Digital Commons Network^™

A Bilingual Ai-Based Chatbot For Nutrition Education In A Food Is Medicine Intervention For High-Risk Pregnant Women: Design And Development Study, Lorena Macias-Navarro, Nalini Ranjit, Gregory W Bounds, Brendon A Providence, Yesmeena Shmaitelly, Naomi M Tice, Shreela V Sharma

Faculty, Staff and Student Publications

Background: Conversational agents (artificial intelligence [AI]-based chatbots) offer a novel approach to health interventions by providing personalized, adaptive interactions that improve over time based on user engagement. In nutrition education, given the wide variation in knowledge, skills, and abilities across participants, AI-based chatbots have the potential to enhance accessibility, engagement, and behavior change. Food is Medicine (FIM) interventions, which aim to improve food security and diet quality among multicultural, at-risk populations, often face challenges related to sustained engagement and use.

Objective: This paper describes the design, development, and iterative refinement of a bilingual AI-driven nutrition chatbot integrated into an FIM …

Computational Modeling Meets 3d Bioprinting: Emerging Synergies In Cardiovascular Disease Modeling, Tanmay Mukherjee, Mehdi Salar Amoli, Sarah Rezapourdamanab, Lama Rita El Shammas, Martin L Tomov, Emilio A Mendiola, Vahid Serpooshan, Reza Avazmohammadi

Faculty, Staff and Student Publications

Cardiovascular diseases (CVDs) remain the leading cause of death worldwide, underscoring the need for improved strategies in diagnosis, treatment, and disease modeling. Traditional in vitro models often fall short in replicating human CV physiology, prompting efforts to advance cardiac tissue engineering and computational modeling. Among these, three-dimensional (3D) bioprinting has emerged as a transformative tool, enabling the creation of biomimetic CV constructs that more faithfully replicate native tissue structure and function. However, challenges persist in achieving appropriate mechanical properties and long-term performance of engineered CV constructs. Computational modeling offers powerful solutions to assist with these challenges, providing predictive insights into …

Ai-Powered Insights In Pediatric Nephrology: Current Applications And Future Opportunities., Arwa Nada, Yamen Ahmed, Jieji Hu, Darcy K. Weidemann, Gregory H. Gorman, Eva Glenn Lecea, Ibrahim A. Sandokji, Stephen Cha, Stella Shin, Salar Bani-Hani, Sai Sudha Mannemuddhu, Rebecca L. Ruebner, Aadil Kakajiwala, Rupesh Raina, Roshan George, Rim Elchaki, Michael L. Moritz, The American Society Of Pediatric Nephrology Quality Improvement And Artificial Intelligence (Aspn Qi/Ai) Interest Group

Manuscripts, Articles, Book Chapters and Other Papers

Artificial intelligence (AI) is rapidly emerging as a transformative force in pediatric nephrology, enabling improvements in diagnostic accuracy, therapeutic precision, and operational workflows. By integrating diverse datasets-including patient histories, genomics, imaging, and longitudinal clinical records-AI-driven tools can detect subtle kidney anomalies, predict acute kidney injury, and forecast disease progression. Deep learning models, for instance, have demonstrated the potential to enhance ultrasound interpretations, refine kidney biopsy assessments, and streamline pathology evaluations. Coupled with robust decision support systems, these innovations also optimize medication dosing and dialysis regimens, ultimately improving patient outcomes. AI-powered chatbots hold promise for improving patient engagement and adherence, while …

Mif-Cd74 Signaling Drives Immune Modulation In Medulloblastoma, Benjamin Draper, Zhen You, Dean Thompson, Xu Guo, Alaide Morcavallo, Diego Chillon Pino, Carlos Lorenzo Gido Nery, Sumana Shrestha, Chantelle E Bowers, Courtney Himsworth, Alberto Delaidelli, Bethany Remeniuk, Sonia Morlando, Brandon Wade, Freya Gordon, Yara Sanchez-Corrales, Bei Hopkins, Natalie Monteiro, Darren Locke, Miao Liu, Jacob Torrejon Diaz, Kevin Greenslade, Barbara Martins Da Costa, Karen Barker, Colin Kwok, Olumide Ogunbiyi, Anya Fletcher, Stacey Richardson, Carlos Custodia, Rafael Roque, Thomas Jackson, Regan Barfoot, Sergi Castellano, Rebecca M Hill, Olivier Saulnier, Thomas S Jacques, Michael D Taylor, Claudia C Faria, Olivier Ayrault, Poul H Sorensen, John Anderson, Louis Chesler, L Frank Huang, Steven C Clifford, Laura K Donovan

Faculty, Staff and Students Publications

Background: Relapsed medulloblastoma remains a significant therapeutic challenge as it is near universally fatal. The tumor microenvironment of medulloblastoma plays a critical role in tumor progression, influencing tumor growth, immune evasion, and therapeutic resistance. We hypothesized that defining tumor-immune interactions in diagnostic and relapsed medulloblastoma may uncover mechanisms of immune evasion and identify novel therapeutic targets.

