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Pennap D, Swain RS, Akhtar S, Liao J, Wei Y, Li J, Wernecke M, MaCurdy TE, Kelman JA, Mosholder AD, Graham DJ. Comparing the Centers for Medicare and Medicaid Services (CMS) enrollment data death dates to the National Death Index (NDI). Pharmacoepidemiol Drug Saf 2024; 33:e5772. [PMID: 38449020 DOI: 10.1002/pds.5772] [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] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 02/07/2024] [Accepted: 02/08/2024] [Indexed: 03/08/2024]
Abstract
PURPOSE In the United States, the National Death Index (NDI) is the most complete source of death information, while epidemiologic studies with mortality outcomes often rely on U.S. Medicare data for outcome ascertainment. The purpose of this study was to assess the agreement of death information between the Centers for Medicare & Medicaid Services (CMS) Medicare enrolment data and NDI. METHODS Using Medicare and NDI data from 1999 through 2016, we identified Medicare beneficiaries who were reported dead in the CMS Medicare enrolment database (EDB) and Common Medicare Environment (CME), linked these beneficiaries to the NDI using CMS Health Insurance Claim number, and compared death dates between the two data sources. To assess agreement between our data sources, we calculated kappa scores; where a kappa of 1 indicates perfect agreement and a kappa of 0 indicates agreement equivalent to chance. We also examined CMS to NDI linkage and death date matching for stability over time. RESULTS Of the 36 785 640, Medicare beneficiaries reported dead in CMS enrollment data from 1999 to 2016, 97.5% were linked to the NDI. A kappa score of 0.98 showed a near perfect agreement between NDI and CMS reported deaths. The percentage of linked cases exactly matching on death dates increased from 94.8% in 1999 to 99.4% in 2016. CONCLUSIONS Our findings suggest strong concordance between death dates as recorded by CMS enrollment data and the NDI in the entire Medicare population.
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Affiliation(s)
- Dinci Pennap
- Formerly Division of Epidemiology, U.S. Food and Drug Administration, Center for Drug Evaluation and Research, Silver Spring, Maryland, USA
| | - Richard S Swain
- Formerly Division of Epidemiology, U.S. Food and Drug Administration, Center for Drug Evaluation and Research, Silver Spring, Maryland, USA
| | | | | | - Yuqin Wei
- Acumen LLC, Burlingame, California, USA
| | - Jiaqi Li
- Acumen LLC, Burlingame, California, USA
| | | | - Thomas E MaCurdy
- Acumen LLC, Burlingame, California, USA
- Department of Economics, Stanford University, Stanford, California, USA
| | - Jeffrey A Kelman
- Centers for Medicare and Medicaid Services, Washington, District of Columbia, USA
| | - Andrew D Mosholder
- U.S. Food and Drug Administration, Center for Drug Evaluation and Research, Silver Spring, Maryland, USA
| | - David J Graham
- U.S. Food and Drug Administration, Center for Drug Evaluation and Research, Silver Spring, Maryland, USA
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Kasi PM, Bucheit LA, Liao J, Starr J, Barata P, Klempner SJ, Gandara D, Shergill A, Madeira da Silva L, Weipert C, Zhang N, Pretz C, Hardin A, Kiedrowski LA, Odegaard JI. Pan-Cancer Prevalence of Microsatellite Instability-High (MSI-H) Identified by Circulating Tumor DNA and Associated Real-World Clinical Outcomes. JCO Precis Oncol 2023; 7:e2300118. [PMID: 37769226 DOI: 10.1200/po.23.00118] [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: 03/09/2023] [Revised: 07/19/2023] [Accepted: 08/07/2023] [Indexed: 09/30/2023] Open
Abstract
PURPOSE Immune checkpoint inhibitors are approved for advanced solid tumors with microsatellite instability-high (MSI-H). Although several technologies can assess MSI-H status, detection and outcomes with circulating tumor DNA (ctDNA)-detected MSI-H are lacking. As such, we examined pan-cancer MSI-H prevalence across 21 cancers and outcomes after ctDNA-detected MSI-H. METHODS Patients with advanced cancer who had ctDNA testing (Guardant360) from October 1, 2018, to June 30, 2022, were retrospectively assessed for prevalence. GuardantINFORM, which includes anonymized genomic and structured payer claims data, was queried to assess outcomes. Patients who initiated new treatment within 90 days of MSI-H detection were sorted into immunotherapy included in treatment (IO) or no immunotherapy included (non-IO) groups. Real-world time to treatment discontinuation (rwTTD) and real-world time to next treatment (rwTTNT) were assessed in months as proxies of progression-free survival (PFS); real-world overall survival (rwOS) was assessed in months. Cox regression tests analyzed differences. Colorectal cancer, non-small-cell lung cancer (NSCLC), prostate cancer, gastroesophageal cancer, and uterine cancer (UC) were assessed independently; all other cancers were grouped. RESULTS In total, 1.4% of 171,881 patients had MSI-H detected. Of 770 patients with outcomes available, rwTTD and rwTTNT were significantly longer for patients who received IO compared with non-IO for all cancers (P ≤ .05; hazard ratio [HR] range, 0.31-0.52 and 0.25-0.54, respectively) except NSCLC. rwOS had limited follow-up for all cohorts except UC (IO 39 v non-IO 23 months; HR, 0.18; P = .004); however, there was a consistent trend toward prolonged OS in IO-treated patients. CONCLUSION These data support use of a well-validated ctDNA assay to detect MSI-H across solid tumors and suggest prolonged PFS in patients treated with IO-containing regimens after detection. Tumor-agnostic, ctDNA-based MSI testing may be reliable for rapid decision making.
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Affiliation(s)
| | | | | | | | - Pedro Barata
- Case Western Reserve University/University Hospitals, Cleveland, OH
| | | | - David Gandara
- UC Davis Comprehensive Cancer Center, Sacramento, CA
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Aalbers J, Akerib DS, Akerlof CW, Al Musalhi AK, Alder F, Alqahtani A, Alsum SK, Amarasinghe CS, Ames A, Anderson TJ, Angelides N, Araújo HM, Armstrong JE, Arthurs M, Azadi S, Bailey AJ, Baker A, Balajthy J, Balashov S, Bang J, Bargemann JW, Barry MJ, Barthel J, Bauer D, Baxter A, Beattie K, Belle J, Beltrame P, Bensinger J, Benson T, Bernard EP, Bhatti A, Biekert A, Biesiadzinski TP, Birch HJ, Birrittella B, Blockinger GM, Boast KE, Boxer B, Bramante R, Brew CAJ, Brás P, Buckley JH, Bugaev VV, Burdin S, Busenitz JK, Buuck M, Cabrita R, Carels C, Carlsmith DL, Carlson B, Carmona-Benitez MC, Cascella M, Chan C, Chawla A, Chen H, Cherwinka JJ, Chott NI, Cole A, Coleman J, Converse MV, Cottle A, Cox G, Craddock WW, Creaner O, Curran D, Currie A, Cutter JE, Dahl CE, David A, Davis J, Davison TJR, Delgaudio J, Dey S, de Viveiros L, Dobi A, Dobson JEY, Druszkiewicz E, Dushkin A, Edberg TK, Edwards WR, Elnimr MM, Emmet WT, Eriksen SR, Faham CH, Fan A, Fayer S, Fearon NM, Fiorucci S, Flaecher H, Ford P, Francis VB, Fraser ED, Fruth T, Gaitskell RJ, Gantos NJ, Garcia D, Geffre A, Gehman VM, Genovesi J, Ghag C, Gibbons R, Gibson E, Gilchriese MGD, Gokhale S, Gomber B, Green J, Greenall A, Greenwood S, van der Grinten MGD, Gwilliam CB, Hall CR, Hans S, Hanzel K, Harrison A, Hartigan-O'Connor E, Haselschwardt SJ, Hernandez MA, Hertel SA, Heuermann G, Hjemfelt C, Hoff MD, Holtom E, Hor JYK, Horn M, Huang DQ, Hunt D, Ignarra CM, Jacobsen RG, Jahangir O, James RS, Jeffery SN, Ji W, Johnson J, Kaboth AC, Kamaha AC, Kamdin K, Kasey V, Kazkaz K, Keefner J, Khaitan D, Khaleeq M, Khazov A, Khurana I, Kim YD, Kocher CD, Kodroff D, Korley L, Korolkova EV, Kras J, Kraus H, Kravitz S, Krebs HJ, Kreczko L, Krikler B, Kudryavtsev VA, Kyre S, Landerud B, Leason EA, Lee C, Lee J, Leonard DS, Leonard R, Lesko KT, Levy C, Li J, Liao FT, Liao J, Lin J, Lindote A, Linehan R, Lippincott WH, Liu R, Liu X, Liu Y, Loniewski C, Lopes MI, Lopez Asamar E, López Paredes B, Lorenzon W, Lucero D, Luitz S, Lyle JM, Majewski PA, Makkinje J, Malling DC, Manalaysay A, Manenti L, Mannino RL, Marangou N, Marzioni MF, Maupin C, McCarthy ME, McConnell CT, McKinsey DN, McLaughlin J, Meng Y, Migneault J, Miller EH, Mizrachi E, Mock JA, Monte A, Monzani ME, Morad JA, Morales Mendoza JD, Morrison E, Mount BJ, Murdy M, Murphy ASJ, Naim D, Naylor A, Nedlik C, Nehrkorn C, Neves F, Nguyen A, Nikoleyczik JA, Nilima A, O'Dell J, O'Neill FG, O'Sullivan K, Olcina I, Olevitch MA, Oliver-Mallory KC, Orpwood J, Pagenkopf D, Pal S, Palladino KJ, Palmer J, Pangilinan M, Parveen N, Patton SJ, Pease EK, Penning B, Pereira C, Pereira G, Perry E, Pershing T, Peterson IB, Piepke A, Podczerwinski J, Porzio D, Powell S, Preece RM, Pushkin K, Qie Y, Ratcliff BN, Reichenbacher J, Reichhart L, Rhyne CA, Richards A, Riffard Q, Rischbieter GRC, Rodrigues JP, Rodriguez A, Rose HJ, Rosero R, Rossiter P, Rushton T, Rutherford G, Rynders D, Saba JS, Santone D, Sazzad ABMR, Schnee RW, Scovell PR, Seymour D, Shaw S, Shutt T, Silk JJ, Silva C, Sinev G, Skarpaas K, Skulski W, Smith R, Solmaz M, Solovov VN, Sorensen P, Soria J, Stancu I, Stark MR, Stevens A, Stiegler TM, Stifter K, Studley R, Suerfu B, Sumner TJ, Sutcliffe P, Swanson N, Szydagis M, Tan M, Taylor DJ, Taylor R, Taylor WC, Temples DJ, Tennyson BP, Terman PA, Thomas KJ, Tiedt DR, Timalsina M, To WH, Tomás A, Tong Z, Tovey DR, Tranter J, Trask M, Tripathi M, Tronstad DR, Tull CE, Turner W, Tvrznikova L, Utku U, Va'vra J, Vacheret A, Vaitkus AC, Verbus JR, Voirin E, Waldron WL, Wang A, Wang B, Wang JJ, Wang W, Wang Y, Watson JR, Webb RC, White A, White DT, White JT, White RG, Whitis TJ, Williams M, Wisniewski WJ, Witherell MS, Wolfs FLH, Wolfs JD, Woodford S, Woodward D, Worm SD, Wright CJ, Xia Q, Xiang X, Xiao Q, Xu J, Yeh M, Yin J, Young I, Zarzhitsky P, Zuckerman A, Zweig EA. First Dark Matter Search Results from the LUX-ZEPLIN (LZ) Experiment. Phys Rev Lett 2023; 131:041002. [PMID: 37566836 DOI: 10.1103/physrevlett.131.041002] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 03/06/2023] [Accepted: 06/07/2023] [Indexed: 08/13/2023]
Abstract
The LUX-ZEPLIN experiment is a dark matter detector centered on a dual-phase xenon time projection chamber operating at the Sanford Underground Research Facility in Lead, South Dakota, USA. This Letter reports results from LUX-ZEPLIN's first search for weakly interacting massive particles (WIMPs) with an exposure of 60 live days using a fiducial mass of 5.5 t. A profile-likelihood ratio analysis shows the data to be consistent with a background-only hypothesis, setting new limits on spin-independent WIMP-nucleon, spin-dependent WIMP-neutron, and spin-dependent WIMP-proton cross sections for WIMP masses above 9 GeV/c^{2}. The most stringent limit is set for spin-independent scattering at 36 GeV/c^{2}, rejecting cross sections above 9.2×10^{-48} cm at the 90% confidence level.
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Affiliation(s)
- J Aalbers
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - D S Akerib
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - C W Akerlof
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
| | - A K Al Musalhi
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - F Alder
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - A Alqahtani
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - S K Alsum
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - C S Amarasinghe
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
| | - A Ames
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - T J Anderson
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - N Angelides
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - H M Araújo
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - J E Armstrong
- University of Maryland, Department of Physics, College Park, Maryland 20742-4111, USA
| | - M Arthurs
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
| | - S Azadi
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
| | - A J Bailey
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - A Baker
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - J Balajthy
- University of California, Davis, Department of Physics, Davis, California 95616-5270, USA
| | - S Balashov
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - J Bang
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - J W Bargemann
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
| | - M J Barry
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - J Barthel
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - D Bauer
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - A Baxter
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - K Beattie
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - J Belle
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510-5011, USA
| | - P Beltrame
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
- University of Edinburgh, SUPA, School of Physics and Astronomy, Edinburgh EH9 3FD, United Kingdom
| | - J Bensinger
- Brandeis University, Department of Physics, Waltham, Massachusetts 02453, USA
| | - T Benson
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - E P Bernard
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - A Bhatti
- University of Maryland, Department of Physics, College Park, Maryland 20742-4111, USA
| | - A Biekert
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - T P Biesiadzinski
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - H J Birch
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - B Birrittella
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - G M Blockinger
- University at Albany (SUNY), Department of Physics, Albany, New York 12222-0100, USA
| | - K E Boast
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - B Boxer
- University of California, Davis, Department of Physics, Davis, California 95616-5270, USA
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - R Bramante
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - C A J Brew
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - P Brás
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - J H Buckley
- Washington University in St. Louis, Department of Physics, St. Louis, Missouri 63130-4862, USA
| | - V V Bugaev
- Washington University in St. Louis, Department of Physics, St. Louis, Missouri 63130-4862, USA
| | - S Burdin
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - J K Busenitz
- University of Alabama, Department of Physics and Astronomy, Tuscaloosa, Alabama 34587-0324, USA
| | - M Buuck
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - R Cabrita
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - C Carels
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - D L Carlsmith
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - B Carlson
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - M C Carmona-Benitez
- Pennsylvania State University, Department of Physics, University Park, Pennsylvania 16802-6300, USA
| | - M Cascella
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - C Chan
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - A Chawla
- Royal Holloway, University of London, Department of Physics, Egham, TW20 0EX, United Kingdom
| | - H Chen
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - J J Cherwinka
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - N I Chott
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - A Cole
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - J Coleman
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - M V Converse
- University of Rochester, Department of Physics and Astronomy, Rochester, New York 14627-0171, USA
| | - A Cottle
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510-5011, USA
| | - G Cox
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
- Pennsylvania State University, Department of Physics, University Park, Pennsylvania 16802-6300, USA
| | - W W Craddock
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
| | - O Creaner
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - D Curran
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - A Currie
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - J E Cutter
- University of California, Davis, Department of Physics, Davis, California 95616-5270, USA
| | - C E Dahl
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510-5011, USA
- Northwestern University, Department of Physics & Astronomy, Evanston, Illinois 60208-3112, USA
| | - A David
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - J Davis
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - T J R Davison
- University of Edinburgh, SUPA, School of Physics and Astronomy, Edinburgh EH9 3FD, United Kingdom
| | - J Delgaudio
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - S Dey
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - L de Viveiros
- Pennsylvania State University, Department of Physics, University Park, Pennsylvania 16802-6300, USA
| | - A Dobi
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - J E Y Dobson
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - E Druszkiewicz
- University of Rochester, Department of Physics and Astronomy, Rochester, New York 14627-0171, USA
| | - A Dushkin
- Brandeis University, Department of Physics, Waltham, Massachusetts 02453, USA
| | - T K Edberg
- University of Maryland, Department of Physics, College Park, Maryland 20742-4111, USA
| | - W R Edwards
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - M M Elnimr
- University of Alabama, Department of Physics and Astronomy, Tuscaloosa, Alabama 34587-0324, USA
| | - W T Emmet
- Yale University, Department of Physics, New Haven, Connecticut 06511-8499, USA
| | - S R Eriksen
- University of Bristol, H.H. Wills Physics Laboratory, Bristol, BS8 1TL, United Kingdom
| | - C H Faham
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - A Fan
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - S Fayer
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - N M Fearon
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - S Fiorucci
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - H Flaecher
- University of Bristol, H.H. Wills Physics Laboratory, Bristol, BS8 1TL, United Kingdom
| | - P Ford
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - V B Francis
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - E D Fraser
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - T Fruth
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - R J Gaitskell
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - N J Gantos
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - D Garcia
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - A Geffre
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - V M Gehman
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - J Genovesi
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - C Ghag
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - R Gibbons
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - E Gibson
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - M G D Gilchriese
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - S Gokhale
- Brookhaven National Laboratory (BNL), Upton, New York 11973-5000, USA
| | - B Gomber
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - J Green
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - A Greenall
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - S Greenwood
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | | | - C B Gwilliam
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - C R Hall
- University of Maryland, Department of Physics, College Park, Maryland 20742-4111, USA
| | - S Hans
- Brookhaven National Laboratory (BNL), Upton, New York 11973-5000, USA
| | - K Hanzel
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - A Harrison
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - E Hartigan-O'Connor
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - S J Haselschwardt
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - M A Hernandez
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
| | - S A Hertel
- University of Massachusetts, Department of Physics, Amherst, Massachusetts 01003-9337, USA
| | - G Heuermann
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
| | - C Hjemfelt
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - M D Hoff
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - E Holtom
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - J Y-K Hor
- University of Alabama, Department of Physics and Astronomy, Tuscaloosa, Alabama 34587-0324, USA
| | - M Horn
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - D Q Huang
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - D Hunt
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - C M Ignarra
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - R G Jacobsen
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - O Jahangir
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - R S James
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - S N Jeffery
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - W Ji
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - J Johnson
- University of California, Davis, Department of Physics, Davis, California 95616-5270, USA
| | - A C Kaboth
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
- Royal Holloway, University of London, Department of Physics, Egham, TW20 0EX, United Kingdom
| | - A C Kamaha
- University at Albany (SUNY), Department of Physics, Albany, New York 12222-0100, USA
- University of Califonia, Los Angeles, Department of Physics and Astronomy, Los Angeles, California 90095-1547
| | - K Kamdin
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - V Kasey
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - K Kazkaz
- Lawrence Livermore National Laboratory (LLNL), Livermore, California 94550-9698, USA
| | - J Keefner
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - D Khaitan
- University of Rochester, Department of Physics and Astronomy, Rochester, New York 14627-0171, USA
| | - M Khaleeq
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - A Khazov
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - I Khurana
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - Y D Kim
- IBS Center for Underground Physics (CUP), Yuseong-gu, Daejeon, Korea
| | - C D Kocher
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - D Kodroff
- Pennsylvania State University, Department of Physics, University Park, Pennsylvania 16802-6300, USA
| | - L Korley
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
- Brandeis University, Department of Physics, Waltham, Massachusetts 02453, USA
| | - E V Korolkova
- University of Sheffield, Department of Physics and Astronomy, Sheffield S3 7RH, United Kingdom
| | - J Kras
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - H Kraus
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - S Kravitz
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - H J Krebs
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
