Digital Commons Network^™

Risk Factors For Sars-Cov-2 Transmission In Close Contacts Of Adults At High Risk Of Infection Due To Occupation: Results From The Contact Tracing Strategy Of The Covida Epidemiological Surveillance Study In Bogotá, Colombia, In 2020-2021, Andrea Ramírez Varela, Sandra Contreras-Arrieta, Guillermo Tamayo-Cabeza, Leonardo Salas Zapata, Yuldor Caballero-Díaz, Luis Jorge Hernández Florez, Andrés Patiño Benavidez, Rachid Laajaj, Fernando De La Hoz, Giancarlo Buitrago Gutierrez, Silvia Restrepo, Eduardo Behrentz

Faculty, Staff and Student Publications

OBJECTIVES: To estimate the risk factors for SARS-CoV-2 transmission in close contacts of adults at high risk of infection due to occupation, participants of the CoVIDA study, in Bogotá D.C., Colombia.

SETTING: The CoVIDA study was the largest COVID-19 intensified sentinel epidemiological surveillance study in Colombia thus far, performing over 60 000 RT-PCR tests for SARS-CoV-2 infection. The study implemented a contact tracing strategy (via telephone call) to support traditional surveillance actions performed by the local health authority.

PARTICIPANTS: Close contacts of participants from the CoVIDA study.

PRIMARY AND SECONDARY OUTCOME MEASURES: SARS-CoV-2 testing results were obtained (RT-PCR with CoVIDA …

A Genome-Wide Association Study Of 2304 Extreme Longevity Cases Identifies Novel Longevity Variants, Harold Bae, Ping An, Mary Feitosa, Et Al.

2020-Current year OA Pubs

We performed a genome-wide association study (GWAS) of human extreme longevity (EL), defined as surviving past the 99th survival percentile, by aggregating data from four centenarian studies. The combined data included 2304 EL cases and 5879 controls. The analysis identified a locus in CDKN2B-AS1 (rs6475609,

Does Receiving A Sars-Cov-2 Antibody Test Result Change Covid-19 Protective Behaviors? Testing Risk Compensation In Undergraduate Students With A Randomized Controlled Trial, Christina Ludema, Molly S Rosenberg, Jonathan T Macy, Sina Kianersi, Maya Luetke, Chen Chen, Lilian Golzarri-Arroyo, Erin Ables, Kevin Maki, David B Allison

Children’s Nutrition Research Center Staff Publications

Background: Risk compensation, or matching behavior to a perceived level of acceptable risk, can blunt the effectiveness of public health interventions. One area of possible risk compensation during the SARS-CoV-2 pandemic is antibody testing. While antibody tests are imperfect measures of immunity, results may influence risk perception and individual preventive actions. We conducted a randomized control trial to assess whether receiving antibody test results changed SARS-CoV-2 protective behaviors.

Purpose: Assess whether objective information about antibody status, particularly for those who are antibody negative and likely still susceptible to SARS-CoV-2 infection, increases protective behaviors. Secondarily, assess whether a positive antibody test …

A Flexible-Hazards Cure Model With Application To Patients With Soft Tissue Sarcoma, Can Xie, Xuelin Huang, Ruosha Li, Peter W T Pisters

Faculty, Staff and Student Publications

In medical research, it is often of great interest to have an accurate estimation of cure rates by different treatment options and for different patient groups. If the follow-up time is sufficiently long and the sample size is large, the proportion of cured patients will make the Kaplan-Meier estimator of survival function have a flat plateau at its tail, whose value indicates the overall cure rate. However, it may be difficult to estimate and compare the cure rates for all the subsets of interest in this way, due to the limit of sample sizes and curse of dimensionality. In the …

Correlations Between Complex Human Phenotypes Vary By Genetic Background, Gender, And Environment, Michael Elgart, Matthew O Goodman, Carmen Isasi, Han Chen, Alanna C Morrison, Paul S De Vries, Huichun Xu, Ani W Manichaikul, Xiuqing Guo, Nora Franceschini, Bruce M Psaty, Stephen S Rich, Jerome I Rotter, Donald M Lloyd-Jones, Myriam Fornage, Adolfo Correa, Nancy L Heard-Costa, Ramachandran S Vasan, Ryan Hernandez, Robert C Kaplan, Susan Redline, Tamar Sofer

Faculty, Staff and Student Publications

We develop a closed-form Haseman-Elston estimator for genetic and environmental correlation coefficients between complex phenotypes, which we term HEc, that is as precise as GCTA yet ∼20× faster. We estimate genetic and environmental correlations between over 7,000 phenotype pairs in subgroups from the Trans-Omics in Precision Medicine (TOPMed) program. We demonstrate substantial differences in both heritabilities and genetic correlations for multiple phenotypes and phenotype pairs between individuals of self-reported Black, Hispanic/Latino, and White backgrounds. We similarly observe differences in many of the genetic and environmental correlations between genders. To estimate the contribution of genetics to the observed phenotypic correlation, we …

An Isochroman Analog Of Cd3254 And Allyl-, Isochroman-Analogs Of Net-Tmn Prove To Be More Potent Retinoid-X-Receptor (Rxr) Selective Agonists Than Bexarotene, Peter W Jurutka, Orsola Di Martino, Et Al.

