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Yin C, Larson M, Lahr N, Paulitz T. Wheat rhizosphere-derived bacteria protect soybean from soilborne diseases. Plant Dis 2023. [PMID: 38105448 DOI: 10.1094/pdis-08-23-1713-re] [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] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Soybean [Glycine max (L.) Merr.] is an important oilseed crop with a high economic value. However, three damaging soybean diseases, soybean cyst nematode (SCN; Heterodera glycines Ichinohe), Sclerotinia stem rot caused by the fungus Sclerotinia sclerotiorum (Lid.) de Bary, and soybean root rot caused by Fusarium spp., are major constraints to soybean production in the Great Plains. Current disease management options, including resistant or tolerant varieties, fungicides, nematicides, and agricultural practices (crop rotation and tillage), have limited efficacy for these pathogens or have adverse effects on the ecosystem. Microbes with antagonistic activity are a promising option to control soybean diseases with the advantage of being environmentally friendly and sustainable. In this study, 61 bacterial strains isolated from wheat rhizospheres were used to examine their antagonistic abilities against three soybean pathogens. Six bacterial strains significantly inhibited the growth of Fusarium graminearum in the dual-culture assay. These bacterial strains were identified as Chryseobacterium ginsengisoli, C. indologenes, Pseudomonas poae, two Pseudomonas spp., and Delftia acidovorans by 16S rRNA gene sequencing. Moreover, C. ginsengisoli, C. indologenes, and P. poae significantly increased the mortality of SCN second-stage juveniles (J2) and two Pseudomonas spp. inhibited the growth of S. sclerotiorum in vitro. Further growth chamber tests found that C. ginsengisoli and C. indologenes reduced soybean Fusarium root rot disease. C. ginsengisoli and P. poae dramatically decreased SCN egg number on SCN susceptible soybean "Williams 82". Two Pseudomonas spp. protected soybean plants from leaf damage and collapse after being infected by S. sclerotiorum. These bacteria exhibit versatile antagonistic potential. This work lays the foundation for further research on the field control of soybean pathogens.
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Affiliation(s)
- Chuntao Yin
- USDA-ARS Plains Area, 57644, USDA-ARS-PA North Central Agricultural Res. Lab, 2923 MEDARY AVENUE, Brookings, South Dakota, United States, 57006;
| | - Matthew Larson
- South Dakota State University, 2019, Brookings, South Dakota, United States;
| | - Nathan Lahr
- USDA-ARS Plains Area, 57644, USDA-ARS-PA North Central Agricultural Res. Lab, Brookings, South Dakota, United States;
| | - Tim Paulitz
- USDA-ARS, Root Disease and Biological Control Unit, Rm. 363 Johnson Hall, Washington State University, Pullman, Washington, United States, 99164-6430;
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2
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Lilieholm T, McMillan A, Ahmed A, Henningsen M, Larson M, Block WF. Neural network for autonomous segmentation and volumetric assessment of clot and edema in acute and subacute intracerebral hemorrhages. Magn Reson Imaging 2023; 103:162-168. [PMID: 37541456 PMCID: PMC10528387 DOI: 10.1016/j.mri.2023.07.015] [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: 10/05/2022] [Revised: 07/28/2023] [Accepted: 07/31/2023] [Indexed: 08/06/2023]
Abstract
INTRODUCTION Minimally-invasive surgical techniques for intracerebral hemorrhage (ICH) evacuation use imaging to guide the suction, lysing and/or drainage from the hemorrhage site via various designs. A previous international surgical study has shown that reduction of hematoma volume below 15 ml is indicative of improved long term patient outcomes. The study noted a need for tools to periodically visualize remaining clot during intervention to increase the likelihood of evacuating sufficient clot volumes without endangering rebleeds. Robust segmentation of MRI could guide surgeons and radiologists regarding remaining regions and approaches for prudent evacuation. We thus propose a Convolutional Neural Network (CNN) to identify and autonomously segment clot and peripheral edema in MR images of the brain and generate an estimate of the remaining clot volume. MATERIALS AND METHODS We used a retrospective, locally-acquired dataset of ICH patient scans taken on 3 T MRI scanners. Three sets of ground truth manual segmentations were independently generated by two imaging scientists and one radiology fellow. Evaluation of clot age was determined based on relative contrast of hemorrhage components and reviewed by a neurosurgeon. Model accuracy was determined by pixel-wise Dice coefficient (DC) calculations between each ground truth manual segmentation and the machine-derived autonomous segmentations. RESULTS The model produced autonomous segmentations of clot core with an average DC of 0.75 ± 0.21 relative to manual segmentations of the same scans. For edema, it produced segmentations with an average DC of 0.68 ± 0.16 relative to manual. From these pixel-wise segmentations, clot volume can be calculated. Model-produced segmentations underestimated clot volumes by an average of 17% relative to ground-truth. CONCLUSION The machine learning models were able to identify and segment volumes of ICH components swiftly and accurately.
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Affiliation(s)
- Thomas Lilieholm
- Department of Medical Physics, University of Wisconsin at Madison, Madison, WI, USA.
| | - Alan McMillan
- Department of Medical Physics, University of Wisconsin at Madison, Madison, WI, USA; Department of Radiology, University of Wisconsin at Madison, Madison, WI, USA; Deparment of Biomedical Engineering, University of Wisconsin at Madison, Madison, WI, USA
| | - Azam Ahmed
- Department of Neurosurgery, University of Wisconsin at Madison, Madison, WI, USA
| | - Matthew Henningsen
- Department of Electrical Engineering, University of Wisconsin at Madison, Madison, WI, USA
| | - Matthew Larson
- Department of Radiology, University of Wisconsin at Madison, Madison, WI, USA
| | - Walter F Block
- Department of Medical Physics, University of Wisconsin at Madison, Madison, WI, USA; Department of Radiology, University of Wisconsin at Madison, Madison, WI, USA; Deparment of Biomedical Engineering, University of Wisconsin at Madison, Madison, WI, USA
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Alam SM, Larson M, Srinivasan P, Genz N, Fleer R, Sardiu M, Thompson J, Lee E, Hamilton-Reeves J, Wulff-Burchfield E. Evaluation of sarcopenia in patients receiving intravesical Bacillus Calmette-Guérin for non-muscle invasive bladder cancer. Urol Oncol 2023; 41:431.e15-431.e20. [PMID: 37487846 DOI: 10.1016/j.urolonc.2023.05.021] [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: 02/11/2023] [Revised: 05/17/2023] [Accepted: 05/30/2023] [Indexed: 07/26/2023]
Abstract
BACKGROUND Sarcopenia is associated with adverse outcomes for patients with muscle invasive bladder cancer (MIBC), but less is known about its impact in the setting of non-muscle invasive bladder cancer (NMIBC). Sarcopenia, skeletal muscle density, and adipose tissue area have been studied as markers of malnutrition and can be determined radiographically. The purpose of this study is to characterize the prevalence of sarcopenia in patients with NMIBC receiving intravesical Bacillus Calmette-Guérin (BCG). METHODS Following institutional review board approval, patients with NMIBC having received intravesical BCG were identified using institutional pharmacy records. Patients having undergone computed tomography (CT) of the abdomen and pelvis within 90 days of treatment were included in the analysis. Using sliceOmatic 5.0 software, skeletal muscle area (cm2) was measured at the L3 level to calculate skeletal muscle index (SMI), a marker of sarcopenia. Subcutaneous, visceral, and intramuscular adipose tissue areas in addition to skeletal muscle density were also measured. Frailty was evaluated as a secondary aim using the 5-Item Modified Frailty Index (mFI-5). Using predefined cutoffs, the prevalence of sarcopenia was determined. Descriptive statistics were used to characterize frailty and secondary body composition characteristics. Statistical analysis was performed to evaluate the impact of sarcopenia on recurrence rate and progression. RESULTS A total of 308 patients having received BCG between 2015 and 2020 were identified, of which 90 met criteria for analysis. Nearly all (94%) patients completed at least 5 out of 6 BCG induction instillations. Median body mass index (kg/m2) was 27.64 (IQR 24.9, 30.5) for females and 27.7 (IQR 24.9, 30.66) for males. Median SMI (cm2/m2) was 49.44 (IQR 39.39, 55.17) for females and 49.58 (IQR 40.25, 55.58) for males. A majority (61%) of patients were found to be sarcopenic. High-risk frailty was identified 36% of patients. There was no association between sarcopenia and recurrence rate or progression. CONCLUSIONS Sarcopenia and frailty are highly prevalent amongst patients with NMIBC. A diagnosis of NMIBC represents a window of opportunity to identify and intervene on modifiable risk factors such as sarcopenia and frailty, which are associated with adverse outcomes in more advanced disease states.
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Affiliation(s)
- Syed M Alam
- Department of Urology, University of Kansas Health System, Kansas City, KS
| | - Matthew Larson
- Department of Urology, University of Kansas Health System, Kansas City, KS
| | | | - Nick Genz
- Department of Urology, University of Kansas Health System, Kansas City, KS
| | - Ryan Fleer
- Department of Pharmacy Practice, University of Kansas Health System, Kansas City, KS
| | - Mihaela Sardiu
- Department of Biostatistics, University of Kansas, Kansas City, KS
| | - Jeffrey Thompson
- Department of Biostatistics, University of Kansas, Kansas City, KS
| | - Eugene Lee
- Department of Urology, University of Kansas Health System, Kansas City, KS
| | - Jill Hamilton-Reeves
- Department of Urology, University of Kansas Health System, Kansas City, KS; Department of Dietetics and Nutrition, University of Kansas, Kansas City, KS; Department of Medicine, Division of Medical Oncology, University of Kansas, Kansas City, KS
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Wright ER, Yang J, Sibert B, Larson M, Kim JY, Parrell D, Sanchez JC, Kumar A, Cai K. Developing Technologies for Correlative Cryo-Imaging Pipelines. Microsc Microanal 2023; 29:1025. [PMID: 37613235 DOI: 10.1093/micmic/ozad067.519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/25/2023]
Affiliation(s)
- Elizabeth R Wright
- Department of Biochemistry, UW-Madison, Madison, WI, United States
- Midwest Center for Cryo-Electron Tomography, UW-Madison, Madison, WI, United States
- Cryo-Electron Microscopy Research Center, UW-Madison, Madison, WI, United States
- Morgridge Institute for Research, UW-Madison, Madison, WI, United States
| | - Jae Yang
- Department of Biochemistry, UW-Madison, Madison, WI, United States
- Midwest Center for Cryo-Electron Tomography, UW-Madison, Madison, WI, United States
- Cryo-Electron Microscopy Research Center, UW-Madison, Madison, WI, United States
| | - Bryan Sibert
- Department of Biochemistry, UW-Madison, Madison, WI, United States
- Midwest Center for Cryo-Electron Tomography, UW-Madison, Madison, WI, United States
- Cryo-Electron Microscopy Research Center, UW-Madison, Madison, WI, United States
| | - Matthew Larson
- Department of Biochemistry, UW-Madison, Madison, WI, United States
- Midwest Center for Cryo-Electron Tomography, UW-Madison, Madison, WI, United States
- Cryo-Electron Microscopy Research Center, UW-Madison, Madison, WI, United States
| | - Joseph Y Kim
- Department of Biochemistry, UW-Madison, Madison, WI, United States
- Department of Chemistry, UW-Madison, Madison, WI, United States
| | - Daniel Parrell
- Department of Biochemistry, UW-Madison, Madison, WI, United States
| | - Juan C Sanchez
- Department of Biochemistry, UW-Madison, Madison, WI, United States
| | - Anil Kumar
- Department of Biochemistry, UW-Madison, Madison, WI, United States
- Midwest Center for Cryo-Electron Tomography, UW-Madison, Madison, WI, United States
- Cryo-Electron Microscopy Research Center, UW-Madison, Madison, WI, United States
| | - Kai Cai
- Department of Biochemistry, UW-Madison, Madison, WI, United States
- Midwest Center for Cryo-Electron Tomography, UW-Madison, Madison, WI, United States
- Cryo-Electron Microscopy Research Center, UW-Madison, Madison, WI, United States
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Yang J, Vrbovská V, Franke T, Sibert B, Larson M, Hall A, Rigort A, Mitchels J, Wright ER. Integrated Fluorescence Microscopy (iFLM) for Cryo-FIB-milling and In-situ Cryo-ET. bioRxiv 2023:2023.07.11.548578. [PMID: 37502891 PMCID: PMC10369943 DOI: 10.1101/2023.07.11.548578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Correlative cryo-FLM-FIB milling is a powerful sample preparation technique for in situ cryo-ET. However, correlative workflows that incorporate precise targeting remain challenging. Here, we demonstrate the development and use of an integrated Fluorescence Light Microscope (iFLM) module within a cryo-FIB-SEM to enable a coordinate-based two-point 3D correlative workflow. The iFLM guided targeting of regions of interest coupled with an automated milling process of the cryo-FIB-SEM instrument allows for the efficient preparation of 9-12 ∼200 nm thick lamellae within 24 hours. Using regular and montage-cryo-ET data collection schemes, we acquired data from FIB-milled lamellae of HeLa cells to examine cellular ultrastructure. Overall, this workflow facilitates on-the-fly targeting and automated FIB-milling of cryo-preserved cells, bacteria, and possibly high pressure frozen tissue, to produce lamellae for downstream cryo-ET data collection.
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Affiliation(s)
- Jae Yang
- Department of Biochemistry, University of Wisconsin, Madison, WI USA
- Midwest Center for Cryo-Electron Tomography, Department of Biochemistry, University of Wisconsin, Madison, WI USA
| | | | | | - Bryan Sibert
- Department of Biochemistry, University of Wisconsin, Madison, WI USA
- Cryo-Electron Microscopy Research Center, Department of Biochemistry, University of Wisconsin, Madison, WI USA
- Midwest Center for Cryo-Electron Tomography, Department of Biochemistry, University of Wisconsin, Madison, WI USA
| | - Matthew Larson
- Department of Biochemistry, University of Wisconsin, Madison, WI USA
- Cryo-Electron Microscopy Research Center, Department of Biochemistry, University of Wisconsin, Madison, WI USA
- Midwest Center for Cryo-Electron Tomography, Department of Biochemistry, University of Wisconsin, Madison, WI USA
| | - Alex Hall
- Thermo Fisher Scientific Brno, Brno, Czech Republic
| | - Alex Rigort
- Thermo Fisher Scientific Brno, Brno, Czech Republic
| | | | - Elizabeth R. Wright
- Department of Biochemistry, University of Wisconsin, Madison, WI USA
- Cryo-Electron Microscopy Research Center, Department of Biochemistry, University of Wisconsin, Madison, WI USA
- Midwest Center for Cryo-Electron Tomography, Department of Biochemistry, University of Wisconsin, Madison, WI USA
- DOE Great Lakes Bioenergy Research Center, University of Wisconsin, Madison, WI USA
- Morgridge Institute for Research, Madison, WI, USA
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Abstract
Patients with gynecologic malignancies often require a multimodality imaging approach for initial staging, treatment response assessment, and surveillance. MRI imaging and PET are two well-established and widely accepted modalities in this setting. Although PET and MRI imaging are often acquired separately on two platforms (a PET/computed tomography [CT] and an MRI imaging scanner), hybrid PET/MRI scanners offer the potential for comprehensive disease assessment in one visit. Gynecologic malignancies have been one of the most successful areas for implementation of PET/MRI. This article provides an overview of the role of this platform in the care of patients with gynecologic malignancies.