| | - L Kreczko
- Brookhaven National Laboratory (BNL), Upton, New York 11973-5000, USA
| | - B Krikler
- Brookhaven National Laboratory (BNL), Upton, New York 11973-5000, USA
| | - V A Kudryavtsev
- University of Sheffield, Department of Physics and Astronomy, Sheffield S3 7RH, United Kingdom
| | - S Kyre
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
| | - B Landerud
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - E A Leason
- University of Edinburgh, SUPA, School of Physics and Astronomy, Edinburgh EH9 3FD, United Kingdom
| | - C Lee
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - J Lee
- IBS Center for Underground Physics (CUP), Yuseong-gu, Daejeon, Korea
| | - D S Leonard
- IBS Center for Underground Physics (CUP), Yuseong-gu, Daejeon, Korea
| | - R Leonard
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - K T Lesko
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - C Levy
- University at Albany (SUNY), Department of Physics, Albany, New York 12222-0100, USA
| | - J Li
- IBS Center for Underground Physics (CUP), Yuseong-gu, Daejeon, Korea
| | - F-T Liao
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - J Liao
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - J Lin
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - A Lindote
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - R Linehan
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - W H Lippincott
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510-5011, USA
| | - R Liu
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - X Liu
- University of Edinburgh, SUPA, School of Physics and Astronomy, Edinburgh EH9 3FD, United Kingdom
| | - Y Liu
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - C Loniewski
- University of Rochester, Department of Physics and Astronomy, Rochester, New York 14627-0171, USA
| | - M I Lopes
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - E Lopez Asamar
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - B López Paredes
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - W Lorenzon
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
| | - D Lucero
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - S Luitz
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
| | - J M Lyle
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - P A Majewski
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - J Makkinje
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - D C Malling
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - A Manalaysay
- University of California, Davis, Department of Physics, Davis, California 95616-5270, USA
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - L Manenti
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - R L Mannino
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - N Marangou
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - M F Marzioni
- University of Edinburgh, SUPA, School of Physics and Astronomy, Edinburgh EH9 3FD, United Kingdom
| | - C Maupin
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - M E McCarthy
- University of Rochester, Department of Physics and Astronomy, Rochester, New York 14627-0171, USA
| | - C T McConnell
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - D N McKinsey
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - J McLaughlin
- Northwestern University, Department of Physics & Astronomy, Evanston, Illinois 60208-3112, USA
| | - Y Meng
- University of Alabama, Department of Physics and Astronomy, Tuscaloosa, Alabama 34587-0324, USA
| | - J Migneault
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - E H Miller
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - E Mizrachi
- University of Maryland, Department of Physics, College Park, Maryland 20742-4111, USA
- Lawrence Livermore National Laboratory (LLNL), Livermore, California 94550-9698, USA
| | - J A Mock
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University at Albany (SUNY), Department of Physics, Albany, New York 12222-0100, USA
| | - A Monte
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510-5011, USA
| | - M E Monzani
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
- Vatican Observatory, Castel Gandolfo, V-00120, Vatican City State
| | - J A Morad
- University of California, Davis, Department of Physics, Davis, California 95616-5270, USA
| | - J D Morales Mendoza
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - E Morrison
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - B J Mount
- Black Hills State University, School of Natural Sciences, Spearfish, South Dakota 57799-0002, USA
| | - M Murdy
- University of Massachusetts, Department of Physics, Amherst, Massachusetts 01003-9337, USA
| | - A St J Murphy
- University of Edinburgh, SUPA, School of Physics and Astronomy, Edinburgh EH9 3FD, United Kingdom
| | - D Naim
- University of California, Davis, Department of Physics, Davis, California 95616-5270, USA
| | - A Naylor
- University of Sheffield, Department of Physics and Astronomy, Sheffield S3 7RH, United Kingdom
| | - C Nedlik
- University of Massachusetts, Department of Physics, Amherst, Massachusetts 01003-9337, USA
| | - C Nehrkorn
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
| | - F Neves
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - A Nguyen
- University of Edinburgh, SUPA, School of Physics and Astronomy, Edinburgh EH9 3FD, United Kingdom
| | - J A Nikoleyczik
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - A Nilima
- University of Edinburgh, SUPA, School of Physics and Astronomy, Edinburgh EH9 3FD, United Kingdom
| | - J O'Dell
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - F G O'Neill
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
| | - K O'Sullivan
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - I Olcina
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - M A Olevitch
- Washington University in St. Louis, Department of Physics, St. Louis, Missouri 63130-4862, USA
| | - K C Oliver-Mallory
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - J Orpwood
- University of Sheffield, Department of Physics and Astronomy, Sheffield S3 7RH, United Kingdom
| | - D Pagenkopf
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
| | - S Pal
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - K J Palladino
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - J Palmer
- Royal Holloway, University of London, Department of Physics, Egham, TW20 0EX, United Kingdom
| | - M Pangilinan
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - N Parveen
- University at Albany (SUNY), Department of Physics, Albany, New York 12222-0100, USA
| | - S J Patton
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - E K Pease
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - B Penning
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
- Brandeis University, Department of Physics, Waltham, Massachusetts 02453, USA
| | - C Pereira
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - G Pereira
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - E Perry
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - T Pershing
- Lawrence Livermore National Laboratory (LLNL), Livermore, California 94550-9698, USA
| | - I B Peterson
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - A Piepke
- University of Alabama, Department of Physics and Astronomy, Tuscaloosa, Alabama 34587-0324, USA
| | - J Podczerwinski
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - D Porzio
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - S Powell
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - R M Preece
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - K Pushkin
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
| | - Y Qie
- University of Rochester, Department of Physics and Astronomy, Rochester, New York 14627-0171, USA
| | - B N Ratcliff
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
| | - J Reichenbacher
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - L Reichhart
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - C A Rhyne
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - A Richards
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - Q Riffard
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - G R C Rischbieter
- University at Albany (SUNY), Department of Physics, Albany, New York 12222-0100, USA
| | - J P Rodrigues
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - A Rodriguez
- Black Hills State University, School of Natural Sciences, Spearfish, South Dakota 57799-0002, USA
| | - H J Rose
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - R Rosero
- Brookhaven National Laboratory (BNL), Upton, New York 11973-5000, USA
| | - P Rossiter
- University of Sheffield, Department of Physics and Astronomy, Sheffield S3 7RH, United Kingdom
| | - T Rushton
- University of Sheffield, Department of Physics and Astronomy, Sheffield S3 7RH, United Kingdom
| | - G Rutherford
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - D Rynders
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - J S Saba
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - D Santone
- Royal Holloway, University of London, Department of Physics, Egham, TW20 0EX, United Kingdom
| | - A B M R Sazzad
- University of Alabama, Department of Physics and Astronomy, Tuscaloosa, Alabama 34587-0324, USA
| | - R W Schnee
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - P R Scovell
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - D Seymour
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - S Shaw
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
| | - T Shutt
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - J J Silk
- University of Maryland, Department of Physics, College Park, Maryland 20742-4111, USA
| | - C Silva
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - G Sinev
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - K Skarpaas
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
| | - W Skulski
- University of Rochester, Department of Physics and Astronomy, Rochester, New York 14627-0171, USA
| | - R Smith
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - M Solmaz
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
| | - V N Solovov
- Laboratório de Instrumentação e Física Experimental de Partículas (LIP), University of Coimbra, P-3004 516 Coimbra, Portugal
| | - P Sorensen
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - J Soria
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - I Stancu
- University of Alabama, Department of Physics and Astronomy, Tuscaloosa, Alabama 34587-0324, USA
| | - M R Stark
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - A Stevens
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - T M Stiegler
- Texas A&M University, Department of Physics and Astronomy, College Station, Texas 77843-4242, USA
| | - K Stifter
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510-5011, USA
| | - R Studley
- Brandeis University, Department of Physics, Waltham, Massachusetts 02453, USA
| | - B Suerfu
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - T J Sumner
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - P Sutcliffe
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - N Swanson
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - M Szydagis
- University at Albany (SUNY), Department of Physics, Albany, New York 12222-0100, USA
| | - M Tan
- University of Oxford, Department of Physics, Oxford OX1 3RH, United Kingdom
| | - D J Taylor
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
| | - R Taylor
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - W C Taylor
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - D J Temples
- Northwestern University, Department of Physics & Astronomy, Evanston, Illinois 60208-3112, USA
| | - B P Tennyson
- Yale University, Department of Physics, New Haven, Connecticut 06511-8499, USA
| | - P A Terman
- Texas A&M University, Department of Physics and Astronomy, College Station, Texas 77843-4242, USA
| | - K J Thomas
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - D R Tiedt
- University of Maryland, Department of Physics, College Park, Maryland 20742-4111, USA
- South Dakota Science and Technology Authority (SDSTA), Sanford Underground Research Facility, Lead, South Dakota 57754-1700, USA
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - M Timalsina
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - W H To
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - A Tomás
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - Z Tong
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - D R Tovey
- University of Sheffield, Department of Physics and Astronomy, Sheffield S3 7RH, United Kingdom
| | - J Tranter
- University of Sheffield, Department of Physics and Astronomy, Sheffield S3 7RH, United Kingdom
| | - M Trask
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
| | - M Tripathi
- University of California, Davis, Department of Physics, Davis, California 95616-5270, USA
| | - D R Tronstad
- South Dakota School of Mines and Technology, Rapid City, South Dakota 57701-3901, USA
| | - C E Tull
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - W Turner
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - L Tvrznikova
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
- Yale University, Department of Physics, New Haven, Connecticut 06511-8499, USA
- Lawrence Livermore National Laboratory (LLNL), Livermore, California 94550-9698, USA
| | - U Utku
- University College London (UCL), Department of Physics and Astronomy, London WC1E 6BT, United Kingdom
| | - J Va'vra
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
| | - A Vacheret
- Imperial College London, Physics Department, Blackett Laboratory, London SW7 2AZ, United Kingdom
| | - A C Vaitkus
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - J R Verbus
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - E Voirin
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510-5011, USA
| | - W L Waldron
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - A Wang
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - B Wang
- University of Alabama, Department of Physics and Astronomy, Tuscaloosa, Alabama 34587-0324, USA
| | - J J Wang
- University of Alabama, Department of Physics and Astronomy, Tuscaloosa, Alabama 34587-0324, USA
| | - W Wang
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
- University of Massachusetts, Department of Physics, Amherst, Massachusetts 01003-9337, USA
| | - Y Wang
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - J R Watson
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - R C Webb
- Texas A&M University, Department of Physics and Astronomy, College Station, Texas 77843-4242, USA
| | - A White
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - D T White
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
| | - J T White
- Texas A&M University, Department of Physics and Astronomy, College Station, Texas 77843-4242, USA
| | - R G White
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, California 94305-4085 USA
| | - T J Whitis
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
- University of California, Santa Barbara, Department of Physics, Santa Barbara, California 93106-9530, USA
| | - M Williams
- University of Michigan, Randall Laboratory of Physics, Ann Arbor, Michigan 48109-1040, USA
- Brandeis University, Department of Physics, Waltham, Massachusetts 02453, USA
| | - W J Wisniewski
- SLAC National Accelerator Laboratory, Menlo Park, California 94025-7015, USA
| | - M S Witherell
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
- University of California, Berkeley, Department of Physics, Berkeley, California 94720-7300, USA
| | - F L H Wolfs
- University of Rochester, Department of Physics and Astronomy, Rochester, New York 14627-0171, USA
| | - J D Wolfs
- University of Rochester, Department of Physics and Astronomy, Rochester, New York 14627-0171, USA
| | - S Woodford
- University of Liverpool, Department of Physics, Liverpool L69 7ZE, United Kingdom
| | - D Woodward
- Pennsylvania State University, Department of Physics, University Park, Pennsylvania 16802-6300, USA
| | - S D Worm
- STFC Rutherford Appleton Laboratory (RAL), Didcot, OX11 0QX, United Kingdom
| | - C J Wright
- Brookhaven National Laboratory (BNL), Upton, New York 11973-5000, USA
| | - Q Xia
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, California 94720-8099, USA
| | - X Xiang
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
- Brookhaven National Laboratory (BNL), Upton, New York 11973-5000, USA
| | - Q Xiao
- University of Wisconsin-Madison, Department of Physics, Madison, Wisconsin 53706-1390, USA
| | - J Xu
- Lawrence Livermore National Laboratory (LLNL), Livermore, California 94550-9698, USA
| | - M Yeh
- Brookhaven National Laboratory (BNL), Upton, New York 11973-5000, USA
| | - J Yin
- University of Rochester, Department of Physics and Astronomy, Rochester, New York 14627-0171, USA
| | - I Young
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510-5011, USA
| | - P Zarzhitsky
- University of Alabama, Department of Physics and Astronomy, Tuscaloosa, Alabama 34587-0324, USA
| | - A Zuckerman
- Brown University, Department of Physics, Providence, Rhode Island 02912-9037, USA
| | - E A Zweig
- University of Califonia, Los Angeles, Department of Physics and Astronomy, Los Angeles, California 90095-1547
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Hu Z, Jiang D, Zhao X, Yang J, Liang D, Wang H, Zhao C, Liao J. Predicting Drug Treatment Outcomes in Childrens with Tuberous Sclerosis Complex-Related Epilepsy: A Clinical Radiomics Study. AJNR Am J Neuroradiol 2023:ajnr.A7911. [PMID: 37348968 PMCID: PMC10337615 DOI: 10.3174/ajnr.a7911] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Accepted: 05/22/2023] [Indexed: 06/24/2023]
Abstract
BACKGROUND AND PURPOSE Highly predictive markers of drug treatment outcomes of tuberous sclerosis complex-related epilepsy are a key unmet clinical need. The objective of this study was to identify meaningful clinical and radiomic predictors of outcomes of epilepsy drug treatment in patients with tuberous sclerosis complex. MATERIALS AND METHODS A total of 105 children with tuberous sclerosis complex-related epilepsy were enrolled in this retrospective study. The pretreatment baseline predictors that were used to predict drug treatment outcomes included patient demographic and clinical information, gene data, electroencephalogram data, and radiomic features that were extracted from pretreatment MR imaging scans. The Spearman correlation coefficient and least absolute shrinkage and selection operator were calculated to select the most relevant features for the drug treatment outcome to build a comprehensive model with radiomic and clinical features for clinical application. RESULTS Four MR imaging-based radiomic features and 5 key clinical features were selected to predict the drug treatment outcome. Good discriminative performances were achieved in testing cohorts (area under the curve = 0.85, accuracy = 80.0%, sensitivity = 0.75, and specificity = 0.83) for the epilepsy drug treatment outcome. The model of radiomic and clinical features resulted in favorable calibration curves in all cohorts. CONCLUSIONS Our results suggested that the radiomic and clinical features model may predict the epilepsy drug treatment outcome. Age of onset, infantile spasms, antiseizure medication numbers, epileptiform discharge in left parieto-occipital area of electroencephalography, and gene mutation type are the key clinical factors to predict the epilepsy drug treatment outcome. The texture and first-order statistic features are the most valuable radiomic features for predicting drug treatment outcomes.
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Affiliation(s)
- Z Hu
- From the Departments of Neurology (Z.H., X.Z., J.L.)
| | - D Jiang
- Research Centre for Medical AI (D.J., J.Y., D.L.)
- Shenzhen College of Advanced Technology (D.J., J.Y., D.L.), University of Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - X Zhao
- From the Departments of Neurology (Z.H., X.Z., J.L.)
| | - J Yang
- Research Centre for Medical AI (D.J., J.Y., D.L.)
- Shenzhen College of Advanced Technology (D.J., J.Y., D.L.), University of Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - D Liang
- Research Centre for Medical AI (D.J., J.Y., D.L.)
- Paul C. Lauterbur Research Center for Biomedical Imaging (D.L., H.W.), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China
- Shenzhen College of Advanced Technology (D.J., J.Y., D.L.), University of Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - H Wang
- Paul C. Lauterbur Research Center for Biomedical Imaging (D.L., H.W.), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - C Zhao
- Radiology (C.Z.), Shenzhen Children's Hospital, Shenzhen, China
| | - J Liao
- From the Departments of Neurology (Z.H., X.Z., J.L.)
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5
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Yu S, Wang G, Liao J, Shen X, Chen J. Integrated analysis of long non-coding RNAs and mRNA expression profiles identified potential interactions regulating melanogenesis in chicken skin. Br Poult Sci 2023; 64:19-25. [PMID: 35979716 DOI: 10.1080/00071668.2022.2113506] [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: 11/02/2022]
Abstract
1. Long non-coding RNAs (lncRNAs) play important roles in various physiological functions. However, the mechanisms underlying the regulation of lncRNAs in melanogenesis remain unclear. To determine the molecular mechanisms involved in skin melanogenesis, the present study depicted the expression profiles of lncRNAs and messenger RNAs (mRNAs) in black- (B group) and white- (W group) skinned chickens using RNA sequencing.2. In total, 373 differentially expressed lncRNAs (DELs; 203 up-regulated and 170 down-regulated) and 253 differentially expressed genes (DEGs; 152 up-regulated and 101 down-regulated) were identified between the B and W groups. A total of eight known melanogenesis-related genes were identified (KIT, TYRP1, DCT (TYRP2), SLC45A2, OCA2, EDNRB2, TRPM1 and RAB38).3. Functional annotation of the co-expressed DEGs and DELs was performed using Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analyses. The co-expressed DEGs were mainly involved in melanogenesis and the co-expressed genes of 117 and 108 DELs were significantly enriched in the melanogenesis and tyrosine metabolism pathways, respectively.4. The DEL-DEG interaction network revealed that three lncRNAs (XR_003072387.1, XR_003075112.1, and XR_003077033.1) and DCT genes may have key roles in regulating melanogenesis in chicken skin. This data provides the groundwork for studying the lncRNA regulatory mechanisms of skin melanogenesis and suggested a new perspective on the modulation of melanogenesis in chicken skin based on a lncRNA-mRNA causal regulatory network.