Methods: We analyzed paired primary and recurrent RNA-sequencing data from 140 medulloblastoma patients to profile immune cell composition and validate spatial relationships within the TME. To identify key tumor-immune interactions, we developed a novel algorithm to detect receptor-ligand pairs using single-cell RNA-sequencing data. These …

Computational Fluid Dynamics-Based Risk Stratification Of Modified Blalock-Taussig-Thomas Shunt Thrombogenicity, Yi Qiao, Ethan Penn, Jacob Miller, Scott Bugenhagen, Ram Rohatgi, Kelsey Mercer, Blaire Kulp, Jinli Wang, Pirooz Eghtesady, Guy M Genin, Edon J Rabinowitz, David Bark

2020-Current year OA Pubs

BACKGROUND: The modified Blalock-Taussig-Thomas shunt (mBTTS) is a critical palliative procedure for infants with single-ventricle physiology, but thrombosis-related occlusion affects 8% to 12% of infants and carries nearly 50% mortality. Meanwhile, existing antithrombotic strategies fail to address the hemodynamic factors driving thrombosis, highlighting the need for a deeper understanding of flow dynamics in shunt failure.

OBJECTIVES: This study aims to identify how mBTTS geometry influences hemodynamics and thrombosis risk, providing quantitative guidance for surgical planning and shunt design optimization.

METHODS: We used patient-specific imaging data to test 54 idealized mBTTS configurations, systematically varying key geometric factors: pulmonary artery diameter, shunt …

A Covalent Allosteric Molecular Glue Suppresses Nrf2-Dependent Cancer Growth, Nilotpal Roy, Ilah Bok, Harit Panda, Dhaval P Bhatt, Emily M Wilkerson, Soma Saeidi, Paul Zolkind, Michael B Major, Et Al.

2020-Current year OA Pubs

UNLABELLED: The NRF2 transcription factor is constitutively active in cancer, in which it functions to maintain oxidative homeostasis and reprogram cellular metabolism. NRF2-active tumors exhibit NRF2 dependency and resistance to chemotherapy/radiotherapy (RT). In this study, we characterize VVD-065, a first-in-class NRF2 inhibitor that acts via an unprecedented allosteric molecular glue mechanism. In the absence of stress or mutation, NRF2 is rapidly degraded by the Kelch-like ECH-associated protein 1 (KEAP1)-cullin3 (CUL3) ubiquitin-ligase complex. VVD-065 specifically and covalently engages Cys151 on KEAP1, which in turn promotes KEAP1-CUL3 complex formation, leading to enhancement of NRF2 degradation. Previously reported Cys151-directed compounds decrease KEAP1-CUL3 interactions …

Adapt-On-Demand: Enabling Flexible And Scalable Adaptive Radiotherapy Through Workflow Automation, Sean Domal, Min Geon Choi, Justin Visak, Ruiqi Li, Taoran Li, Boon-Keng Kevin Teo, Xiaodong Zhao, Matthew Schmidt, Eric Laugeman, David Parsons, Yang Kyun Park, Shahed Badiyan, David Sher, Mu-Han Lin

2020-Current year OA Pubs

PURPOSE: CT-guided adaptive radiotherapy (CTgART) offers significant clinical benefits, but its utilization is often limited by resource demands and rigid workflows. This study presents a flexible and scalable "Adapt-on-Demand" (AOD) framework that integrates the adaptive capabilities of the Varian Ethos platform with the high-throughput IGRT delivery of the Varian Halcyon, supported by automated scripting.

METHODS: We developed an end-to-end dual-platform workflow that dynamically transitions between ART and IGRT delivery based on patient needs. Key components include Eclipse Scripting API (ESAPI) automation to streamline adapted plan ingestion from the Ethos Treatment Planning and Management System (TPMS) export directory, compatibility conversion for …

Sympathetic And Parasympathetic Ganglion Blocks For Treatment Of Long Covid-19 Symptoms: A Scoping Review, Abhay Tyagi, Khushboo Singh, Preet Mohinder Singh, Frederic J Gerges

2020-Current year OA Pubs

BACKGROUND: Long COVID-19 affects approximately 10-30% of individuals who are infected with SARS-CoV-2 and is associated with persistent functional impairment and reduced quality of life. The heterogeneous, multisystemic nature and nonspecific symptomatology of long COVID-19 makes its treatment challenging. This scoping review evaluates existing evidence on sympathetic and parasympathetic ganglion blocks as potential interventions for patients suffering from long COVID-19.