2020-Current year OA Pubs

Bexarotene is an FDA-approved drug for the treatment of cutaneous T-cell lymphoma (CTCL); however, its use provokes or disrupts other retinoid-X-receptor (RXR)-dependent nuclear receptor pathways and thereby incites side effects including hypothyroidism and raised triglycerides. Two novel bexarotene analogs, as well as three unique CD3254 analogs and thirteen novel NEt-TMN analogs, were synthesized and characterized for their ability to induce RXR agonism in comparison to bexarotene (

Protocol For Mathematical Prediction Of Patient Response And Survival To Immune Checkpoint Inhibitor Immunotherapy, Joseph D Butner, Maguy Farhat, Vittorio Cristini, Caroline Chung, Zhihui Wang

Faculty, Staff and Student Publications

This protocol describes the application of a mechanistic mathematical model of immune checkpoint inhibitor (ICI) immunotherapy to patient tumor imaging data for predicting solid tumor response and patient survival under ICI intervention. We describe steps for data collection and processing, data pipelines, and approaches to increase precision. The protocol is highly predictive as early as the first restaging after treatment start and can be used with standard-of-care imaging measures. For complete details on the use and execution of this protocol, please refer to Butner et al. (2020)

Tissue Registration And Exploration User Interfaces In Support Of A Human Reference Atlas, Katy Börner, Andreas Bueckle, Bruce W Herr 2nd, Leonard E Cross, Ellen M Quardokus, Elizabeth G Record, Yingnan Ju, Jonathan C Silverstein, Kristen M Browne, Sanjay Jain, Clive H Wasserfall, Marda L Jorgensen, Jeffrey M Spraggins, N Heath Patterson, Griffin M Weber

2020-Current year OA Pubs

Seventeen international consortia are collaborating on a human reference atlas (HRA), a comprehensive, high-resolution, three-dimensional atlas of all the cells in the healthy human body. Laboratories around the world are collecting tissue specimens from donors varying in sex, age, ethnicity, and body mass index. However, harmonizing tissue data across 25 organs and more than 15 bulk and spatial single-cell assay types poses challenges. Here, we present software tools and user interfaces developed to spatially and semantically annotate ("register") and explore the tissue data and the evolving HRA. A key part of these tools is a common coordinate framework, providing standard …

Experiences Of Parents With Opioid Use Disorder During Their Attempts To Seek Treatment: A Qualitative Analysis, Christine Bakos-Block, Angela J Nash, A Sarah Cohen, Tiffany Champagne-Langabeer

Faculty, Staff and Student Publications

In the U.S., 12.3% of children live with at least one parent who has a substance use disorder. Prior research has shown that men are more likely to seek treatment than women and that the barriers are different; however, there is limited research focusing specifically on opioid use disorder (OUD). We sought to understand the barriers and motivators for parents with OUD. We conducted a qualitative study by interviewing parents with OUD who were part of an outpatient treatment program. Interviews followed a semi-structured format with questions on access to and motivation for treatment. The interviews were recorded and transcribed …

High-Frequency Ultrasound In Patients With Seronegative Rheumatoid Arthritis, Junkui Wang, Miao Wang, Qinghua Qi, Zhibin Wu, Jianguo Wen

Faculty, Staff and Student Publications

This study aimed to investigate the value of high-frequency ultrasound (HFUS) in differentiation of the seronegative rheumatoid arthritis (SNRA) and osteoarthritis (OA) and in the diagnosis of SNRA. 83 patients diagnosed with SNRA (SNRA group) and 40 diagnosed with OA (OA group) who received HFUS were retrospectively analyzed. The grayscale (GS) scores, power Doppler (PD) scores, and bone erosion (BE)scores were recorded, and added up to calculate the total scores of US variables. The correlations of the total scores of US variables with the 28-joint disease activity score (DAS28), erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) were analyzed. The …

Open-Source Benchmarking Of Ibd Segment Detection Methods For Biobank-Scale Cohorts, Kecong Tang, Ardalan Naseri, Yuan Wei, Shaojie Zhang, Degui Zhi

Faculty, Staff and Student Publications

In the recent biobank era of genetics, the problem of identical-by-descent (IBD) segment detection received renewed interest, as IBD segments in large cohorts offer unprecedented opportunities in the study of population and genealogical history, as well as genetic association of long haplotypes. While a new generation of efficient methods for IBD segment detection becomes available, direct comparison of these methods is difficult: existing benchmarks were often evaluated in different datasets, with some not openly accessible; methods benchmarked were run under suboptimal parameters; and benchmark performance metrics were not defined consistently. Here, we developed a comprehensive and completely open-source evaluation of …