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Affiliation(s)
- Matthew Larson
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, 600 Highland Avenue, E3/352, Madison, WI 53792, USA
| | - Petra Lovrec
- Department of Radiology, Loyola University Medical Center, 2160 First Avenue, Maywood, IL 60153, USA
| | - Elizabeth A Sadowski
- Departments of Radiology, Obstetrics and Gynecology, University of Wisconsin-Madison School of Medicine and Public Health, 600 Highland Avenue, E3/372, Madison, WI 53792-3252, USA
| | - Ali Pirasteh
- Departments of Radiology and Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, 1111 Highland Avenue, WIMR II 2423, Madison, WI 53705, USA.
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7
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Pati S, Baid U, Edwards B, Sheller M, Wang SH, Reina GA, Foley P, Gruzdev A, Karkada D, Davatzikos C, Sako C, Ghodasara S, Bilello M, Mohan S, Vollmuth P, Brugnara G, Preetha CJ, Sahm F, Maier-Hein K, Zenk M, Bendszus M, Wick W, Calabrese E, Rudie J, Villanueva-Meyer J, Cha S, Ingalhalikar M, Jadhav M, Pandey U, Saini J, Garrett J, Larson M, Jeraj R, Currie S, Frood R, Fatania K, Huang RY, Chang K, Balaña C, Capellades J, Puig J, Trenkler J, Pichler J, Necker G, Haunschmidt A, Meckel S, Shukla G, Liem S, Alexander GS, Lombardo J, Palmer JD, Flanders AE, Dicker AP, Sair HI, Jones CK, Venkataraman A, Jiang M, So TY, Chen C, Heng PA, Dou Q, Kozubek M, Lux F, Michálek J, Matula P, Keřkovský M, Kopřivová T, Dostál M, Vybíhal V, Vogelbaum MA, Mitchell JR, Farinhas J, Maldjian JA, Yogananda CGB, Pinho MC, Reddy D, Holcomb J, Wagner BC, Ellingson BM, Cloughesy TF, Raymond C, Oughourlian T, Hagiwara A, Wang C, To MS, Bhardwaj S, Chong C, Agzarian M, Falcão AX, Martins SB, Teixeira BCA, Sprenger F, Menotti D, Lucio DR, LaMontagne P, Marcus D, Wiestler B, Kofler F, Ezhov I, Metz M, Jain R, Lee M, Lui YW, McKinley R, Slotboom J, Radojewski P, Meier R, Wiest R, Murcia D, Fu E, Haas R, Thompson J, Ormond DR, Badve C, Sloan AE, Vadmal V, Waite K, Colen RR, Pei L, Ak M, Srinivasan A, Bapuraj JR, Rao A, Wang N, Yoshiaki O, Moritani T, Turk S, Lee J, Prabhudesai S, Morón F, Mandel J, Kamnitsas K, Glocker B, Dixon LVM, Williams M, Zampakis P, Panagiotopoulos V, Tsiganos P, Alexiou S, Haliassos I, Zacharaki EI, Moustakas K, Kalogeropoulou C, Kardamakis DM, Choi YS, Lee SK, Chang JH, Ahn SS, Luo B, Poisson L, Wen N, Tiwari P, Verma R, Bareja R, Yadav I, Chen J, Kumar N, Smits M, van der Voort SR, Alafandi A, Incekara F, Wijnenga MMJ, Kapsas G, Gahrmann R, Schouten JW, Dubbink HJ, Vincent AJPE, van den Bent MJ, French PJ, Klein S, Yuan Y, Sharma S, Tseng TC, Adabi S, Niclou SP, Keunen O, Hau AC, Vallières M, Fortin D, Lepage M, Landman B, Ramadass K, Xu K, Chotai S, Chambless LB, Mistry A, Thompson RC, Gusev Y, Bhuvaneshwar K, Sayah A, Bencheqroun C, Belouali A, Madhavan S, Booth TC, Chelliah A, Modat M, Shuaib H, Dragos C, Abayazeed A, Kolodziej K, Hill M, Abbassy A, Gamal S, Mekhaimar M, Qayati M, Reyes M, Park JE, Yun J, Kim HS, Mahajan A, Muzi M, Benson S, Beets-Tan RGH, Teuwen J, Herrera-Trujillo A, Trujillo M, Escobar W, Abello A, Bernal J, Gómez J, Choi J, Baek S, Kim Y, Ismael H, Allen B, Buatti JM, Kotrotsou A, Li H, Weiss T, Weller M, Bink A, Pouymayou B, Shaykh HF, Saltz J, Prasanna P, Shrestha S, Mani KM, Payne D, Kurc T, Pelaez E, Franco-Maldonado H, Loayza F, Quevedo S, Guevara P, Torche E, Mendoza C, Vera F, Ríos E, López E, Velastin SA, Ogbole G, Soneye M, Oyekunle D, Odafe-Oyibotha O, Osobu B, Shu'aibu M, Dorcas A, Dako F, Simpson AL, Hamghalam M, Peoples JJ, Hu R, Tran A, Cutler D, Moraes FY, Boss MA, Gimpel J, Veettil DK, Schmidt K, Bialecki B, Marella S, Price C, Cimino L, Apgar C, Shah P, Menze B, Barnholtz-Sloan JS, Martin J, Bakas S. Author Correction: Federated learning enables big data for rare cancer boundary detection. Nat Commun 2023; 14:436. [PMID: 36702828 PMCID: PMC9879935 DOI: 10.1038/s41467-023-36188-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Affiliation(s)
- Sarthak Pati
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
| | - Ujjwal Baid
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | | | | | | | | | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Chiharu Sako
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Satyam Ghodasara
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Michel Bilello
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Suyash Mohan
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Philipp Vollmuth
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Gianluca Brugnara
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | | | - Felix Sahm
- Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Neuropathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Klaus Maier-Hein
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
- Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Maximilian Zenk
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Wolfgang Wick
- Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ), Heidelberg, Germany
- Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany
| | - Evan Calabrese
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Jeffrey Rudie
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Javier Villanueva-Meyer
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Soonmee Cha
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Madhura Ingalhalikar
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Manali Jadhav
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Umang Pandey
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Jitender Saini
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - John Garrett
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Matthew Larson
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Robert Jeraj
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Stuart Currie
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Russell Frood
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Kavi Fatania
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Raymond Y Huang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ken Chang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | | | | | - Josep Puig
- Department of Radiology (IDI), Girona Biomedical Research Institute (IdIBGi), Josep Trueta University Hospital, Girona, Spain
| | - Johannes Trenkler
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Josef Pichler
- Department of Neurooncology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Georg Necker
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Andreas Haunschmidt
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Stephan Meckel
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
- Institute of Diagnostic and Interventional Neuroradiology, RKH Klinikum Ludwigsburg, Ludwigsburg, Germany
| | - Gaurav Shukla
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiation Oncology, Christiana Care Health System, Philadelphia, PA, USA
| | - Spencer Liem
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - Gregory S Alexander
- Department of Radiation Oncology, University of Maryland, Baltimore, MD, USA
| | - Joseph Lombardo
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Joshua D Palmer
- Department of Radiation Oncology, The James Cancer Hospital and Solove Research Institute, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
| | - Adam E Flanders
- Department of Radiology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Adam P Dicker
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Haris I Sair
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Craig K Jones
- The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Archana Venkataraman
- Department of Electrical and Computer Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Meirui Jiang
- The Chinese University of Hong Kong, Hong Kong, China
| | - Tiffany Y So
- The Chinese University of Hong Kong, Hong Kong, China
| | - Cheng Chen
- The Chinese University of Hong Kong, Hong Kong, China
| | | | - Qi Dou
- The Chinese University of Hong Kong, Hong Kong, China
| | - Michal Kozubek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Filip Lux
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Jan Michálek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Petr Matula
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Miloš Keřkovský
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
| | - Tereza Kopřivová
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
| | - Marek Dostál
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
- Department of Biophysics, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Václav Vybíhal
- Department of Neurosurgery, Faculty of Medicine, Masaryk University, Brno, and University Hospital and Czech Republic, Brno, Czech Republic
| | - Michael A Vogelbaum
- Department of Neuro Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - J Ross Mitchell
- University of Alberta, Edmonton, AB, Canada
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
| | - Joaquim Farinhas
- Department of Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | | | | | - Marco C Pinho
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Divya Reddy
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - James Holcomb
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | | | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- UCLA Neuro-Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CaA, USA
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CaA, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Talia Oughourlian
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Akifumi Hagiwara
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Chencai Wang
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Minh-Son To
- College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
- Division of Surgery and Perioperative Medicine, Flinders Medical Centre, Bedford Park, SA, Australia
| | - Sargam Bhardwaj
- College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
| | - Chee Chong
- South Australia Medical Imaging, Flinders Medical Centre, Bedford Park, SA, Australia
| | - Marc Agzarian
- South Australia Medical Imaging, Flinders Medical Centre, Bedford Park, SA, Australia
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | | | | | - Bernardo C A Teixeira
- Instituto de Neurologia de Curitiba, Curitiba, Paraná, Brazil
- Department of Radiology, Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Flávia Sprenger
- Department of Radiology, Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - David Menotti
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Diego R Lucio
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Pamela LaMontagne
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Daniel Marcus
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Benedikt Wiestler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
| | - Florian Kofler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
- Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany
| | - Ivan Ezhov
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
- Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany
| | - Marie Metz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Rajan Jain
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
- Department of Neurosurgery, NYU Grossman School of Medicine, New York, NY, USA
| | - Matthew Lee
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Yvonne W Lui
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Richard McKinley
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Johannes Slotboom
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Piotr Radojewski
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Raphael Meier
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Roland Wiest
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Derrick Murcia
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Eric Fu
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Rourke Haas
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - John Thompson
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - David Ryan Ormond
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Chaitra Badve
- Department of Radiology, University Hospitals Cleveland, Cleveland, OH, USA
| | - Andrew E Sloan
- Department of Neurological Surgery, University Hospitals-Seidman Cancer Center, Cleveland, OH, USA
- Case Comprehensive Cancer Center, Cleveland, OH, USA
- Department of Neurosurgery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Vachan Vadmal
- Department of Neurosurgery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Kristin Waite
- National Cancer Institute, National Institute of Health, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
| | - Rivka R Colen
- Department of Radiology, Neuroradiology Division, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Linmin Pei
- University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Murat Ak
- Department of Radiology, Neuroradiology Division, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ashok Srinivasan
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - J Rajiv Bapuraj
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Arvind Rao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas Wang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Ota Yoshiaki
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Toshio Moritani
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Sevcan Turk
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Joonsang Lee
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Snehal Prabhudesai
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Fanny Morón
- Department of Radiology, Baylor College of Medicine, Houston, TX, USA
| | - Jacob Mandel
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | - Konstantinos Kamnitsas
- Department of Computing, Imperial College London, London, UK
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Ben Glocker
- Department of Computing, Imperial College London, London, UK
| | - Luke V M Dixon
- Department of Radiology, Imperial College NHS Healthcare Trust, London, UK
| | - Matthew Williams
- Computational Oncology Group, Institute for Global Health Innovation, Imperial College London, London, UK
| | - Peter Zampakis
- Department of NeuroRadiology, University of Patras, Patras, Greece
| | | | - Panagiotis Tsiganos
- Clinical Radiology Laboratory, Department of Medicine, University of Patras, Patras, Greece
| | - Sotiris Alexiou
- Department of Electrical and Computer Engineering, University of Patras, Patras, Greece
| | - Ilias Haliassos
- Department of Neuro-Oncology, University of Patras, Patras, Greece
| | - Evangelia I Zacharaki
- Department of Electrical and Computer Engineering, University of Patras, Patras, Greece
| | | | | | | | | | | | | | - Sung Soo Ahn
- Yonsei University College of Medicine, Seoul, Korea
| | - Bing Luo
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
| | - Laila Poisson
- Public Health Sciences, Henry Ford Health System, Detroit, MI, USA
| | - Ning Wen
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
- SJTU-Ruijin-UIH Institute for Medical Imaging Technology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China
| | | | - Ruchika Verma
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
- Case Western Reserve University, Cleveland, OH, USA
| | - Rohan Bareja
- Case Western Reserve University, Cleveland, OH, USA
| | - Ipsa Yadav
- Case Western Reserve University, Cleveland, OH, USA
| | | | - Neeraj Kumar
- University of Alberta, Edmonton, AB, Canada
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Sebastian R van der Voort
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Ahmed Alafandi
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Fatih Incekara
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Maarten M J Wijnenga
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Georgios Kapsas
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Renske Gahrmann
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Joost W Schouten
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Hendrikus J Dubbink
- Department of Pathology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Arnaud J P E Vincent
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Martin J van den Bent
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Pim J French
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Stefan Klein
- Biomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Yading Yuan
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sonam Sharma
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Tzu-Chi Tseng
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Saba Adabi
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Simone P Niclou
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Olivier Keunen
- Translation Radiomics, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Ann-Christin Hau
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
- Luxembourg Center of Neuropathology, Laboratoire National De Santé, Luxembourg, Luxembourg
| | - Martin Vallières
- Department of Computer Science, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - David Fortin
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Division of Neurosurgery and Neuro-Oncology, Faculty of Medicine and Health Science, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Martin Lepage
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Department of Nuclear Medicine and Radiobiology, Sherbrooke Molecular Imaging Centre, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Bennett Landman
- Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Karthik Ramadass
- Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Kaiwen Xu
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Silky Chotai
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lola B Chambless
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Akshitkumar Mistry
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Reid C Thompson
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yuriy Gusev
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Krithika Bhuvaneshwar
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Anousheh Sayah
- Division of Neuroradiology & Neurointerventional Radiology, Department of Radiology, MedStar Georgetown University Hospital, Washington, DC, USA
| | - Camelia Bencheqroun
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Anas Belouali
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Subha Madhavan
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Thomas C Booth
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
- Department of Neuroradiology, Ruskin Wing, King's College Hospital NHS Foundation Trust, London, UK
| | - Alysha Chelliah
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Marc Modat
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Haris Shuaib
- Stoke Mandeville Hospital, Mandeville Road, Aylesbury, UK
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
| | - Carmen Dragos
- Stoke Mandeville Hospital, Mandeville Road, Aylesbury, UK
| | | | | | | | | | - Shady Gamal
- University of Cairo School of Medicine, Giza, Egypt
| | | | | | | | - Ji Eun Park
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Jihye Yun
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Ho Sung Kim
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Abhishek Mahajan
- The Clatterbridge Cancer Centre NHS Foundation Trust Pembroke Place, Liverpool, UK
| | - Mark Muzi
- Department of Radiology, University of Washington, Seattle, WA, USA
| | - Sean Benson
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Regina G H Beets-Tan
- Department of Radiology, Netherlands Cancer Institute, Amsterdam, Netherlands
- GROW School of Oncology and Developmental Biology, Maastricht, Netherlands
| | - Jonas Teuwen
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | | | | | - William Escobar
- Clínica Imbanaco Grupo Quirón Salud, Cali, Colombia
- Universidad del Valle, Cali, Colombia
| | | | - Jose Bernal
- Universidad del Valle, Cali, Colombia
- The University of Edinburgh, Edinburgh, UK
| | | | - Joseph Choi
- Department of Industrial and Systems Engineering, University of Iowa, Iowa, USA