OBJECTIVE: Our primary objective was to assess the effectiveness of sympathetic and parasympathetic ganglion blocks in treating patients with long COVID-19 by identifying the most commonly reported symptoms, symptom response to different block regimens, and any adverse effects associated with …

Culturally Tailored Materials For Smoking Cessation And Hiv Care Adherence Among Hispanic Adults: Protocol For Content Development And Formative Evaluation, Lorra Garey, Jacqueline J Charles, Ashley L Ruiz, Rodrigo Castillo-Avilés, Virmarie Correa-Fernández, Marshall K Cheney, Thomas P Giordano, Michael J Zvolensky

Faculty, Staff and Students Publications

Background: Hispanic people with HIV who smoke cigarettes experience unique stressors (eg, stigma), which contribute to health disparities. Anxiety sensitivity (AS) may worsen mood management problems, which are a leading barrier to smoking cessation. Interventions targeting AS can improve HIV-specific outcomes and smoking cessation. However, no prior research has culturally tailored an AS reduction program to improve quality of life among Hispanic people with HIV who smoke. The research team previously developed a mobile health (mHealth) intervention addressing AS reduction, smoking cessation, and HIV care management for Black people with HIV who smoke. Building on this work, this study represents …

Changes In Internet Search Term Popularity In Elder Mistreatment (2018-2023): Infodemiology Study Of Google Trends Data, Nicholas Sevey, Melvin Livingston, Kristin Lees-Haggerty, Olanike Ojelabi, Randi Campetti, Jason Burnett, Carolyn E Z Pickering, David Hancock, Rachit Sabharwal, Michael Brad Cannell

Faculty, Staff and Student Publications

Background: Elder mistreatment (EM) is a significant public health problem that is frequently underdetected and underreported. Insufficient public recognition and engagement have been hypothesized as one contributor to this underreporting; however, few data sources exist to quantify public awareness or engagement with EM at the population level.

Objective: This study examined relative internet search interest in EM compared with other forms of abuse (child abuse and domestic violence) in the United States using Google Trends data.

Methods: We analyzed Google Trends data to compare the Relative Search Index (RSI) for the terms "elder abuse," "child abuse," and "domestic violence" in …

Ms-Gator: Multi-Scale Graph Attention With Topological Reasoning For Segmentation And Classification Of Prostate Cancer Based On Gleason Scores Using Histopathology Images, Sujata Patil, Mahadeva Swamy, Kavitha Sooda, Rajanikanth Vadigepalli, Khalid Nazim Abdul Sattar, Md Rafeeq

Department of Pathology, Anatomy, and Cell Biology Faculty Papers

Prostate cancer is one of the prevalent and potentially fatal malignancies, affecting men globally. Accurate segmentation and classification of prostate cancer in histopathology images remain challenging due to complex tissue architecture, staining variability, and high inter-observer differences in manual diagnosis. To address these challenges, this research proposes a Multi-Scale Graph Attention with Topological Reasoning (MS-GATOR) for segmentation and classification of prostate cancer based on Gleason Scores (GS). The MS-GATOR incorporates topological reasoning with hierarchical biological structures by constructing a graph-based representation among three spatial scales such as nuclei, glands, and tissues using Delaunay triangulation to capture both geometric and photometric …

Engineering Of Genetically Encoded Programmable Calcium Channel Inhibitory Binders, Xiaoxuan Liu, Sher Ali, Tien-Hung Lan, Decheng Wang, Brendan Mckee, Tatsuki Nonomura, Siyao Liu, Feng Zhao, Michael X Zhu, Yun Huang, Qing Deng, Guolin Ma, Yubin Zhou

Faculty, Staff and Student Publications

Store-operated Ca2+ release-activated Ca2+ (CRAC) channels, composed of STIM and ORAI, are essential for immune and developmental processes, and their dysregulation underlies channelopathies such as Stormorken syndrome. Here, we report the engineering of genetically encoded CRAC channel inhibitory binders (CRABs) derived from the ORAI C-terminal tail. Guided by deep mutational scanning, we optimize a membrane-anchored CRAB variant that potently inhibits Ca2+ influx and NFAT signaling, and rescues thrombocytopenia-like phenotypes in a zebrafish model of Stormorken syndrome. To enable tunable inhibition, we further design oligomeric, optogenetic (Opto-CRAB), and chemogenetic (Chemo-CRAB) variants, providing graded and real-time control of CRAC activity. Chemo-CRAB further …

Experiences And Service-Uptake Factors Of Receiving And Providing Care For Meningitis And Its Sequelae: A Qualitative Systematic Review, Margarita Andreeva, Maria Pyatnitskaya, Karina Kochneva, Ekaterina Sviatskaia, Maria Spryshkova, Melissa Meyer, Dina Baimukhambetova, Mark Kosenko, Aigun Mursalova, Nina Avdeenko, Elena Kondrikova, Jonathan Zheng, Ka Yan Cheung, Audrey Dunn Galvin, Tom Jewell, Zoe Moula, Sarah Neill, Mikhail Zinchuk, Alla Guekht, Daniel Munblit

