Digital Commons Network^™

Peroxisomal Integrity In Demyelination-Associated Microglia Enables Cellular Debris Clearance And Myelin Renewal In Mice, Joseph A Barnes-Vélez, Xiaohong Zhang, Yaren L Peña Señeriz, Kiersten A Scott, Yinglu Guan, Jian Hu

Faculty, Staff and Student Publications

Demyelination associated microglia (DMAM) orchestrate the regenerative response to demyelination by clearing myelin debris and promoting oligodendrocyte maturation. Peroxisomal metabolism has emerged as a candidate regulator of DMAMs, though the cell-intrinsic contribution in microglia remains undefined. Here we elucidate the role of peroxisome integrity in DMAMs, using cuprizone-mediated demyelination coupled with conditional KO of peroxisome biogenesis factor 5 (PEX5) in microglia. Absent demyelination, PEX5 conditional KO (PEX5cKO) had minimal impact on homeostatic microglia. However, during cuprizone-induced demyelination, the emergence of DMAMs unmasked a critical requirement for peroxisome integrity. At peak demyelination, PEX5cKO DMAMs exhibited increased lipid droplet burden and reduced …

Ventilation-Perfusion Scan: A Functional Imaging Approach To Regional Lung Disease In Primary Ciliary Dyskinesia, Gabriel Román-Ríos, Gabriel Rosario-Ortiz, Marcos J Ramos-Benitez, Ricardo A Mosquera, Wilfredo De Jesús-Rojas

Faculty, Staff and Student Publications

Introduction: As a rare genetic disorder defined by defective ciliary motility, Primary Ciliary Dyskinesia (PCD) leads to chronic respiratory complications. A founder variant in the RSPH4A [c.921+3_921+6delAAGT] gene, common in Puerto Rico, impairs ciliary function and contributes to progressive lung disease. Today, the clinical value of ventilation/perfusion (V/Q) scans in PCD has not been thoroughly investigated as well as pulmonary function tests (PFTs) and chest imaging. To explore the role and clinical utility of V/Q scans in PCD.

Methods: Retrospective evaluation of pulmonary function tests, chest imaging, and Tc-99m DTPA ventilation and Tc-99m MAA perfusion scans in ten patients with …

Racial And Ethnic Disparities In Clinical Characteristics And Outcomes In Adults With Encephalitis: A Retrospective Study, Sienna Wu, Rodrigo Hasbun, Ralph Habis, Jordan Benderoth, Ivany Patel, Ashutosh Gupta, Megan Goyal, Arun Venkatesan, John C Probasco, Paris Bean, Ashley Heck, Laya Rao, Rajesh K Gupta

Faculty, Staff and Student Publications

Background and objectives: This study aims to assess whether adult patients with encephalitis from different racial and ethnic backgrounds exhibit significant differences in clinical presentation, diagnostic findings, and outcomes.

Design and methods: A retrospective cohort study was conducted by utilizing the electronic health records of encephalitis patients in the greater Houston and Baltimore areas. Patients were categorized by race/ethnicity into White or ethnic minority (including Black, Hispanic, and Asian patients). Data was analyzed for the presence of significant differences in clinical characteristics between the two groups.

Results: Among 599 patients, 312 (52.1%) were White and 287 (47.9%) were of an …

Accelerating Ai Innovation In Healthcare: Real-World Clinical Research Applications On The Mayo Clinic Platform, Yue Yu, Xinyue Hu, Sivaraman Rajaganapathy, Jingna Feng, Ahmed Abdelhameed, Xiaodi Li, Jianfu Li, Xiaoke Liu, Liu Yang, Nilüfer Ertekin-Taner, Phil Fiero, Soulmaz Boroumand, Richard Larsen, Maneesh Goyal, Clark C Otley, Nansu Zong, Vijay H Shah, John D Halamka, Cui Tao

Faculty, Staff and Student Publications

Artificial intelligence (AI) holds promise for healthcare, but real-world implementation remains difficult. The Mayo clinic platform (MCP) addresses this by providing scalable, multi-institutional, de-identified data and analytical tools. Through four research projects, we demonstrate MCP's ability to support efficient cohort identification, AI model development, and real-world evidence generation. MCP enables broader accessibility and standardization compared to institutional EHRs, positioning it as a powerful platform for advancing translational research and precision medicine.