Federated Learning Enables Big Data For Rare Cancer Boundary Detection, Sarthak Pati, Ujjwal Baid, Brandon Edwards, Micah Sheller, Shih-Han Wang, G. Anthony Reina, Patrick Foley, Alexey Gruzdev, Deepthi Karkada, Christos Davatzikos, Chiharu Sako, Satyam Ghodasara, Michel Bilello, Suyash Mohan, Philipp Vollmuth, Gianluca Brugnara, Chandrakanth J. Preetha, Felix Sahm, Klaus Maier-Hein, Maximilian Zenk, Martin Bendszus, Wolfgang Wick, Evan Calabrese, Jeffrey Rudie, Javier Villanueva-Meyer, Soonmee Cha, Madhura Ingalhalikar, Manali Jadhav, Umang Pandey, Jitender Saini, John Garrett, Matthew Larson, Robert Jeraj, Stuart Currie, Russell Frood, Kavi Fatania, Raymond Y Huang, Ken Chang, Carmen Balaña, Jaume Capellades, Josep Puig, Johannes Trenkler, Josef Pichler, Georg Necker, Andreas Haunschmidt, Stephan Meckel, Gaurav Shukla, Spencer Liem, Gregory S Alexander, Joseph Lombardo, Joshua D Palmer, Adam E Flanders, Adam P Dicker, Haris I Sair, Craig K Jones, Archana Venkataraman, Meirui Jiang, Tiffany Y So, Cheng Chen, Pheng Ann Heng, Qi Dou, Michal Kozubek, Filip Lux, Jan Michálek, Petr Matula, Miloš Keřkovský, Tereza Kopřivová, Marek Dostál, Václav Vybíhal, Michael A Vogelbaum, J Ross Mitchell, Joaquim Farinhas, Joseph A Maldjian, Chandan Ganesh Bangalore Yogananda, Marco C Pinho, Divya Reddy, James Holcomb, Benjamin C Wagner, Benjamin M Ellingson, Timothy F Cloughesy, Catalina Raymond, Talia Oughourlian, Akifumi Hagiwara, Chencai Wang, Minh-Son To, Sargam Bhardwaj, Chee Chong, Marc Agzarian, Alexandre Xavier Falcão, Samuel B Martins, Bernardo C A Teixeira, Flávia Sprenger, David Menotti, Diego R Lucio, Pamela Lamontagne, Daniel Marcus, Benedikt Wiestler, Florian Kofler, Ivan Ezhov, Marie Metz, Rajan Jain, Matthew Lee, Yvonne W Lui, Richard Mckinley, Johannes Slotboom, Piotr Radojewski, Raphael Meier, Roland Wiest, Derrick Murcia, Eric Fu, Rourke Haas, John Thompson, David Ryan Ormond, Chaitra Badve, Andrew E Sloan, Vachan Vadmal, Kristin Waite, Rivka R Colen, Linmin Pei, Murat Ak, Ashok Srinivasan, J Rajiv Bapuraj, Arvind Rao, Nicholas Wang, Ota Yoshiaki, Toshio Moritani, Sevcan Turk, Joonsang Lee, Snehal Prabhudesai, Fanny Morón, Jacob Mandel, Konstantinos Kamnitsas, Ben Glocker, Luke V M Dixon, Matthew Williams, Peter Zampakis, Vasileios Panagiotopoulos, Panagiotis Tsiganos, Sotiris Alexiou, Ilias Haliassos, Evangelia I Zacharaki, Konstantinos Moustakas, Christina Kalogeropoulou, Dimitrios M Kardamakis, Yoon Seong Choi, Seung-Koo Lee, Jong Hee Chang, Sung Soo Ahn, Bing Luo, Laila M. Poisson, Ning Wen, Pallavi Tiwari, Ruchika Verma, Rohan Bareja, Ipsa Yadav, Jonathan Chen, Neeraj Kumar, Marion Smits, Sebastian R Van Der Voort, Ahmed Alafandi, Fatih Incekara, Maarten M J Wijnenga, Georgios Kapsas, Renske Gahrmann, Joost W Schouten, Hendrikus J Dubbink, Arnaud J P E Vincent, Martin J Van Den Bent, Pim J French, Stefan Klein, Yading Yuan, Sonam Sharma, Tzu-Chi Tseng, Saba Adabi, Simone P Niclou, Olivier Keunen, Ann-Christin Hau, Martin Vallières, David Fortin, Martin Lepage, Bennett Landman, Karthik Ramadass, Kaiwen Xu, Silky Chotai, Lola B Chambless, Akshitkumar Mistry, Reid C Thompson, Yuriy Gusev, Krithika Bhuvaneshwar, Anousheh Sayah, Camelia Bencheqroun, Anas Belouali, Subha Madhavan, Thomas C Booth, Alysha Chelliah, Marc Modat, Haris Shuaib, Carmen Dragos, Aly Abayazeed, Kenneth Kolodziej, Michael Hill, Ahmed Abbassy, Shady Gamal, Mahmoud Mekhaimar, Mohamed Qayati, Mauricio Reyes, Ji Eun Park, Jihye Yun, Ho Sung Kim, Abhishek Mahajan, Mark Muzi, Sean Benson, Regina G H Beets-Tan, Jonas Teuwen, Alejandro Herrera-Trujillo, Maria Trujillo, William Escobar, Ana Abello, Jose Bernal, Jhon Gómez, Joseph Choi, Stephen Baek, Yusung Kim, Heba Ismael, Bryan Allen, John M Buatti, Aikaterini Kotrotsou, Hongwei Li, Tobias Weiss, Michael Weller, Andrea Bink, Bertrand Pouymayou, Hassan F Shaykh, Joel Saltz, Prateek Prasanna, Sampurna Shrestha, Kartik M Mani, David Payne, Tahsin Kurc, Enrique Pelaez, Heydy Franco-Maldonado, Francis Loayza, Sebastian Quevedo, Pamela Guevara, Esteban Torche, Cristobal Mendoza, Franco Vera, Elvis Ríos, Eduardo López, Sergio A Velastin, Godwin Ogbole, Mayowa Soneye, Dotun Oyekunle, Olubunmi Odafe-Oyibotha, Babatunde Osobu, Mustapha Shu'aibu, Adeleye Dorcas, Farouk Dako, Amber L Simpson, Mohammad Hamghalam, Jacob J Peoples, Ricky Hu, Anh Tran, Danielle Cutler, Fabio Y Moraes, Michael A Boss, James Gimpel, Deepak Kattil Veettil, Kendall Schmidt, Brian Bialecki, Sailaja Marella, Cynthia Price, Lisa Cimino, Charles Apgar, Prashant Shah, Bjoern Menze, Jill S Barnholtz-Sloan, Jason Martin, Spyridon Bakas