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Affiliation(s)
- S Yu
- Engineering Research Center of Sichuan Province Higher School of Local Chicken Breeds Industrialization in Southern Sichuan, College of Life Science, Leshan Normal University, Leshan, Shizhong, China
| | - G Wang
- Engineering Research Center of Sichuan Province Higher School of Local Chicken Breeds Industrialization in Southern Sichuan, College of Life Science, Leshan Normal University, Leshan, Shizhong, China
| | - J Liao
- Engineering Research Center of Sichuan Province Higher School of Local Chicken Breeds Industrialization in Southern Sichuan, College of Life Science, Leshan Normal University, Leshan, Shizhong, China
| | - X Shen
- Engineering Research Center of Sichuan Province Higher School of Local Chicken Breeds Industrialization in Southern Sichuan, College of Life Science, Leshan Normal University, Leshan, Shizhong, China
| | - J Chen
- Engineering Research Center of Sichuan Province Higher School of Local Chicken Breeds Industrialization in Southern Sichuan, College of Life Science, Leshan Normal University, Leshan, Shizhong, China
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Kasi PM, Weipert C, Nguyen T, Liao J, Zhang N, Forbes S, Gordon S, Tan BR. Use of circulating tumor DNA (ctDNA) for early assessment of treatment response in patients with advanced colorectal cancer (aCRC): A real-world (RW) analysis. J Clin Oncol 2023. [DOI: 10.1200/jco.2023.41.4_suppl.246] [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: 01/25/2023] Open
Abstract
246 Background: Data suggests that changes in ctDNA quantity correlate with response to therapy in patients with advanced solid malignancies. However, there is little consistency on how to calculate and interpret such changes. Here, we apply a clinically-validated molecular response algorithm to a RW cohort of patients with aCRC to further evaluate its ability to assess treatment outcomes. Methods: We queried the Guardant INFORM database, which comprises aggregated commercial payer health claims and de-identified records from patients with comprehensive ctDNA testing via Guardant360 (G360) from September 2018-March 2022. Patients with aCRC who received G360 within 15 weeks prior to new treatment initiation (any line of therapy) and a second test 3-15 weeks after treatment initiation were retrospectively evaluated using the G360 Response algorithm. Cox proportional hazards (CPH) were used for RW time to next treatment (TTNT), time to treatment discontinuation (TTD), and overall survival (rwOS) analyses. Patients categorized as molecular responders had a >50% decrease in mean variant allele fraction (VAF) ratio from pre-treatment to on-treatment. Gender, age, line of therapy (LOT) and comorbidities were included as covariates. Median TTNT, TTD, and rwOS were calculated by Kaplan Meier. Results: Of 185 aCRC patients with eligible MR results, 65% received chemotherapy +/- VEGF, 21% received regimens containing anti-EGFR monoclonal antibodies, and 14% received other therapies. 43% of aCRC patients were classified as molecular responders, 42% were non-responders, and 15% were not evaluable by the algorithm due to no/low ctDNA at one or both timepoints. 16% of patients cleared their ctDNA on treatment (i.e., ctDNA became undetectable). Molecular responders had significantly longer TTNT (median 10.1 months vs 6.1 months; HR p < 0.005), TTD (median 5.2 Months vs 3.9 months, HR p=0.041), and rwOS (not reached vs 17.8 months, HR p=0.017). Conclusions: Patients with aCRC classified as molecular responders, as calculated by this algorithm, had prolonged time on treatment and overall survival. Compared to tumor markers, ctDNA has a short half-life, which can allow for early response assessment, as shown by our study. These findings are relevant for clinical care, with future potential to allow for adaptive clinical trial design. [Table: see text]
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Calhoun S, Gao Z, Vachhani B, Brandt K, Shah K, Liao J, He F, Vgontzas A, Liao D, Bixler E, Fernandez-Mendoza J. Sleep disordered breathing since childhood associated with atherosclerosis in adulthood. Sleep Med 2022. [DOI: 10.1016/j.sleep.2022.05.550] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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Chen YR, Wang XW, Liao J, Yi YX, Zhang W. [Application of robot-assisted laparoscopic sentinel lymph node tracing in treating endometrial carcinoma]. Zhonghua Fu Chan Ke Za Zhi 2022; 57:830-835. [PMID: 36456479 DOI: 10.3760/cma.j.cn112141-20221009-00621] [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: 06/17/2023]
Abstract
Objective: To investigate the value of robot-assisted laparoscopic indocyanine green sentinel lymph node (SLN) tracing in treating endometrial carcinoma. Methods: Thirty-two patients with early-staging endometrial carcinoma were operated with laparoscopic comprehensive staging laparotomy from January 2019 to December 2021. At the same time, the SLN detection was performed by near-infrared fluorescence imaging tracer technology, in which the tracer was indocyanine green. Sixteen cases were injected with indocyanine green before laparoscopic surgery, and 16 cases were injected with indocyanine green before robot-assisted laparoscopic surgery. The operation index, postoperative complications, prognosis, and lymph node dissection were compared between the two groups. Results: (1) The mean age of patients in the robot group was (54.7±8.1) years old, and was (54.9±8.8) years old in the laparoscopic group. There were no significant difference between the two groups (t=0.06, P=0.951). (2) Intraoperative blood loss [(131±40) vs (169±57) ml], hemoglobin difference before and after surgery [(11.2±5.4) vs (15.5±5.7) g/L], the length of stay after operation [(6.2±1.3) vs (8.6±1.4) days] between the robot group and the laparoscopic group were compared, and the differences were statistically significant (all P<0.05). (3) SLNs were detected in all 16 patients in the robotic group, and a total of 41 SLNs were detected. SLNs were detected in 15 of the 16 patients in the laparoscopy group, and a total of 40 SLNs were detected. Compared with the laparoscopic group (15/16), the total detection rate of SLN in the robotic group (16/16), there were no statistical significance (χ2=1.03, P=0.310). Compared with the laparoscopic group (7/15), the SLN bilateral detection rate in the robotic group (10/16), there were also no significant difference (χ2=0.78, P=0.376). The number of lymph nodes detected in surgery group (16.6±4.1) were lower than those in the laparoscopy surgery group (21.0±7.1), while there were no statistically difference between the two groups (χ2=2.01, P=0.054). There was no tumor metastasis in the resected lymph nodes and SLN between the two groups. The false negative rate of SLN in diagnosing endometrial cancer postoperative lymph node metastasis was 0, and the negative predictive value was 100%. (4) The pelvic and retroperitoneal lymph nodes were divided into five regions, which were the left pelvis, the right pelvis, the presacral region, the deep inguinal region, and the abdominal aorta. The numbers of SLN of unilateral detection and bilateral pelvic detection between two groups showed no significant differences (all P>0.05). The left pelvis had the most SLN imaging in both groups, followed by the right pelvis, para-aortic, and deep groin. (5) There was one patient in both robotic group and laparoscopic group with postoperative complications, which were urinary retention and pelvic lymph node cyst respectively. There were no significant differences in the incidence of complications between the two groups (χ2=0.97, P=1.000). The median follow-up time after operation was 14 months (range 6-24 months). During the follow-up period, no local recurrence or distant metastasis was found between the two groups of endometrial cancer patients. Conclusions: Compared with the laparoscopic group, the robot group has less intraoperative blood loss and shorter postoperative hospital stay. The bilateral detection rate of SLN in the group was better than that of laparoscopy.
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Affiliation(s)
- Y R Chen
- Department of Obstetrics and Gynecology, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - X W Wang
- Department of Obstetrics and Gynecology, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - J Liao
- Department of Obstetrics and Gynecology, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - Y X Yi
- Department of Obstetrics and Gynecology, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - W Zhang
- Department of Obstetrics and Gynecology, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
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Liao J, Mehta M, Hsu F. LIMITED CUTANEOUS SYSTEMIC SCLEROSIS MIMICKING HEREDITARY ANGIOEDEMA WITH NORMAL C1 INHIBITOR. Ann Allergy Asthma Immunol 2022. [DOI: 10.1016/j.anai.2022.08.830] [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: 11/11/2022]
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Caplette JN, Gfeller L, Lei D, Liao J, Xia J, Zhang H, Feng X, Mestrot A. Antimony release and volatilization from rice paddy soils: Field and microcosm study. Sci Total Environ 2022; 842:156631. [PMID: 35691353 DOI: 10.1016/j.scitotenv.2022.156631] [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] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 06/01/2022] [Accepted: 06/07/2022] [Indexed: 06/15/2023]
Abstract
The fate of antimony (Sb) in submerged soils and the impact of common agricultural practices (e.g., manuring) on Sb release and volatilization is understudied. We investigated porewater Sb release and volatilization in the field and laboratory for three rice paddy soils. In the field study, the porewater Sb concentration (up to 107.1 μg L-1) was associated with iron (Fe) at two sites, and with pH, Fe, manganese (Mn), and sulfate (SO42-) at one site. The surface water Sb concentrations (up to 495.3 ± 113.7 μg L-1) were up to 99 times higher than the regulatory values indicating a potential risk to aquaculture and rice agriculture. For the first time, volatile Sb was detected in rice paddy fields using a validated quantitative method (18.1 ± 5.2 to 217.9 ± 160.7 mg ha-1 y-1). We also investigated the influence of two common rice agriculture practices (flooding and manuring) on Sb release and volatilization in a 56-day microcosm experiment using the same soils from the field campaign. Flooding induced an immediate, but temporary, Sb release into the porewater that declined with SO42-, indicating that SO42- reduction may reduce porewater Sb concentrations. A secondary Sb release, corresponding to Fe reduction in the porewater, was observed in some of the microcosms. Our results suggest flooding-induced Sb release into rice paddy porewaters is temporary but relevant. Manuring the soils did not impact the porewater Sb concentration but did enhance Sb volatilization. Volatile Sb (159.6 ± 108.4 to 2237.5 ± 679.7 ng kg-1 y-1) was detected in most of the treatments and was correlated with the surface water Sb concentration. Our study indicates that Sb volatilization could be occurring at the soil-water interface or directly in the surface water and highlights that future works should investigate this potentially relevant mechanism.
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Affiliation(s)
| | - L Gfeller
- Institute of Geography, University of Bern, Switzerland
| | - D Lei
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, PR China
| | - J Liao
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, PR China
| | - J Xia
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, PR China
| | - H Zhang
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, PR China
| | - X Feng
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, PR China.
| | - A Mestrot
- Institute of Geography, University of Bern, Switzerland.
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Mosholder AD, Ma Y, Akhtar S, Podskalny GD, Feng Y, Lyu H, Liao J, Wei Y, Wernecke M, Leishear K, Nelson LM, MaCurdy TE, Kelman JA, Graham DJ. Mortality Among Parkinson's Disease Patients Treated With Pimavanserin or Atypical Antipsychotics: An Observational Study in Medicare Beneficiaries. Am J Psychiatry 2022; 179:553-561. [PMID: 35702829 DOI: 10.1176/appi.ajp.21090876] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
OBJECTIVE Pimavanserin, a serotonin 5-HT2 antagonist, is indicated for treatment of hallucinations and delusions associated with Parkinson's disease psychosis. In premarketing trials in patients with Parkinson's disease psychosis, 11% of patients died during open-label pimavanserin treatment. Antipsychotics, which are used off-label in Parkinson's disease psychosis, increase mortality in dementia patients. The authors compared mortality with pimavanserin and atypical antipsychotics in a large database. METHODS This was a retrospective new-user cohort study of Medicare beneficiaries with Parkinson's disease initiating pimavanserin (N=3,227) or atypical antipsychotics (N=18,442) from April 2016 to March 2019. All-cause mortality hazard ratios and 95% confidence intervals were estimated for pimavanserin compared with atypical antipsychotics, using segmented proportional hazards regression over 1-180 and 181+ days of treatment. Potential confounding was addressed through inverse probability of treatment weighting (IPTW). RESULTS Pimavanserin users had a mean age of approximately 78 years, and 45% were female. Before IPTW, some comorbidities were more prevalent in atypical antipsychotic users; after IPTW, comorbidities were well balanced between groups. In the first 180 days of treatment, mortality was approximately 35% lower with pimavanserin than with atypical antipsychotics (hazard ratio=0.65, 95% CI=0.53, 0.79), with approximately one excess death per 30 atypical antipsychotic-treated patients; however, during treatment beyond 180 days, there was no additional mortality advantage with pimavanserin (hazard ratio=1.05, 95% CI=0.82, 1.33). Pimavanserin showed no mortality advantage in nursing home patients. CONCLUSIONS Pimavanserin use was associated with lower mortality than atypical antipsychotic use during the first 180 days of treatment, but only in community-dwelling patients, not nursing home residents.
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Affiliation(s)
- Andrew D Mosholder
- Division of Epidemiology 1 (Mosholder, Leishear), Division of Neurology 1 (Podskalny), Office of Pharmacovigilance and Epidemiology (Graham), and Division of Biometrics 7 (Ma), U.S. Food and Drug Administration Center for Drug Evaluation and Research, Silver Spring, Md.; Acumen LLC, Burlingame, Calif. (Akhtar, Feng, Lyu, Liao, Wei, Wernecke, Nelson, MaCurdy); Guardant Health, Redwood City, Calif. (Liao); Department of Epidemiology and Population Health (Nelson) and Department of Economics (MaCurdy), Stanford University, Stanford, Calif.; Centers for Medicare and Medicaid Services, Washington, DC (Kelman)
| | - Yong Ma
- Division of Epidemiology 1 (Mosholder, Leishear), Division of Neurology 1 (Podskalny), Office of Pharmacovigilance and Epidemiology (Graham), and Division of Biometrics 7 (Ma), U.S. Food and Drug Administration Center for Drug Evaluation and Research, Silver Spring, Md.; Acumen LLC, Burlingame, Calif. (Akhtar, Feng, Lyu, Liao, Wei, Wernecke, Nelson, MaCurdy); Guardant Health, Redwood City, Calif. (Liao); Department of Epidemiology and Population Health (Nelson) and Department of Economics (MaCurdy), Stanford University, Stanford, Calif.; Centers for Medicare and Medicaid Services, Washington, DC (Kelman)
| | - Sandia Akhtar
- Division of Epidemiology 1 (Mosholder, Leishear), Division of Neurology 1 (Podskalny), Office of Pharmacovigilance and Epidemiology (Graham), and Division of Biometrics 7 (Ma), U.S. Food and Drug Administration Center for Drug Evaluation and Research, Silver Spring, Md.; Acumen LLC, Burlingame, Calif. (Akhtar, Feng, Lyu, Liao, Wei, Wernecke, Nelson, MaCurdy); Guardant Health, Redwood City, Calif. (Liao); Department of Epidemiology and Population Health (Nelson) and Department of Economics (MaCurdy), Stanford University, Stanford, Calif.; Centers for Medicare and Medicaid Services, Washington, DC (Kelman)
| | - Gerald D Podskalny
- Division of Epidemiology 1 (Mosholder, Leishear), Division of Neurology 1 (Podskalny), Office of Pharmacovigilance and Epidemiology (Graham), and Division of Biometrics 7 (Ma), U.S. Food and Drug Administration Center for Drug Evaluation and Research, Silver Spring, Md.; Acumen LLC, Burlingame, Calif. (Akhtar, Feng, Lyu, Liao, Wei, Wernecke, Nelson, MaCurdy); Guardant Health, Redwood City, Calif. (Liao); Department of Epidemiology and Population Health (Nelson) and Department of Economics (MaCurdy), Stanford University, Stanford, Calif.; Centers for Medicare and Medicaid Services, Washington, DC (Kelman)
| | - Yuhui Feng
- Division of Epidemiology 1 (Mosholder, Leishear), Division of Neurology 1 (Podskalny), Office of Pharmacovigilance and Epidemiology (Graham), and Division of Biometrics 7 (Ma), U.S. Food and Drug Administration Center for Drug Evaluation and Research, Silver Spring, Md.; Acumen LLC, Burlingame, Calif. (Akhtar, Feng, Lyu, Liao, Wei, Wernecke, Nelson, MaCurdy); Guardant Health, Redwood City, Calif. (Liao); Department of Epidemiology and Population Health (Nelson) and Department of Economics (MaCurdy), Stanford University, Stanford, Calif.; Centers for Medicare and Medicaid Services, Washington, DC (Kelman)
| | - Hai Lyu
- Division of Epidemiology 1 (Mosholder, Leishear), Division of Neurology 1 (Podskalny), Office of Pharmacovigilance and Epidemiology (Graham), and Division of Biometrics 7 (Ma), U.S. Food and Drug Administration Center for Drug Evaluation and Research, Silver Spring, Md.; Acumen LLC, Burlingame, Calif. (Akhtar, Feng, Lyu, Liao, Wei, Wernecke, Nelson, MaCurdy); Guardant Health, Redwood City, Calif. (Liao); Department of Epidemiology and Population Health (Nelson) and Department of Economics (MaCurdy), Stanford University, Stanford, Calif.; Centers for Medicare and Medicaid Services, Washington, DC (Kelman)
| | - Jiemin Liao
- Division of Epidemiology 1 (Mosholder, Leishear), Division of Neurology 1 (Podskalny), Office of Pharmacovigilance and Epidemiology (Graham), and Division of Biometrics 7 (Ma), U.S. Food and Drug Administration Center for Drug Evaluation and Research, Silver Spring, Md.; Acumen LLC, Burlingame, Calif. (Akhtar, Feng, Lyu, Liao, Wei, Wernecke, Nelson, MaCurdy); Guardant Health, Redwood City, Calif. (Liao); Department of Epidemiology and Population Health (Nelson) and Department of Economics (MaCurdy), Stanford University, Stanford, Calif.; Centers for Medicare and Medicaid Services, Washington, DC (Kelman)
| | - Yuqin Wei
- Division of Epidemiology 1 (Mosholder, Leishear), Division of Neurology 1 (Podskalny), Office of Pharmacovigilance and Epidemiology (Graham), and Division of Biometrics 7 (Ma), U.S. Food and Drug Administration Center for Drug Evaluation and Research, Silver Spring, Md.; Acumen LLC, Burlingame, Calif. (Akhtar, Feng, Lyu, Liao, Wei, Wernecke, Nelson, MaCurdy); Guardant Health, Redwood City, Calif. (Liao); Department of Epidemiology and Population Health (Nelson) and Department of Economics (MaCurdy), Stanford University, Stanford, Calif.; Centers for Medicare and Medicaid Services, Washington, DC (Kelman)
| | - Michael Wernecke
- Division of Epidemiology 1 (Mosholder, Leishear), Division of Neurology 1 (Podskalny), Office of Pharmacovigilance and Epidemiology (Graham), and Division of Biometrics 7 (Ma), U.S. Food and Drug Administration Center for Drug Evaluation and Research, Silver Spring, Md.; Acumen LLC, Burlingame, Calif. (Akhtar, Feng, Lyu, Liao, Wei, Wernecke, Nelson, MaCurdy); Guardant Health, Redwood City, Calif. (Liao); Department of Epidemiology and Population Health (Nelson) and Department of Economics (MaCurdy), Stanford University, Stanford, Calif.; Centers for Medicare and Medicaid Services, Washington, DC (Kelman)
| | - Kira Leishear
- Division of Epidemiology 1 (Mosholder, Leishear), Division of Neurology 1 (Podskalny), Office of Pharmacovigilance and Epidemiology (Graham), and Division of Biometrics 7 (Ma), U.S. Food and Drug Administration Center for Drug Evaluation and Research, Silver Spring, Md.; Acumen LLC, Burlingame, Calif. (Akhtar, Feng, Lyu, Liao, Wei, Wernecke, Nelson, MaCurdy); Guardant Health, Redwood City, Calif. (Liao); Department of Epidemiology and Population Health (Nelson) and Department of Economics (MaCurdy), Stanford University, Stanford, Calif.; Centers for Medicare and Medicaid Services, Washington, DC (Kelman)
| | - Lorene M Nelson
- Division of Epidemiology 1 (Mosholder, Leishear), Division of Neurology 1 (Podskalny), Office of Pharmacovigilance and Epidemiology (Graham), and Division of Biometrics 7 (Ma), U.S. Food and Drug Administration Center for Drug Evaluation and Research, Silver Spring, Md.; Acumen LLC, Burlingame, Calif. (Akhtar, Feng, Lyu, Liao, Wei, Wernecke, Nelson, MaCurdy); Guardant Health, Redwood City, Calif. (Liao); Department of Epidemiology and Population Health (Nelson) and Department of Economics (MaCurdy), Stanford University, Stanford, Calif.; Centers for Medicare and Medicaid Services, Washington, DC (Kelman)
| | - Thomas E MaCurdy
- Division of Epidemiology 1 (Mosholder, Leishear), Division of Neurology 1 (Podskalny), Office of Pharmacovigilance and Epidemiology (Graham), and Division of Biometrics 7 (Ma), U.S. Food and Drug Administration Center for Drug Evaluation and Research, Silver Spring, Md.; Acumen LLC, Burlingame, Calif. (Akhtar, Feng, Lyu, Liao, Wei, Wernecke, Nelson, MaCurdy); Guardant Health, Redwood City, Calif. (Liao); Department of Epidemiology and Population Health (Nelson) and Department of Economics (MaCurdy), Stanford University, Stanford, Calif.; Centers for Medicare and Medicaid Services, Washington, DC (Kelman)
| | - Jeffrey A Kelman
- Division of Epidemiology 1 (Mosholder, Leishear), Division of Neurology 1 (Podskalny), Office of Pharmacovigilance and Epidemiology (Graham), and Division of Biometrics 7 (Ma), U.S. Food and Drug Administration Center for Drug Evaluation and Research, Silver Spring, Md.; Acumen LLC, Burlingame, Calif. (Akhtar, Feng, Lyu, Liao, Wei, Wernecke, Nelson, MaCurdy); Guardant Health, Redwood City, Calif. (Liao); Department of Epidemiology and Population Health (Nelson) and Department of Economics (MaCurdy), Stanford University, Stanford, Calif.; Centers for Medicare and Medicaid Services, Washington, DC (Kelman)
| | - David J Graham
- Division of Epidemiology 1 (Mosholder, Leishear), Division of Neurology 1 (Podskalny), Office of Pharmacovigilance and Epidemiology (Graham), and Division of Biometrics 7 (Ma), U.S. Food and Drug Administration Center for Drug Evaluation and Research, Silver Spring, Md.; Acumen LLC, Burlingame, Calif. (Akhtar, Feng, Lyu, Liao, Wei, Wernecke, Nelson, MaCurdy); Guardant Health, Redwood City, Calif. (Liao); Department of Epidemiology and Population Health (Nelson) and Department of Economics (MaCurdy), Stanford University, Stanford, Calif.; Centers for Medicare and Medicaid Services, Washington, DC (Kelman)
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Abubaker K, Wang D, Feng Z, Stroh C, Liao J, Otto G, Scheuenpflug J. Abstract 5245: Characterization of sub-clonal RAS/BRAF alterations in an anti-EGFR treated advanced CRC cohort using a liquid biopsy-based real world clinical genomics database. Cancer Res 2022. [DOI: 10.1158/1538-7445.am2022-5245] [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: 11/16/2022]
Abstract
Abstract
Background: Anti-EGFR monoclonal antibodies are treatment options for RAS and BRAF V600 mutation-negative CRC patients. However, the literature suggests that CRC patients with sub-clonal RAS and BRAF mutations may still benefit from anti-EGFR therapies. The Guardant INFORM™ real-world clinical-genomic database was utilized to assess the impact of sub-clonal RAS and BRAF alterations detected in circulating tumor DNA (ctDNA) by the Guardant360® test on the clinical outcome of CRC patients treated with anti-EGFR therapy.