| | - Stephen Baek
- Department of Industrial and Systems Engineering, Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Yusung Kim
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Heba Ismael
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Bryan Allen
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - John M Buatti
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | | | - Hongwei Li
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Tobias Weiss
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Michael Weller
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Andrea Bink
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Bertrand Pouymayou
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | | | - Joel Saltz
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Prateek Prasanna
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Sampurna Shrestha
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Kartik M Mani
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
- Department of Radiation Oncology, Stony Brook University, Stony Brook, NY, USA
| | - David Payne
- Department of Radiology, Stony Brook University, Stony Brook, NY, USA
| | - Tahsin Kurc
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
- Scientific Data Group, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Enrique Pelaez
- Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador
| | | | - Francis Loayza
- Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador
| | | | | | | | | | - Franco Vera
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Elvis Ríos
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Eduardo López
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Sergio A Velastin
- School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK
| | - Godwin Ogbole
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Mayowa Soneye
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Dotun Oyekunle
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | | | - Babatunde Osobu
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Mustapha Shu'aibu
- Department of Radiology, Muhammad Abdullahi Wase Teaching Hospital, Kano, Nigeria
| | - Adeleye Dorcas
- Department of Radiology, Obafemi Awolowo University Ile-Ife, Ile-Ife, Osun, Nigeria
| | - Farouk Dako
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Global Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Amber L Simpson
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Mohammad Hamghalam
- School of Computing, Queen's University, Kingston, ON, Canada
- Department of Electrical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
| | - Jacob J Peoples
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Ricky Hu
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Anh Tran
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Danielle Cutler
- The Faculty of Arts & Sciences, Queen's University, Kingston, ON, Canada
| | - Fabio Y Moraes
- Department of Oncology, Queen's University, Kingston, ON, Canada
| | - Michael A Boss
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - James Gimpel
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Deepak Kattil Veettil
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Kendall Schmidt
- Data Science Institute, American College of Radiology, Reston, VA, USA
| | - Brian Bialecki
- Data Science Institute, American College of Radiology, Reston, VA, USA
| | - Sailaja Marella
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Cynthia Price
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Lisa Cimino
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Charles Apgar
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | | | - Bjoern Menze
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Jill S Barnholtz-Sloan
- National Cancer Institute, National Institute of Health, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
- Center for Biomedical Informatics and Information Technology, National Cancer Institute (NCI), National Institute of Health, Bethesda, MD, USA
| | | | - Spyridon Bakas
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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Pati S, Baid U, Edwards B, Sheller M, Wang SH, Reina GA, Foley P, Gruzdev A, Karkada D, Davatzikos C, Sako C, Ghodasara S, Bilello M, Mohan S, Vollmuth P, Brugnara G, Preetha CJ, Sahm F, Maier-Hein K, Zenk M, Bendszus M, Wick W, Calabrese E, Rudie J, Villanueva-Meyer J, Cha S, Ingalhalikar M, Jadhav M, Pandey U, Saini J, Garrett J, Larson M, Jeraj R, Currie S, Frood R, Fatania K, Huang RY, Chang K, Balaña C, Capellades J, Puig J, Trenkler J, Pichler J, Necker G, Haunschmidt A, Meckel S, Shukla G, Liem S, Alexander GS, Lombardo J, Palmer JD, Flanders AE, Dicker AP, Sair HI, Jones CK, Venkataraman A, Jiang M, So TY, Chen C, Heng PA, Dou Q, Kozubek M, Lux F, Michálek J, Matula P, Keřkovský M, Kopřivová T, Dostál M, Vybíhal V, Vogelbaum MA, Mitchell JR, Farinhas J, Maldjian JA, Yogananda CGB, Pinho MC, Reddy D, Holcomb J, Wagner BC, Ellingson BM, Cloughesy TF, Raymond C, Oughourlian T, Hagiwara A, Wang C, To MS, Bhardwaj S, Chong C, Agzarian M, Falcão AX, Martins SB, Teixeira BCA, Sprenger F, Menotti D, Lucio DR, LaMontagne P, Marcus D, Wiestler B, Kofler F, Ezhov I, Metz M, Jain R, Lee M, Lui YW, McKinley R, Slotboom J, Radojewski P, Meier R, Wiest R, Murcia D, Fu E, Haas R, Thompson J, Ormond DR, Badve C, Sloan AE, Vadmal V, Waite K, Colen RR, Pei L, Ak M, Srinivasan A, Bapuraj JR, Rao A, Wang N, Yoshiaki O, Moritani T, Turk S, Lee J, Prabhudesai S, Morón F, Mandel J, Kamnitsas K, Glocker B, Dixon LVM, Williams M, Zampakis P, Panagiotopoulos V, Tsiganos P, Alexiou S, Haliassos I, Zacharaki EI, Moustakas K, Kalogeropoulou C, Kardamakis DM, Choi YS, Lee SK, Chang JH, Ahn SS, Luo B, Poisson L, Wen N, Tiwari P, Verma R, Bareja R, Yadav I, Chen J, Kumar N, Smits M, van der Voort SR, Alafandi A, Incekara F, Wijnenga MMJ, Kapsas G, Gahrmann R, Schouten JW, Dubbink HJ, Vincent AJPE, van den Bent MJ, French PJ, Klein S, Yuan Y, Sharma S, Tseng TC, Adabi S, Niclou SP, Keunen O, Hau AC, Vallières M, Fortin D, Lepage M, Landman B, Ramadass K, Xu K, Chotai S, Chambless LB, Mistry A, Thompson RC, Gusev Y, Bhuvaneshwar K, Sayah A, Bencheqroun C, Belouali A, Madhavan S, Booth TC, Chelliah A, Modat M, Shuaib H, Dragos C, Abayazeed A, Kolodziej K, Hill M, Abbassy A, Gamal S, Mekhaimar M, Qayati M, Reyes M, Park JE, Yun J, Kim HS, Mahajan A, Muzi M, Benson S, Beets-Tan RGH, Teuwen J, Herrera-Trujillo A, Trujillo M, Escobar W, Abello A, Bernal J, Gómez J, Choi J, Baek S, Kim Y, Ismael H, Allen B, Buatti JM, Kotrotsou A, Li H, Weiss T, Weller M, Bink A, Pouymayou B, Shaykh HF, Saltz J, Prasanna P, Shrestha S, Mani KM, Payne D, Kurc T, Pelaez E, Franco-Maldonado H, Loayza F, Quevedo S, Guevara P, Torche E, Mendoza C, Vera F, Ríos E, López E, Velastin SA, Ogbole G, Soneye M, Oyekunle D, Odafe-Oyibotha O, Osobu B, Shu'aibu M, Dorcas A, Dako F, Simpson AL, Hamghalam M, Peoples JJ, Hu R, Tran A, Cutler D, Moraes FY, Boss MA, Gimpel J, Veettil DK, Schmidt K, Bialecki B, Marella S, Price C, Cimino L, Apgar C, Shah P, Menze B, Barnholtz-Sloan JS, Martin J, Bakas S. Federated learning enables big data for rare cancer boundary detection. Nat Commun 2022; 13:7346. [PMID: 36470898 PMCID: PMC9722782 DOI: 10.1038/s41467-022-33407-5] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 09/16/2022] [Indexed: 12/12/2022] Open
Abstract
Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.
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Affiliation(s)
- Sarthak Pati
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
| | - Ujjwal Baid
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | | | | | | | | | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Chiharu Sako
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Satyam Ghodasara
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Michel Bilello
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Suyash Mohan
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Philipp Vollmuth
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Gianluca Brugnara
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | | | - Felix Sahm
- Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Neuropathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Klaus Maier-Hein
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
- Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Maximilian Zenk
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Wolfgang Wick
- Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ), Heidelberg, Germany
- Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany
| | - Evan Calabrese
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Jeffrey Rudie
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Javier Villanueva-Meyer
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Soonmee Cha
- Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Madhura Ingalhalikar
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Manali Jadhav
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Umang Pandey
- Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, Maharashtra, India
| | - Jitender Saini
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - John Garrett
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Matthew Larson
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Robert Jeraj
- Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Stuart Currie
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Russell Frood
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Kavi Fatania
- Leeds Teaching Hospitals Trust, Department of Radiology, Leeds, UK
| | - Raymond Y Huang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ken Chang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | | | | | - Josep Puig
- Department of Radiology (IDI), Girona Biomedical Research Institute (IdIBGi), Josep Trueta University Hospital, Girona, Spain
| | - Johannes Trenkler
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Josef Pichler
- Department of Neurooncology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Georg Necker
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Andreas Haunschmidt
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
| | - Stephan Meckel
- Institute of Neuroradiology, Neuromed Campus (NMC), Kepler University Hospital Linz, Linz, Austria
- Institute of Diagnostic and Interventional Neuroradiology, RKH Klinikum Ludwigsburg, Ludwigsburg, Germany
| | - Gaurav Shukla
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiation Oncology, Christiana Care Health System, Philadelphia, PA, USA
| | - Spencer Liem
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - Gregory S Alexander
- Department of Radiation Oncology, University of Maryland, Baltimore, MD, USA
| | - Joseph Lombardo
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Joshua D Palmer
- Department of Radiation Oncology, The James Cancer Hospital and Solove Research Institute, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
| | - Adam E Flanders
- Department of Radiology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Adam P Dicker
- Department of Radiation Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Haris I Sair
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Craig K Jones
- The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Archana Venkataraman
- Department of Electrical and Computer Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Meirui Jiang
- The Chinese University of Hong Kong, Hong Kong, China
| | - Tiffany Y So
- The Chinese University of Hong Kong, Hong Kong, China
| | - Cheng Chen
- The Chinese University of Hong Kong, Hong Kong, China
| | | | - Qi Dou
- The Chinese University of Hong Kong, Hong Kong, China
| | - Michal Kozubek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Filip Lux
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Jan Michálek
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Petr Matula
- Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Brno, Czech Republic
| | - Miloš Keřkovský
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
| | - Tereza Kopřivová
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
| | - Marek Dostál
- Department of Radiology and Nuclear Medicine, Faculty of Medicine, Masaryk University, Brno and University Hospital Brno, Brno, Czech Republic
- Department of Biophysics, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Václav Vybíhal
- Department of Neurosurgery, Faculty of Medicine, Masaryk University, Brno, and University Hospital and Czech Republic, Brno, Czech Republic
| | - Michael A Vogelbaum
- Department of Neuro Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - J Ross Mitchell
- University of Alberta, Edmonton, AB, Canada
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
| | - Joaquim Farinhas
- Department of Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | | | | | - Marco C Pinho
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Divya Reddy
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - James Holcomb
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | | | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- UCLA Neuro-Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CaA, USA
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CaA, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Talia Oughourlian
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Akifumi Hagiwara
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Chencai Wang
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Minh-Son To
- College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
- Division of Surgery and Perioperative Medicine, Flinders Medical Centre, Bedford Park, SA, Australia
| | - Sargam Bhardwaj
- College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia
| | - Chee Chong
- South Australia Medical Imaging, Flinders Medical Centre, Bedford Park, SA, Australia
| | - Marc Agzarian
- South Australia Medical Imaging, Flinders Medical Centre, Bedford Park, SA, Australia
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | | | | | - Bernardo C A Teixeira
- Instituto de Neurologia de Curitiba, Curitiba, Paraná, Brazil
- Department of Radiology, Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Flávia Sprenger
- Department of Radiology, Hospital de Clínicas da Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - David Menotti
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Diego R Lucio
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Pamela LaMontagne
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Daniel Marcus
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Benedikt Wiestler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
| | - Florian Kofler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
- Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany
| | - Ivan Ezhov
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
- TranslaTUM (Zentralinstitut für translationale Krebsforschung der Technischen Universität München), Klinikum rechts der Isar, Munich, Germany
- Image-Based Biomedical Modeling, Department of Informatics, Technical University of Munich, Munich, Germany
| | - Marie Metz
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Rajan Jain
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
- Department of Neurosurgery, NYU Grossman School of Medicine, New York, NY, USA
| | - Matthew Lee
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Yvonne W Lui
- Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Richard McKinley
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Johannes Slotboom
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Piotr Radojewski
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Raphael Meier
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Roland Wiest
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Derrick Murcia
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Eric Fu
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Rourke Haas
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - John Thompson
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - David Ryan Ormond
- Department of Neurosurgery, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Chaitra Badve
- Department of Radiology, University Hospitals Cleveland, Cleveland, OH, USA
| | - Andrew E Sloan
- Department of Neurological Surgery, University Hospitals-Seidman Cancer Center, Cleveland, OH, USA
- Case Comprehensive Cancer Center, Cleveland, OH, USA
- Department of Neurosurgery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Vachan Vadmal
- Department of Neurosurgery, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Kristin Waite
- National Cancer Institute, National Institute of Health, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
| | - Rivka R Colen
- Department of Radiology, Neuroradiology Division, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Linmin Pei
- University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Murat Ak
- Department of Radiology, Neuroradiology Division, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ashok Srinivasan
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - J Rajiv Bapuraj
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Arvind Rao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas Wang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Ota Yoshiaki
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Toshio Moritani
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Sevcan Turk
- Department of Neuroradiology, University of Michigan, Ann Arbor, MI, USA
| | - Joonsang Lee
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Snehal Prabhudesai
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Fanny Morón
- Department of Radiology, Baylor College of Medicine, Houston, TX, USA
| | - Jacob Mandel
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
| | - Konstantinos Kamnitsas
- Department of Computing, Imperial College London, London, UK
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Ben Glocker
- Department of Computing, Imperial College London, London, UK
| | - Luke V M Dixon
- Department of Radiology, Imperial College NHS Healthcare Trust, London, UK
| | - Matthew Williams
- Computational Oncology Group, Institute for Global Health Innovation, Imperial College London, London, UK
| | - Peter Zampakis
- Department of NeuroRadiology, University of Patras, Patras, Greece
| | | | - Panagiotis Tsiganos
- Clinical Radiology Laboratory, Department of Medicine, University of Patras, Patras, Greece
| | - Sotiris Alexiou
- Department of Electrical and Computer Engineering, University of Patras, Patras, Greece
| | - Ilias Haliassos
- Department of Neuro-Oncology, University of Patras, Patras, Greece
| | - Evangelia I Zacharaki
- Department of Electrical and Computer Engineering, University of Patras, Patras, Greece
| | | | | | | | | | | | | | - Sung Soo Ahn
- Yonsei University College of Medicine, Seoul, Korea
| | - Bing Luo
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
| | - Laila Poisson
- Public Health Sciences, Henry Ford Health System, Detroit, MI, USA
| | - Ning Wen
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
- SJTU-Ruijin-UIH Institute for Medical Imaging Technology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China
| | | | - Ruchika Verma
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
- Case Western Reserve University, Cleveland, OH, USA
| | - Rohan Bareja
- Case Western Reserve University, Cleveland, OH, USA
| | - Ipsa Yadav
- Case Western Reserve University, Cleveland, OH, USA
| | | | - Neeraj Kumar
- University of Alberta, Edmonton, AB, Canada
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Sebastian R van der Voort
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Ahmed Alafandi
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Fatih Incekara
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Maarten M J Wijnenga
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Georgios Kapsas
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Renske Gahrmann
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Joost W Schouten
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Hendrikus J Dubbink