School of Nursing and Midwifery

Background: Meningitis is a life-threatening condition with substantial morbidity and mortality, especially in low- and middle-income countries (LMICs). While quantitative research has enhanced the understanding of diagnostic and treatment efficacy, qualitative data regarding the lived experiences remain underexplored. This systematic review synthesises qualitative evidence on the experiences of patients, caregivers, and healthcare providers regarding meningitis diagnosis, treatment, and care, as well as the barriers and facilitators influencing service uptake and provision. The review aimed to inform the development of World Health Organization guidelines for improving meningitis care. Methods: This systematic review was registered in PROSPERO (CRD42024514413). A comprehensive search of …

Loss Of Znrf3/Rnf43 Unleashes Egrfr In Cancer, Fei Yue, Amy T Ku, Payton D Stevens, Megan N Michalski, Weiyu Jiang, Jianghua Tu, Zhongcheng Shi, Yongchao Dou, Yi Wang, Xin-Hua Feng, Galen Hostetter, Xiangwei Wu, Shixia Huang, Noah F Shroyer, Bing Zhang, Bart O Williams, Qingyun Liu, Xia Lin, Yi Li

Faculty, Staff and Students Publications

ZNRF3 and RNF43 are closely related transmembrane E3 ubiquitin ligases with significant roles in development and cancer. Conventionally, their biological functions have been associated with regulating WNT signaling receptor ubiquitination and degradation. However, our proteogenomic studies have revealed EGFR as the protein most negatively correlated with ZNRF3/RNF43 mRNA levels in multiple human cancers. Through biochemical investigations, we demonstrate that ZNRF3/RNF43 interact with EGFR via their extracellular domains, leading to EGFR ubiquitination and subsequent degradation facilitated by the E3 ligase RING domain. Overexpression of ZNRF3 reduces EGFR levels and suppresses cancer cell growth in vitro and in vivo, whereas knockout of …

Utility Of Right Ventricular Mass Ratios In Recipients With Pulmonary Hypertension: A United Network For Organ-Sharing Database Analysis, Matthew P. Weber, Danial Ahmad, Howard J. Eisen, Eugene Storozynsky, René J. Alvarez, J. Eduardo Rame, Keshava Rajagopal, John W. Entwistle, Charles Hoopes, Vakhtang Tchantchaleishvili

Division of Cardiology Faculty Papers

PURPOSE: There is a lack of data reviewing the role of predicted cardiac mass ratio (PCMR) in transplant recipients with pulmonary hypertension (PH). In particular, the right ventricular (RV) mass ratio (RVMR) is a component of PCMR not yet studied separately for this purpose. We aimed to review the relationship of PCMR and RVMR with PH in terms of post-transplant overall survival.

METHODS: The United Network for Organ-Sharing (UNOS) database was queried for primary heart transplant (HTx) patients from 2004 to 2023. Predicted RVMR was calculated for donors and recipients. A parsimonious multivariable model Cox model was formed for risk …

Characterization Of Subclonal Variants In Hg002 Genome In A Bottle Reference Material As A Resource For Benchmarking Variant Callers., Camille A. Daniels, Adetola A. Abdulkadir, Megan H. Cleveland, Jennifer H. Mcdaniel, David Jáspez, Luis Alberto Rubio-Rodríguez, Adrián Muñoz-Barrera, José Miguel Lorenzo-Salazar, Carlos Flores, Byunggil Yoo, Sayed Mohammad Ebrahim Sahraeian, Yina Wang, Massimiliano Rossi, Arun Visvanath, Lisa Murray, Wei-Ting Chen, Severine Catreux, James Han, Rami Mehio, Gavin Parnaby, Andrew Carroll, Pi-Chuan Chang, Kishwar Shafin, Daniel Cook, Alexey Kolesnikov, Lucas Brambrink, Mohammed Faizal Eeman Mootor, Yash Patel, Takafumi N. Yamaguchi, Paul C. Boutros, Karolina Sienkiewicz, Jonathan Foox, Christopher E. Mason, Bryan R. Lajoie, Carlos A. Ruiz-Perez, Semyon Kruglyak, Justin M. Zook, Nathan D. Olson

Manuscripts, Articles, Book Chapters and Other Papers

We developed a benchmark set of subclonal variants in the Genome in a Bottle (GIAB) Consortium HG002 reference material (RM) DNA for evaluating lower-frequency variant callsets. We used a somatic variant caller with high-coverage (300×) whole-genome sequencing data from the GIAB Ashkenazi Jewish trio to identify potential subclonal variants in the HG002 RM DNA. Using orthogonal sequencing data and manual curation, we defined a benchmark set with 85 high-confidence subclonal single-nucleotide variants (SNVs) (allele frequency [AF] > 5%) and a benchmark region covering 2.45 Gbp of the autosomes. External validation supported that it can be used to reliably identify both false …

A Prolonged Nightly Fasting Plus Telehealth Coaching Intervention (Pnf+) For Men On Androgen Deprivation Therapy For Pca: A Pilot Feasibility Randomized Controlled Trial, Kuang-Yi Wen, Julianne Freedman, Kevin K. Zarrabi, Rachel Slamon, Rita Smith, Jessica Liang, Patrick Mille, William J. Tester, William Kevin Kelly

Department of Medical Oncology Faculty Papers

Background/Objectives: This study aimed to assess the feasibility and acceptability of a 3-month health coaching intervention to promote PNF and healthy diet for men on ADT for PCa.