Methods: Patients were selected from the Guardant INFORM™ database using the following inclusion criteria: diagnosed with advanced CRC in the US; treated with anti-EGFR therapies starting within 90 days after a Guardant360 test result; and the presence of BRAF V600E and/or canonical KRAS/NRAS mutations (codons 12, 13, 59, 61, 117, 146). Time to next treatment (TTNT) and overall survival (OS) were compared for various RAS/BRAF mutation clonality cutoffs using the Cox proportional hazards model.
Results: Of the 13,798 CRC patients in the Guardant INFORM database, 91% had detectable ctDNA, 913 received a Guardant360® test before anti-EGFR therapy, and 446 (48.8%) initiated anti-EGFR therapy within 90 days after the test. Among this cohort, 11% (n = 50) had a BRAF V600E mutation and 9% (n = 40) had a RAS mutation. The median RAS/BRAF clonality was 0.84 (IQR = 0.57, 1.00). The associated clinical outcomes for patients with sub-clonal and clonal RAS/BRAF mutations using clonality cutoffs from 0.3 to 0.8 are reported (Table).
Conclusion: Using a liquid biopsy-based clinical-genomic dataset, we demonstrate that patients harboring sub-clonal RAS or BRAF mutations benefit from anti-EGFR therapy to a degree similar to wild-type patients. Given the limited patient numbers, this finding warrants additional investigation into the utility of ant-EGFR therapies as a treatment option for this subgroup of CRC patients.
RAS/BRAF Mutation Clonality* Cutoff Sub-clonal** Clonal** HR (95% CI) P value HR (95% CI) P value TTNT 0.3 0.96 (0.42, 2.18) 0.913 1.72 (1.15, 2.59) 0.009 0.4 1.03 (0.48, 2.21) 0.946 1.72 (1.14, 2.60) 0.010 0.5 0.97 (0.45, 2.08) 0.931 1.77 (1.17, 2.66) 0.007 0.6 1.04 (0.51, 2.13) 0.922 1.76 (1.16, 2.66) 0.008 0.7 1.03 (0.55, 1.94) 0.919 1.90 (1.23, 2.93) 0.004 0.8 1.30 (0.75, 2.24) 0.350 1.72 (1.08, 2.74) 0.022 OS 0.3 1.72 (0.84, 3.54) 0.142 2.47 (1.61, 3.79) <0.001 0.4 1.85 (0.93, 3.66) 0.079 2.42 (1.57, 3.74) <0.001 0.5 1.79 (0.90, 3.54) 0.097 2.46 (1.59, 3.80) <0.001 0.6 1.92 (1.00, 3.69) 0.050 2.40 (1.55, 3.73) <0.001 0.7 1.83 (1.03, 3.26) 0.041 2.60 (1.63, 4.14) <0.001 0.8 2.16 (1.29, 3.61) 0.003 2.33 (1.40, 3.86) 0.001 *Clonality = (RAS or BRAF MAF)/(maximum MAF). **Reference group is patients without RAS/BRAF mutations.
Citation Format: Khalid Abubaker, Danyi Wang, Zheng Feng, Christopher Stroh, Jiemin Liao, Gordon Otto, Juergen Scheuenpflug. Characterization of sub-clonal RAS/BRAF alterations in an anti-EGFR treated advanced CRC cohort using a liquid biopsy-based real world clinical genomics database [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5245.
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Affiliation(s)
| | - Danyi Wang
- 2EMD Serono Research and Development Institute, Inc, Billerica, MA
| | - Zheng Feng
- 2EMD Serono Research and Development Institute, Inc, Billerica, MA
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Wander SA, Weipert C, Liao J, Zhang N, Razavi P. Use of real-world data (RWD) to assess the utility of cell-free circulating tumor DNA (cfDNA) in identifying resistance to early treatment in advanced breast cancer (aBC). J Clin Oncol 2022. [DOI: 10.1200/jco.2022.40.16_suppl.1011] [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: 11/20/2022] Open
Abstract
1011 Background: The approvals of CDK4/6 inhibitors (CDK4/6i) and alpelisib (a PI3Ka inhibitor, PI3Ki) have overhauled early treatment of hormone positive aBC. While some clinical trials have investigated mechanisms of resistance to these drugs, their impact on tumor evolution requires further exploration. Here we use cfDNA to examine molecular changes pre- and post-CDK4/6i or PI3Ki treatment and use RWD to assess the impact of putative resistance alterations on response to treatment. Methods: Patients (pts) with aBC were identified via the Guardant INFORM database and included if they had a cfDNA test within 90 days prior to therapy initiation and/or 90 days after therapy discontinuation with CDK4/6i or PI3Ki. Pts with RB1 loss of function (LOF) alterations (alts) who received CDK4/6i and pts with PTEN LOF alts who received PI3Ki were separately identified, and these cohorts were matched 1:3 with a RB1/PTEN negative population respectively, by age (+/- 5 years), sex, year of cfDNA test, and line of therapy. Log-rank tests were used to assess differences in time to discontinuation (TTD) and time to next treatment (TTNT). Results: Differences in the frequencies of certain alts detected in pts pre- and post-CDK4/6i or PI3Ki treatment are shown (Table). Pts with RB1 LOF alts prior to the start of CDK4/6i had significantly worse TTD and numerically worse TTNT versus controls (TTD = 3 mos vs 4.7 mos, p=0.018; TTNT = 7.3 mos vs 8 mos, p=0.082). Pts with PTEN LOF alts prior to start of PI3Ki had no significant difference in TTD or TTNT versus controls (TTD = 4.1 mos vs 4.1 mos, p=0.92; TTNT = 7.4 mos vs 7 mos, p=0.32). Notably, 54% of pts receiving CDK4/6i and 84% of pts receiving PI3Ki were on their third or later line of therapy. Conclusions: Using cfDNA, we were able to further characterize the resistance landscape of both CDK4/6i and PI3Ki, and identified specific ESR1, RB1 and PTEN alterations that appear likely to occur under the pressure of therapy. Our real-world analysis examining RB1 LOF alts added further evidence to suggest it may be both a primary and acquired resistance mechanism to CDK4/6i. As a non-invasive alternative to tissue biopsies, this data further illustrates that cfDNA can provide unique insight into tumor evolution and disease progression in the aBC setting. [Table: see text]
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Affiliation(s)
| | | | | | | | - Pedram Razavi
- Memorial Sloan Kettering Cancer Center, New York, NY
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Nakamura Y, Olsen S, Zhang N, Liao J, Yoshino T. Comprehensive Genomic Profiling of Circulating Tumor DNA in Patients with Previously Treated Metastatic Colorectal Cancer: Analysis of a Real-World Healthcare Claims Database. Curr Oncol 2022; 29:3433-3448. [PMID: 35621667 PMCID: PMC9139639 DOI: 10.3390/curroncol29050277] [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] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 04/26/2022] [Accepted: 04/29/2022] [Indexed: 11/27/2022] Open
Abstract
We used a real-world database (GuardantINFORMTM) to analyze the treatment choices for patients with mCRC who underwent next-generation sequencing of circulating tumor DNA (ctDNA) using a commercially available test (Guardant360®) after first- or second-line therapy. From 18,875 patients with claims for CRC, 1064 had confirmed metastatic disease and sufficient histories for analysis (median age 59 years, 44.8% female, 44.5% left-sided). ctDNA was detectable for 997/1064 (93.7%) patients. Clinically actionable molecular profiles were present for 507/1064 (47.7%) patients, including those who had not received targeted therapy in the previous line (410/926, 44.3%). Second- or third-line targeted therapies were administered to 338/1064 patients (31.8%) and were considered matched for 193/338 (57.1%) patients. Therapies administered after testing were informed by the ctDNA results in 56.7% of patients overall (603/1064). Time to treatment discontinuation was most favorable for patients with a clinically actionable ctDNA profile who received matched therapy. This analysis demonstrates the real-world clinical value of plasma-based comprehensive genomic profiling for selecting appropriate molecular-targeted therapies in mCRC patients with disease progression after first- or second-line therapy.
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Affiliation(s)
- Yoshiaki Nakamura
- Department of Gastroenterology and Gastrointestinal Oncology, National Cancer Center Hospital East, Kashiwa 277-8577, Japan; (Y.N.); (T.Y.)
- Translational Research Support Section, National Cancer Center Hospital East, Kashiwa 277-8577, Japan
| | - Steven Olsen
- Department of Medical Affairs, Guardant Health Asia, Middle East, Africa, Inc., Tokyo Port City Takeshiba Office Tower 9th Floor, 1-7-1 Kaigan, Minato-ku, Tokyo 105-7590, Japan
- Correspondence: ; Tel.: +81-3-6778-5160
| | - Nicole Zhang
- Department of Outcomes and Evidence, Guardant Health, Inc., Redwood City, CA 94063, USA; (N.Z.); (J.L.)
| | - Jiemin Liao
- Department of Outcomes and Evidence, Guardant Health, Inc., Redwood City, CA 94063, USA; (N.Z.); (J.L.)
| | - Takayuki Yoshino
- Department of Gastroenterology and Gastrointestinal Oncology, National Cancer Center Hospital East, Kashiwa 277-8577, Japan; (Y.N.); (T.Y.)
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Cui GZ, Zhou QS, Cheng QQ, Rao FQ, Cheng YM, Tian Y, Zhang T, Chen ZH, Liao J, Guan ZZ, Qi XL, Wu Q, Hong W. [Transcriptomic analysis of the ΔPaLoc mutant of Clostridioides difficile and verification of its toxicity]. Zhonghua Yu Fang Yi Xue Za Zhi 2022; 56:601-608. [PMID: 35644974 DOI: 10.3760/cma.j.cn112150-20220222-00166] [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: Comparative analyses of wild-type Clostridioides difficile 630 (Cd630) strain and pathogenicity locus (PaLoc) knockout mutant (ΔPaLoc) by using RNA-seq technology. Analysis of differential expression of Cd630 wild-type strain and ΔPaLoc mutant strain and measurement of its cellular virulence changes. Lay the foundation for the construction of an toxin-attenuated vaccine strain against Clostridioides difficile. Methods: Analysis of Cd630 and ΔPaLoc mutant strains using high-throughput sequencing (RNA-seq). Clustering differentially expressed genes and screening differentially expressed genes by DESeq software. Further analysis of differential genes using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Finally, cytotoxicity assays of ΔPaLoc and Cd630 strains were performed in the African monkey kidney epithelial cell (Vero) and the human colonic cell (Caco-2) lines. Results: The transcriptome data showed that the ΔPaLoc mutant toxin genes tcdA and tcdB were not transcribed. Compared to the wild-type strain, CD630_36010, CD630_020910,CD630_02080 and cel genes upregulated 17.92,11.40,8.93 and 7.55 fold, respectively. Whereas the hom2 (high serine dehydrogenase), the CD630_15810 (spore-forming protein), CD630_23230 (zinc-binding dehydrogenase) and CD630_23240 (galactitol 1-phosphate 5-dehydrogenase) genes were down-regulated by 0.06, 0.075, 0.133 and 0.183 fold, respectively. The GO and KEGG enrichment analyses showed that the differentially transcribed genes in ΔPaLoc were enriched in the density-sensing system, ABC transport system, two-component system, phosphotransferase (PTS) system, and sugar metabolism pathway, as well as vancomycin resistance-related pathways. Cytotoxicity assays showed that the ΔPaLoc mutant strain lost its virulence to Vero and Caco-2 cells compared to the wild-type Cd630 strain. Conclusion: Transcriptional sequencing analysis of the Cd630 and ΔPaLoc mutant strains showed that the toxin genes were not transcribed. Those other differential genes could provide a reference for further studies on the physiological and biochemical properties of the ΔPaLoc mutant strain. Cytotoxicity assays confirmed that the ΔPaLoc mutant lost virulence to Vero and Caco-2 cells, thus laying the foundation for constructing an toxin-attenuated vaccine strain against C. difficile.