Radiation Oncology Articles

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 …

Federated Learning Enables Big Data For Rare Cancer Boundary Detection, Sarthak Pati, Ujjwal Baid, Brandon Edwards, Micah Sheller, Shih-Han Wang, G Anthony Reina, Patrick Foley, Alexey Gruzdev, Deepthi Karkada, Christos Davatzikos, Chiharu Sako, Satyam Ghodasara, Michel Bilello, Suyash Mohan, Philipp Vollmuth, Gianluca Brugnara, Chandrakanth J Preetha, Felix Sahm, Klaus Maier-Hein, Maximilian Zenk, Martin Bendszus, Wolfgang Wick, Evan Calabrese, Jeffrey Rudie, Javier Villanueva-Meyer, Soonmee Cha, Madhura Ingalhalikar, Manali Jadhav, Umang Pandey, Jitender Saini, John Garrett, Matthew Larson, Robert Jeraj, Stuart Currie, Russell Frood, Kavi Fatania, Raymond Y Huang, Ken Chang, Carmen Balaña, Jaume Capellades, Josep Puig, Johannes Trenkler, Josef Pichler, Georg Necker, Andreas Haunschmidt, Stephan Meckel, Gaurav Shukla, Spencer Liem, Gregory S Alexander, Joseph Lombardo, Joshua D Palmer, Adam E Flanders, Adam P Dicker, Haris I Sair, Craig K Jones, Archana Venkataraman, Meirui Jiang, Tiffany Y So, Cheng Chen, Pheng Ann Heng, Qi Dou, Michal Kozubek, Filip Lux, Jan Michálek, Petr Matula, Miloš Keřkovský, Tereza Kopřivová, Marek Dostál, Václav Vybíhal, Michael A Vogelbaum, J Ross Mitchell, Joaquim Farinhas, Joseph A Maldjian, Chandan Ganesh Bangalore Yogananda, Marco C Pinho, Divya Reddy, James Holcomb, Benjamin C Wagner, Benjamin M Ellingson, Timothy F Cloughesy, Catalina Raymond, Talia Oughourlian, Akifumi Hagiwara, Chencai Wang, Minh-Son To, Sargam Bhardwaj, Chee Chong, Marc Agzarian, Alexandre Xavier Falcão, Samuel B Martins, Bernardo C A Teixeira, Flávia Sprenger, David Menotti, Diego R Lucio, Pamela Lamontagne, Daniel Marcus, Benedikt Wiestler, Florian Kofler, Ivan Ezhov, Marie Metz, Rajan Jain, Matthew Lee, Yvonne W Lui, Richard Mckinley, Johannes Slotboom, Piotr Radojewski, Raphael Meier, Roland Wiest, Derrick Murcia, Eric Fu, Rourke Haas, John Thompson, David Ryan Ormond, Chaitra Badve, Andrew E Sloan, Vachan Vadmal, Kristin Waite, Rivka R Colen, Linmin Pei, Murat Ak, Ashok Srinivasan, J Rajiv Bapuraj, Arvind Rao, Nicholas Wang, Ota Yoshiaki, Toshio Moritani, Sevcan Turk, Joonsang Lee, Snehal Prabhudesai, Fanny Morón, Jacob Mandel, Konstantinos Kamnitsas, Ben Glocker, Luke V M Dixon, Matthew Williams, Peter Zampakis, Vasileios Panagiotopoulos, Panagiotis Tsiganos, Sotiris Alexiou, Ilias Haliassos, Evangelia I Zacharaki, Konstantinos Moustakas, Christina Kalogeropoulou, Dimitrios M Kardamakis, Yoon Seong Choi, Seung-Koo Lee, Jong Hee Chang, Sung Soo Ahn, Bing Luo, Laila Poisson, Ning Wen, Pallavi Tiwari, Ruchika Verma, Rohan Bareja, Ipsa Yadav, Jonathan Chen, Neeraj Kumar, Marion Smits, Sebastian R Van Der Voort, Ahmed Alafandi, Fatih Incekara, Maarten M J Wijnenga, Georgios Kapsas, Renske Gahrmann, Joost W Schouten, Hendrikus J Dubbink, Arnaud J P E Vincent, Martin J Van Den Bent, Pim J French, Stefan Klein, Yading Yuan, Sonam Sharma, Tzu-Chi Tseng, Saba Adabi, Simone P Niclou, Olivier Keunen, Ann-Christin Hau, Martin Vallières, David Fortin, Martin Lepage, Bennett Landman, Karthik Ramadass, Kaiwen Xu, Silky Chotai, Lola B Chambless, Akshitkumar Mistry, Reid C Thompson, Yuriy Gusev, Krithika Bhuvaneshwar, Anousheh Sayah, Camelia Bencheqroun, Anas Belouali, Subha Madhavan, Thomas C Booth, Alysha Chelliah, Marc Modat, Haris Shuaib, Carmen Dragos, Aly Abayazeed, Kenneth Kolodziej, Michael Hill, Ahmed Abbassy, Shady Gamal, Mahmoud Mekhaimar, Mohamed Qayati, Mauricio Reyes, Ji Eun Park, Jihye Yun, Ho Sung Kim, Abhishek Mahajan, Mark Muzi, Sean Benson, Regina G H Beets-Tan, Jonas Teuwen, Alejandro Herrera-Trujillo, Maria Trujillo, William Escobar, Ana Abello, Jose Bernal, Jhon Gómez, Joseph Choi, Stephen Baek, Yusung Kim, Heba Ismael, Bryan Allen, John M Buatti, Aikaterini Kotrotsou, Hongwei Li, Tobias Weiss, Michael Weller, Andrea Bink, Bertrand Pouymayou, Hassan F Shaykh, Joel Saltz, Prateek Prasanna, Sampurna Shrestha, Kartik M Mani, David Payne, Tahsin Kurc, Enrique Pelaez, Heydy Franco-Maldonado, Francis Loayza, Sebastian Quevedo, Pamela Guevara, Esteban Torche, Cristobal Mendoza, Franco Vera, Elvis Ríos, Eduardo López, Sergio A Velastin, Godwin Ogbole, Mayowa Soneye, Dotun Oyekunle, Olubunmi Odafe-Oyibotha, Babatunde Osobu, Mustapha Shu'aibu, Adeleye Dorcas, Farouk Dako, Amber L Simpson, Mohammad Hamghalam, Jacob J Peoples, Ricky Hu, Anh Tran, Danielle Cutler, Fabio Y Moraes, Michael A Boss, James Gimpel, Deepak Kattil Veettil, Kendall Schmidt, Brian Bialecki, Sailaja Marella, Cynthia Price, Lisa Cimino, Charles Apgar, Prashant Shah, Bjoern Menze, Jill S Barnholtz-Sloan, Jason Martin, Spyridon Bakas