Methods: The study was carried out via a two-armed randomized controlled trial including 40 patients with PCa at a medical center in Philadelphia. During the 3-month period, the intervention group (PNF+) received health coaching utilizing an interactive text message system, and the control group received healthy eating text messages for the same duration. The outcome variables were feasibility and acceptability.

Results: The PNF+ group (n = 27) had high …

Mondo: Integrating Disease Terminology Across Communities., Nicole A Vasilevsky, Sabrina Toro, Nicolas Matentzoglu, Joseph E Flack, Kathleen R Mullen, Harshad Hegde, Sarah Gehrke, Patricia L Whetzel, Yousif Shwetar, Nomi L Harris, Mee S Ngu, Gioconda L Alyea, Megan S Kane, Paola Roncaglia, Eric Sid, Courtney L Thaxton, Valerie Wood, Roshini S Abraham, Maria Isabel Achatz, Pamela Ajuyah, Joanna S Amberger, Lawrence Babb, Jasmine Baker, James P Balhoff, Jonathan S Berg, Amol Bhalla, Xavier Bofill-De Ros, Ian R Braun, Eleanor C Broeren, Blake K Byer, Alicia B Byrne, Tiffany J Callahan, Leigh Carmody, Lauren E Chan, Amanda R Clause, Julie S Cohen, Marcello Deluca, Natalie T Deuitch, May Flowers, Jamie Fraser, Toyofumi Fujiwara, Vanessa Gitau, Jennifer L Goldstein, Dylan Gration, Tudor Groza, Benjamin M Gyori, William Hankey, Jason A Hilton, Daniel S Himmelstein, Stephanie S Hong, Charles T Hoyt, Robert Huether, Eric Hurwitz, Julius O B Jacobsen, Atsuo Kikuchi, Sebastian Köhler, Daniel R Korn, David Lagorce, Bryan J Laraway, Jane Y Li, Adriana J Malheiro, James Mclaughlin, Birgit H M Meldal, Shruthi Mohan, Sierra A T Moxon, Monica C Munoz-Torres, Tristan H Nelson, Frank W Nicholas, David Ochoa, Daniel Olson, Tudor I Oprea, Tomiko T Oskotsky, David Osumi-Sutherland, Kelley Paris, Helen E Parkinson, Zoë M Pendlington, Xiao P Peng, Amy Pizzino, Sharon E Plon, Bradford C Powell, Julie C Ratliff, Heidi L Rehm, Lyubov Remennik, Erin R Riggs, Sean Roberts, Peter N Robinson, Justyne E Ross, Kevin Schaper, Brian M Schilder, Johanna L Schmidt, Elliott W Sharp, Morgan N Similuk, Damian Smedley, Tam P Sneddon, Rachel Sparks, Ray Stefancsik, Gregory S Stupp, Shilpa Sundar, Terue Takatsuki, Imke Tammen, Kezang C Tshering, Deepak R Unni, Eloise Valasek, Adeline Vanderver, Alex H Wagner, Ryan F Webb, Danielle Welter, Doron Yaya-Stupp, Andreas Zankl, Xingmin Aaron Zhang, Julie A Mcmurry, Christopher G Chute, Ada Hamosh, Christopher J Mungall, Melissa A Haendel

Faculty Research 2026

Precision medicine aims to enhance diagnosis, treatment, and prognosis by integrating multimodal data at the point of care. However, challenges arise due to the vast number of diseases, differing methods of classification, and conflicting terminological coding systems and practices used to represent molecular definitions of disease. This lack of interoperability artificially constrains the potential for diagnosis, clinical decision support, care outcome analysis, as well as data linkage across research domains to support the development or repurposing of therapeutics. There is a clear and pressing need for a unified system for managing disease entities⁠-including identifiers, synonyms, and definitions. To address these …