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Affiliation(s)
- G Z Cui
- Key Laboratory of Microbiology and Parasitology of Education Department of Guizhou, Guizhou Medical University, Guiyang 550004, China
| | - Q S Zhou
- Key Laboratory of Endemic and Ethnic Diseases, Ministry of Education & Key Laboratory of Medical Molecular Biology of Guizhou Province, Guizhou Medical University, Guiyang 550001, China
| | - Q Q Cheng
- Department of Clinical Laboratory, Shanghai 10th People's Hospital of Tongji University, Shanghai 200072, China
| | - F Q Rao
- Key Laboratory of Endemic and Ethnic Diseases, Ministry of Education & Key Laboratory of Medical Molecular Biology of Guizhou Province, Guizhou Medical University, Guiyang 550001, China
| | - Y M Cheng
- General ICU of the Affiliated Hospital of Guizhou Medical University, Guiyang 550001, China
| | - Y Tian
- Guizhou Polytechnic of Construction, Qingzhen 551400, China
| | - T Zhang
- Key Laboratory of Endemic and Ethnic Diseases, Ministry of Education & Key Laboratory of Medical Molecular Biology of Guizhou Province, Guizhou Medical University, Guiyang 550001, China
| | - Z H Chen
- Key Laboratory of Microbiology and Parasitology of Education Department of Guizhou, Guizhou Medical University, Guiyang 550004, China
| | - J Liao
- Stomatological Hospital of Guizhou Medical University, Guiyang 550001, China
| | - Z Z Guan
- Key Laboratory of Endemic and Ethnic Diseases, Ministry of Education & Key Laboratory of Medical Molecular Biology of Guizhou Province, Guizhou Medical University, Guiyang 550001, China
| | - X L Qi
- Key Laboratory of Endemic and Ethnic Diseases, Ministry of Education & Key Laboratory of Medical Molecular Biology of Guizhou Province, Guizhou Medical University, Guiyang 550001, China
| | - Q Wu
- Department of Clinical Laboratory, Shanghai 10th People's Hospital of Tongji University, Shanghai 200072, China
| | - Wei Hong
- Key Laboratory of Microbiology and Parasitology of Education Department of Guizhou, Guizhou Medical University, Guiyang 550004, China Key Laboratory of Endemic and Ethnic Diseases, Ministry of Education & Key Laboratory of Medical Molecular Biology of Guizhou Province, Guizhou Medical University, Guiyang 550001, China
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Geng X, Yang Z, Liao J, Mirkheshti N, Mehra R, Cullen K, Dan H. Targeting PI3Kα/δ and the ErbB Family of Protein-Tyrosine Kinases in Cisplatin-Resistant Head and Neck Squamous Cell Carcinomas. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2021.12.112] [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: 10/18/2022]
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Juric D, Weipert C, Bucheit L, Nagy R, Odegaard J, Yu J, Zhang N, Liao J. Abstract P1-18-07: Impact of PIK3CA mutation ( PIK3CA-mt) clonality on alpelisib (ALP) activity based on real-world evidence (RWE) following liquid biopsy testing. Cancer Res 2022. [DOI: 10.1158/1538-7445.sabcs21-p1-18-07] [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: 11/16/2022]
Abstract
Abstract
Background:ALP is an alpha-selective PI3K-inhibitor approved in combination with fulvestrant for PIK3CA-mt HR+/HER2- advanced breast cancer (aBC). These mutations may either be truncal (clonal) or acquired (subclonal) under treatment pressure; however, data regarding the efficacy of ALP in these two populations are currently limited. This study utilized RWE to assess how the PIK3CA genomic environment impacts ALP response. Methods: RWE was sourced from the GuardantINFORM (Guardant Health) database, which comprises aggregated commercial payer health claims and de-identified records from over 100,000 individuals with comprehensive ctDNA results via Guardant360 (G360). All HR+/HER2- aBC patients with one or more of the 11 PIK3CA-mt cited in the Therascreen PIK3CA RGQ PCR Kit ALP companion diagnostic approval (P190001) identified on a G360 since May 2019 were included. Patients must have had at least one claim of ALP after the index G360 test. Patients who received ALP claim(s) in the six months prior to their G360 test were excluded. PIK3CA-mt were defined by clonal fraction (copy number-adjusted PIK3CA mutation allelic fraction/maximum somatic mutation allelic fraction) >50% (clonal) or ≤50% (subclonal). Real-world time to discontinuation (rwTTD) and real-world time to next treatment (rwTTNT) were assessed as proxies for progression free survival. Log-rank tests were used to assess differences in rwTTD and rwTTNT and Chi-squared tests were used to compare the proportion of PIK3CA-mt and other co-occurring alterations between patients with only clonal and only subclonal PIK3CA-mt. Results:Of 223 eligible patients, 216 (96%) had no prior ALP exposure and were included for further analysis. Most patients had one PIK3CA-mt (199, 73%); 177 (82%) harbored only clonal mutations, 34 (16%) harbored only subclonal mutations, 5 (2%) harbored both. We saw no significant difference in rwTTD or rwTTNT for ALP in patients with clonal vs. subclonal PIK3CA-mt [median months to discontinuation = 5.0 (95% CI 4.0 - 6.9) vs. 7.4 (95% CI 3.7 - 11.1) p=0.82; median months to next treatment =7.0 (95% CI 5.5-9.4) vs. 9.0 (95% CI 4.0-12.6) p=0.81]. We observed no significant differences in the frequency of co-occurring alterations between samples with clonal vs. subclonal PIK3CA-mt (Table 1). Many alterations known to be associated with resistance to ALP and/or CDK4/6 inhibitors were identified, including RB1 and PTEN loss of function mutations. Patients with only subclonal PIK3CA-mt had a significantly higher proportion of E545K and E545G alterations compared to patients with only clonal PIK3CA-mt (E545K: 44% vs 26%, p=0.03; E545G: 6% vs 1%, p=0.017). Conclusions:Examination of RWE in patients treated with ALP after identification of PIK3CA-mt on G360 showed no significant difference in treatment outcomes or co-occurring mutations for clonal vs. subclonal PIK3CA-mt, suggesting that patients with PIK3CA-mt should be considered for ALP therapy irrespective of mutation clonality. While this study focused on outcomes related to PIK3CA hotspot alterations, a significant percentage of patients have PIK3CA non-hotspot alterations; assessment of ALP outcomes in this population is warranted.
Table 1.Frequency of co-occurring alterations by PIK3CA-mt clonalityGeneClonal (N=177)Subclonal (N=34)p valueNo.%No.%TP538649%1441%0.428ESR18146%1338%0.419ATM3319%926%0.295EGFR3218%824%0.458RB12514%412%0.714PTEN2212%412%0.914FGFR12112%515%0.644FGFR22011%412%0.938MET1810%26%0.434SMAD4169%13%0.232ARID1A158%515%0.256APC148%39%0.858BRAF148%26%0.683GATA3137%26%0.761KRAS137%39%0.765BRCA1127%39%0.671KIT116%13%0.450CDK12106%13%0.515AR85%39%0.301BRCA285%26%0.732
Citation Format: Dejan Juric, Caroline Weipert, Leslie Bucheit, Rebecca Nagy, Justin Odegaard, Junhua Yu, Nicole Zhang, Jiemin Liao. Impact of PIK3CA mutation (PIK3CA-mt) clonality on alpelisib (ALP) activity based on real-world evidence (RWE) following liquid biopsy testing [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-18-07.
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Kasi PM, Klempner SJ, Starr JS, Shergill A, Bucheit LA, Weipert C, Liao J, Zhao J, Hardin A, Zhang N, Lang K. Clinical utility of microsatellite instability (MSI-H) identified on liquid biopsy in advanced gastrointestinal cancers (aGI). J Clin Oncol 2022. [DOI: 10.1200/jco.2022.40.4_suppl.056] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
56 Background: Identification of MSI-H is clinically meaningful in patients with aGI given the associated approval of multiple immune checkpoint inhibitors. MSI-H has long been assessed via tissue analysis; and insights from plasma-based approaches are limited to small validation studies. We sought to assess prevalence of initial and acquired MSI-H status across aGI and report real-world outcomes of colorectal (CRC) patients who received ICI after MSI-H identification by a commercially available liquid biopsy (LBx) assay. Methods: Genomic results from a well-validated LBx assay (Guardant360) completed as part of usual clinical care between 10/1/2018-9/7/2021 in patients with aGI were queried to assess MSI-H prevalence and identify cases of potential acquired MSI-H. Real-world evidence (RWE) was sourced from the GuardantINFORM database comprised of aggregated payer claims and de-identified records from 11/1/2018-3/31/2021. Patients with plasma-identified MSI-H who started new therapy < 60 days after assay report date were sorted into treatment groups: chemotherapy +/- biologic therapy (“chemo”) or immunotherapy via pembrolizumab or nivolumab (“ICI”). Real-world time to discontinuation (rwTTD) and real-world time to next treatment (rwTTNT) were assessed as proxies for progression free survival. Log-rank tests were used to assess differences in rwTTD, rwTTNT and overall survival. Results: Prevalence of MSI-H was ̃2% across aGI (Table). Five cases were observed to have potential acquired MSI not attributable to tumor shed identified on serial LBx tests. Of 222 MSI-H CRC patients eligible for RWE analysis, 89(40%) started new therapy within 60 days of results: 42(48%) received ICI, 39(44%) received chemo, 8(9%) received other/mixed regimens. Patients who received ICI had significantly longer rwTTD and rwTTNT compared to patients who received chemo [median months to discontinuation = 7.5 (95% CI 3.4-12.3) vs. 2 (95% 1.4-3.3) p<0.001; median months to next treatment = 23.8 (95% 10.6-NA) vs. 4.5 (95% CI 2.9-NA) p=0.006]; no overall survival difference was observed (p=0.559). Conclusions: This LBx assay detected MSI-H at similar frequencies to published tissue cohorts and may identify acquired MSI-H following early lines of therapy. Patients who received ICI following LBx identification of MSI-H achieved responses in line with published data in previously treated aGI. Well-validated LBx is a viable tool to identify initial and acquired MSI-H in aGI and may expand the number of patients who could benefit from ICI therapy, particularly in cases where access to tissue specimens is not feasible. [Table: see text]
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Affiliation(s)
| | | | - Jason S. Starr
- University of Florida Health Cancer Center, Jacksonville, FL
| | - Ardaman Shergill
- The University of Chicago, Medical and Biological Sciences, Chicago, IL
| | | | | | | | - Jing Zhao
- Guardant Health, Inc, Redwood City, CA
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Goud R, Lufkin B, Duffy J, Whitaker B, Wong HL, Liao J, Lo AC, Parulekar S, Agger P, Anderson SA, Wernecke M, MaCurdy TE, Weintraub E, Kelman JA, Forshee RA. Risk of Guillain-Barré Syndrome Following Recombinant Zoster Vaccine in Medicare Beneficiaries. JAMA Intern Med 2021; 181:1623-1630. [PMID: 34724025 PMCID: PMC8561433 DOI: 10.1001/jamainternmed.2021.6227] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [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]
Abstract
IMPORTANCE Guillain-Barré syndrome can be reported after vaccination. This study assesses the risk of Guillain-Barré syndrome after administration of recombinant zoster vaccine (RZV or Shingrix), which is administered in 2 doses 2 to 6 months apart. OBJECTIVE Use Medicare claims data to evaluate risk of developing Guillain-Barré syndrome following vaccination with zoster vaccine. DESIGN, SETTING, AND PARTICIPANTS This case series cohort study included 849 397 RZV-vaccinated and 1 817 099 zoster vaccine live (ZVL or Zostavax)-vaccinated beneficiaries aged 65 years or older. Self-controlled analyses included events identified from 2 113 758 eligible RZV-vaccinated beneficiaries 65 years or older. We compared the relative risk of Guillain-Barré syndrome after RZV vs ZVL, followed by claims-based and medical record-based self-controlled case series analyses to assess risk of Guillain-Barré syndrome during a postvaccination risk window (days 1-42) compared with a control window (days 43-183). In self-controlled analyses, RZV vaccinees were observed from October 1, 2017, to February 29, 2020. Patients were identified in the inpatient, outpatient procedural (including emergency department), and office settings using Medicare administrative data. EXPOSURES Vaccination with RZV or ZVL vaccines. MAIN OUTCOMES AND MEASURES Guillain-Barré syndrome was identified in Medicare administrative claims data, and cases were assessed through medical record review using the Brighton Collaboration case definition. RESULTS Amongst those who received RZV vaccinees, the mean age was 74.8 years at first dose, and 58% were women, whereas among those who received the ZVL vaccine, the mean age was 74.3 years, and 60% were women. In the cohort analysis we detected an increase in risk of Guillain-Barré syndrome among RZV vaccinees compared with ZVL vaccinees (rate ratio [RR], 2.34; 95% CI, 1.01-5.41; P = .047). In the self-controlled analyses, we observed 24 and 20 cases during the risk and control period, respectively. Our claims-based analysis identified an increased risk in the risk window compared with the control window (RR, 2.84; 95% CI, 1.53-5.27; P = .001), with an attributable risk of 3 per million RZV doses (95% CI, 0.62-5.64). Our medical record-based analysis confirmed this increased risk (RR, 4.96; 95% CI, 1.43-17.27; P = .01). CONCLUSIONS AND RELEVANCE Findings of this case series cohort study indicate a slightly increased risk of Guillain-Barré syndrome during the 42 days following RZV vaccination in the Medicare population, with approximately 3 excess Guillain-Barré syndrome cases per million vaccinations. Clinicians and patients should be aware of this risk, while considering the benefit of decreasing the risk of herpes zoster and its complications through an efficacious vaccine, as risk-benefit balance remains in favor of vaccination.
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Affiliation(s)
- Ravi Goud
- Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland
| | | | - Jonathan Duffy
- Immunization Safety Office, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Barbee Whitaker
- Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland
| | - Hui-Lee Wong
- Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland
| | | | | | | | - Paula Agger
- Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland
| | - Steven A Anderson
- Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland
| | | | - Thomas E MaCurdy
- Acumen, LLC.,Department of Economics, Stanford University, Stanford, California
| | - Eric Weintraub
- Immunization Safety Office, Centers for Disease Control and Prevention, Atlanta, Georgia
| | | | - Richard A Forshee
- Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland
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Liao J, Kwah J, Shafi S. M041 DRUG REACTION WITH EOSINOPHILIA AND SYSTEMIC SYMPTOMS SYNDROME CAUSED BY INTERMITTENT USE OF BUPROPION. Ann Allergy Asthma Immunol 2021. [DOI: 10.1016/j.anai.2021.08.215] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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21
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Centorame A, Ondra M, Dumut D, Shah J, Liao J, Hanrahan J, Sanctis JD, Hajduch M, Radzioch D. 627: Investigation of pharmacological correction of F508del-CFTR protein during chronic infections. J Cyst Fibros 2021. [DOI: 10.1016/s1569-1993(21)02050-6] [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: 11/29/2022]
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22
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Ondra M, Centorame A, Dumut D, Liao J, Hanrahan J, De Sanctis J, Hajduch M, Radzioch D. 678: Design and validation of luminescent HTS tool for discovery and optimization of novel combination of CFTR correctors and modifiers. J Cyst Fibros 2021. [DOI: 10.1016/s1569-1993(21)02101-9] [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: 11/17/2022]
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23
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Yue Y, Chen H, Wang L, Du XB, Gao XF, Liao J, Zhou R, Chen ZH, Chen YZ, Huang WW, Huang XF, Hu M, Zhao CL, Du CH, Deng LL, Liang X, Liu Z. [Analysis on the imported Coronavirus Disease 2019 related cluster epidemic in rural areas of Chengdu]. Zhonghua Yu Fang Yi Xue Za Zhi 2021; 55:1240-1244. [PMID: 34706511 DOI: 10.3760/cma.j.cn112150-20210421-00396] [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: 11/05/2022]
Abstract
An epidemiological investigation was carried out on a local cluster of outbreak caused by imported cases of Coronavirus Disease 2019 (COVID-19) in rural areas of Chengdu in December 2020, to find out the source of infection and the chain of transmission. According to Prevention and Control Protocol for COVID-19 (Version 7), field epidemiological investigation was adopted, combined with big data technology, video image investigation, gene sequencing and other methods to carry out investigation into COVID-19 cases and infections source tracing, analyze the epidemiological association, and map the chain of transmission. From December 7 to 17, 2020, 13 local COVID-19 confirmed cases and 1 asymptomatic case were diagnosed in Chengdu, of which 12 cases (85.71%) had a history of residence and activity in the village courtyard of Taiping (TP), Pidu (P) District, Chengdu. From November 8, 2020 to November 28, 2020, a group of inbound people form Nepal were transferred to the designated entry personnel quarantine hotel of P District which was adjacent to the TP village. During quarantine, there were 5 cases who tested positive for COVID-19. Through gene sequencing alignment, genes of local cases and Nepalese imported cases from the same period are homologous, all belong to the lineage of L2.2.3 (B.1.36 according to Pangolin lineage typing method). According to the results of field epidemiological investigation and gene sequencing analysis, the index case was most likely infected by contact with household waste of quarantine site. Under the situation of normalization prevention and control of COVID-19, sentinel monitoring of fever clinics in primary medical institutions is the key to early detection of the epidemic. The multi-department joint epidemiological investigation and the application of gene technology are the core links of the investigation and traceability of modern infectious diseases. The allocation of public health resources in rural areas needs to be strengthened. We need to improve the capacity for early surveillance and early warning of the epidemic in rural areas.
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Affiliation(s)
- Y Yue
- Chengdu Center for Disease Control and Prevention, Chengdu 610041, China Chengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - H Chen
- Chengdu Center for Disease Control and Prevention, Chengdu 610041, China Chengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - L Wang
- Chengdu Center for Disease Control and Prevention, Chengdu 610041, China Chengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - X B Du
- Chengdu Center for Disease Control and Prevention, Chengdu 610041, China Chengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - X F Gao
- Chengdu Center for Disease Control and Prevention, Chengdu 610041, China Chengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - J Liao
- Chengdu Center for Disease Control and Prevention, Chengdu 610041, China Chengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - R Zhou
- Chengdu Center for Disease Control and Prevention, Chengdu 610041, China Chengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Z H Chen
- Chengdu Center for Disease Control and Prevention, Chengdu 610041, China Chengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Y Z Chen
- Chengdu Center for Disease Control and Prevention, Chengdu 610041, China Chengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - W W Huang
- Chengdu Center for Disease Control and Prevention, Chengdu 610041, China Chengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - X F Huang
- Pidu District Center for Disease Control and Prevention, Chengdu 611730, China Chengdu Center for Disease Control and Prevention, Chengdu 610041, China Chengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - M Hu
- Chengdu Center for Disease Control and Prevention, Chengdu 610041, China Chengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - C L Zhao
- Chengdu Center for Disease Control and Prevention, Chengdu 610041, China Chengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - C H Du
- Chengdu Center for Disease Control and Prevention, Chengdu 610041, China Chengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - L L Deng
- Chengdu Center for Disease Control and Prevention, Chengdu 610041, China Chengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - X Liang
- Chengdu Center for Disease Control and Prevention, Chengdu 610041, China Chengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Z Liu
- Chengdu Center for Disease Control and Prevention, Chengdu 610041, China Chengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Chengdu 610041, China
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Bierma M, Goff P, Hippe D, Lachance K, Schaub S, Tseng Y, Apisarnthanarax S, Liao J, Parvathaneni U, Nghiem P. LB759 Post-operative radiation therapy to prevent local recurrence of low-risk Merkel cell carcinomas of the head and neck versus other sites. J Invest Dermatol 2021. [DOI: 10.1016/j.jid.2021.07.101] [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]
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25
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Lee WT, Ng KW, Liao J, Luk ACS, Suen HC, Chan THT, Cheung MY, Chu D, Zhao M, Chan YL, Li TC, Lee TL. P–547 Single-cell RNA sequencing identifies molecular regulations associated with poor maturation performance on rescue in vitro matured oocytes. Hum Reprod 2021. [DOI: 10.1093/humrep/deab130.546] [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: 11/12/2022] Open
Abstract
Abstract
Study question
What is the transcriptome signature associated with rescuein vitro matured (rIVM) oocytes?