Faculty, Staff and Student Publications

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 …

Comparing The Outcomes Of Face-To-Face And Synchronous Online Research Mentor Training Using Propensity Score Matching, Jenna Rogers, Xue Gong, Angela Byars-Winston, Melissa Mcdaniels, Nancy Thayer-Hart, Philip Cheng, Kelly Diggs-Andrews, Kermin J. Martínez-Hernández, Christine Pfund

Sleep Medicine Articles

In this study, propensity score matching (PSM) was conducted to examine differences in the effectiveness of research mentor training (RMT) implemented using two modes-face-to-face or synchronous online training. This study investigated each training mode and assessed participants' perceived gains in mentoring skills, ability to meet mentees' expectations, and overall quality of mentoring, as well as intention to make changes to their mentoring practices. Additional factors that may contribute to participant outcomes were also examined. In total, 152 mentors trained using a synchronous online platform and 655 mentors trained in in-person workshops were analyzed using the PSM method. Mentors were matched …

Drug Abuse Ontology To Harness Web-Based Data For Substance Use Epidemiology Research, Usha Lokala, Francois Lamy, Raminta Daniulaityte, Manas Gaur, Amelie Gyrard, Krishnaprasad Thirunarayan, Ugur Kursuncu, Amit Sheth

Computer Science and Engineering Faculty Publications

Background: Web-based resources and social media platforms play an increasingly important role in health-related knowledge and experience sharing. There is a growing interest in the use of these novel data sources for epidemiological surveillance of substance use behaviors and trends. Objective: The key aims were to describe the development and application of the drug abuse ontology (DAO) as a framework for analyzing web-based and social media data to inform public health and substance use research in the following areas: determining user knowledge, attitudes, and behaviors related to nonmedical use of buprenorphine and illicitly manufactured opioids through the analysis of web …

Intraoperative Localization And Preservation Of Reading In Ventral Occipitotemporal Cortex, Oscar Woolnough, Kathryn M Snyder, Cale W Morse, Meredith J Mccarty, Samden D Lhatoo, Nitin Tandon

Faculty, Staff and Student Publications

OBJECTIVE: Resective surgery in language-dominant ventral occipitotemporal cortex (vOTC) carries the risk of causing impairment to reading. Because it is not on the lateral surface, it is not easily accessible for intraoperative mapping, and extensive stimulation mapping can be time-consuming. Here the authors assess the feasibility of using task-based electrocorticography (ECoG) recordings intraoperatively to help guide stimulation mapping of reading in vOTC.