- Department of Pathology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Arnaud J P E Vincent
- Department of Neurosurgery, Brain Tumor Center, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Martin J van den Bent
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Pim J French
- Department of Neurology, Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Stefan Klein
- Biomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Centre Rotterdam, Rotterdam, Netherlands
| | - Yading Yuan
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sonam Sharma
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Tzu-Chi Tseng
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Saba Adabi
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Simone P Niclou
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Olivier Keunen
- Translation Radiomics, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Ann-Christin Hau
- NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg
- Luxembourg Center of Neuropathology, Laboratoire National De Santé, Luxembourg, Luxembourg
| | - Martin Vallières
- Department of Computer Science, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - David Fortin
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Division of Neurosurgery and Neuro-Oncology, Faculty of Medicine and Health Science, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Martin Lepage
- Centre de Recherche du Centre Hospitalière Universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Department of Nuclear Medicine and Radiobiology, Sherbrooke Molecular Imaging Centre, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Bennett Landman
- Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Karthik Ramadass
- Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Kaiwen Xu
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Silky Chotai
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lola B Chambless
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Akshitkumar Mistry
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Reid C Thompson
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yuriy Gusev
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Krithika Bhuvaneshwar
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Anousheh Sayah
- Division of Neuroradiology & Neurointerventional Radiology, Department of Radiology, MedStar Georgetown University Hospital, Washington, DC, USA
| | - Camelia Bencheqroun
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Anas Belouali
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Subha Madhavan
- Innovation Center for Biomedical Informatics (ICBI), Georgetown University, Washington, DC, USA
| | - Thomas C Booth
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
- Department of Neuroradiology, Ruskin Wing, King's College Hospital NHS Foundation Trust, London, UK
| | - Alysha Chelliah
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Marc Modat
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Haris Shuaib
- Stoke Mandeville Hospital, Mandeville Road, Aylesbury, UK
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
| | - Carmen Dragos
- Stoke Mandeville Hospital, Mandeville Road, Aylesbury, UK
| | | | | | | | | | - Shady Gamal
- University of Cairo School of Medicine, Giza, Egypt
| | | | | | | | - Ji Eun Park
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Jihye Yun
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Ho Sung Kim
- Department of Radiology, Asan Medical Center, Seoul, South Korea
| | - Abhishek Mahajan
- The Clatterbridge Cancer Centre NHS Foundation Trust Pembroke Place, Liverpool, UK
| | - Mark Muzi
- Department of Radiology, University of Washington, Seattle, WA, USA
| | - Sean Benson
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Regina G H Beets-Tan
- Department of Radiology, Netherlands Cancer Institute, Amsterdam, Netherlands
- GROW School of Oncology and Developmental Biology, Maastricht, Netherlands
| | - Jonas Teuwen
- Netherlands Cancer Institute, Amsterdam, Netherlands
| | | | | | - William Escobar
- Clínica Imbanaco Grupo Quirón Salud, Cali, Colombia
- Universidad del Valle, Cali, Colombia
| | | | - Jose Bernal
- Universidad del Valle, Cali, Colombia
- The University of Edinburgh, Edinburgh, UK
| | | | - Joseph Choi
- Department of Industrial and Systems Engineering, University of Iowa, Iowa, USA
| | - Stephen Baek
- Department of Industrial and Systems Engineering, Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Yusung Kim
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Heba Ismael
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - Bryan Allen
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | - John M Buatti
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
| | | | - Hongwei Li
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Tobias Weiss
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Michael Weller
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Andrea Bink
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Bertrand Pouymayou
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | | | - Joel Saltz
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Prateek Prasanna
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Sampurna Shrestha
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Kartik M Mani
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
- Department of Radiation Oncology, Stony Brook University, Stony Brook, NY, USA
| | - David Payne
- Department of Radiology, Stony Brook University, Stony Brook, NY, USA
| | - Tahsin Kurc
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
- Scientific Data Group, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Enrique Pelaez
- Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador
| | | | - Francis Loayza
- Escuela Superior Politecnica del Litoral, Guayaquil, Guayas, Ecuador
| | | | | | | | | | - Franco Vera
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Elvis Ríos
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Eduardo López
- Universidad de Concepción, Concepción, Biobío, Chile
| | - Sergio A Velastin
- School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK
| | - Godwin Ogbole
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Mayowa Soneye
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Dotun Oyekunle
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | | | - Babatunde Osobu
- Department of Radiology, University College Hospital Ibadan, Oyo, Nigeria
| | - Mustapha Shu'aibu
- Department of Radiology, Muhammad Abdullahi Wase Teaching Hospital, Kano, Nigeria
| | - Adeleye Dorcas
- Department of Radiology, Obafemi Awolowo University Ile-Ife, Ile-Ife, Osun, Nigeria
| | - Farouk Dako
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Global Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Amber L Simpson
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Mohammad Hamghalam
- School of Computing, Queen's University, Kingston, ON, Canada
- Department of Electrical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
| | - Jacob J Peoples
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Ricky Hu
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Anh Tran
- School of Computing, Queen's University, Kingston, ON, Canada
| | - Danielle Cutler
- The Faculty of Arts & Sciences, Queen's University, Kingston, ON, Canada
| | - Fabio Y Moraes
- Department of Oncology, Queen's University, Kingston, ON, Canada
| | - Michael A Boss
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - James Gimpel
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Deepak Kattil Veettil
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Kendall Schmidt
- Data Science Institute, American College of Radiology, Reston, VA, USA
| | - Brian Bialecki
- Data Science Institute, American College of Radiology, Reston, VA, USA
| | - Sailaja Marella
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Cynthia Price
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Lisa Cimino
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | - Charles Apgar
- Center for Research and Innovation, American College of Radiology, Philadelphia, PA, USA
| | | | - Bjoern Menze
- Department of Informatics, Technical University of Munich, Munich, Bavaria, Germany
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Jill S Barnholtz-Sloan
- National Cancer Institute, National Institute of Health, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
- Center for Biomedical Informatics and Information Technology, National Cancer Institute (NCI), National Institute of Health, Bethesda, MD, USA
| | | | - Spyridon Bakas
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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9
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Van de Winckel A, De Patre D, Rigoni M, Fiecas M, Hendrickson TJ, Larson M, Jagadeesan BD, Mueller BA, Elvendahl W, Streib C, Ikramuddin F, Lim KO. Exploratory study of how Cognitive Multisensory Rehabilitation restores parietal operculum connectivity and improves upper limb movements in chronic stroke. Sci Rep 2020; 10:20278. [PMID: 33219267 PMCID: PMC7680110 DOI: 10.1038/s41598-020-77272-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Accepted: 11/09/2020] [Indexed: 11/30/2022] Open
Abstract
Cognitive Multisensory Rehabilitation (CMR) is a promising therapy for upper limb recovery in stroke, but the brain mechanisms are unknown. We previously demonstrated that the parietal operculum (parts OP1/OP4) is activated with CMR exercises. In this exploratory study, we assessed the baseline difference between OP1/OP4 functional connectivity (FC) at rest in stroke versus healthy adults to then explore whether CMR affects OP1/OP4 connectivity and sensorimotor recovery after stroke. We recruited 8 adults with chronic stroke and left hemiplegia/paresis and 22 healthy adults. Resting-state FC with the OP1/OP4 region-of-interest in the affected hemisphere was analysed before and after 6 weeks of CMR. We evaluated sensorimotor function and activities of daily life pre- and post-CMR, and at 1-year post-CMR. At baseline, we found decreased FC between the right OP1/OP4 and 34 areas distributed across all lobes in stroke versus healthy adults. After CMR, only four areas had decreased FC compared to healthy adults. Compared to baseline (pre-CMR), participants improved on motor function (MESUPES arm p = 0.02; MESUPES hand p = 0.03; MESUPES total score p = 0.006); on stereognosis (p = 0.03); and on the Frenchay Activities Index (p = 0.03) at post-CMR and at 1-year follow-up. These results suggest enhanced sensorimotor recovery post-stroke after CMR. Our results justify larger-scale studies.
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Affiliation(s)
- A Van de Winckel
- Division of Physical Therapy, Division of Rehabilitation Science, Department of Rehabilitation Medicine, Medical School, University of Minnesota, Minneapolis, USA.
| | - D De Patre
- Centro Studi Di Riabilitazione Neurocognitiva - Villa Miari (Study Center for Cognitive Multisensory Rehabilitation), Santorso, Vicenza, Italy
| | - M Rigoni
- Centro Studi Di Riabilitazione Neurocognitiva - Villa Miari (Study Center for Cognitive Multisensory Rehabilitation), Santorso, Vicenza, Italy
| | - M Fiecas
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, USA
| | - T J Hendrickson
- University of Minnesota Informatics Institute, Office of the Vice President for Research, University of Minnesota, Minneapolis, USA
| | - M Larson
- Division of Rehabilitation Science, Department of Rehabilitation Medicine, Medical School, University of Minnesota, Minneapolis, USA
| | - B D Jagadeesan
- Department of Radiology, Medical School, University of Minnesota, Minneapolis, USA
| | - B A Mueller
- Department of Psychiatry, Medical School, University of Minnesota, Minneapolis, USA
| | - W Elvendahl
- Center of Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, USA
| | - C Streib
- Department of Neurology, Medical School, University of Minnesota, Minneapolis, USA
| | - F Ikramuddin
- Division of Physical Medicine and Rehabilitation, Department of Rehabilitation Medicine, Medical School, University of Minnesota, Minneapolis, USA
| | - K O Lim
- Department of Psychiatry, Medical School, University of Minnesota, Minneapolis, USA
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Abstract
Motivation Cell-free nucleic acid (cfNA) sequencing data require improvements to existing fusion detection methods along multiple axes: high depth of sequencing, low allele fractions, short fragment lengths and specialized barcodes, such as unique molecular identifiers. Results AF4 was developed to address these challenges. It uses a novel alignment-free kmer-based method to detect candidate fusion fragments with high sensitivity and orders of magnitude faster than existing tools. Candidate fragments are then filtered using a max-cover criterion that significantly reduces spurious matches while retaining authentic fusion fragments. This efficient first stage reduces the data sufficiently that commonly used criteria can process the remaining information, or sophisticated filtering policies that may not scale to the raw reads can be used. AF4 provides both targeted and de novo fusion detection modes. We demonstrate both modes in benchmark simulated and real RNA-seq data as well as clinical and cell-line cfNA data. Availability and implementation AF4 is open sourced, licensed under Apache License 2.0, and is available at: https://github.com/grailbio/bio/tree/master/fusion.
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11
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McCafferty B, Meh Chu G, Joe W, Larson M, Devane M, Sing R, Madassery S, Gunn A. Abstract No. 733 Bone penetration by inferior vena cava filters: feasibility and safety of percutaneous retrieval. J Vasc Interv Radiol 2020. [DOI: 10.1016/j.jvir.2019.12.792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
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12
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Zhao FJ, Bonmarin M, Chen ZC, Larson M, Fay D, Runnoe D, Heikenfeld J. Ultra-simple wearable local sweat volume monitoring patch based on swellable hydrogels. Lab Chip 2020; 20:168-174. [PMID: 31796944 DOI: 10.1039/c9lc00911f] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Quantifiably monitoring sweat rate and volume is important to assess the stress level of individuals and/or prevent dehydration, but despite intense research, a convenient, continuous, and low-cost method to monitor sweat rate and total sweat volume loss remains an un-met need. We present here an ultra-simple wearable sensor capable of measuring sweat rate and volume accurately. The device continuously monitors sweat rate by wicking the produced sweat into hydrogels that measurably swell in their physical geometry. The device has been designed as a simple to fabricate, low-cost, disposable patch. This patch exhibits stable and predictable operation over the maximum variable chemistry expected for sweat (pH 4-9 and salinity 0-100 mM NaCl). Preliminary in vivo testing of the patch has been achieved during aerobic exercise, and the sweat rates measured via the patch accurately follow actual sweat rates.
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Affiliation(s)
- F J Zhao
- College of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, Guangxi 541004, China and Novel Devices Laboratory, University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - M Bonmarin
- Novel Devices Laboratory, University of Cincinnati, Cincinnati, Ohio 45221, USA and School of Engineering, Zurich University of Applied Sciences, Technikumstrasse 9, Winterthur, Zurich 8400, Switzerland
| | - Z C Chen
- College of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, Guangxi 541004, China
| | - M Larson
- Eccrine Systems Inc., 1775 Mentor Ave, Cincinnati, Ohio 45212, USA
| | - D Fay
- Eccrine Systems Inc., 1775 Mentor Ave, Cincinnati, Ohio 45212, USA
| | - D Runnoe
- Eccrine Systems Inc., 1775 Mentor Ave, Cincinnati, Ohio 45212, USA
| | - J Heikenfeld
- Novel Devices Laboratory, University of Cincinnati, Cincinnati, Ohio 45221, USA
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13
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Larson M, Lindaman B. Catastrophic Antiphospholipid Syndrome Presenting with Genitourinary Manifestations. S D Med 2019; 72:464-466. [PMID: 31816208] [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: 06/10/2023]
Abstract
Catastrophic antiphospholipid syndrome (CAPS) is a rare disorder characterized by acute, multi-system dysfunc- tion due to small-vessel thrombosis related to anti-phospholipid antibodies. Here we present an unusual case of CAPS presenting with genitourinary manifestations. A 72-year-old male developed a series of symptoms over the course of two weeks. His symptoms included testicular inflammation, scrotal edema, priapism, hematuria, penile eschar, elbow eschars, and acute kidney injury. He was found to have anti-phospholipid antibodies and treated with anticoagulation, high-dose steroids and plasma exchange. His symptoms resolved with minimal lasting effects. This case is unique to the literature because of the extensive genitourinary involvement.
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Affiliation(s)
- Matthew Larson
- University of South Dakota Sanford School of Medicine, Sioux Falls, South Dakota
- Urology Residency Program, University of Kansas Medical Center, Kansas City, Kansas
| | - Brian Lindaman
- University of South Dakota Sanford School of Medicine, Sioux Falls, South Dakota
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14
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Huang G, Baltuck C, Funkhouser E, Wang HFC, Todoki L, Finkleman S, Shapiro P, Khosravi R, Ko HCJ, Greenlee G, De Jesus-Vinas J, Vermette M, Larson M, Dolce C, Kau CH, Harnick D. The National Dental Practice-Based Research Network Adult Anterior Open Bite Study: Treatment recommendations and their association with patient and practitioner characteristics. Am J Orthod Dentofacial Orthop 2019; 156:312-325. [PMID: 31474261 DOI: 10.1016/j.ajodo.2019.05.005] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 05/01/2019] [Accepted: 05/01/2019] [Indexed: 10/26/2022]
Abstract
INTRODUCTION This aim of this paper is to describe and identify the practitioner and patient characteristics that are associated with treatment recommendations for adult anterior open bite patients across the United States. METHODS Practitioners and patients were recruited within the framework of the National Dental Practice-Based Research Network. Practitioners were asked about their demographic characteristics and their treatment recommendations for these patients. The practitioners also reported on their patients' dentofacial characteristics and provided initial cephalometric scans and intraoral photographs. Patients were asked about their demographic characteristics, previous orthodontic treatment, and goals for treatment. Four main treatment groups were evaluated: aligners, fixed appliances, temporary anchorage devices (TADs), and orthognathic surgery. Extractions were also investigated. Predictive multivariable models were created comparing various categories of treatment as well as extraction/nonextraction decisions. RESULTS Ninety-one practitioners (mostly orthodontists) and 347 patients were recruited from October 2015 to December 2016. Increased aligner recommendations were associated with white and Asian patients, the presence of tongue habits, and female practitioners. TADs were recommended more often in academic settings. Recommendations for orthognathic surgery were associated with demographic factors, such as availability of insurance coverage and practitioner race/ethnicity, and dentofacial characteristics, such as anteroposterior discrepancies, more severe open bites, and steeper mandibular plane angles. Extraction recommendations were largely associated with severe crowding and incisor proclination. CONCLUSIONS Both doctor and patient demographic factors, as well as dentofacial characteristics, were significantly associated with treatment recommendations for adult anterior open bite patients.