Summary answer
GATA–1/CREB1/WNT signaling axis was repressed in rIVM oocytes of poor quality.
What is known already
rIVM aims to produce mature oocytes (MII) for in vitro fertilization (IVF) through IVM of immature oocytes collected from stimulated ovaries. It is less popular due to limited success rate in infertility treatment. Genetic aberrations, cellular stress, and the absence of cumulus cell support in oocytes could account for the failure of rIVM.
Study design, size, duration
We applied single-cell RNA sequencing (scRNA-seq) to capture the transcriptomes of human in vivo (IVO) oocytes (n = 10) from 7 donors and rIVM oocytes (n = 10) from 10 donors, followed by studying the maternal age effect and ovarian responses on rIVM oocyte transcriptomes.
Participants/materials, setting, methods
Human oocytes were collected from donors aged 28–41 years with a body mass index of < 30. RNA extraction, cDNA generation, library construction and sequencing were performed in one preparation. scRNA-seq data were then processed and analyzed. Selected genes in therIVM vs. IVO comparison were validated by quantitative real-time PCR.
Main results and the role of chance
The transcriptome profiles of rIVM/IVO showed distinctive differences. A total of 1559 differentially expressed genes (DEGs, genes with at least two-fold change and adjusted p < 0.05) were found to be enriched in metabolic processes, biosynthesis, and oxidative phosphorylation. Among these DEGs, we identified a repression of WNT/β-catenin signaling in rIVM when compared with IVO oocytes. We found that estradiol level exhibited a significant age-independent correlation with the IVO mature oocyte ratio (MII ratio). rIVM oocytes with higher MII ratio showed over-represented cellular processes such as anti-apoptosis. To further identify targets that contribute to the poor outcomes of rIVM, we compared oocytes collected from young donors with high MII ratio versus donors of advanced maternal age and revealed CREB1was an important regulator in rIVM. Our study identified GATA–1/CREB1/WNT signaling was repressed in both rIVM condition and rIVM oocytes of low-quality.
Limitations, reasons for caution
In the rIVM oocytes of high- and low-quality comparison, the number of samples was limited after data filtering with stringent selection criteria. For the oocyte stage identification, we were unable to predict the presence of oocyte spindle so polar body extrusion was the only indicator.
Wider implications of the findings: This study showed that GATA–1/CREB1/WNT signaling and antioxidant actions were repressed in rIVM condition and was further downregulated in rIVM oocytes of low-quality, providing us the foundation of subsequent follow-up research on human subjects.
Trial registration number
Not applicable
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Affiliation(s)
- W T Lee
- The Chinese University of Hong Kong, School of Biomedical Sciences, Hong Kong, Hong Kong
| | - K W Ng
- The Chinese University of Hong Kong, School of Biomedical Sciences, Hong Kong, Hong Kong
| | - J Liao
- The Chinese University of Hong Kong, School of Biomedical Sciences, Hong Kong, Hong Kong
| | - A C S Luk
- The Chinese University of Hong Kong, School of Biomedical Sciences, Hong Kong, Hong Kong
| | - H C Suen
- The Chinese University of Hong Kong, School of Biomedical Sciences, Hong Kong, Hong Kong
| | - T H T Chan
- The Chinese University of Hong Kong, School of Biomedical Sciences, Hong Kong, Hong Kong
| | - M Y Cheung
- The Chinese University of Hong Kong, School of Biomedical Sciences, Hong Kong, Hong Kong
| | - D Chu
- The Chinese University of Hong Kong, School of Biomedical Sciences, Hong Kong, Hong Kong
| | - M Zhao
- The Chinese University of Hong Kong, Department of Obstetrics and Gynaecology, Hong Kong, Hong Kong
| | - Y L Chan
- The Chinese University of Hong Kong, Department of Obstetrics and Gynaecology, Hong Kong, Hong Kong
| | - T C Li
- The Chinese University of Hong Kong, Department of Obstetrics and Gynaecology, Hong Kong, Hong Kong
| | - T L Lee
- The Chinese University of Hong Kong, School of Biomedical Sciences, Hong Kong, Hong Kong
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26
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Lee AWT, Ng JKW, Liao J, Luk AC, Suen AHC, Chan TTH, Cheung MY, Chu HT, Tang NLS, Zhao MP, Lian Q, Chan WY, Chan DYL, Leung TY, Chow KL, Wang W, Wang LH, Chen NCH, Yang WJ, Huang JY, Li TC, Lee TL. Single-cell RNA sequencing identifies molecular targets associated with poor in vitro maturation performance of oocytes collected from ovarian stimulation. Hum Reprod 2021; 36:1907-1921. [PMID: 34052851 DOI: 10.1093/humrep/deab100] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [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: 10/12/2020] [Revised: 03/08/2021] [Indexed: 12/14/2022] Open
Abstract
STUDY QUESTION What is the transcriptome signature associated with poor performance of rescue IVM (rIVM) oocytes and how can we rejuvenate them? SUMMARY ANSWER The GATA-1/CREB1/WNT signalling axis was repressed in rIVM oocytes, particularly those of poor quality; restoration of this axis may produce more usable rIVM oocytes. WHAT IS KNOWN ALREADY rIVM aims to produce mature oocytes (MII) for IVF through IVM of immature oocytes collected from stimulated ovaries. It is not popular due to limited success rate in infertility treatment. Genetic aberrations, cellular stress and the absence of cumulus cell support in oocytes could account for the failure of rIVM. STUDY DESIGN, SIZE, DURATION We applied single-cell RNA sequencing (scRNA-seq) to capture the transcriptomes of human in vivo oocytes (IVO) (n = 10) from 7 donors and rIVM oocytes (n = 10) from 10 donors. The effects of maternal age and ovarian responses on rIVM oocyte transcriptomes were also studied. In parallel, we studied the effect of gallic acid on the maturation rate of mouse oocytes cultured in IVM medium with (n = 84) and without (n = 85) gallic acid. PARTICIPANTS/MATERIALS, SETTING, METHODS Human oocytes were collected from donors aged 28-41 years with a body mass index of <30. RNA extraction, cDNA generation, library construction and sequencing were performed in one preparation. scRNA-seq data were then processed and analysed. Selected genes in the rIVM versus IVO comparison were validated by quantitative real-time PCR. For the gallic acid study, we collected immature oocytes from 5-month-old mice and studied the effect of 10-μM gallic acid on their maturation rate. MAIN RESULTS AND THE ROLE OF CHANCE The transcriptome profiles of rIVM/IVO oocytes showed distinctive differences. A total of 1559 differentially expressed genes (DEGs, genes with at least 2-fold change and adjusted P < 0.05) were found to be enriched in metabolic processes, biosynthesis and oxidative phosphorylation. Among these DEGs, we identified a repression of WNT/β-catenin signalling in rIVM when compared with IVO oocytes. We found that oestradiol levels exhibited a significant age-independent correlation with the IVO mature oocyte ratio (MII ratio) for each donor. rIVM oocytes from women with a high MII ratio were found to have over-represented cellular processes such as anti-apoptosis. To further identify targets that contribute to the poor clinical outcomes of rIVM, we compared oocytes collected from young donors with a high MII ratio with oocytes from donors of advanced maternal age and lower MII ratio, and revealed that CREB1 is an important regulator. Thus, our study identified that GATA-1/CREB1/WNT signalling was repressed in both rIVM oocytes versus IVO oocytes and in rIVM oocytes of lower versus higher quality. Consequently we investigated gallic acid, as a potential antioxidant substrate in human rIVM medium, and found that it increased the mouse oocyte maturation rate by 31.1%. LARGE SCALE DATA Raw data from this study can be accessed through GSE158539. LIMITATIONS, REASONS FOR CAUTION In the rIVM oocytes of the high- and low-quality comparison, the number of samples was limited after data filtering with stringent selection criteria. For the oocyte stage identification, we were unable to predict the presence of oocyte spindle, so polar body extrusion was the only indicator. WIDER IMPLICATIONS OF THE FINDINGS This study showed that GATA-1/CREB1/WNT signalling was repressed in rIVM oocytes compared with IVO oocytes and was further downregulated in low-quality rIVM oocytes, providing us the foundation of subsequent follow-up research on human oocytes and raising safety concerns about the clinical use of rescued oocytes. STUDY FUNDING/COMPETING INTEREST(S) This work was supported by the Collaborative Research Fund, Research Grants Council, C4054-16G, and Research Committee Funding (Research Sustainability of Major RGC Funding Schemes), The Chinese University of Hong Kong. The authors have no conflicts of interest to declare.
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Affiliation(s)
- A W T Lee
- Developmental and Regenerative Biology Program, School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, PR China
| | - J K W Ng
- Developmental and Regenerative Biology Program, School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, PR China
| | - J Liao
- Developmental and Regenerative Biology Program, School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, PR China
| | - A C Luk
- Developmental and Regenerative Biology Program, School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, PR China
| | - A H C Suen
- Developmental and Regenerative Biology Program, School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, PR China
| | - T T H Chan
- Developmental and Regenerative Biology Program, School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, PR China
| | - M Y Cheung
- Developmental and Regenerative Biology Program, School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, PR China
| | - H T Chu
- Developmental and Regenerative Biology Program, School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, PR China
| | - N L S Tang
- Department of Chemical Pathology, and Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, PR China
| | - M P Zhao
- Assisted Reproductive Technology Unit, Department of Obstetrics and Gynaecology, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, PR China
| | - Q Lian
- Department of Medicine, The University of Hong Kong, Hong Kong SAR, PR China
| | - W Y Chan
- Developmental and Regenerative Biology Program, School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, PR China
| | - D Y L Chan
- Assisted Reproductive Technology Unit, Department of Obstetrics and Gynaecology, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, PR China
| | - T Y Leung
- Department of Medicine, The University of Hong Kong, Hong Kong SAR, PR China
| | - K L Chow
- Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, N.T., Hong Kong SAR, PR China.,Division of Life Science, Hong Kong University of Science and Technology, Shatin, N.T., Hong Kong SAR, PR China
| | - W Wang
- Department of Obstetrics and Gynecology, IVF Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - L H Wang
- Institute of Molecular and Cellular Biology & Department of Medical Sciences, National Tsing Hua University, Hsinchu, Taiwan
| | - N C H Chen
- Department of Infertility and Reproductive Medicine, Taiwan IVF Group Center, Hsinchu City, Taiwan
| | - W J Yang
- Department of Infertility and Reproductive Medicine, Taiwan IVF Group Center, Hsinchu City, Taiwan
| | - J Y Huang
- Department of Infertility and Reproductive Medicine, Taiwan IVF Group Center, Hsinchu City, Taiwan
| | - T C Li
- Assisted Reproductive Technology Unit, Department of Obstetrics and Gynaecology, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, PR China
| | - T L Lee
- Developmental and Regenerative Biology Program, School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, PR China
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Tian X, Li X, Yu Q, Zhao H, Liao J. Asymmetric expression patterns of B- and C-class MADS-box genes correspond to the asymmetrically specified androecial identities of Canna indica. Plant Biol (Stuttg) 2021; 23:540-545. [PMID: 33342001 DOI: 10.1111/plb.13231] [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] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 12/04/2020] [Indexed: 06/12/2023]
Abstract
Canna indica is a common ornamental plant with asymmetric flowers having colourful petaloid staminodes. The only fertile stamen comprises a one-theca anther and a petaloid appendage and represents the lowest stamen number in the order Zingiberales. The molecular mechanism for the asymmetric androecial petaloidy remains poorly understood. Here, we studied the identity specification in Canna stamen. We observed four types of abnormal flower in terms of androecium identity transformation and analysed the corresponding floral symmetry changes. We further tested the expression patterns of B- and C-class MADS-box genes using in situ hybridization in normal Canna stamen. Homeotic conversions in the androecium were accompanied by floral symmetry changes, and the asymmetric stamen is key in contributing to the floral asymmetry. Both B- and C-class genes exhibited higher expression levels in the anther primordium than in other androecial parts. This asymmetric expression pattern precisely corresponded to the asymmetric identities of the Canna androecium. We identified C. indica as a model species for studying androecial organ identity and floral symmetry synthetically in Zingiberales. We hypothesized that homeotic genes specify floral organ identity in a putative dose-dependent manner. The results add to the current understanding of organ identity-related floral symmetry.
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Affiliation(s)
- X Tian
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, Guangdong, China
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - X Li
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Q Yu
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, Guangdong, China
| | - H Zhao
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, Guangdong, China
- Xinxing Vocational School of Traditional Chinese Medicine, Xinxing, Guangdong, China
| | - J Liao
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, Guangdong, China
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Zhang T, Li W, Qiu X, Liu B, Li G, Feng C, Liao J, Lin K. [CRISPR/Cas9-mediated TEAD1 knockout induces phenotypic modulation of corpus cavernosum smooth muscle cells in diabetic rats with erectile dysfunction]. Nan Fang Yi Ke Da Xue Xue Bao 2021; 41:567-573. [PMID: 33963717 DOI: 10.12122/j.issn.1673-4254.2021.04.13] [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] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
OBJECTIVE To construct a corpus cavemosum smooth muscle cell (CCSMCs) line with TEAD1 knockout from diabetic rats with erectile dysfunction (ED) using CRISPR/Cas9 technology and explore the role of TEAD1 in phenotypic modulation of CCSMCs in diabetic rats with ED. OBJECTIVE Models of diabetic ED were established in male Sprague-Dawley rats by intraperitoneal injection of streptozotocin. CCSMCs from the rat models were primarily cultured and identified with immunofluorescence assay. Three sgRNAs (sgRNA-1, sgRNA-2 and sgRNA-3) were transfected via lentiviral vectors into 293T cells to prepare the sgRNA-Cas9 lentivirus. CCSMCs from diabetic rats with ED were infected by the lentivirus, and the cellular expression of TEAD1 protein was detected using Western blotting. In CCSMCs infected with the sgRNA-Cas9 lentivirus (CCSMCs-sgRNA-2), or the empty lentiviral vector (CCSMCs-sgRNA-NC) and the blank control cells (CCSMCs-CK), the expressions of cellular phenotypic markers SMMHC, calponin and PCNA at the mRNA and protein levels were detected using real-time fluorescence quantitative RT-PCR (qRT-PCR) and Western blotting, respectively. OBJECTIVE The primarily cultured CCSMCs from diabetic rats with ED showed a high α-SMA-positive rate of over 95%. The recombinant lentivirus of TEAD1-sgRNA was successfully packaged, and stable TEAD1-deficient CCSMC lines derived from diabetic rat with ED were obtained. Western blotting confirmed that the protein expression of TEAD1 in TEAD1-sgRNA-2 group was the lowest (P < 0.05), and this cell line was used in subsequent experiment. The results of qRT-PCR and Western blotting showed significantly up-regulated expressions of SMMHC and calponin (all P < 0.05) and down-regulated expression of PCNA (all P < 0.05) at both the mRNA and protein levels in TEAD1-deficient CCSMCs from diabetic rats with ED. OBJECTIVE We successfully constructed a stable CCSMCs line with CRISPR/Cas9-mediated TEAD1 knockout from diabetic rats with ED. TEAD1 gene knockout can induce phenotype transformation of the CCSMCs from diabetic rats with ED from the synthetic to the contractile type.
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Affiliation(s)
- T Zhang
- Department of Urology, Second Guangdong Provincial People's Hospital, Guangzhou 510317, China
| | - W Li
- Department of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - X Qiu
- Department of Urology, Second Guangdong Provincial People's Hospital, Guangzhou 510317, China
| | - B Liu
- Department of Urology, Second Guangdong Provincial People's Hospital, Guangzhou 510317, China
| | - G Li
- Department of Urology, Second Guangdong Provincial People's Hospital, Guangzhou 510317, China
| | - C Feng
- Department of Urology, Second Guangdong Provincial People's Hospital, Guangzhou 510317, China
| | - J Liao
- Department of Urology, Second Guangdong Provincial People's Hospital, Guangzhou 510317, China
| | - K Lin
- Department of Urology, Second Guangdong Provincial People's Hospital, Guangzhou 510317, China
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Liao J, Li Y, Deng J, Li H, Wang W, Zhang D, Wang J, Zhang L, Xie M. Response to: Rationale of bedside ultrasound-guided inferior vena cava filter implantation in COVID-19 patients with deep venous thrombosis. QJM 2021; 114:148-149. [PMID: 33515258 PMCID: PMC7928591 DOI: 10.1093/qjmed/hcaa338] [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] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Indexed: 11/15/2022] Open
Affiliation(s)
- J Liao
- From the Department of Ultrasound, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
| | - Y Li
- From the Department of Ultrasound, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
| | - J Deng
- Department of Cardiovascular Imaging, St Bartholomew's Hospital, London, UK
| | - H Li
- From the Department of Ultrasound, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
| | - W Wang
- Department of vascular surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - D Zhang
- From the Department of Ultrasound, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
| | - J Wang
- From the Department of Ultrasound, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
| | - L Zhang
- From the Department of Ultrasound, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
| | - M Xie
- From the Department of Ultrasound, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
- Address correspondence to M. Xie, Department of Ultrasound, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
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Liu X, Wang Y, Qin Q, Zhang L, Liao J, Li Q, Jiang B. P32.02 Cohort Study of Rehabilitation Quality in Patients With U-VATS and M-VATS Lobectomy. J Thorac Oncol 2021. [DOI: 10.1016/j.jtho.2021.01.663] [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: 10/21/2022]
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31
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Wu FF, Chen XX, Wei GF, Lin SR, Liao J, Lin WN. [One case of removal of complex esophageal foreign body guided by ultrasound gastroscope]. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 2021; 56:79-80. [PMID: 33472307 DOI: 10.3760/cma.j.cn115330-20200520-00426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- F F Wu
- Department of Otorhinolaryngology Head and Neck Surgery, First Hospital Affiliated to Fujian Medical University, Quanzhou 362000, China
| | - X X Chen
- Department of Gastroscopy, First Hospital Affiliated to Fujian Medical University, Quanzhou 362000, China
| | - G F Wei
- Department of Otorhinolaryngology Head and Neck Surgery, First Hospital Affiliated to Fujian Medical University, Quanzhou 362000, China
| | - S R Lin
- Department of Otorhinolaryngology Head and Neck Surgery, First Hospital Affiliated to Fujian Medical University, Quanzhou 362000, China
| | - J Liao
- Department of Otorhinolaryngology Head and Neck Surgery, First Hospital Affiliated to Fujian Medical University, Quanzhou 362000, China
| | - W N Lin
- Department of Otorhinolaryngology Head and Neck Surgery, First Hospital Affiliated to Fujian Medical University, Quanzhou 362000, China
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Menis M, Whitaker BI, Wernecke M, Jiao Y, Eder A, Kumar S, Xu W, Liao J, Wei Y, MaCurdy TE, Kelman JA, Anderson SA, Forshee RA. Babesiosis Occurrence Among United States Medicare Beneficiaries, Ages 65 and Older, During 2006-2017: Overall and by State and County of Residence. Open Forum Infect Dis 2020; 8:ofaa608. [PMID: 33598501 DOI: 10.1093/ofid/ofaa608] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [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: 09/08/2020] [Accepted: 12/09/2020] [Indexed: 12/29/2022] Open
Abstract
Background Human babesiosis is a mild-to-severe parasitic infection that poses health concerns especially in older and other at-risk populations. The study objective was to assess babesiosis occurrence among US Medicare beneficiaries, ages 65 and older, during 2006-2017. Methods Our retrospective claims-based study used Medicare databases. Babesiosis cases were identified using recorded diagnosis codes. The study estimated rates (per 100 000 beneficiary-years) overall, by year, diagnosis month, demographics, and state and county of residence. Results Nationwide, 19 469 beneficiaries had babesiosis recorded, at a rate of 6 per 100 000 person-years, ranging from 4 in 2006 to 9 in 2017 (P < .05). The highest babesiosis rates by state were in the following: Massachusetts (62), Rhode Island (61), Connecticut (51), New York (30), and New Jersey (19). The highest rates by county were in the following: Nantucket, Massachusetts (1089); Dukes, Massachusetts (236); Barnstable, Massachusetts (213); and Dutchess, New York (205). Increasing rates, from 2006 through 2017 (P < .05), were identified in multiple states, including states previously considered nonendemic. New Hampshire, Maine, Vermont, Pennsylvania, and Delaware saw rates increase by several times. Conclusions Our 12-year study shows substantially increasing babesiosis diagnosis trends, with highest rates in well established endemic states. It also suggests expansion of babesiosis infections in other states and highlights the utility of real-world evidence.