Mondo: Integrating Disease Terminology Across Communities, Nicole A Vasilevsky, Sabrina Toro, Nicolas Matentzoglu, Joseph E Flack, Kathleen R Mullen, Harshad Hegde, Sarah Gehrke, Patricia L Whetzel, Yousif Shwetar, Nomi L Harris, Mee S Ngu, Gioconda L Alyea, Megan S Kane, Paola Roncaglia, Eric Sid, Courtney L Thaxton, Valerie Wood, Roshini S Abraham, Maria Isabel Achatz, Pamela Ajuyah, Joanna S Amberger, Lawrence Babb, Jasmine Baker, James P Balhoff, Jonathan S Berg, Amol Bhalla, Xavier Bofill-De Ros, Ian R Braun, Eleanor C Broeren, Blake K Byer, Alicia B Byrne, Tiffany J Callahan, Leigh C Carmody, Lauren E Chan, Amanda R Clause, Julie S Cohen, Marcello Deluca, Natalie T Deuitch, May Flowers, Jamie Fraser, Toyofumi Fujiwara, Vanessa Gitau, Jennifer L Goldstein, Dylan Gration, Tudor Groza, Benjamin M Gyori, William Hankey, Jason A Hilton, Daniel S Himmelstein, Stephanie S Hong, Charles T Hoyt, Robert Huether, Eric Hurwitz, Julius O B Jacobsen, Atsuo Kikuchi, Sebastian Köhler, Daniel R Korn, David Lagorce, Bryan J Laraway, Jane Y Li, Adriana J Malheiro, James Mclaughlin, Birgit H M Meldal, Shruthi Mohan, Sierra A T Moxon, Monica C Munoz-Torres, Tristan H Nelson, Frank W Nicholas, David Ochoa, Daniel Olson, Tudor I Oprea, Tomiko T Oskotsky, David Osumi-Sutherland, Kelley Paris, Helen E Parkinson, Zoë M Pendlington, Xiao P Peng, Amy Pizzino, Sharon E Plon, Bradford C Powell, Julie C Ratliff, Heidi L Rehm, Lyubov Remennik, Erin R Riggs, Sean Roberts, Peter N Robinson, Justyne E Ross, Kevin Schaper, Brian M Schilder, Johanna L Schmidt, Elliott W Sharp, Morgan N Similuk, Damian Smedley, Tam P Sneddon, Rachel Sparks, Ray Stefancsik, Gregory S Stupp, Shilpa Sundar, Terue Takatsuki, Imke Tammen, Kezang C Tshering, Deepak R Unni, Eloise Valasek, Adeline Vanderver, Alex H Wagner, Ryan F Webb, Danielle Welter, Doron Yaya-Stupp, Andreas Zankl, Xingmin Aaron Zhang, Julie A Mcmurry, Christopher G Chute, Ada Hamosh, Christopher J Mungall, Melissa A Haendel

Faculty, Staff and Students Publications

Precision medicine aims to enhance diagnosis, treatment, and prognosis by integrating multimodal data at the point of care. However, challenges arise due to the vast number of diseases, differing methods of classification, and conflicting terminological coding systems and practices used to represent molecular definitions of disease. This lack of interoperability artificially constrains the potential for diagnosis, clinical decision support, care outcome analysis, as well as data linkage across research domains to support the development or repurposing of therapeutics. There is a clear and pressing need for a unified system for managing disease entities⁠-including identifiers, synonyms, and definitions. To address these …

Nanog Proximity Proteomics Maps Neighborhood Hubs Linked To Mesenchymal Stem Cell Stemness And Chromatin Control, Kyoung-Jae Choi, Michail Tyryshkin, Harathi Jonnagaddala, Allan Chris M Ferreon, Marian Kalocsay, Josephine C Ferreon

Faculty, Staff and Students Publications

NANOG overexpression has been reported to reverse aging-associated decline in mesenchymal stem/stromal cell (MSC) function, but the molecular machinery engaged by NANOG in MSCs remains incompletely defined. Here, we applied APEX proximity labeling coupled with quantitative mass spectrometry to define the NANOG proximity interactome (proxeome) in human MSCs. Of 1040 quantified proteins, 828 were significantly enriched in the APEX-NANOG (H2O2 labeling) samples, consistent with a broad NANOG-centered neighborhood rather than a single stoichiometric complex. Enriched proteins encompass RNA-processing pathways (including splicing/RNP factors and selected m6A-related proteins), transcriptional coactivation and elongation control (Mediator and 7SK/P-TEFb regulators), chromatin repression/poising modules (Polycomb and …

Natural Language Generation In Healthcare: A Review Of Methods And Applications, Mengxian Lyu, Xiaohan Li, Ziyi Chen, Jinqian Pan, Cheng Peng, Sankalp Talankar, Yonghui Wu

Faculty, Staff and Student Publications

Objective: This study presents a systematic review of natural language generation (NLG) methods and applications in the medical domain, providing quantitative and qualitative analyses to answer four key research questions regarding methods, evaluation, applications, and challenges of NLG in healthcare.

Methods: We searched PubMed, ACM Digital Library, Web of Science, Science Direct, Scopus, Embase, and ACL Anthology for NLG-related studies in healthcare from 2018 to 2024. Out of 3,988 research articles, 113 met the inclusion criteria and were analyzed across data modality, model architecture, evaluation metrics, and application domain.