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Affiliation(s)
- Greg Huang
- Department of Orthodontics, University of Washington, Seattle, Wash.
| | - Camille Baltuck
- Western Region, National Dental Practice-Based Research Network, Portland, Ore
| | - Ellen Funkhouser
- Division of Preventive Medicine, School of Medicine, University of Alabama, Birmingham, Ala
| | - Hsuan-Fang Cathy Wang
- Department of Orthodontics, University of Washington, Seattle, Wash; Division of Orthodontics, Department of Dentistry, Far Eastern Memorial Hospital, Taipei, Taiwan
| | - Lauren Todoki
- Department of Orthodontics, University of Washington, Seattle, Wash
| | - Sam Finkleman
- Department of Orthodontics, University of Washington, Seattle, Wash
| | - Peter Shapiro
- Department of Orthodontics, University of Washington, Seattle, Wash
| | - Roozbah Khosravi
- Department of Orthodontics, University of Washington, Seattle, Wash
| | | | | | | | | | | | - Calogero Dolce
- Department of Orthodontics, University of Florida, Gainesville, Fla
| | - Chung How Kau
- Department of Orthodontics, University of Alabama, Birmingham, Ala
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- National Dental Practice-Based Research Network (PBRN) Collaborative Group includes practitioner, faculty, and staff investigators who contributed to this activity. A full list is available at http://nationaldentalpbrn.org/collaborative-group.php
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15
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Larson M, Ludy M, Kiss J, Morgan A. Comparison of Body Composition Assessment Techniques in Women’s Collegiate Swimmers and Divers. J Acad Nutr Diet 2019. [DOI: 10.1016/j.jand.2019.06.086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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16
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Triolo TM, Fouts A, Pyle L, Yu L, Gottlieb PA, Steck AK, Greenbaum CJ, Atkinson M, Baidal D, Battaglia M, Becker D, Bingley P, Bosi E, Buckner J, Clements M, Colman P, DiMeglio L, Gitelman S, Goland R, Gottlieb P, Herold K, Knip M, Krischer J, Lernmark A, Moore W, Moran A, Muir A, Palmer J, Peakman M, Philipson L, Raskin P, Redondo M, Rodriguez H, Russell W, Spain L, Schatz D, Sosenko J, Wentworth J, Wherrett D, Wilson D, Winter W, Ziegler A, Anderson M, Antinozzi P, Benoist C, Blum J, Bourcier K, Chase P, Clare-Salzler M, Clynes R, Eisenbarth G, Fathman C, Grave G, Hering B, Insel R, Kaufman F, Kay T, Leschek E, Mahon J, Marks J, Nanto-Salonen K, Nepom G, Orban T, Parkman R, Pescovitz M, Peyman J, Pugliese A, Roep B, Roncarolo M, Savage P, Simell O, Sherwin R, Siegelman M, Skyler J, Steck A, Thomas J, Trucco M, Wagner J, Krischer JP, Leschek E, Rafkin L, Bourcier K, Cowie C, Foulkes M, Insel R, Krause-Steinrauf H, Lachin JM, Malozowski S, Peyman J, Ridge J, Savage P, Skyler JS, Zafonte SJ, Rafkin L, Sosenko JM, Kenyon NS, Santiago I, Krischer JP, Bundy B, Abbondondolo M, Dixit S, Pasha M, King K, Adcock H, Atterberry L, Fox K, Englert N, Mauras J, Permuy K, Sikes T, Adams T, Berhe B, Guendling L, McLennan L, Paganessi C, Murphy M, Draznin M, Kamboj S, Sheppard V, Lewis L, Coates W, Amado D, Moore G, Babar J, Bedard D, Brenson-Hughes J, Cernich M, Clements R, Duprau S, Goodman L, Hester L, Huerta-Saenz A, Asif I, Karmazin T, Letjen S, Raman D, Morin W, Bestermann E, Morawski J, White A, Brockmyer R, Bays S, Campbell A, Boonstra M, Stapleton N, Stone A, Donoho H, Everett H, Hensley M, Johnson C, Marshall N, Skirvin P, Taylor R, Williams L, Burroughs C, Ray C, Wolverton D, Nickels C, Dothard P, Speiser M, Pellizzari L, Bokor K, Izuora S, Abdelnour P, Cummings S, Cuthbertson D, Paynor M, Leahy M, Riedl S, Shockley R, Saad T, Briones S, Casella C, Herz K, Walsh J, Greening F, Deemer M, Hay S, Hunt N, Sikotra L, Simons D, Karounos R, Oremus L, Dye L, Myers D, Ballard W, Miers R, Eberhard C, Sparks K, Thraikill K, Edwards J, Fowlkes S, Kemp A, Morales L, Holland L, Johnson P, Paul A, Ghatak K, Fiske S, Phelen H, Leyland T, Henderson D, Brenner E, Oppenheimer I, Mamkin C, Moniz C, Clarson M, Lovell A, Peters V, Ford J, Ruelas D, Borut D, Burt M, Jordan S, Castilla P, Flores M, Ruiz L, Hanson J, Green-Blair R, Sheridan K, Garmeson J, Wintergerst G, Pierce A, Omoruyi M, Foster S, Kingery A, Lunsford I, Cervantes T, Parker P, Price J, Urben I, Guillette H, Doughty H, Haydock V, Parker P, Bergman S, Duncum C, Rodda A, Perelman R, Calendo C, Barrera E, Arce-Nunez Y, Geyer S, Martinez M, De la Portilla I, Cardenas L, Garrido M, Villar R, Lorini E, Calandra G, D’Annuzio K, Perri N, Minuto C, Hays B, Rebora R, Callegari O, Ali J, Kramer B, Auble S, Cabrera P, Donohoue R, Fiallo-Scharer M, Hessner P, Wolfgram A, Henderson C, Kansra N, Bettin R, McCuller A, Miller S, Accacha J, Corrigan E, Fiore R, Levine T, Mahoney C, Polychronakos V, Henry M, Gagne H, Starkman M, Fox D, Chin F, Melchionne L, Silverman I, Marshall L, Cerracchio J, Cruz A, Viswanathan J, Heyman K, Wilson S, Chalew S, Valley S, Layburn A, Lala P, Clesi M, Genet G, Uwaifo A, Charron T, Allerton W, Hsiao B, Cefalu L, Melendez-Ramirez R, Richards C, Alleyn E, Gustafson M, Lizanna J, Wahlen S, Aleiwe M, Hansen H, Wahlen C, Karges C, Levy A, Bonaccorso R, Rapaport Y, Tomer D, Chia M, Goldis L, Iazzetti M, Klein C, Levister L, Waldman E, Keaton N, Wallach M, Regelmann Z, Antal M, Aranda C, Reynholds A, Vinik P, Barlow M, Bourcier M, Nevoret J, Couper S, Kinderman A, Beresford N, Thalagne H, Roper J, Gibbons J, Hill S, Balleaut C, Brennan J, Ellis-Gage L, Fear T, Gray L, Law P, Jones C, McNerney L, Pointer N, Price K, Few D, Tomlinson N, Leech D, Wake C, Owens M, Burns J, Leinbach A, Wotherspoon A, Murray K, Short G, Curry S, Kelsey J, Lawson J, Porter S, Stevens E, Thomson S, Winship L, Liu S, Wynn E, Wiltshire J, Krebs P, Cresswell H, Faherty C, Ross L, Denvir J, Drew T, Randell P, Mansell S, Lloyd J, Bell S, Butler Y, Hooton H, Navarra A, Roper G, Babington L, Crate H, Cripps A, Ledlie C, Moulds R, Malloy J, Norton B, Petrova O, Silkstone C, Smith K, Ghai M, Murray V, Viswanathan M, Henegan O, Kawadry J, Olson L, Maddox K, Patterson T, Ahmad B, Flores D, Domek S, Domek K, Copeland M, George J, Less T, Davis M, Short A, Martin J, Dwarakanathan P, O’Donnell B, Boerner L, Larson M, Phillips M, Rendell K, Larson C, Smith K, Zebrowski L, Kuechenmeister M, Miller J, Thevarayapillai M, Daniels H, Speer N, Forghani R, Quintana C, Reh A, Bhangoo P, Desrosiers L, Ireland T, Misla C, Milliot E, Torres S, Wells J, Villar M, Yu D, Berry D, Cook J, Soder A, Powell M, Ng M, Morrison Z, Moore M, Haslam M, Lawson B, Bradley J, Courtney C, Richardson C, Watson E, Keely D, DeCurtis M, Vaccarcello-Cruz Z, Torres K, Muller S, Sandberg H, Hsiang B, Joy D, McCormick A, Powell H, Jones J, Bell S, Hargadon S, Hudson M, Kummer S, Nguyen T, Sauder E, Sutton K, Gensel R, 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Manning G, Hendry B, Taylor S, Jones W, Strader M, Bencomo T, Bailey L, Bedolla C, Roldan C, Moudiotis B, Vaidya C, Anning S, Bunce S, Estcourt E, Folland E, Gordon C, Harrill J, Ireland J, Piper L, Scaife K, Sutton S, Wilkins M, Costelloe J, Palmer L, Casas C, Miller M, Burgard C, Erickson J, Hallanger-Johnson P, Clark W, Taylor A, Lafferty S, Gillett C, Nolan M, Pathak L, Sondrol T, Hjelle S, Hafner J, Kotrba R, Hendrickson A, Cemeroglu T, Symington M, Daniel Y, Appiagyei-Dankah D, Postellon M, Racine L, Kleis K, Barnes S, Godwin H, McCullough K, Shaheen G, Buck L, Noel M, Warren S, Weber S, Parker I, Gillespie B, Nelson C, Frost J, Amrhein E, Moreland A, Hayes J, Peggram J, Aisenberg M, Riordan J, Zasa E, Cummings K, Scott T, Pinto A, Mokashi K, McAssey E, Helden P, Hammond L, Dinning S, Rahman S, Ray C, Dimicri S, Guppy H, Nielsen C, Vogel C, Ariza L, Morales Y, Chang R, Gabbay L, Ambrocio L, Manley R, Nemery W, Charlton P, Smith L, Kerr B, Steindel-Kopp M, Alamaguer D, Liljenquist G, Browning T, Coughenour M, Sulk E, Tsalikan M, Tansey J, Cabbage N. Identical and Nonidentical Twins: Risk and Factors Involved in Development of Islet Autoimmunity and Type 1 Diabetes. Diabetes Care 2019; 42:192-199. [PMID: 30061316 PMCID: PMC6341285 DOI: 10.2337/dc18-0288] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2018] [Accepted: 06/28/2018] [Indexed: 02/03/2023]
Abstract
OBJECTIVE There are variable reports of risk of concordance for progression to islet autoantibodies and type 1 diabetes in identical twins after one twin is diagnosed. We examined development of positive autoantibodies and type 1 diabetes and the effects of genetic factors and common environment on autoantibody positivity in identical twins, nonidentical twins, and full siblings. RESEARCH DESIGN AND METHODS Subjects from the TrialNet Pathway to Prevention Study (N = 48,026) were screened from 2004 to 2015 for islet autoantibodies (GAD antibody [GADA], insulinoma-associated antigen 2 [IA-2A], and autoantibodies against insulin [IAA]). Of these subjects, 17,226 (157 identical twins, 283 nonidentical twins, and 16,786 full siblings) were followed for autoantibody positivity or type 1 diabetes for a median of 2.1 years. RESULTS At screening, identical twins were more likely to have positive GADA, IA-2A, and IAA than nonidentical twins or full siblings (all P < 0.0001). Younger age, male sex, and genetic factors were significant factors for expression of IA-2A, IAA, one or more positive autoantibodies, and two or more positive autoantibodies (all P ≤ 0.03). Initially autoantibody-positive identical twins had a 69% risk of diabetes by 3 years compared with 1.5% for initially autoantibody-negative identical twins. In nonidentical twins, type 1 diabetes risk by 3 years was 72% for initially multiple autoantibody-positive, 13% for single autoantibody-positive, and 0% for initially autoantibody-negative nonidentical twins. Full siblings had a 3-year type 1 diabetes risk of 47% for multiple autoantibody-positive, 12% for single autoantibody-positive, and 0.5% for initially autoantibody-negative subjects. CONCLUSIONS Risk of type 1 diabetes at 3 years is high for initially multiple and single autoantibody-positive identical twins and multiple autoantibody-positive nonidentical twins. Genetic predisposition, age, and male sex are significant risk factors for development of positive autoantibodies in twins.
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Affiliation(s)
- Taylor M. Triolo
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - Alexandra Fouts
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - Laura Pyle
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Liping Yu
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - Peter A. Gottlieb
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - Andrea K. Steck
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO
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| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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Göransson G, Norrman J, Larson M. Contaminated landslide runout deposits in rivers - Method for estimating long-term ecological risks. Sci Total Environ 2018; 642:553-566. [PMID: 29909322 DOI: 10.1016/j.scitotenv.2018.06.078] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Revised: 06/07/2018] [Accepted: 06/07/2018] [Indexed: 06/08/2023]
Abstract
The potential catastrophic event of a landslide bringing contaminants to surface waters has been highlighted in public media, but there are still few scientific studies analyzing the risk of landslides with contaminated soil. The aim of this study is to present a method to estimate the risk of potential long-term ecological effects on water bodies due to contaminated soil released into a river through a landslide. The study constitutes further development of previous work focusing on the instantaneous (short-term) release of contaminants and associated effects. Risk is here defined as the probability of surface water failing to comply with environmental quality standards (EQS). The transport model formulation is kept simple enough to allow for a probabilistic analysis as a first assessment of the impact on the river water quality from a landslide runout deposit containing contaminated soil. The model is applied at a contaminated site located adjacent to the Göta Älv River that discharges into the Gothenburg estuary, in southwest Sweden. The results from the case study show that a contaminated runout deposit will likely cause contamination levels above EQSs in the near area for a long time and that it will take several years for the deposit to erode, with the greatest erosion at the beginning when water velocities are their highest above the deposit. A contaminated landslide runout deposit will thus act as a source of contamination to the downstream water system until all the contaminated deposit has been eroded away and the contaminants have been transported from the deposit to the river, and further to the river mouth - diluted but not necessarily negligible. Therefore, it is important to prevent landslides of contaminated soil or waste, and if such events were to occur, to remove the contaminated runout deposit as soon as possible.
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Affiliation(s)
- G Göransson
- Climate Adaptation, Swedish Geotechnical Institute, SE-412 96 Gothenburg, Sweden.
| | - J Norrman
- Architecture and Civil Engineering, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden.
| | - M Larson
- Water Resources Engineering, Lund University, SE-221 00 Lund, Sweden.