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Affiliation(s)
- Mikhail Menis
- Food and Drug Administration, Silver Spring, Maryland, USA
| | | | | | | | - Anne Eder
- Food and Drug Administration, Silver Spring, Maryland, USA
| | - Sanjai Kumar
- Food and Drug Administration, Silver Spring, Maryland, USA
| | - Wenjie Xu
- Acumen LLC, Burlingame, California, USA
| | | | - Yuqin Wei
- Acumen LLC, Burlingame, California, USA
| | - Thomas E MaCurdy
- Acumen LLC, Burlingame, California, USA.,Stanford University, Stanford, California, USA
| | - Jeffrey A Kelman
- Centers for Medicare & Medicaid Services, Baltimore, Maryland, USA
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Eworuke E, Crisafi L, Liao J, Akhtar S, Van Clief M, Racoosin JA, Wernecke M, MaCurdy TE, Kelman JA, Graham DJ. Risk of serious spinal adverse events associated with epidural corticosteroid injections in the Medicare population. Reg Anesth Pain Med 2020; 46:203-209. [PMID: 33277405 DOI: 10.1136/rapm-2020-101778] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 10/30/2020] [Accepted: 11/04/2020] [Indexed: 01/31/2023]
Abstract
BACKGROUND Epidural corticosteroid injections (ESIs) are widely performed and have an unquantified risk of serious spinal adverse events (SSAEs). We sought to determine the rate of SSAEs following ESI and to compare the rates by spinal level, injection approach and corticosteroid formulation. METHODS We included patients enrolled in Medicare parts A and B who had an ESI between 1 January 2009 and 30 September 2015. We identified potential cases as patients with spine-related diagnoses within 3 days after the first eligible ESI. Event categorization as probable, possible or non-case was based on review of medical records. The rates of probable and possible cases were expressed per 1 000 000 patients overall, and by spinal level, injection approach and corticosteroid formulation. A score test was used to compare these rates. RESULTS We identified 1 355 957 eligible ESIs during the study period. Of the 110 potential cases, 43 were selected for medical record review and 11 were categorized as probable, yielding a rate of 8.1 per 1 000 000 patients (95% CI 4.5 to 14.5). Risk of SSAEs was statistically higher with cervical/thoracic injections (29.4, 95% CI 12.5 to 68.8) compared with lumbar/sacral injections (5.1, 95% CI 2.3 to 11.0) (p value 0.001). Event rates for lumbar/sacral non-transforaminal injections was 8.8 (95% CI 4.0 to 19.1). Event rates for particulate (7.5, 95% CI 3.9 to 14.2) and non-particulate formulations (13.1, 95% CI 3.6 to 47.9) appeared similar (p value 0.47). CONCLUSION Between 2009 and 2015, rates of SSAEs following ESI in the Medicare population were low. Patients receiving cervical/thoracic ESIs were at higher risk of SSAE than those receiving lumbar/sacral ESIs. Event rates were similar for each corticosteroid formulation.
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Affiliation(s)
- Efe Eworuke
- Division of Epidemiology, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Leah Crisafi
- Department of Perioperative Medicine, Clinical Center, National Institutes of Health, Bethesda, Maryland, USA
| | | | | | - Martha Van Clief
- Division of Epidemiology, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Judith A Racoosin
- Division of Epidemiology, US Food and Drug Administration, Silver Spring, Maryland, USA
| | | | | | - Jeffrey A Kelman
- Centers for Medicare and Medicaid Services Washington DC Office, Washington, District of Columbia, USA
| | - David J Graham
- Division of Epidemiology, US Food and Drug Administration, Silver Spring, Maryland, USA
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34
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Akerib D, Alsum S, Araújo H, Bai X, Balajthy J, Baxter A, Bernard E, Bernstein A, Biesiadzinski T, Boulton E, Boxer B, Brás P, Burdin S, Byram D, Carmona-Benitez M, Chan C, Cutter J, de Viveiros L, Druszkiewicz E, Fan A, Fiorucci S, Gaitskell R, Ghag C, Gilchriese M, Gwilliam C, Hall C, Haselschwardt S, Hertel S, Hogan D, Horn M, Huang D, Ignarra C, Jacobsen R, Jahangir O, Ji W, Kamdin K, Kazkaz K, Khaitan D, Korolkova E, Kravitz S, Kudryavtsev V, Leason E, Lenardo B, Lesko K, Liao J, Lin J, Lindote A, Lopes M, Manalaysay A, Mannino R, Marangou N, McKinsey D, Mei DM, Moongweluwan M, Morad J, Murphy A, Naylor A, Nehrkorn C, Nelson H, Neves F, Nilima A, Oliver-Mallory K, Palladino K, Pease E, Riffard Q, Rischbieter G, Rhyne C, Rossiter P, Shaw S, Shutt T, Silva C, Solmaz M, Solovov V, Sorensen P, Sumner T, Szydagis M, Taylor D, Taylor R, Taylor W, Tennyson B, Terman P, Tiedt D, To W, Tvrznikova L, Utku U, Uvarov S, Vacheret A, Velan V, Webb R, White J, Whitis T, Witherell M, Wolfs F, Woodward D, Xu J, Zhang C. Discrimination of electronic recoils from nuclear recoils in two-phase xenon time projection chambers. Int J Clin Exp Med 2020. [DOI: 10.1103/physrevd.102.112002] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [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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Yu S, Wang G, Liao J, Chen X. A functional mutation in the AMPD1 promoter region affects promoter activity and breast meat freshness in chicken. Anim Genet 2020; 52:121-125. [PMID: 33226134 DOI: 10.1111/age.13025] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [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: 08/06/2020] [Revised: 09/26/2020] [Accepted: 10/30/2020] [Indexed: 12/24/2022]
Abstract
Freshness is an important index to determine the quality deterioration (protein degradation and changes in appearance) of chilled chicken meat and is a primary consideration of consumers. Adenosine monophosphate deaminase 1 (AMPD1) catalyzes the deamination of adenosine monophosphate to inosine monophosphate in skeletal muscle and is the rate-limiting step in the purine nucleotide cycle. Inosine monophosphate is regarded as an important indicator of meat freshness in chicken. This study investigated the association of polymorphisms in the chicken AMPD1 promoter region with meat freshness during freezing storage. An SNP (c. -905G>A) was found to be associated with the freshness (K-value) of chicken breast meat. Chickens with the AA genotype had significantly lower K-values than those with GG and AG genotypes (P < 0.01). Individuals with the AA genotype also had higher breast meat AMPD1 mRNA levels than did those with the GG and AG genotypes (P < 0.01, P < 0.05). A luciferase assay revealed that genotype AA had greater transcriptional activity than genotype GG. Transcription factor binding site analysis identified distinct putative transcription factor binding sites in the two alleles of mutation site c. -905. In summary, we identified an SNP (c. -905G>A) in the promoter region of the AMPD1 gene that may modulate the binding affinity of different transcription factors to control AMPD1 expression and affect the freshness K-value of chicken meat.
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Affiliation(s)
- S Yu
- Engineering Research Center of Sichuan Province Higher School of Local Chicken Breeds Industrialization in Southern Sichuan, College of Life Science, Leshan Normal University, Leshan, 614000, China
| | - G Wang
- Engineering Research Center of Sichuan Province Higher School of Local Chicken Breeds Industrialization in Southern Sichuan, College of Life Science, Leshan Normal University, Leshan, 614000, China
| | - J Liao
- Engineering Research Center of Sichuan Province Higher School of Local Chicken Breeds Industrialization in Southern Sichuan, College of Life Science, Leshan Normal University, Leshan, 614000, China
| | - X Chen
- Leshan Academy of Agricultural Sciences, Leshan, 614000, China
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Perez-Vilar S, Hu M, Weintraub E, Arya D, Lufkin B, Myers T, Woo EJ, Lo AC, Chu S, Swarr M, Liao J, Wernecke M, MaCurdy T, Kelman J, Anderson S, Duffy J, Forshee RA. Guillain-Barré Syndrome After High-Dose Influenza Vaccine Administration in the United States, 2018-2019 Season. J Infect Dis 2020; 223:416-425. [PMID: 33137184 DOI: 10.1093/infdis/jiaa543] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [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: 03/31/2020] [Accepted: 09/09/2020] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND The Vaccine Safety Datalink (VSD) identified a statistical signal for an increased risk of Guillain-Barré syndrome (GBS) in days 1-42 after 2018-2019 high-dose influenza vaccine (IIV3-HD) administration. We evaluated the signal using Medicare. METHODS We conducted early- and end-of-season claims-based self-controlled risk interval analyses among Medicare beneficiaries ages ≥65 years, using days 8-21 and 1-42 postvaccination as risk windows and days 43-84 as control window. The VSD conducted chart-confirmed analyses. RESULTS Among 7 453 690 IIV3-HD vaccinations, we did not detect a statistically significant increased GBS risk for either the 8- to 21-day (odds ratio [OR], 1.85; 95% confidence interval [CI], 0.99-3.44) or 1- to 42-day (OR, 1.31; 95% CI, 0.78-2.18) risk windows. The findings from the end-of-season analyses were fully consistent with the early-season analyses for both the 8- to 21-day (OR, 1.64; 95% CI, 0.92-2.91) and 1- to 42-day (OR, 1.12; 95% CI, 0.70-1.79) risk windows. The VSD's chart-confirmed analysis, involving 646 996 IIV3-HD vaccinations, with 1 case each in the risk and control windows, yielded a relative risk of 1.00 (95% CI, 0.06-15.99). CONCLUSIONS The Medicare analyses did not exclude an association between IIV3-HD and GBS, but it determined that, if such a risk existed, it was similar in magnitude to prior seasons. Chart-confirmed VSD results did not confirm an increased risk of GBS.
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Affiliation(s)
- Silvia Perez-Vilar
- Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Mao Hu
- Acumen LLC, Burlingame, California, USA
| | - Eric Weintraub
- Immunization Safety Office, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Deepa Arya
- Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | | | - Tanya Myers
- Immunization Safety Office, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Emily Jane Woo
- Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - An-Chi Lo
- Acumen LLC, Burlingame, California, USA
| | - Steve Chu
- Centers for Medicare & Medicaid Services, Washington, DC, USA
| | | | | | | | - Tom MaCurdy
- Acumen LLC, Burlingame, California, USA.,Department of Economics, Stanford University, Stanford, California, USA
| | - Jeffrey Kelman
- Centers for Medicare & Medicaid Services, Washington, DC, USA
| | - Steven Anderson
- Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Jonathan Duffy
- Immunization Safety Office, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Richard A Forshee
- Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
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Joshi M, Zakharia Y, Kaag M, Kilari D, Holder S, Emamekhoo H, Sankin A, Liao J, Merrill S, DeGraff D, Zheng H, Warrick J, Hauke R, Gartrell B, Stein M, Drabick J, Tuanquin L. Concurrent Durvalumab And Radiation Therapy (DUART) followed by Adjuvant Durvalumab in Patients with Localized Urothelial Cancer of Bladder: BTCRC-GU15-023. Int J Radiat Oncol Biol Phys 2020. [DOI: 10.1016/j.ijrobp.2020.07.2124] [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: 11/29/2022]
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Liao J, Dong LP. Linc00261 suppresses growth and metastasis of non-small cell lung cancer via repressing epithelial-mesenchymal transition. Eur Rev Med Pharmacol Sci 2020; 23:3829-3837. [PMID: 31115010 DOI: 10.26355/eurrev_201905_17810] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Long non-coding RNAs (lncRNAs) have been identified to participate in the development and progression of various types of cancers, including non-small cell lung cancer (NSCLC). However, the expression and function of linc00261 in NSCLC has not been studied yet. We aim to explore the role and potential of linc00261 in NSCLC tumorigenesis. PATIENTS AND METHODS The expression level of linc00261 in 71 paired of NSCLC tissues and matched normal tissues, was detected using quantitative Real-time polymerase chain reaction (qRT-PCR). Linc00261 expression in NSCLC cells was also measured. NSCLC cells were transfected with pcDNA3.1 or siRNA linc00261 to upregulate or downregulate linc00261 expression, respectively. MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide) assay and colony formation assay were utilized for examining the proliferative ability of NSCLC cells. Wound-healing and transwell assays were performed for detecting the metastatic ability of NSCLC cells. Protein levels of epithelial-mesenchymal transition markers were detected by Western blot. Furthermore, in vivo function of linc00261 was evaluated using the nude mice. RESULTS Linc00261 expressed significantly lower in NSCLC tissues and cell lines than that in the adjacent normal tissues or control cell line. Over-expression of linc00261 significantly inhibited proliferation, invasion and migration of NSCLC cells. On the contrast, knockdown of linc00261 promoted cell growth and metastasis of NSCLC cells. Furthermore, linc00261 inhibited the epithelial-mesenchymal transition of NSCLC via downregulating Snail. Linc00261 could slow down the growth of xenograft of NSCLC in vivo. CONCLUSIONS We demonstrated that linc00261 was lowly expressed in NSCLC tissues and cells. It inhibited cell proliferation and metastasis by downregulating Snail expression via EMT. This might provide a novel sight for the biological treatment for NSCLC.
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Affiliation(s)
- J Liao
- Department of Thoracic Surgery, Yantaishan Hospital, Yantai, China.
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Abstract
1. Muchuan black-bone chicken is well known in China for its meat quality and medicinal properties; however, its egg-laying performance is not ideal. To better understand the molecular mechanisms of black-boned chicken egg-laying, high-throughput RNA sequencing was performed to compare differences in the pituitary transcriptome between three high-rate (group H) and three low-rate (group L) egg production chickens. 2. In total, 171 differentially expressed genes (DEGs) were identified between the two groups, of which 113 were upregulated and 58 were downregulated in group L. Some of these genes are known to be related to hormone secretion or the regulation of reproductive processes; these include prolactin-releasing hormone (PRLH), distal-less homeobox 6 (DLX6), interferon regulatory factor 4 (IRF4), and cilia and flagella associated protein 69 (CFAP69). Notably, expression pattern analysis indicated that both PRLH and DLX6 may influence egg-laying performance. 3. The dataset provided a foundation for discovering important genes and pathways involved in the chicken egg-laying process, and may help to improve understanding of the molecular mechanisms of chicken reproduction.
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Affiliation(s)
- S Yu
- Engineering Research Center of Sichuan Province Higher School of Local Chicken Breeds Industrialization in Southern Sichuan, College of Life Science, Leshan Normal University , Leshan, China
| | - G Wang
- Engineering Research Center of Sichuan Province Higher School of Local Chicken Breeds Industrialization in Southern Sichuan, College of Life Science, Leshan Normal University , Leshan, China
| | - J Liao
- Engineering Research Center of Sichuan Province Higher School of Local Chicken Breeds Industrialization in Southern Sichuan, College of Life Science, Leshan Normal University , Leshan, China
| | - M Tang
- Engineering Research Center of Sichuan Province Higher School of Local Chicken Breeds Industrialization in Southern Sichuan, College of Life Science, Leshan Normal University , Leshan, China
| | - J Chen
- Engineering Research Center of Sichuan Province Higher School of Local Chicken Breeds Industrialization in Southern Sichuan, College of Life Science, Leshan Normal University , Leshan, China
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Liao J, Wang R, Mishra A, Emanuel E, Zhu J, Cousins D, Navathe A. Spillover Effects of the Comprehensive Care for Joint Replacement Program Among Non‐Medicare Patients. Health Serv Res 2020. [DOI: 10.1111/1475-6773.13506] [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: 11/26/2022] Open
Affiliation(s)
- J. Liao
- Department of Medicine University of Washington Seattle WA United States
- Leonard Davis Institute of Health Economics University of Pennsylvania Philadelphia PA United States
| | - R. Wang
- University of Pennsylvania Philadelphia PA United States
| | - A. Mishra
- Department of Medical Ethics and Health Policy University of Pennsylvania Philadelphia PA United States
| | - E. Emanuel
- Department of Medical Ethics and Health Policy University of Pennsylvania Philadelphia PA United States
| | - J. Zhu
- University of Pennsylvania Philadelphia PA United States
| | - D. Cousins
- Department of Medical Ethics and Health Policy University of Pennsylvania Philadelphia PA United States
| | - A. Navathe
- Leonard Davis Institute of Health Economics University of Pennsylvania Philadelphia PA United States
- University of Pennsylvania Philadelphia PA United States
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Yu S, Wang G, Liao J, Tang M, Chen J. Identification of key microRNAs affecting melanogenesis of breast muscle in Muchuan black-boned chickens by RNA sequencing. Br Poult Sci 2020; 61:225-231. [PMID: 31918572 DOI: 10.1080/00071668.2019.1709619] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
1. Melanin content is considered an important indicator of meat quality in black-boned chickens, which have a high market value. To understand the complex physiological processes underlying muscle melanogenesis in this chicken, differentially expressed miRNAs (DEMs) were detected between black muscle (BM) and white muscle (WM) of chickens using high-throughput sequencing technology. Six small RNA libraries were constructed, and more than 16.75 million clean reads were obtained for each library. 2. A total of 582 known miRNAs and 65 novel miRNAs were identified from the six chicken sequence libraries. A total of 19 DEMs were identified between the two groups, of which nine were upregulated and 10 were downregulated. Furthermore, the DEMs were predicted to target 572 genes. 3. Certain DEMs (such as miR-204, miR-133b, and miR-12 229-3p) and their target genes may play an important role in muscle melanogenesis of chickens. These findings provide a foundation for clarifying the miRNA regulatory mechanisms involved in muscle pigmentation in avian species.