METHODS: In 11 patients undergoing extraoperative, intracranial seizure mapping, the authors recorded induced broadband gamma activation (70-150 Hz) during a visual category localizer. In 2 additional patients, whose pathologies necessitated resections in language-dominant vOTC, task-based functional mapping was …

Soy Isoflavones Decrease Fibroglandular Breast Tissue Measured By Magnetic Resonance Imaging In Premenopausal Women: A 2-Year Randomized Double-Blind Placebo Controlled Clinical Trial, Lee-Jane W Lu, Nai-Wei Chen, Donald G Brunder, Fatima Nayeem, Manubai Nagamani, Thomas K Nishino, Karl E Anderson, Tuenchit Khamapirad

Faculty, Staff and Student Publications

BACKGROUND & AIMS: Populations consuming soy have reduced risk for breast cancer, but the mechanisms are unclear. We tested the hypothesis that soy isoflavones, which have ovarian hormone-like effects, can reduce fibroglandular breast tissue (FGBT, 'breast density'), a strong risk marker for breast cancer.

METHODS: Premenopausal women (age 30-42 years) were randomized to consume isoflavones (136.6 mg as aglycone equivalents, n = 99) or placebo (n = 98) for 5 days per week up to 2 years, and changes in breast composition measured by magnetic resonance imaging at baseline and yearly intervals were compared after square root transformation using linear …

Identification Of Patients With Ovarian Cancer Experiencing The Highest Benefit From Bevacizumab In The First-Line Setting On The Basis Of Their Tumor-Intrinsic Chemosensitivity (Kelim): The Gog-0218 Validation Study, Benoit You, David Mutch, Et Al.

2020-Current year OA Pubs

PURPOSE: In patients with high-grade ovarian cancer, predictors of bevacizumab efficacy in first-line setting are needed. In the ICON-7 trial, a poor tumor intrinsic chemosensitivity (defined by unfavorable modeled cancer antigen-125 [CA-125] ELIMination rate constant K [KELIM] score) was a predictive biomarker. Only the patients with high-risk disease (suboptimally resected stage III, or stage IV) exhibiting unfavorable KELIM score < 1.0 had overall survival (OS) benefit from bevacizumab (median: 29.7

METHODS: In GOG-0218, 1,873 patients were treated with carboplatin-paclitaxel ± concurrent-maintenance bevacizumab/placebo. Patient KELIM values were calculated with CA-125 kinetics during the first 100 chemotherapy days by the Lyon University team. The association between KELIM score (favorable ≥ 1.0, or unfavorable …

Dietary And Complementary Feeding Practices Of Us Infants, 6 To 12 Months: A Narrative Review Of The Federal Nutrition Monitoring Data, Regan L Bailey, Jaime S Stang, Teresa A Davis, Timothy S Naimi, Barbara O Schneeman, Kathryn G Dewey, Sharon M Donovan, Rachel Novotny, Ronald E Kleinman, Elsie M Taveras, Lydia Bazzano, Linda G Snetselaar, Janet De Jesus, Kellie O Casavale, Eve E Stoody, Joseph D Goldman, Alanna J Moshfegh, Donna G Rhodes, Kirsten A Herrick, Kristin Koegel, Cria G Perrine, Tusarebecca Pannucci

Children’s Nutrition Research Center Staff Publications

Complementary foods and beverages (CFBs) are key components of an infant’s diet in the second 6 months of life. This article summarizes nutrition and feeding practices examined by the 2020 Dietary Guidelines Advisory Committees during the CFB life stage. Breastfeeding initiation is high (84%), but exclusive breastfeeding at 6 months (26%) is below the Healthy People 2030 goal (42%). Most infants (51%) are introduced to CFBs sometime before 6 months. The primary mode of feeding (ie, human milk fed [HMF]; infant formula or mixed formula and human milk fed [FMF]) at the initiation of CFBs is associated with the timing …

Radiomics In Abdominopelvic Solid-Organ Oncologic Imaging: Current Status, Xiaoyang Liu, Mohamed G Elbanan, Antonio Luna, Masoom A Haider, Andrew D Smith, Carl F Sabottke, Bradley M Spieler, Baris Turkbey, David Fuentes, Ahmed Moawad, Serageldin Kamel, Natally Horvat, Khaled M Elsayes

Faculty, Staff and Student Publications

Radiomics is the process of extraction of high-throughput quantitative imaging features from medical images. These features represent noninvasive quantitative biomarkers that go beyond the traditional imaging features visible to the human eye. This article first reviews the steps of the radiomics pipeline, including image acquisition, ROI selection and image segmentation, image preprocessing, feature extraction, feature selection, and model development and application. Current evidence for the application of radiomics in abdominopelvic solid-organ cancers is then reviewed. Applications including diagnosis, subtype determination, treatment response assessment, and outcome prediction are explored within the context of hepatobiliary and pancreatic cancer, renal cell carcinoma, prostate …

Genetic Landscape Of Indolent And Aggressive Kaposi Sarcomas, G G Malouf, X Lu, R Mouawad, J-P Spano, P Grange, F Yan, S Aractingi, X Su, N Dupin

Faculty, Staff and Student Publications

Background: Kaposi sarcoma (KS) is a rare skin tumour caused by herpesvirus 8 infection and characterized by either indolence or an aggressive course necessitating systemic therapies. The genetic basis of this difference remains unknown.