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Sweeten G, Larson M, Piquero AR. Predictors of emotional and physical dating violence in a sample of serious juvenile offenders. Crim Behav Ment Health 2016; 26:263-277. [PMID: 27709748 DOI: 10.1002/cbm.2015] [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] [Subscribe] [Scholar Register] [Received: 07/27/2016] [Accepted: 08/02/2016] [Indexed: 06/06/2023]
Abstract
AIM We estimate group-based dating violence trajectories and identify the adolescent risk factors that explain membership in each trajectory group. METHOD Using longitudinal data from the Pathways to Desistance Study, which follows a sample of 1354 serious juvenile offenders from Philadelphia, Pennsylvania and Phoenix, Arizona between mid-adolescence and early adulthood, we estimate group-based trajectory models of both emotional dating violence and physical dating violence over a span of five years in young adulthood. We then estimate multinomial logistic regression models to identify theoretically motivated risk factors that predict membership in these groups. RESULTS We identified three developmental patterns of emotional dating violence: none (33%), low-level (59%) and high-level decreasing (8%). The best-fitting model for physical dating violence also had three groups: none (73%), low-level (24%) and high-level (3%). Race/ethnicity, family and psychosocial variables were among the strongest predictors of both emotional and physical dating violence. In addition, delinquency history variables predicted emotional dating violence and relationship variables predicted physical dating violence. CONCLUSIONS Dating violence is quite prevalent in young adulthood among serious juvenile offenders. Numerous predictors distinguish between chronic dating violence perpetrators and other groups. These may suggest points of intervention for reducing future violence. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Gary Sweeten
- School of Criminology and Criminal Justice, Arizona State University, Phoenix, USA.
| | - Matthew Larson
- Department of Criminal Justice, Wayne State University, Detroit, USA
| | - Alex R Piquero
- Program in Criminology, University of Texas at Dallas, Richardson, USA
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19
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Vaughn MG, Salas-Wright CP, Cooper-Sadlo S, Maynard BR, Larson M. Are immigrants more likely than native-born Americans to perpetrate intimate partner violence? J Interpers Violence 2015; 30:1888-1904. [PMID: 25217226 DOI: 10.1177/0886260514549053] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Despite an emerging body of research indicating that immigrants are less likely than native-born Americans to engage in crime and antisocial behavior, less attention has focused specifically on intimate partner violence (IPV) perpetration among immigrant populations. We address this gap by using data from Wave II of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) and compare immigrants from Asia, Africa, Europe, and Latin America to native-born Americans with respect to multiple forms of IPV. After controlling for an extensive array of confounds, results indicate that in the aggregate, immigrants are significantly more likely to perpetrate IPV. However, examination of major world regions indicates these results are driven by Latin American immigrants. Immigrants from Asia, Africa, and Europe report a lower prevalence of IPV perpetration than native-born Americans. This study extends prior research on the immigrant paradox and suggests that future studies take into account regional heterogeneity when examining IPV and other forms of violence in immigrant populations.
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20
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Larson M, Sweeten G, Piquero AR. With or Without You? Contextualizing the Impact of Romantic Relationship Breakup on Crime Among Serious Adolescent Offenders. J Youth Adolesc 2015; 45:54-72. [PMID: 26092231 DOI: 10.1007/s10964-015-0318-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [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: 04/06/2015] [Accepted: 06/06/2015] [Indexed: 11/27/2022]
Abstract
The decline and delay of marriage has prolonged adolescence and the transition to adulthood, and consequently fostered greater romantic relationship fluidity during a stage of the life course that is pivotal for both development and offending. Yet, despite a growing literature of the consequences of romantic relationships breakup, little is known about its connection with crime, especially among youth enmeshed in the criminal justice system. This article addresses this gap by examining the effects of relationship breakup on crime among justice-involved youth-a key policy-relevant group. We refer to data from the Pathways to Desistance Study, a longitudinal study of 1354 (14% female) adjudicated youth from the juvenile and adult court systems in Phoenix and Philadelphia, to assess the nature and complexity of this association. In general, our results support prior evidence of breakup's criminogenic influence. Specifically, they suggest that relationship breakup's effect on crime is particularly acute among this at-risk sample, contingent upon post-breakup relationship transitions, and more pronounced for relationships that involve cohabitation. Our results also extend prior work by demonstrating that breakup is attenuated by changes in psychosocial characteristics and peer associations/exposure. We close with a discussion of our findings, their policy implications, and what they mean for research on relationships and crime among serious adolescent offenders moving forward.
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Affiliation(s)
- Matthew Larson
- Department of Criminal Justice, Wayne State University, 3291 Faculty/Administration Building, Detroit, MI, 48202, USA.
| | - Gary Sweeten
- School of Criminology and Criminal Justice, Arizona State University, 411 N. Central Avenue, MC 4420, Phoenix, AZ, 85004, USA.
| | - Alex R Piquero
- Ashbel Smith Professor of Criminology, Program in Criminology, EPPS, University of Texas at Dallas, 800 W. Campbell Road, GR31, Richardson, TX, 75080, USA
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21
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Tintle NL, Pottala JV, Lacey S, Ramachandran V, Westra J, Rogers A, Clark J, Olthoff B, Larson M, Harris W, Shearer GC. A genome-wide association study of saturated, mono- and polyunsaturated red blood cell fatty acids in the Framingham Heart Offspring Study. Prostaglandins Leukot Essent Fatty Acids 2015; 94:65-72. [PMID: 25500335 PMCID: PMC4339483 DOI: 10.1016/j.plefa.2014.11.007] [Citation(s) in RCA: 56] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2014] [Revised: 11/14/2014] [Accepted: 11/17/2014] [Indexed: 01/06/2023]
Abstract
Most genome-wide association studies have explored relationships between genetic variants and plasma phospholipid fatty acid proportions, but few have examined apparent genetic influences on the membrane fatty acid profile of red blood cells (RBC). Using RBC fatty acid data from the Framingham Offspring Study, we analyzed over 2.5 million single nucleotide polymorphisms (SNPs) for association with 14 RBC fatty acids identifying 191 different SNPs associated with at least 1 fatty acid. Significant associations (p<1×10(-8)) were located within five distinct 1MB regions. Of particular interest were novel associations between (1) arachidonic acid and PCOLCE2 (regulates apoA-I maturation and modulates apoA-I levels), and (2) oleic and linoleic acid and LPCAT3 (mediates the transfer of fatty acids between glycerolipids). We also replicated previously identified strong associations between SNPs in the FADS (chromosome 11) and ELOVL (chromosome 6) regions. Multiple SNPs explained 8-14% of the variation in 3 high abundance (>11%) fatty acids, but only 1-3% in 4 low abundance (<3%) fatty acids, with the notable exception of dihomo-gamma linolenic acid with 53% of variance explained by SNPs. Further studies are needed to determine the extent to which variations in these genes influence tissue fatty acid content and pathways modulated by fatty acids.
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Affiliation(s)
- N L Tintle
- Department of Mathematics, Statistics and Computer Science, Dordt College, Sioux Center, IA 51250, USA.
| | - J V Pottala
- Health Diagnostic Laboratory, Richmond, VA, USA; Department of Internal Medicine, Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, USA
| | - S Lacey
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Ave., Boston, MA, USA
| | - V Ramachandran
- Framingham Heart Study, 73 Mt. Wayte Ave., Framingham, MA 01702, USA; Boston University School of Medicine, 72 E. Concord St., Boston, MA 02118, USA
| | - J Westra
- Department of Mathematics, Statistics and Computer Science, Dordt College, Sioux Center, IA 51250, USA
| | - A Rogers
- Department of Mathematics, Statistics and Computer Science, Dordt College, Sioux Center, IA 51250, USA
| | - J Clark
- Department of Mathematics, Statistics and Computer Science, Dordt College, Sioux Center, IA 51250, USA
| | - B Olthoff
- Department of Mathematics, Statistics and Computer Science, Dordt College, Sioux Center, IA 51250, USA
| | - M Larson
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Ave., Boston, MA, USA; Boston University School of Medicine, 72 E. Concord St., Boston, MA 02118, USA; Department of Mathematics and Statistics, Boston University, 111 Cummington St., Boston, MA, USA
| | - W Harris
- Health Diagnostic Laboratory, Richmond, VA, USA; Department of Internal Medicine, Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, USA; OmegaQuant, Sioux Falls, SD, USA
| | - G C Shearer
- Department of Nutritional Sciences, Pennsylvania State University, University Park, PA, USA
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22
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Vaughn MG, Salas-Wright CP, DeLisi M, Larson M. Deliberate self-harm and the nexus of violence, victimization, and mental health problems in the United States. Psychiatry Res 2015; 225:588-95. [PMID: 25500323 DOI: 10.1016/j.psychres.2014.11.041] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [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] [Received: 02/07/2014] [Revised: 11/04/2014] [Accepted: 11/17/2014] [Indexed: 10/24/2022]
Abstract
Deliberate self-harm (DSH) is associated with diverse psychiatric diagnoses and broad psychopathology but less is known about its association with other forms of interpersonal violence and crime. Using the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), the current study examined linkages between not only DSH and mental health and substance abuse comorbidity, but also childhood abuse, lifetime victimization, and a variety of violent behaviors. We identified a prevalence of 2.91% for DSH and found that DSH is associated with generalized and severe psychopathology, wide-ranging substance abuse, and adverse childhood experiences. Contrary to other studies, we found significant racial and ethnic differences in DSH. African-American, Latinos, and Asians, were substantially less likely than Whites to report DSH. Our hypothesis that DSH would be associated with a variety of violent behaviors including robbery, intimate partner violence, forced sex, cruelty to animals, and use of a weapon was supported even after adjusting for an array of covariates. We extend previous research on DSH by examining its prevalence in one the largest comorbidity surveys ever conducted and show that DSH is associated with multiple forms of violent behavior toward others, including animals.
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Affiliation(s)
- Michael G Vaughn
- School of Social Work, College for Public Health and Social Justice, Saint Louis University, Tegeler Hall, 3550 Lindell Boulevard, St. Louis, MO 63103, United States.
| | | | - Matt DeLisi
- Criminal Justice Studies, Iowa State University, Ames, IA, United States
| | - Matthew Larson
- Department of Criminal Justice, Wayne State University, Detroit, MI, United States
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23
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Yang Y, Winger RC, Lee PW, Nuro-Gyina PK, Minc A, Larson M, Liu Y, Pei W, Rieser E, Racke MK, Lovett-Racke AE. Impact of suppressing retinoic acid-related orphan receptor gamma t (ROR)γt in ameliorating central nervous system autoimmunity. Clin Exp Immunol 2015; 179:108-18. [PMID: 25142403 DOI: 10.1111/cei.12441] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/15/2014] [Indexed: 12/15/2022] Open
Abstract
Multiple sclerosis (MS) is an immune-mediated chronic central nervous system (CNS) disease affecting more than 400 000 people in the United States. Myelin-reactive CD4 T cells play critical roles in the formation of acute inflammatory lesions and disease progression in MS and experimental autoimmune encephalomyelitis (EAE), a well-defined mouse model for MS. Current MS therapies are only partially effective, making it necessary to develop more effective therapies that specifically target pathogenic myelin-specific CD4 T cells for MS treatment. While suppressing T-bet, the key transcription factor in T helper type 1 (Th1) cells, has been demonstrated to be beneficial in prevention and treatment of EAE, the therapeutic potential of retinoic acid-related orphan receptor gamma t (ROR)γt, the key transcription factor for Th17 cells, has not been well-characterized. In this study, we characterized the correlation between RORγt expression and other factors affecting T cell encephalitogenicity and evaluated the therapeutic potential of targeting RORγt by siRNA inhibition of RORγt. Our data showed that RORγt expression correlates with interleukin (IL)-17 production, but not with the encephalitogenicity of myelin-specific CD4 T cells. IL-23, a cytokine that enhances encephalitogenicity, does not enhance RORγt expression significantly. Additionally, granulocyte-macrophage colony-stimulating factor (GM-CSF) levels, which correlate with the encephalitogenicity of different myelin-specific CD4 T cell populations, do not correlate with RORγt. More importantly, inhibiting RORγt expression in myelin-specific CD4 T cells with an siRNA does not reduce disease severity significantly in adoptively transferred EAE. Thus, RORγt is unlikely to be a more effective therapeutic target for ameliorating pathogenicity of encephalitogenic CD4 T cells.
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Affiliation(s)
- Y Yang
- Department of Neurology, The Ohio State University Wexner Medical Center, Columbus, OH, USA
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24
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Lee JH, Isayeva T, Larson M, Chanda D, Chesnokov I, Ponnazhagan S. Abstract 612: Endostatin is a novel inhibitor of androgen receptor function in prostate cancer. Cancer Res 2014. [DOI: 10.1158/1538-7445.am2014-612] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [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
Abnormalities in androgen-androgen receptor (AR) axis have long been recognized for their roles in promoting prostate tumor growth and metastasis. Conventional therapies targeting androgen ablation show transient tumor regression, however, when the tumor recurs during castration-refractory metastatic stage, the current treatment options are very limited. Although the precise mechanism by which prostate cancer (PCa) cells circumvent the androgen deprivation is unclear, recurring tumors have been shown to retain AR activity and upregulation of AR-target gene expression such as prostate specific antigen (PSA), suggesting that targeting AR remains a key component of developing novel therapeutic strategies. Here, we show a profound effect of endostatin, an endogenous angiogenesis inhibitor, on proliferation and invasion of AR-positive PCa cells by targeting AR function. The present study identified that intracellular trafficking of endostatin and direct interaction with AR disrupts AR nuclear translocation and the consequent transcriptional activation of PSA gene. In addition, our structural modeling and site-directed mutagenesis studies suggest that the binding mechanism may include the interaction of bulky side chains (F31 and F34) present in endostatin with the co-activator binding interface (AF-2) in AR ligand-binding domain (LBD). Regarding drug resistance to the second-generation androgen antagonists in patients with metastatic PCa, recent studies revealed that a missense mutation in AR LBD (F876L) and the consequential antagonist-to-agonist switch confers continued AR activity. In this context, our study suggests that endostatin can be recognized as an endogenous AR inhibitor where its molecular interaction with AR may prevent from agonistic switch of AR function by fully masking the AF-2 subdomain. Overall, the current finding provides new insights into endostatin whose anti-cancer activity is not only limited to inhibiting angiogenesis, but can also be expanded to suppressing AR-mediated PCa progression by disrupting AR transactivation.