Genome-Wide Gene-Sleep Interaction Study Identifies Novel Lipid Loci In 732,564 Participants, Raymond Noordam, Wenyi Wang, Pavithra Nagarajan, Heming Wang, Michael R Brown, Amy R Bentley, Qin Hui, Aldi T Kraja, John L Morrison, Jeffrey R O'Connel, Songmi Lee, Karen Schwander, Traci M Bartz, Lisa De Las Fuentes, Mary F Feitosa, Xiuqing Guo, Xu Hanfei, Sarah E Harris, Zhijie Huang, Mart Kals, Christophe Lefevre, Massimo Mangino, Yuri Milaneschi, Peter J Van Der Most, Natasha L Pacheco, Nicholette D Palmer, Varun Rao, Rainer Rauramaa, Quan Sun, Yasuharu Tabara, Dina Vojinovic, Yujie Wang, Stefan Weiss, Qian Yang, Wei Zhao, Wanying Zhu, Md Abu Yusuf Ansari, Hugues Aschard, Pramod Anugu, Themistocles L Assimes, John Attia, Laura D Baker, Christie Ballantyne, Lydia Bazzano, Eric Boerwinkle, Brain Cade, Hung-Hsin Chen, Wei Chen, Yii-Der Ida Chen, Zekai Chen, Kelly Cho, Ileana De Anda-Duran, Latchezar Dimitrov, Anh Do, Todd Edwards, Tariq Faquih, Aroon Hingorani, Susan P Fisher-Hoch, J Michael Gaziano, Sina A Gharib, Ayush Giri, Mohsen Ghanbari, Hans Jörgen Grabe, Mariaelisa Graff, C Charles Gu, Jiang He, Sami Heikkinen, James Hixson, Yuk-Lam Ho, Michelle M Hood, Serena C Houghton, Carrie A Karvonen-Gutierrez, Takahisa Kawaguchi, Tuomas O Kilpeläinen, Pirjo Komulainen, Henry J Lin, Gregorio V Linchangco, Annemarie I Luik, Jintao Ma, James B Meigs, Joseph B Mccormick, Cristina Menni, Ilja M Nolte, Jill M Norris, Lauren E Petty, Hannah G Polikowsky, Laura M Raffield, Stephen S Rich, Renata L Riha, Thomas C Russ, Edward A Ruiz-Narvaez, Colleen M Sitlani, Jennifer A Smith, Harold Snieder, Tamar Sofer, Botong Shen, Jingxian Tang, Kent D Taylor, Maris Teder-Laving, Rima Triatin, Michael Y Tsai, Henry Völzke, Kenneth E Westerman, Rui Xia, Jie Yao, Kristin L Young, Ruiyuan Zhang, Alan B Zonderman, Xiaofeng Zhu, Jennifer E Below, Simon R Cox, Michelle Evans, Myriam Fornage, Ervin R Fox, Nora Franceschini, Sioban D Harlow, Elizabeth Holliday, M Arfan Ikram, Tanika Kelly, Timo A Lakka, Deborah A Lawlor, Changwei Li, Ching-Ti Liu, Reedik Mägi, Alisa K Manning, Fumihiko Matsuda, Alanna C Morrison, Matthias Nauck, Kari E North, Brenda Wjh Penninx, Michael A Province, Bruce M Psaty, Jerome I Rotter, Tim D Spector, Lynne E Wagenknecht, Ko Willems Van Dijk, Lifelines Cohort Study, Million Veteran Program, Cashell E Jaquish, Peter Wf Wilson, Patricia A Peyser, Patricia B Munroe, Paul S De Vries, W James Gauderman, Yan V Sun, Han Chen, Clint L Miller, Thomas W Winkler, Dabeeru C Rao, Susan Redline, Diana Van Heemst

Faculty, Staff and Student Publications

Background and aims: Deviations from the population mean in sleep duration have been associated with increased risk for developing dyslipidemia and atherosclerotic cardiovascular disease, but the mechanism of effect is poorly characterized. We performed large-scale genome-wide gene-sleep interaction analyses of lipid levels to identify genetic variants underpinning the biomolecular pathways of sleep-associated lipid disturbances and to suggest possible druggable targets.