Objectives: To explore the tumour mutational burden in indolent and aggressive KS.

Methods: We performed whole-exome sequencing on a cohort of 21 KS patients. We compared genetic landscape including tumor mutational burden between the two forms of indolent and agressive KS.

Results: Aggressive KS tumours had a significantly higher TMB and a larger cumulative number of deleterious mutations than indolent KS tumours. In addition, all aggressive …

Development Of A Distributed International Patient Data Registry For Hairy Cell Leukemia, Leslie A Andritsos, Mirela Anghelina, Jasmine Neal, James S Blachly, Puneet Mathur, Omkar Lele, Claire Dearden, Sunil Iyengar, Matthew Cross, Clive S Zent, Kerry A Rogers, Narendranath Epperla, Gerard Lozanski, Christopher C Oakes, Eric Kraut, Amy S Ruppert, Qiuhong Zhao, Seema A Bhat, Francesco Forconi, Versha Banerji, Sasanka Handunnetti, Constantine S Tam, John F Seymour, Monica Else, Robert J Kreitman, Alan Saven, Timothy Call, Sameer A Parikh, Farhad Ravandi, James B Johnston, Enrico Tiacci, Xavier Troussard, Martin S Tallman, Sascha Dietrich, Tamar Tadmor, Alessandro Gozzetti, Pier Luigi Zinzani, Tadeusz Robak, Graeme Quest, Judit Demeter, Kanti Rai, Soledad A Fernandez, Michael Grever

Faculty, Staff and Student Publications

Hairy cell leukemia (HCL) is a rare lymphoproliferative disorder, comprising only 2% of all leukemias. The Hairy Cell Leukemia Foundation (HCLF) has developed a patient data registry to enable investigators to better study the clinical features, treatment outcomes, and complications of patients with HCL. This system utilizes a centralized registry architecture. Patients are enrolled at HCL Centers of Excellence (COE) or via a web-based portal. All data are de-identified, which reduces regulatory burden and increases opportunities for data access and re-use. To date, 579 patients have been enrolled in the registry. Efforts are underway to engage additional COE's to expand …

From Model Organisms To Humans, The Opportunity For More Rigor In Methodologic And Statistical Analysis, Design, And Interpretation Of Aging And Senescence Research, Daniella E Chusyd, Steven N Austad, Andrew W Brown, Xiwei Chen, Stephanie L Dickinson, Keisuke Ejima, David Fluharty, Lilian Golzarri-Arroyo, Richard Holden, Yasaman Jamshidi-Naeini, Doug Landsittel, Stella Lartey, Edward Mannix, Colby J Vorland, David B Allison

Children’s Nutrition Research Center Staff Publications

This review identifies frequent design and analysis errors in aging and senescence research and discusses best practices in study design, statistical methods, analyses, and interpretation. Recommendations are offered for how to avoid these problems. The following issues are addressed: (a) errors in randomization, (b) errors related to testing within-group instead of between-group differences, (c) failing to account for clustering, (d) failing to consider interference effects, (e) standardizing metrics of effect size, (f) maximum life-span testing, (g) testing for effects beyond the mean, (h) tests for power and sample size, (i) compression of morbidity versus survival curve squaring, and (j) other …

Privacy-Aware Estimation Of Relatedness In Admixed Populations, Su Wang, Miran Kim, Wentao Li, Xiaoqian Jiang, Han Chen, Arif Harmanci

Faculty, Staff and Student Publications

BACKGROUND: Estimation of genetic relatedness, or kinship, is used occasionally for recreational purposes and in forensic applications. While numerous methods were developed to estimate kinship, they suffer from high computational requirements and often make an untenable assumption of homogeneous population ancestry of the samples. Moreover, genetic privacy is generally overlooked in the usage of kinship estimation methods. There can be ethical concerns about finding unknown familial relationships in third-party databases. Similar ethical concerns may arise while estimating and reporting sensitive population-level statistics such as inbreeding coefficients for the concerns around marginalization and stigmatization.