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Affiliation(s)
- S Yu
- Engineering Research Center of Sichuan Province Higher School of Local Chicken Breeds Industrialization in Southern Sichuan, College of Life Science, Leshan Normal University , Leshan, China
| | - G Wang
- Engineering Research Center of Sichuan Province Higher School of Local Chicken Breeds Industrialization in Southern Sichuan, College of Life Science, Leshan Normal University , Leshan, China
| | - J Liao
- Engineering Research Center of Sichuan Province Higher School of Local Chicken Breeds Industrialization in Southern Sichuan, College of Life Science, Leshan Normal University , Leshan, China
| | - M Tang
- Engineering Research Center of Sichuan Province Higher School of Local Chicken Breeds Industrialization in Southern Sichuan, College of Life Science, Leshan Normal University , Leshan, China
| | - J Chen
- Engineering Research Center of Sichuan Province Higher School of Local Chicken Breeds Industrialization in Southern Sichuan, College of Life Science, Leshan Normal University , Leshan, China
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Liao J, Xie N. Long noncoding RNA DSCAM-AS1 functions as an oncogene in non-small cell lung cancer by targeting BCL11A. Eur Rev Med Pharmacol Sci 2020; 23:1087-1092. [PMID: 30779076 DOI: 10.26355/eurrev_201902_16998] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Long noncoding RNAs (lncRNAs) have attracted more attention for their role in tumor progression recently. The aim of this study was to investigate the role of DSCAM-AS1 in the progression of non-small cell lung cancer (NSCLC), and to elucidate its possible underlying mechanism. PATIENTS AND METHODS DSCAM-AS1 expression in both NSCLC cells and tissue samples was detected by Real Time quantitative-Polymerase Chain Reaction (RT-qPCR). Moreover, the association between the DSCAM-AS1 expression level and patients' overall survival rate was explored. Furthermore, wound healing assay and transwell assay were conducted. In addition, RT-qPCR and Western blot assay were used to elucidate the underlying mechanism. RESULTS DSCAM-AS1 expression level in NSCLC samples was significantly higher than that of the corresponding normal tissues. The expression level of DSCAM-AS1 was associated with an overall survival time of NSCLC patients. Besides, the migration and invasion abilities of NSCLC cells were remarkably promoted after DSCAM-AS1 overexpression in vitro. Moreover, the mRNA and protein expression of BCL11A was significantly upregulated after the overexpression of DSCAM-AS1. Furthermore, the expression of BCL11A was positively correlated with DSCAM-AS1 expression in NSCLC tissues. CONCLUSIONS We observed that DSCAM-AS1 could enhance NSCLC cell migration and invasion via upregulating BCL11A. Furthermore, DSCAM-AS1 might be a potential therapeutic target for NSCLC.
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Affiliation(s)
- J Liao
- Department of Thoracic Surgery, Yantaishan Hospital, Yantai, China.
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Cheuk W, Liao J, Chan JKC. "Baby Spleen Sleeping in a Cradle": An Intrapancreatic Accessory Spleen. Int J Surg Pathol 2020; 29:516-517. [PMID: 32552218 DOI: 10.1177/1066896920935586] [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: 11/16/2022]
Affiliation(s)
- W Cheuk
- Queen Elizabeth Hospital, Hong Kong, SAR China
| | - J Liao
- Queen Elizabeth Hospital, Hong Kong, SAR China
| | - J K C Chan
- Queen Elizabeth Hospital, Hong Kong, SAR China
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Norsworthy KJ, Avagyan A, Bird ST, Li Y, Akhtar S, Liao J, Wernecke M, Deisseroth AB, Chuk M, MaCurdy TE, Swain R, Kelman JA, Farrell AT, de Claro RA, Pazdur R, Blumenthal G, Graham DJ. Second cancers in adults with acute promyelocytic leukemia treated with or without arsenic trioxide: a SEER-medicare analysis. Leukemia 2020; 34:3082-3084. [DOI: 10.1038/s41375-020-0905-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Revised: 05/22/2020] [Accepted: 06/01/2020] [Indexed: 12/11/2022]
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Fernandez-Mendoza J, Puzino K, Calhoun SL, Qureshi M, He F, Liao J, Vgontzas AN, Liao D, Bixler EO. 0936 Cardiometabolic Disorders are Independently Associated with Excessive Daytime Sleepiness in Young Adults. Sleep 2020. [DOI: 10.1093/sleep/zsaa056.932] [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: 11/14/2022] Open
Abstract
Abstract
Introduction
Cardiometabolic risk factors (CMR), including obesity, hypertension, diabetes and hypercholesterolemia, have been associated with sleep apnea and insufficient sleep, both of which can lead to excessive daytime sleepiness (EDS). We hypothesized that CMR are associated with EDS in young adults independent of sleep apnea, sleep duration and mental health disorders (MHD).
Methods
The Penn State Child Cohort is a population-based longitudinal sample of 700 children (8.7±1.7y), of whom 421 were followed-up 8.3 years later during adolescence (17.0±2.3y) and 425 another 7.0 years later during young adulthood (24.4±2.6y). Subjects underwent a 9-h in-lab polysomnography in childhood and adolescence and parent- or self-reported standardized surveys at all time points. Self-reports in young adulthood and in-lab measurements in childhood were used to ascertain CMR and sleep apnea. Parent-reports in childhood and self-reports in young adulthood were used to ascertain the presence of MHD and EDS. Logistic regression models adjusted for age, race, sex, snoring/observed apneas, insomnia symptoms, and sleep duration in young adulthood as well as mean arterial blood pressure, body mass index percentile and apnea/hypopnea index in childhood.
Results
CMR (OR=2.71, 95%CI=1.69-4.36) and MHD (OR=4.61, 95%CI=2.79-7.62) were associated with EDS in univariate models. After adjusting for covariates in childhood and young adulthood, CMR and MHD remained independently associated with EDS (OR=2.32, 95%CI=1.29-4.16 and OR=2.78, 95%CI=1.59-4.87, respectively).
Conclusion
EDS in young adults with CMR or MHD does not solely arise from sleep apnea, insufficient sleep or other sleep disturbances. EDS may be the result of central pathophysiologic mechanisms or the functional impairment associated with cardiovascular, metabolic and mental health disorders. These data further support that youth with these disorders should be screened for EDS and appropriately managed.
Support
National Institutes of Health (R01HL136587, R01HL97165, R01HL63772, UL1TR000127)
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Affiliation(s)
| | - K Puzino
- Penn State College of Medicine, Hershey, PA
| | | | - M Qureshi
- Penn State College of Medicine, Hershey, PA
| | - F He
- Penn State College of Medicine, Hershey, PA
| | - J Liao
- Penn State College of Medicine, Hershey, PA
| | | | - D Liao
- Penn State College of Medicine, Hershey, PA
| | - E O Bixler
- Penn State College of Medicine, Hershey, PA
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Fernandez-Mendoza J, Gao Z, Brandt K, Houser L, Calhoun SL, He F, Liao J, Vgontzas AN, Liao D, Bixler EO. 0890 Sleep Disordered Breathing is Associated With Endothelial Dysfunction and Atherosclerosis in Young Adults: Preliminary Longitudinal Findings in the Penn State Child Cohort. Sleep 2020. [DOI: 10.1093/sleep/zsaa056.886] [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: 11/13/2022] Open
Abstract
Abstract
Introduction
Sleep disordered breathing (SDB) in middle-age is an established risk factor for cardiovascular disease. However, population-based studies supporting its cardiovascular contribution at earlier stages of development are lacking, particularly with long-term follow-ups.
Methods
The Penn State Child Cohort is a population-based longitudinal sample of 700 children (8.7±1.7y), of whom 421 were followed-up 8.3 years later during adolescence (17.0±2.3y) with in-lab polysomnography (PSG). To date, 425 have been followed-up another 7.4 years later during young adulthood (24.4±2.6y) via a standardized survey and 136 of them (55.1% female, 21.3% racial/ethnic minority) have undergone a repeat of their PSG to ascertain apnea/hypopnea index. Subjects (n=121) also underwent Doppler ultrasounds to assess flow-mediated dilation (FMD) and carotid intima-media thickness (CIMT). Linear regression models stratified by body mass index in young adulthood.
Results
SDB was cross-sectionally associated with lower FMD (β=-0.239, p=0.008) and greater CIMT (β=0.330, p<0.001) in young adulthood. Longitudinally, childhood (n=121) and adolescence (n=90) SDB were significantly associated with CIMT (β=0.327, p<0.001 and β=0.286, p=0.006, respectively), but not with FMD (β=-0.158, p=0.08 and β=-0.101, p=0.35, respectively). These associations, particularly longitudinal ones between childhood and adolescence SDB with CIMT in young adulthood, were stronger in overweight than normal weight subjects (e.g., β=0.310, p=0.030 and β =0.089, p=0.582, respectively).
Conclusion
SDB and obesity appear to be synergistically associated with endothelial dysfunction and atherosclerosis in young adults from the general population. These data suggest that a childhood exposure to chronic SDB is associated with long-term atherosclerosis, while endothelial dysfunction may be a short-term outcome. This ongoing 16-year longitudinal study will test whether the natural history of SDB from childhood through adolescence into young adulthood shows differential trajectories for cardiovascular morbidity.
Support
National Institutes of Health (R01HL136587, R01HL97165, R01HL63772, UL1TR000127)
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Affiliation(s)
| | - Z Gao
- Penn State College of Medicine, Hershey, PA
| | - K Brandt
- Penn State College of Medicine, Hershey, PA
| | - L Houser
- Penn State College of Medicine, Hershey, PA
| | | | - F He
- Penn State College of Medicine, Hershey, PA
| | - J Liao
- Penn State College of Medicine, Hershey, PA
| | | | - D Liao
- Penn State College of Medicine, Hershey, PA
| | - E O Bixler
- Penn State College of Medicine, Hershey, PA
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Izem R, Liao J, Hu M, Wei Y, Akhtar S, Wernecke M, MaCurdy TE, Kelman J, Graham DJ. Comparison of propensity score methods for pre-specified subgroup analysis with survival data. J Biopharm Stat 2020; 30:734-751. [DOI: 10.1080/10543406.2020.1730868] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Affiliation(s)
- Rima Izem
- Division of Biostatistics and Epidemiology, Children’s National Research Institute, and Department of Pediatrics, George Washington University, Washington, USA
| | | | - Mao Hu
- Acumen LLC, Burlingame, CA, USA
| | | | | | | | - Thomas E. MaCurdy
- Acumen LLC, Burlingame, CA, USA
- Department of Economics, Stanford University
| | - Jeffrey Kelman
- The Center for Medicaid at the Centers for Medicare and Medicaid Services, Baltimore, MD, USA
| | - David J Graham
- Food and Drug Administration, Center for Drug Evaluations and Research, Silver Spring, MD, USA
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Hua TQ, Lee SJ, Liao J, Moisseytsev A, Ferroni P, Karahan A, Paik CY, Tentner AM, Sofu T. Development of Mechanistic Source Term Analysis Tool SAS4A-FATE for Lead- and Sodium-Cooled Fast Reactors. NUCL TECHNOL 2020. [DOI: 10.1080/00295450.2019.1598715] [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: 10/26/2022]
Affiliation(s)
- T. Q. Hua
- Argonne National Laboratory, 9700 South Cass Avenue, Lemont, Illinois 60439
| | - S. J. Lee
- Fauske & Associates, LLC, 16W070 83rd Street, Burr Ridge, Illinois 60527
| | - J. Liao
- Westinghouse Electric Company, 1000 Westinghouse Drive, Cranberry Township, Pennsylvania 16066
| | - A. Moisseytsev
- Argonne National Laboratory, 9700 South Cass Avenue, Lemont, Illinois 60439
| | - P. Ferroni
- Westinghouse Electric Company, 1000 Westinghouse Drive, Cranberry Township, Pennsylvania 16066
| | - A. Karahan
- Argonne National Laboratory, 9700 South Cass Avenue, Lemont, Illinois 60439
| | - C. Y. Paik
- Fauske & Associates, LLC, 16W070 83rd Street, Burr Ridge, Illinois 60527
| | - A. M. Tentner
- Argonne National Laboratory, 9700 South Cass Avenue, Lemont, Illinois 60439
| | - T. Sofu
- Argonne National Laboratory, 9700 South Cass Avenue, Lemont, Illinois 60439
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Jiang JH, Lv QY, Yi YX, Liao J, Wang XW, Zhang W. MicroRNA-200a promotes proliferation and invasion of ovarian cancer cells by targeting PTEN. Eur Rev Med Pharmacol Sci 2019; 22:6260-6267. [PMID: 30338796 DOI: 10.26355/eurrev_201810_16033] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE We investigate whether microRNA-200a could regulate proliferation and invasion of ovarian cancer cells, thereby participating in the occurrence and development of ovarian cancer. We also explore the specific mechanism of microRNA-200a in regulating ovarian cancer. PATIENTS AND METHODS Expression level of microRNA-200a in ovarian cancer tissues and paracancerous tissues were detected by quantitative Real-time polymerase chain reaction (qRT-PCR). The regulatory effects of microRNA-200a on proliferation and invasion of ovarian cancer cells were examined by Cell counting kit-8 (CCK-8) and cell invasion assay, respectively. Dual-luciferase reporter gene assay was performed to confirm the binding relationship between microRNA-200a and PTEN (phosphatase and tensin homolog deleted on chromosome ten). The regulatory role of microRNA-200a in PTEN expression was accessed by Western blot. Rescue experiments were conducted to assess whether microRNA-200a regulated proliferation and invasion of ovarian cancer cells by inhibiting PTEN expression. RESULTS MicroRNA-200a expression in ovarian cancer tissues was significantly higher than that of paracancerous tissues. Besides, microRNA-200a was also overexpressed in ovarian cancer cell lines than that of normal ovarian cells. Overexpression of microRNA-200a promoted the proliferative and invasive abilities of SKOV3 and OVCAR3 cells. Dual-luciferase reporter gene assay showed that microRNA-200a could directly degrade PTEN. Overexpression of PTEN in SKOV3 and OVCAR3 cells partially reversed the increased cell proliferation and invasion induced by overexpressed microRNA-200a. CONCLUSIONS Overexpressed microRNA-200a promoted the proliferative and invasive abilities of ovarian cancer cells, which might be related to the targeted regulation of PTEN expression.
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Affiliation(s)
- J-H Jiang
- Department of Gynecology, Zhongnan Hospital of Wuhan University, Wuhan, China.
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Mysona DP, Tran LKH, Tran PMH, Gehrig PA, Van Le L, Ghamande S, Rungruang BJ, Java J, Mann AK, Liao J, Kapp DS, Santos BD, She JX, Chan JK. Clinical calculator predictive of chemotherapy benefit in stage 1A uterine papillary serous cancers. Gynecol Oncol 2019; 156:77-84. [PMID: 31796203 DOI: 10.1016/j.ygyno.2019.10.017] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Revised: 10/14/2019] [Accepted: 10/15/2019] [Indexed: 02/07/2023]
Abstract
OBJECTIVE Determine the utility of a clinical calculator to predict the benefit of chemotherapy in stage IA uterine papillary serous cancer (UPSC). PATIENTS AND METHODS Data were collected from NCDB from years 2010-2014. Based on demographic and surgical characteristics, a clinical score was developed using the random survival forest machine learning algorithm. RESULTS Of 1,751 patients with stage IA UPSC, 1,012 (58%) received chemotherapy and 739 (42%) did not. Older age (HR 1.06), comorbidities (HR 1.31), larger tumor size (HR 1.27), lymphovascular invasion (HR 1.86), positive peritoneal cytology (HR 2.62), no pelvic lymph node dissection (HR 1.51), and no chemotherapy (HR 2.16) were associated with poorer prognosis. Compared to no chemotherapy, patients who underwent chemotherapy had a 5-year overall survival of 80% vs. 67%. To better delineate those who may derive more benefit from chemotherapy, we designed a clinical calculator capable of dividing patients into low, moderate, and high-risk groups with associated 5-year OS of 86%, 73%, and 53%, respectively. Using the calculator to assess the relative benefit of chemotherapy in each risk group, chemotherapy improved the 5-year OS in the high (42% to 64%; p < 0.001) and moderate risk group (66% to 79%; p < 0.001) but did not benefit the low risk group (84% to 87%; p = 0.29). CONCLUSION Our results suggest a clinical calculator is useful for counseling and personalizing chemotherapy for stage IA UPSC.
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Affiliation(s)
- D P Mysona
- The University of North Carolina, Chapel Hill, NC, USA; The Medical College of Georgia at Augusta University, Augusta, GA, USA
| | - L K H Tran
- The Medical College of Georgia at Augusta University, Augusta, GA, USA
| | - P M H Tran
- The Medical College of Georgia at Augusta University, Augusta, GA, USA
| | - P A Gehrig
- University of North Carolina Lineberger Comprehensive Cancer Center, Chapel Hill, NC, USA
| | - L Van Le
- University of North Carolina Lineberger Comprehensive Cancer Center, Chapel Hill, NC, USA
| | - S Ghamande
- The Medical College of Georgia at Augusta University, Augusta, GA, USA
| | - B J Rungruang
- The Medical College of Georgia at Augusta University, Augusta, GA, USA
| | - J Java
- Genomics Research Center, University of Rochester Medical Center, Rochester, NY, USA
| | - A K Mann
- Palo Alto Medical Foundation Research Institute, Palo Alto, CA, USA
| | - J Liao
- Palo Alto Medical Foundation Research Institute, Palo Alto, CA, USA
| | - D S Kapp
- Stanford University School of Medicine, Stanford, CA, USA
| | | | - J X She
- The Medical College of Georgia at Augusta University, Augusta, GA, USA; Jinfinti Precision Medicine, Inc, Augusta, GA, USA.
| | - J K Chan
- Palo Alto Medical Foundation Research Institute, Palo Alto, CA, USA; California Pacific & Palo Alto Medical Foundation/Sutter Health Research Institute, San Francisco, CA, USA.
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