Citation Format: Joo Hyoung Lee, Tatyana Isayeva, Matthew Larson, Diptiman Chanda, Igor Chesnokov, Selvarangan Ponnazhagan. Endostatin is a novel inhibitor of androgen receptor function in prostate cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 612. doi:10.1158/1538-7445.AM2014-612
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Purushotham S, Larson M, Banas J, Deivanayagam C. Structure/Function studies on Glucan Binding Protein C of Streptococcus mutans. Acta Crystallogr A Found Adv 2014. [DOI: 10.1107/s2053273314083600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Streptococcus mutans is a known etiological agent in dental caries. In the past several years, we have taken a concerted effort toward understanding the adhesion mechanisms adopted by the surface proteins S. mutans. The Glucan Binding Protein C (GBPC) is a LPXTG anchored surface protein on S. mutans that has been widely implicated to play a significant role in biofilm formation. GBPC displays limited homology to the V-region of Antigen I/II (AgI/II), another surface protein of S. mutans (1,2). We undertook to crystallize and resolve the structure of GBPC. Recombinant GbpC111-552 (residues encompassing 111-552) was cloned into a pET23d vector, and thereafter expressed in E.coli BL21(DE3). GbpC111-552 purified initially using affinity chromatography (his-tag), followed by anion exchange (MonoQ) and finally polished with size exclusion (Superdex 75). GbpC111-552 was crystallized using the vapor diffusion method by scanning various commercial crystallization kits on a 96 well plate format through the Art Robbins Gryphon robot. Large crystals were obtained from a refined droplet condition that contained 1 μl of protein (43.3 mg/ml) mixed with 1 μl of reservoir made of 100 mM Bis-Tris pH 6.5 and 25% (w/v) PEG3350. The crystal structure could not be resolved by molecular replacement. Therefore crystals were soaked in Sodium Iodide (NaI) and thereafter flash frozen with 9% glycerol as crytoprotectant. MAD data sets were collected and the crystal structure was resolved. We will present the crystal structure, and how based on its structural homology we discovered similar functionalities among the surface proteins of S. mutans. The structural and functional studies of these surface proteins we hope would allow the identification of the adherence motifs, which would aid in development of inhibitors. The development of such anti-adhesive inhibitors would aid in disease preventative therapies.
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Casas-Agustench P, Sloan S, Jacques P, Willinger C, Yin X, Courchesne P, Ramachandran V, Robin S, Larson M, Chen B, Mendelson M, Levy D, Ordovás J. Connections between dark fish intake, lipidomics and plasma triglycerides in the framingham heart study. Atherosclerosis 2014. [DOI: 10.1016/j.atherosclerosis.2014.05.542] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Singal A, Hamel A, Larson M, Kelner H, Almekkawy M, John R, Eckman P. Peripheral Pulse Wave Analysis Technique to Detect Aortic Valve State in Continuous-flow LVADs. J Heart Lung Transplant 2014. [DOI: 10.1016/j.healun.2014.01.235] [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] Open
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Canales C, Larson M, Grauer D, Sheats R, Stevens C, Ko CC. A novel biomechanical model assessing continuous orthodontic archwire activation. Am J Orthod Dentofacial Orthop 2013; 143:281-90. [PMID: 23374936 DOI: 10.1016/j.ajodo.2012.06.019] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2012] [Revised: 06/01/2012] [Accepted: 06/01/2012] [Indexed: 10/27/2022]
Abstract
INTRODUCTION The biomechanics of a continuous archwire inserted into multiple orthodontic brackets is poorly understood. The purpose of this research was to apply the birth-death technique to simulate the insertion of an orthodontic wire and the consequent transfer of forces to the dentition in an anatomically accurate model. METHODS A digital model containing the maxillary dentition, periodontal ligament, and surrounding bone was constructed from computerized tomography data. Virtual brackets were placed on 4 teeth (central and lateral incisors, canine, and first premolar), and a steel archwire (0.019 × 0.025 in) with a 0.5-mm step bend to intrude the lateral incisor was virtually inserted into the bracket slots. Forces applied to the dentition and surrounding structures were simulated by using the birth-death technique. RESULTS The goal of simulating a complete bracket-wire system on accurate anatomy including multiple teeth was achieved. Orthodontic forces delivered by the wire-bracket interaction were 19.1 N on the central incisor, 21.9 N on the lateral incisor, and 19.9 N on the canine. Loading the model with equivalent point forces showed a different stress distribution in the periodontal ligament. CONCLUSIONS The birth-death technique proved to be a useful biomechanical simulation method for placement of a continuous archwire in orthodontic brackets. The ability to view the stress distribution with proper anatomy and appliances advances our understanding of orthodontic biomechanics.
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Affiliation(s)
- Christopher Canales
- Department of Orthodontics, School of Dentistry, University of North Carolina, Chapel Hill, NC 27599, USA
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Wiggman K, Larson M, Larson O, Semb G, Brattstrom V. The influence of the initial width of the cleft in patients with unilateral cleft lip and palate related to final treatment outcome in the maxilla at 17 years of age. Eur J Orthod 2012; 35:335-40. [DOI: 10.1093/ejo/cjr144] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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McDowell ET, Kapteyn J, Schmidt A, Li C, Kang JH, Descour A, Shi F, Larson M, Schilmiller A, An L, Jones AD, Pichersky E, Soderlund CA, Gang DR. Comparative functional genomic analysis of Solanum glandular trichome types. Plant Physiol 2011; 155:524-39. [PMID: 21098679 PMCID: PMC3075747 DOI: 10.1104/pp.110.167114] [Citation(s) in RCA: 116] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2010] [Accepted: 11/18/2010] [Indexed: 05/19/2023]
Abstract
Glandular trichomes play important roles in protecting plants from biotic attack by producing defensive compounds. We investigated the metabolic profiles and transcriptomes to characterize the differences between different glandular trichome types in several domesticated and wild Solanum species: Solanum lycopersicum (glandular trichome types 1, 6, and 7), Solanum habrochaites (types 1, 4, and 6), Solanum pennellii (types 4 and 6), Solanum arcanum (type 6), and Solanum pimpinellifolium (type 6). Substantial chemical differences in and between Solanum species and glandular trichome types are likely determined by the regulation of metabolism at several levels. Comparison of S. habrochaites type 1 and 4 glandular trichomes revealed few differences in chemical content or transcript abundance, leading to the conclusion that these two glandular trichome types are the same and differ perhaps only in stalk length. The observation that all of the other species examined here contain either type 1 or 4 trichomes (not both) supports the conclusion that these two trichome types are the same. Most differences in metabolites between type 1 and 4 glands on the one hand and type 6 glands on the other hand are quantitative but not qualitative. Several glandular trichome types express genes associated with photosynthesis and carbon fixation, indicating that some carbon destined for specialized metabolism is likely fixed within the trichome secretory cells. Finally, Solanum type 7 glandular trichomes do not appear to be involved in the biosynthesis and storage of specialized metabolites and thus likely serve another unknown function, perhaps as the site of the synthesis of protease inhibitors.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | - David R. Gang
- Bio5 Institute (E.T.M., J.K., A.D., C.A.S., D.R.G.) and Department of Agricultural and Biosystems Engineering (L.A.), University of Arizona, Tucson, Arizona 85721; Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, Michigan 48109–1048 (A.S., E.P.); Department of Chemistry (C.L., F.S., A.D.J.), Department of Energy-Plant Research Laboratory (J.-H.K.), and Department of Biochemistry and Molecular Biology (M.L., A.S., A.D.J.), Michigan State University, East Lansing, Michigan 48824–1319; Institute of Biological Chemistry, Washington State University, Pullman, Washington 99164–6340 (D.R.G.)
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Schilmiller AL, Miner DP, Larson M, McDowell E, Gang DR, Wilkerson C, Last RL. Studies of a biochemical factory: tomato trichome deep expressed sequence tag sequencing and proteomics. Plant Physiol 2010; 153:1212-23. [PMID: 20431087 PMCID: PMC2899918 DOI: 10.1104/pp.110.157214] [Citation(s) in RCA: 65] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2010] [Accepted: 04/27/2010] [Indexed: 05/18/2023]
Abstract
Shotgun proteomics analysis allows hundreds of proteins to be identified and quantified from a single sample at relatively low cost. Extensive DNA sequence information is a prerequisite for shotgun proteomics, and it is ideal to have sequence for the organism being studied rather than from related species or accessions. While this requirement has limited the set of organisms that are candidates for this approach, next generation sequencing technologies make it feasible to obtain deep DNA sequence coverage from any organism. As part of our studies of specialized (secondary) metabolism in tomato (Solanum lycopersicum) trichomes, 454 sequencing of cDNA was combined with shotgun proteomics analyses to obtain in-depth profiles of genes and proteins expressed in leaf and stem glandular trichomes of 3-week-old plants. The expressed sequence tag and proteomics data sets combined with metabolite analysis led to the discovery and characterization of a sesquiterpene synthase that produces beta-caryophyllene and alpha-humulene from E,E-farnesyl diphosphate in trichomes of leaf but not of stem. This analysis demonstrates the utility of combining high-throughput cDNA sequencing with proteomics experiments in a target tissue. These data can be used for dissection of other biochemical processes in these specialized epidermal cells.
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Affiliation(s)
- Anthony L Schilmiller
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824-1319, USA.
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Larson M, Larson M, Li Z, Larson M, Li Z, Hall CL, Jensen E, McAllister DM, Kalyanaraman B, Zhao M. Physiological fluctuation of (99m)Tc-sestamibi uptake in normal mammary glands: a systematic investigation in female rats. Acta Radiol 2009; 50:975-8. [PMID: 19863405 DOI: 10.3109/02841850903134127] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [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]
Abstract
BACKGROUND Scintimammography is an imaging tool for the diagnosis and management of primary breast tumors. There remains a significant knowledge gap regarding the physiological fluctuations in the basal level of (99m)Tc-sestamibi uptake in normal mammary tissues with respect to the female reproductive cycle. PURPOSE To systematically characterize (99m)Tc-sestamibi uptake in normal mammary tissues in female Sprague Dawley (SD) rats in different estrous phases. MATERIAL AND METHODS The exact phase of the reproductive cycle was determined in 18 female SD rats. Each rat was sacrificed at 20 min after (99m)Tc-sestamibi injection (14.8 MBq/kg). The mammary glands were dissected, and the radioactivity uptake was measured by gamma counting. RESULTS Tc-99m-sestamibi uptake oscillates by about twofold and reaches a maximum at the proestrous phase of the rat reproductive cycle. CONCLUSION Tc-99m-sestamibi uptake fluctuates significantly in normal mammary tissues in synchrony with the female reproductive cycle, and peaks in the proestrous phase in rats, which is equivalent to the early to mid-follicular phase in the human menstrual cycle. This finding will likely benefit the detection of breast lesions that may otherwise be obscured by fluctuating background signals in surrounding normal breast tissues.
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Affiliation(s)
- M. Larson
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - M. Larson
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
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Beste LA, Straits-Troster K, Zickmund S, Larson M, Chapko M, Dominitz JA. Specialty care and education associated with greater disease-specific knowledge but not satisfaction with care for chronic hepatitis C. Aliment Pharmacol Ther 2009; 30:275-82. [PMID: 19438425 DOI: 10.1111/j.1365-2036.2009.04036.x] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND Little is known about differences among hepatitis C virus (HCV) patients managed by generalists vs. specialists with respect to patient-centred outcomes, such as disease-specific knowledge, health-related quality of life (HRQoL) and satisfaction with care. AIM To examine selected patient-centred outcomes of HCV-related care provided in primary care, specialty care or both. METHODS A total of 629 chronic HCV patients completed a survey including an HCV knowledge assessment and validated instruments for satisfaction and HRQoL. Multivariable linear regression was used to compare outcomes between groups. RESULTS Adjusted total HCV knowledge score was lower among patients who did not attend specialty care (P < 0.01). Primary care and specialty patients did not differ in adjusted general HRQoL or satisfaction. Sixty percent of specialty patients underwent formal HCV education, which was associated with 5% higher knowledge score (P = 0.01). General HRQoL and patient satisfaction did not differ between primary care and specialty groups. Disease-specific knowledge and care satisfaction were independent of mental illness, substance abuse, socio-economic variables, history of antiviral treatment, formal HCV education and duration of time between last visit and survey completion. CONCLUSIONS Primary care patients with chronic HCV have lower adjusted disease-specific knowledge than specialty patients, but no difference in general HRQoL or patient satisfaction.
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Affiliation(s)
- L A Beste
- Health Services Research and Development Center of Excellence, VA Puget Sound Healthcare System, Seattle, WA 98101, USA.
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Schilmiller AL, Schauvinhold I, Larson M, Xu R, Charbonneau AL, Schmidt A, Wilkerson C, Last RL, Pichersky E. Monoterpenes in the glandular trichomes of tomato are synthesized from a neryl diphosphate precursor rather than geranyl diphosphate. Proc Natl Acad Sci U S A 2009. [PMID: 19487664 DOI: 10.1073/pnas.0904113106\r0904113106] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/07/2023] Open
Abstract
We identified a cis-prenyltransferase gene, neryl diphosphate synthase 1 (NDPS1), that is expressed in cultivated tomato (Solanum lycopersicum) cultivar M82 type VI glandular trichomes and encodes an enzyme that catalyzes the formation of neryl diphosphate from isopentenyl diphosphate and dimethylallyl diphosphate. mRNA for a terpene synthase gene, phellandrene synthase 1 (PHS1), was also identified in these glands. It encodes an enzyme that uses neryl diphosphate to produce beta-phellandrene as the major product as well as a variety of other monoterpenes. The profile of monoterpenes produced by PHS1 is identical with the monoterpenes found in type VI glands. PHS1 and NDPS1 map to chromosome 8, and the presence of a segment of chromosome 8 derived from Solanum pennellii LA0716 causes conversion from the M82 gland monoterpene pattern to that characteristic of LA0716 plants. The data indicate that, contrary to the textbook view of geranyl diphosphate as the "universal" substrate of monoterpene synthases, in tomato glands neryl diphosphate serves as a precursor for the synthesis of monoterpenes.