RESULTS: Here, we present SIGFRIED, which makes …

Cerebral Blood Flow And Cardiovascular Risk Effects On Resting Brain Regional Homogeneity, Bhim M Adhikari, L Elliot Hong, Zhiwei Zhao, Danny J J Wang, Paul M Thompson, Neda Jahanshad, Alyssa H Zhu, Stefan Holiga, Jessica A Turner, Theo G M Van Erp, Vince D Calhoun, Kathryn S Hatch, Heather Bruce, Stephanie M Hare, Joshua Chiappelli, Eric L Goldwaser, Mark D Kvarta, Yizhou Ma, Xiaoming Du, Thomas E Nichols, Alan R Shuldiner, Braxton D Mitchell, Juergen Dukart, Shuo Chen, Peter Kochunov

Faculty, Staff and Student Publications

Regional homogeneity (ReHo) is a measure of local functional brain connectivity that has been reported to be altered in a wide range of neuropsychiatric disorders. Computed from brain resting-state functional MRI time series, ReHo is also sensitive to fluctuations in cerebral blood flow (CBF) that in turn may be influenced by cerebrovascular health. We accessed cerebrovascular health with Framingham cardiovascular risk score (FCVRS). We hypothesize that ReHo signal may be influenced by regional CBF; and that these associations can be summarized as FCVRS→CBF→ReHo. We used three independent samples to test this hypothesis. A test-retest sample of N = 30 healthy …

Medicc2: Whole-Genome Doubling Aware Copy-Number Phylogenies For Cancer Evolution, Tom L Kaufmann, Marina Petkovic, Thomas B K Watkins, Emma C Colliver, Sofya Laskina, Nisha Thapa, Darlan C Minussi, Nicholas Navin, Charles Swanton, Peter Van Loo, Kerstin Haase, Maxime Tarabichi, Roland F Schwarz

Faculty, Staff and Student Publications

Aneuploidy, chromosomal instability, somatic copy-number alterations, and whole-genome doubling (WGD) play key roles in cancer evolution and provide information for the complex task of phylogenetic inference. We present MEDICC2, a method for inferring evolutionary trees and WGD using haplotype-specific somatic copy-number alterations from single-cell or bulk data. MEDICC2 eschews simplifications such as the infinite sites assumption, allowing multiple mutations and parallel evolution, and does not treat adjacent loci as independent, allowing overlapping copy-number events. Using simulations and multiple data types from 2780 tumors, we use MEDICC2 to demonstrate accurate inference of phylogenies, clonal and subclonal WGD, and ancestral copy-number states.

A Comprehensive Artificial Intelligence Framework For Dental Diagnosis And Charting, Tanjida Kabir, Chun-Teh Lee, Luyao Chen, Xiaoqian Jiang, Shayan Shams

Faculty, Staff and Student Publications

BACKGROUND: The aim of this study was to develop artificial intelligence (AI) guided framework to recognize tooth numbers in panoramic and intraoral radiographs (periapical and bitewing) without prior domain knowledge and arrange the intraoral radiographs into a full mouth series (FMS) arrangement template. This model can be integrated with different diseases diagnosis models, such as periodontitis or caries, to facilitate clinical examinations and diagnoses.

METHODS: The framework utilized image segmentation models to generate the masks of bone area, tooth, and cementoenamel junction (CEJ) lines from intraoral radiographs. These masks were used to detect and extract teeth bounding boxes utilizing several …

Atomistic Measurement And Modeling Of Intrinsic Fracture Toughness Of Two-Dimensional Materials, Xu Zhang, Hoang Nguyen, Xiang Zhang, Pulickel M Ajayan, Jianguo Wen, Horacio D Espinosa

Faculty, Staff and Student Publications

Quantifying the intrinsic mechanical properties of two-dimensional (2D) materials is essential to predict the long-term reliability of materials and systems in emerging applications ranging from energy to health to next-generation sensors and electronics. Currently, measurements of fracture toughness and identification of associated atomistic mechanisms remain challenging. Herein, we report an integrated experimental-computational framework in which in-situ high-resolution transmission electron microscopy (HRTEM) measurements of the intrinsic fracture energy of monolayer MoS

Phenome-Wide Analysis Of Taiwan Biobank Reveals Novel Glycemia-Related Loci And Genetic Risks For Diabetes, Chia-Jung Lee, Ting-Huei Chen, Aylwin Ming Wee Lim, Chien-Ching Chang, Jia-Jyun Sie, Pei-Lung Chen, Su-Wei Chang, Shang-Jung Wu, Chia-Lin Hsu, Ai-Ru Hsieh, Wei-Shiung Yang, Cathy S J Fann

2020-Current year OA Pubs

To explore the complex genetic architecture of common diseases and traits, we conducted comprehensive PheWAS of ten diseases and 34 quantitative traits in the community-based Taiwan Biobank (TWB). We identified 995 significantly associated loci with 135 novel loci specific to Taiwanese population. Further analyses highlighted the genetic pleiotropy of loci related to complex disease and associated quantitative traits. Extensive analysis on glycaemic phenotypes (T2D, fasting glucose and HbA

Netie: Inferring The Evolution Of Neoantigen-T Cell Interactions In Tumors, Tianshi Lu, Seongoh Park, Yi Han, Yunguan Wang, Shawna Marie Hubert, P Andy Futreal, Ignacio Wistuba, John V Heymach, Alexandre Reuben, Jianjun Zhang, Tao Wang

Faculty, Staff and Student Publications

Neoantigens are the key targets of antitumor immune responses from cytotoxic T cells and play a critical role in affecting tumor progressions and immunotherapy treatment responses. However, little is known about how the interaction between neoantigens and T cells ultimately affects the evolution of cancerous masses. Here, we develop a hierarchical Bayesian model, named neoantigen-T cell interaction estimation (netie) to infer the history of neoantigen-CD8