Results and conclusion: NLG in healthcare has grown substantially, with annual …

Predicting Ventilation From Single Breathing Phase Non-Contrast Ct Using Swin Transformers, Yi-Kuan Liu, Hsu-Ting Kuo, Alaa Melek, Richard Castillo, Yevgeniy Vinogradskiy, Lili Zhao, Girish Nair, Edward Castillo

Department of Radiation Oncology Faculty Papers

BACKGROUND: Pulmonary ventilation imaging enables functional avoidance radiotherapy treatment plans by quantifying regional lung function. However, current clinical standards, such as 99𝑚Tc-based single-photon emission computed tomography (SPECT), rely on radioactive tracers, which can introduce imaging deposition artifacts. CT ventilation imaging (CTVI) methods based on both physical models and deep learning approaches currently require multiple CT images as input, such as the inhale/exhale phases of a 4DCT. While the theoretical foundation of physics-based CTVI is built on multi-phase information, the feasibility of single-phase deep learning CTV models has not been determined.

PURPOSE: While deep learning methods have predicted SPECT ventilation from …

Multiscale Metabolic Covariance Networks Uncover Stage-Specific Biomarker Signatures Across The Alzheimer's Disease Continuum., Juan Antonio K Chong Chie, Scott A Persohn, Ravi S Pandey, Olivia R Simcox, Gregory W. Carter, Paul Salama, Paul R Territo, The Alzheimer’S Disease Neuroimaging Initiative

Faculty Research 2026

INTRODUCTION: Functional connectomics studies leverage the power of interregional brain relationships using graph theory of glycolytic metabolism to establish neural connections and their roles in cognition and disease and to monitor therapeutic responses.

METHODS: Using a retrospective clinical population (N = 431) from ADNI, we evaluated disease changes using metabolic covariance analysis. In addition, we developed a novel region set enrichment analysis (RSEA) to detect brain functional changes based on metabolic variations. Results were aligned with transcriptomic signatures and clinical cognitive assessments (CCAs).

RESULTS: Our findings highlight sexual dimorphic changes across the disease spectrum, which suggest brain network reorganization occurs …

Deep Learning In Fetal, Infant, And Toddler Neuroimaging Research, Jenna H Chin, Madeleine K Wyburd, Vladislav Ayzenberg, Laurie Bayet, Berkin Bilgic, Emily M Chen, Yuting Chen, Áine Dineen, Shohei Fujita, Janelle Liu, Yohan Jun, M Catalina Camacho, Lilla Zöllei

2020-Current year OA Pubs

Artificial intelligence (AI) is increasingly being integrated into everyday tasks and work environments. However, its adoption in medical image analysis has progressed more slowly due to high clinical stakes, limited availability of labeled data, and substantial variability in imaging protocols and population. These challenges are further pronounced in the field of fetal, infant, and toddler (FIT) neuroimaging, where datasets are especially scarce and subject to large amounts of anatomical variability. However, deep learning (DL), a specific method within machine learning, which is itself a subfield of AI, has emerged as a powerful framework to adapt to the challenges of medical …

Influence Of Gut Microbiota On Response To Immune Check Point Inhibitors In Masld Patients With Hcc: Unraveling The Connection, Mazen Elsheikh, Mohamad Ali Ibrahim, Sherry Fares, Megha Bhongade, Karim Adhem, Ximena I Ramirez-Morales, Ahmed O Kaseb, Joseph Petrosino, Manal M Hassan, Prasun K Jalal

Faculty, Staff and Students Publications

Immune checkpoint inhibitors (ICIs) have emerged as a promising treatment for various cancers, including advanced hepatocellular carcinoma (HCC). However, a significant proportion of patients with HCC, particularly those with metabolic dysfunction-associated liver disease (MASLD), exhibit resistance to ICI therapy. Studies have revealed that the presence of specific gut bacteria, such as Akkermansia, Bifidobacterium, and Lachnoclostridium, is associated with improved outcomes with ICI-treated HCC patients. Conversely, the overgrowth of bacteria like Enterobacteriaceae is linked to resistance to therapy. This review investigates the role of gut microbiota in shaping immune checkpoint inhibitor responses in MASLD-related hepatocellular carcinoma, focusing on how dysbiosis may …

Driveline Infections Among Patients Supported With Left Ventricular Assist Devices: A Single Center Sixteen-Year Longitudinal Profile, Anh Nguyen, Alexis Shafii, Gabriel Loor, Andrew Civitello, O Howard Frazier, Todd Rosengart, Kenneth Liao

Faculty, Staff and Students Publications

Background: Left ventricular assist device (LVAD) driveline infections significantly impact patient outcomes. This study aimed to identify their risk factors.

Methods: We analyzed LVAD data from our institutional Intermacs database (January 1, 2008-December 31, 2023), combining primary implants and pump exchanges. Patient characteristics were summarized as frequencies for categorical variables and median (IQR) for continuous variables. The nature of repeated infection events was handled by the Andersen-Gill method within a multivariable Cox proportional hazards model for cause-specific hazard of driveline infections, accounting for death and heart transplant as competing risks.

Results: Our cohort included 1026 LVAD implants. Median patient age …

Preoperative Imaging For Cochlear Implantation: A Global Consensus, Farid Alzhrani, Craig Buchman, Et Al.

2020-Current year OA Pubs

OBJECTIVE: Preoperative imaging is vital for cochlear implant surgeries, aiding diagnosis, and surgical planning. This study evaluated global practices and the value of preoperative imaging through an international survey.