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Affiliation(s)
- Anthony L Schilmiller
- Department of Biochemistry and Molecular Biology, Research Technology Support Facility, Michigan State University, East Lansing, MI 48824-1319, USA
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Braun E, Katz D, Venugopal P, Larson M, Shammo J, Fung H, Gregory S. Safety analysis of radioimmunotherapy (RIT) in patients with relapsed or refractory low grade, follicular or transformed non-Hodgkin's lymphoma and mantle cell lymphoma based on age at time of therapy. J Clin Oncol 2009. [DOI: 10.1200/jco.2009.27.15_suppl.e19529] [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
e19529 Background: Radioimmunotherapy is a therapeutic option for relapsed or refractory indolent, follicular and transformed non Hodgkin's lymphoma and mantle cell lymphoma. Although prolongued myelotoxicity has been described with use of iodine I 131 tositumomab (TOSI) and yttrium 90 ibritumomab tiuxetan (IBRI), analysis of toxicity according to patients’ age at therapy still lacks. Methods: Utilizing the Rush University Medical Center database 61 subjects who received RIT between November/2003 and June/2008, either with TOSI or IBRI were divided in 2 groups according to age at time of therapy. Group 1 included patients between 33 and 60 (51.8±6.5) years of age (N=29) and group 2 included patients 61 years old or older (70.1±7.8) (N=32). Parameters compared between groups were: Time to nadir of lowest absolute neutrophil count (ANC), time to recovery ANC above 1000/mcL, time to nadir of lowest hemoglobin levels, time to recovery to hemoglobin levels above 8g/dL, time to lowest platelet count and time to recovery to platelet count above 100,000/mcL. Incidence o myelodysplastic syndrome (MDS) was also compared between groups. Groups characteristics such as sex, type of RIT, presence of disease in bone marrow, FLIPI/IPI and use of G-CSF were noted. Results: There was no significant statistical difference between groups in time (number of days) to achieve nadir of ANC (group 1 85.3±208; group 2 50.3±19.9), nadir of hemoglobin levels (group 1 106±60.6; group 2 84±57.0) and time to nadir of platelet level (group 1 53.5±70.7; group 2 41.8±9.6). There was no statistical significant difference between groups in duration of cytopenias, except for time for platelet recovery which was significant longer in group 2 using the Pearson Correlation analysis. (p=0.008). (Days for platelets recovery to levels above 100,000/mcL group 1 29.4±27.7; group 2 108.8 ±207.3). One patient in group 1 and three patients on group 2 were diagnosed with MDS but were also treated with different chemotherapy regimens. Conclusions: RIT should be considered a safe therapeutic modality in patients with refractory or relapsed indolent, follicular, NHL, transformed and Mantle Cell lymphoma regardless of age. [Table: see text]
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Affiliation(s)
- E. Braun
- Rush University Medical Center, Chicago, IL
| | - D. Katz
- Rush University Medical Center, Chicago, IL
| | | | - M. Larson
- Rush University Medical Center, Chicago, IL
| | - J. Shammo
- Rush University Medical Center, Chicago, IL
| | - H. Fung
- Rush University Medical Center, Chicago, IL
| | - S. Gregory
- Rush University Medical Center, Chicago, IL
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Nathan S, Tuncer H, Maciejewski J, Venugopal P, Larson M, Shammo J, Gregory S, Fung H. Conditioning with Non-Targeted Busulfan and Fludarabine Followed by Allogeneic Stem Cell Transplantation: A Study of Engraftment Kinetics. Biol Blood Marrow Transplant 2009. [DOI: 10.1016/j.bbmt.2008.12.345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Larson M, Li Z, Hall CL, Jensen E, McAllister DM, Kalyanaraman B, Zhao M. Physiological Fluctuation of 99mTc-Sestamibi Uptake in Normal Mammary Glands: A Systematic Investigation in Female Rats. Acta Radiol 2009. [DOI: 10.1080/02841850903134127] [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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Saint Pierre C, Peterson C, Ross A, Ohm J, Verhoeven M, Larson M, Hoefer B. Winter wheat genotypes under different levels of nitrogen and water stress: Changes in grain protein composition. J Cereal Sci 2008. [DOI: 10.1016/j.jcs.2007.05.007] [Citation(s) in RCA: 52] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Corzillus M, Euler H, Larson M, Schroeder J, Liang M. Aktivitätsindizes bei systemischem Lupus erythematodes: Vergleich der Eignung für retrospektive und Verlaufsuntersuchungen. AKTUEL RHEUMATOL 2008. [DOI: 10.1055/s-2008-1047329] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [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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Skarda DE, Taylor JH, Chipman JG, Larson M, Baker JV, Schacker TW, Beilman GJ. Inguinal Lymph Node Biopsy in Patients Infected with the Human Immunodeficiency Virus Is Safe. Surg Infect (Larchmt) 2007; 8:173-8. [PMID: 17437362 DOI: 10.1089/sur.2006.020] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND AND PURPOSE The incidence of postoperative complications in human immunodeficiency virus (HIV)-infected patients remains controversial. Published data suggest that these patients are at higher risk for postoperative surgical site infections (SSIs) than are uninfected patients if the site is contaminated. To determine the incidence of postoperative SSI in HIV-infected patients undergoing aseptic surgery at uncontaminated sites, we performed a prospective case series analysis. We hypothesized that the rate of postoperative SSI would be low for this aseptic procedure, irrespective of CD4(+) lymphocyte counts. Additionally, we monitored the rates of other complications, namely, hematoma, dorsal vein thrombosis, epididymitis, lymphocele, and suture extrusion. METHODS From May 1, 2000, through January 31, 2006, we performed 137 sterile inguinal lymph node biopsies in 44 HIV-infected patients as part of a funded study evaluating the role of peripheral lymphatic tissue in the pathophysiology of HIV infection. Postoperatively, we followed all patients for a minimum of 30 days. RESULTS Postoperatively, we noted one instance each (0.7%) of infection, dorsal vein thrombosis with epididymitis (0.7%), and lymphocele and two cases each (1.4%) of hematoma and suture extrusion. The CD4(+) count at the time of biopsy did not correlate with postoperative complications. CONCLUSIONS Inguinal lymph node biopsy in HIV-infected patients is safe, irrespective of CD4(+) lymphocyte count.
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Affiliation(s)
- David E Skarda
- Department of Surgery, University of Minnesota, Minneapolis, MN 55455, USA
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Schacker TW, Brenchley JM, Beilman GJ, Reilly C, Pambuccian SE, Taylor J, Skarda D, Larson M, Douek DC, Haase AT. Lymphatic tissue fibrosis is associated with reduced numbers of naive CD4+ T cells in human immunodeficiency virus type 1 infection. Clin Vaccine Immunol 2006; 13:556-60. [PMID: 16682476 PMCID: PMC1459657 DOI: 10.1128/cvi.13.5.556-560.2006] [Citation(s) in RCA: 116] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
The organized structure of lymphatic tissues (LTs) constitutes a microenvironment referred to as a niche that plays a critical role in immune system homeostasis by promoting cellular interactions and providing access to cytokines and growth factors on which cells are dependent for survival, proliferation, and differentiation. In chronic human immunodeficiency virus type 1 (HIV-1) infection, immune activation and inflammation result in collagen deposition and disruption of this LT niche. We have previously shown that these fibrotic changes correlate with a reduction in the size of the total population of CD4+ T cells. We now show that this reduction is most substantial within the naïve CD4+ T-cell population and is in proportion to the extent of LT collagen deposition in HIV-1 infection. Thus, the previously documented depletion of naïve CD4+ T cells in LTs in HIV-1 infection may be a consequence not only of a decreased supply of thymic emigrants or chronic immune activation but also of the decreased ability of those cells to survive in a scarred LT niche. We speculate that LT collagen deposition might therefore limit repopulation of naïve CD4+ T cells with highly active antiretroviral therapy, and thus, additional treatments directed to limiting or reversing inflammatory damage to the LT niche could potentially improve immune reconstitution.
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Affiliation(s)
- Timothy W Schacker
- Department of Medicine/Infectious Diseases, University of Minnesota, MMC 250, 516 Delaware Street, Minneapolis, MN 55455, USA.
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Schacker TW, Reilly C, Beilman GJ, Taylor J, Skarda D, Krason D, Larson M, Haase AT. Amount of lymphatic tissue fibrosis in HIV infection predicts magnitude of HAART-associated change in peripheral CD4 cell count. AIDS 2005; 19:2169-71. [PMID: 16284469 DOI: 10.1097/01.aids.0000194801.51422.03] [Citation(s) in RCA: 95] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
The structure of lymphatic tissues is an important component of lymphatic tissue T-cell homeostasis. Collagen deposition in lymphatic tissues (common in HIV infection) disrupts the niche and limits the size of the resident CD4 cell population. In this report we show that a single measurement of lymphatic tissue collagen predicts the magnitude of recovery of the peripheral CD4 cell pool with HAART (P < 0.001). This suggests that collagen-targeted therapies might be of benefit.
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Affiliation(s)
- Timothy W Schacker
- Department of Medicine, University of Minnesota, Minneapolis, Minnesota, USA
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Maher D, Wu X, Schacker T, Larson M, Southern P. A model system of oral HIV exposure, using human palatine tonsil, reveals extensive binding of HIV infectivity, with limited progression to primary infection. J Infect Dis 2004; 190:1989-97. [PMID: 15529264 DOI: 10.1086/425423] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2004] [Accepted: 05/17/2004] [Indexed: 11/03/2022] Open
Abstract
Oral exposure to human immunodeficiency virus (HIV) type 1 results in systemic infection, but many details surrounding virus transmission remain unresolved. We developed a mucosal model, using human palatine tonsil with intact external epithelium, to study events after oral exposure to HIV. When applied to the external epithelium, semen from an HIV-seropositive patient and cell-free virus both established HIV infection in individual tonsillar cells. However, clusters of infected tonsillar cells were detected where the epithelial surface was damaged. Investigation of the initial events in HIV transmission revealed extensive and stable binding of HIV virions and seminal cells to tonsil epithelium. In experiments modeling physiologically relevant events, the addition of seminal plasma resulted in enhanced virion binding to epithelial cells. These results indicate that, although extensive binding of HIV virions and seminal cells can be demonstrated at an exposed mucosal surface, there is only limited progression from binding to primary infection.
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Affiliation(s)
- Diane Maher
- Department of Microbiology, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN 55455, USA
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Brenchley JM, Schacker TW, Ruff LE, Price DA, Taylor JH, Beilman GJ, Nguyen PL, Khoruts A, Larson M, Haase AT, Douek DC. CD4+ T cell depletion during all stages of HIV disease occurs predominantly in the gastrointestinal tract. ACTA ACUST UNITED AC 2004; 200:749-59. [PMID: 15365096 PMCID: PMC2211962 DOI: 10.1084/jem.20040874] [Citation(s) in RCA: 1335] [Impact Index Per Article: 66.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The mechanisms underlying CD4+ T cell depletion in human immunodeficiency virus (HIV) infection are not well understood. Comparative studies of lymphoid tissues, where the vast majority of T cells reside, and peripheral blood can potentially illuminate the pathogenesis of HIV-associated disease. Here, we studied the effect of HIV infection on the activation and depletion of defined subsets of CD4+ and CD8+ T cells in the blood, gastrointestinal (GI) tract, and lymph node (LN). We also measured HIV-specific T cell frequencies in LNs and blood, and LN collagen deposition to define architectural changes associated with chronic inflammation. The major findings to emerge are the following: the GI tract has the most substantial CD4+ T cell depletion at all stages of HIV disease; this depletion occurs preferentially within CCR5+ CD4+ T cells; HIV-associated immune activation results in abnormal accumulation of effector-type T cells within LNs; HIV-specific T cells in LNs do not account for all effector T cells; and T cell activation in LNs is associated with abnormal collagen deposition. Taken together, these findings define the nature and extent of CD4+ T cell depletion in lymphoid tissue and point to mechanisms of profound depletion of specific T cell subsets related to elimination of CCR5+ CD4+ T cell targets and disruption of T cell homeostasis that accompanies chronic immune activation.
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Affiliation(s)
- Jason M Brenchley
- Human Immunology Section, Vaccine Research Center, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, 40 Convent Dr., Room 3509, Bethesda, MD 20892, USA
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Affiliation(s)
- C Schneider
- Department of Internal Medicine, Marshfield Clinic, Marshfield, Wisconsin 54449, USA
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Abstract
Distension of an isolated preparation of guinea pig ileum triggers the peristaltic reflex, a characteristic movement of the intestinal walls which generates luminal pressures and clearance of luminal contents. To determine how the reflex responds to properties of luminal contents, we compared the responses triggered by boluses of air, oil, and cellulose to boluses of Krebs' solution. We found that oil and cellulose increased pressures and contraction length and decreased outflow. Cellulose, but not oil, slowed the velocity with which the contraction propagated and increased the delay with which the end point (upstream edge) of the contraction started to propagate after the lead point (downstream edge). Air tended to produce short contraction segments and high velocity. We conclude that bolus properties such as viscosity determine the response that isolated intestinal segments generate to distension. Response patterns are reflected in contraction length, propagation velocity, and other visual parameters that define wall movements.
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Affiliation(s)
- M Larson
- Gastroenterology Research, VAMC Iowa City, and Department of Medicine, University of Iowa, Iowa City, Iowa, USA
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Schacker TW, Nguyen PL, Beilman GJ, Wolinsky S, Larson M, Reilly C, Haase AT. Collagen deposition in HIV-1 infected lymphatic tissues and T cell homeostasis. J Clin Invest 2002. [DOI: 10.1172/jci0216413] [Citation(s) in RCA: 174] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
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Schacker TW, Nguyen PL, Beilman GJ, Wolinsky S, Larson M, Reilly C, Haase AT. Collagen deposition in HIV-1 infected lymphatic tissues and T cell homeostasis. J Clin Invest 2002; 110:1133-9. [PMID: 12393849 PMCID: PMC150803 DOI: 10.1172/jci16413] [Citation(s) in RCA: 130] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
Lymphatic tissues (LTs) are structurally organized to promote interaction between antigens, chemokines, growth factors, and lymphocytes to generate an immunologic response and maintain normal-sized populations of CD4(+) and CD8(+) T cells. Inflammation and tissue remodeling that accompany local innate and adaptive immune responses to HIV-1 replication cause damage to the LT architecture. As a result, normal populations of CD4(+) and CD8(+) T cells cannot be supported and antigen-lymphocyte interactions are impaired. This conclusion is supported herein following LT sampling before and during anti-HIV therapy in persons with acute, chronic, and late-stage HIV-1 infection. Among seven individuals treated with anti-retroviral therapy (ART) and four individuals deferring therapy we found evidence of significant paracortical T cell zone damage associated with deposition of collagen, the extent of which was inversely correlated with both the size of the LT CD4(+) T cell population and the change in peripheral CD4(+) T cell count with anti-HIV therapy. The HIV-1-associated inflammatory changes and scarring in LT both limit the ability of the tissue to support and reestablish normal-sized populations of CD4(+) T cells and suggest a novel mechanism of T cell depletion that may explain the failure of ART to significantly increase CD4(+) T cell populations in some HIV-1-infected persons.
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Affiliation(s)
- Timothy W Schacker
- Department of Medicine/Infectious Diseases, University of Minnesota, MMC 250, 516 Delaware Street, Minneapolis, Minnesota 55455, USA.
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Mahvi DM, Shi FS, Yang NS, Weber S, Hank J, Albertini M, Schiller J, Schalch H, Larson M, Pharo L, Gan J, Heisey D, Warner T, Sondel PM. Immunization by particle-mediated transfer of the granulocyte-macrophage colony-stimulating factor gene into autologous tumor cells in melanoma or sarcoma patients: report of a phase I/IB study. Hum Gene Ther 2002; 13:1711-21. [PMID: 12396624 DOI: 10.1089/104303402760293556] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
The primary objective of this phase I study was to determine the safety of an autologous tumor vaccine given by intradermal injection of lethally irradiated granulocyte-macrophage colony-stimulating factor (GM-CSF) gene-transfected autologous melanoma and sarcoma cells. Secondary objectives included validation of the gene delivery technology (particle-mediated gene transfer), determining the host immune response to the tumor after vaccination, and monitoring patients for evidence of antitumor response. Sixteen patients were treated with either of two different doses of GM-CSF-treated tumor cells. One patient received treatment with both doses of tumor cells. No treatment-related local or systemic toxicity was noted in any patient. Patients administered 100% treated cells (i.e., with a preparation of tumor cells that had all been exposed to GM-CSF DNA transfection) had a more extensive lymphocytic infiltrate at the vaccine site than did patients given 10% treated cells (a preparation of tumor cells in which 10% had been exposed to GM-CSF transfection) or nontreated tumor. The generation of a systemic immune response to autologous tumor by a delayed-type hypersensitivity response to the intradermal placement of nontransfected tumor cells was noted in one patient. One patient had a transient partial response of metastatic tumor sites. The entire procedure, from tumor removal to vaccine placement, was accomplished in less than 6 hr in all patients. Four of 17 patient tumor preparations produced greater than 3.0 ng of GM-CSF per 10(6) cells per 24 hr in vitro. The one patient with greater than 30 ng of GM-CSF per 10(6) cells per 24 hr in vitro had positive DTH, a significant histologic inflammatory response, and clinically stable disease. This technique of gene transfer was safe and feasible, but resulted in clinically relevant levels of gene expression in only a minority of patients.
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Affiliation(s)
- D M Mahvi
- Department of Surgery, University of Wisconsin School of Medicine, Madison, WI 53792, USA.
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