang
- University of Tennessee, Knoxville, TN, United States
| | | | - D. Torretta
- Fermi National Accelerator Laboratory, Batavia, IL, United States
| | - M. Toups
- Fermi National Accelerator Laboratory, Batavia, IL, United States
| | | | - M. Tripathi
- University of Florida, Gainesville, FL, United States
| | - S. Tufanli
- CERN, European Organization for Nuclear Research, Geneva, Switzerland
| | - E. Tyley
- Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom
| | | | - E. Worcester
- Brookhaven National Laboratory, Upton, NY, United States
| | - M. Worcester
- Brookhaven National Laboratory, Upton, NY, United States
| | - G. Yarbrough
- University of Tennessee, Knoxville, TN, United States
| | - J. Yu
- University of Texas at Arlington, Arlington, TX, United States
| | | | - J. Zennamo
- Fermi National Accelerator Laboratory, Batavia, IL, United States
| | - A. Zglam
- Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom
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