METHODS: A cross-sectional survey was conducted among international cochlear implantation experts using a 112-item questionnaire. The study explored imaging modalities, anatomical targets, evaluated parameters, and different imaging approaches' perceived value and risks. Participants were recruited from a global consortium of otolaryngology, otology, neurotology, and cochlear implant surgery professionals.

RESULTS: Thirty-nine practitioners from 36 centers in 16 countries completed the survey (95.1% response rate). All used computed tomography (CT) and magnetic resonance …

Gene-Agnostic Therapeutic Strategies For Inherited Retinal Diseases: Neuroprotection And Immunomodulation, Lucas W. Rowe, S. Patricia Becerra, Robert E. Maclaren, Robert L. Avery, Charles C. Wykoff, Allen C. Ho, Carl D. Regillo, Dean Eliott, Andrew Osborne, Katie M. Binley, Thomas A. Ciulla

Wills Eye Hospital Papers

Background/Objectives: Inherited retinal diseases (IRDs) represent a genetically heterogeneous group of disorders caused by mutations in over 280 genes with more than 3100 identified variants. While gene-specific replacement therapies have achieved landmark success with voretigene neparvovec (Luxturna) for biallelic RPE65-associated retinal dystrophy, developing individual therapies for each genetic subtype remains impractical. This review examines gene-agnostic therapeutic approaches utilizing neuroprotection and immunomodulation that target common pathophysiological mechanisms shared across multiple IRD genotypes. Methods: We reviewed the literature on neuroprotective and immunomodulatory gene therapy strategies for IRDs, focusing on neurotrophic factors and complement system modulation. Results: Neuroprotective approaches delivering neurotrophic factors—including pigment …

From Fair To Cure: Guidelines For Computational Models Of Biological Systems, Herbert M. Sauro, Eran Agmon, Michael L. Blinov, John H. Gennari, Joseph L. Hellerstein, Adel Heydarabadipour, Bartholomew E. Jardine, Elebeoba May, David P. Nickerson, Lucian P. Smith, Gary D. Bader, Frank T. Bergmann, Patrick M. Boyle, Andreas Dräger, James R. Faeder, Song Feng, Juliana Freire, Fabian Fröhlich, James A. Glazier, Thomas E. Gorochowski, Tomas Helikar, Henning Hermjakob, Stefan Hoops, Peter Hunter, Princess I. Imoukhuede, Sarah M. Keating, Matthias König, Reinhard Laubenbacher, Leslie M. Loew, Carlos F. Lopez, William W. Lytton, Rahuman S. Malik-Sheriff, Andrew Mcculloch, Pedro Mendes, Lealem Mulugeta, Chris J. Myers, Jerry G. Myers, Anna Niarakis, David D. Van Niekerk, Brett G. Olivier, Alexander A. Patrie, Ellen M. Quardokus, Nicole Radde, Johann M. Rohwer, Sven Sahle, James C. Schaff, Falk Schreiber, T. J. Sego, Janis Shin, Jacky L. Snoep, Rajanikanth Vadigepalli, H. Steven Wiley, Dagmar Waltemath, Ion I. Moraru

Computational Medicine Center Faculty Papers

Guidelines for managing scientific data have been established under the FAIR principles, requiring that data be Findable, Accessible, Interoperable, and Reusable. In many scientific disciplines, especially computational biology, both data and models are key to progress. For this reason, and recognizing that such models are a very special type of "data", we argue that computational models, especially mechanistic models prevalent in medicine, physiology and systems biology, deserve a complementary set of guidelines. We propose the CURE principles, emphasizing that models should be Credible, Understandable, Reproducible, and Extensible. We delve into each principle, discussing verification, validation, and uncertainty quantification for model …

Functional And Structural Basis Of A Hypermorphic Trpc3 Variant, Briar Bell, Angela M Jaramillo-Granada, Luis O Romero, Irene A Gutierrez, Venkata K P S Mallampalli, Guizhen Fan, Sameer Varma, Matthew L Baker, Irina I Serysheva, Valeria Vásquez, Julio F Cordero-Morales

Faculty, Staff and Student Publications

Cerebellar ataxias are characterized by impaired motor coordination resulting from neuronal dysfunction within the cerebellum. The mechanisms underlying this pathology and its cerebellar-specific neurodegeneration remain unknown. We uncover how a gain-of-function canonical transient receptor potential member 3 (TRPC3) mutation, coupled with a cerebellum-specific isoform, stabilizes the channel’s open state, resists the leading inhibitor Pyr3, and drives calcium-dependent cell death. Restoring calcium homeostasis by expressing a Purkinje cell calcium pump improves cell viability. Transgenic expression of the TRPC3 hypermorphic variant in Caenorhabditis elegans induces neurodegeneration, confirming its pathogenicity across species. Cryo–electron microscopy and molecular simulations reveal the structural basis for the …