Methods: We collected data from 55 cohorts with a combined sample size of 732,564 participants (87 % European ancestry) with data on lipid traits (high-density lipoprotein [HDL-c] and low-density lipoprotein [LDL-c] cholesterol and triglycerides [TG]). Short (STST) and long (LTST) …

Blood Flow Regulates Metabolism In Hematopoietic Development, Pamela L Wenzel

Faculty, Staff and Student Publications

Blood flow modifies oxygen availability and biomechanical forces within the vasculature of the embryo as the hematopoietic system develops. The aorta-gonad-mesonephros (AGM) envelops the largest artery in the body and is a critical site for the emergence of hematopoietic stem cells (HSCs). Herein, I discuss the role of hypoxia-inducible factors (HIFs) and force as determinants of metabolism and fate determination. To address the effects of blood flow on hematopoietic development, I employ mouse embryo models and biomimetic culture. Real-time cell metabolic analyses show that oxygen consumption rates (OCR) and extracellular acidification rates (ECAR) are altered by flow in cultures of …

Multisite, Multiancestry Genome-Wide Association Study Meta-Analysis Of Functional Seizure Disorder In A Hospital Sample Of 675,680 Patients, Slavina B Goleva, Costin Leu, Yen-Chen Anne Feng, David Burstein, Sanan Venkatesh, Rebecca Birnbaum, Veera M Rajagopal, Peter Straub, Jakob Christensen, Jocelyn F Bautista, Robyn M Busch, Imad M Najm, Jakob Grove, Anders D Børglum, Georgios Voloudakis, Panos Roussos, Jordan Smoller, Dennis Lal, Lea K Davis

Faculty, Staff and Student Publications

Background: Functional seizures (FS) are paroxysmal episodes that phenotypically resemble epileptic seizures but are not associated with brain epileptiform discharges; they are also known as psychogenic nonepileptic seizures. The exact etiology and pathophysiology of FS is unknown; however, trauma and stress-related disorders are known risk factors.

Methods: We used a validated algorithm applied to electronic health records to identify individuals with FS in 6 international biobanks and hospital sites. We conducted a multisite FS genome-wide association study (GWAS) meta-analysis, including 10,910 FS cases (9040 predicted European ancestry [EA] and 1870 predicted African ancestry [AA]) and 664,500 (561,150 EA and 103,350 …

Latent Classification Of Time-Dependent Transition Rates In Longitudinal Binary Outcome Data, Joonha Chang, Wenyaw Chan

Faculty, Staff and Student Publications

Continuous-time Markov chain (CTMC) models and latent classification methods are commonly used to analyze longitudinal categorical outcomes in medical research. While CTMC models are popular for their simplicity and effectiveness, their assumption of constant transition rates presents limitations in capturing dynamic behaviors. To address this, non-homogeneous continuous-time Markov chains (NH-CTMCs) have been developed, incorporating time-varying transition rates to enhance model flexibility. In this study, we leverage closed-form transition probabilities for a fully ergodic two-state NH-CTMC model and propose a latent class clustering approach to identify heterogeneous transition rate patterns within the population. We emphasize the potential advantages of these models …

“If He Did It, I Can Do It, Too. I Can Change My Life Around”: The Social Model Of Recovery Within The Context Of Recovery Homes Accepting Residents Prescribed Medications For Opioid Use Disorder, Jodie M Dewey, Kathryn R Gallardo, Meenakshi S Subbaraman, Amy A Mericle

Faculty, Staff and Student Publications

Introduction: This paper provides an in-depth examination of examines four recovery residences, that serve individuals prescribed medications for opioid use disorder (MOUD). The study has two primary aims: first, to deepen understanding of how recovery residences adopt and operationalize Social Model of Recovery principles; and second, to identify gaps in staff integration of residents receiving MOUD-gaps that may either support or undermine the integrity of the social model within these settings.

Methods: We conducted semi-structured interviews with 17 residents receiving MOUD living in four participating recovery homes. The interviews were conducted between August 2022 and January 2024 using a semi-structured …

Pregnancy And Breastfeeding Are Associated With Less Later-Life Cognitive Decline In A Longitudinal, Prospective Cohort, Molly M Fox, Jennifer E Bramen, Dayoon Kwon, Mark A Espeland, Yijia Sun, Li Zhang, Aladdin H Shadyab, Ramon Casanova, Joann E Manson, Marcus Y Chang, Verna R Porter, Leslie V Farland, Qian Xiao, Robert A Wild, Prabha Siddarth, Carolyn J Crandall

Faculty, Staff and Student Publications

Introduction: The brains of female mammals evolved to undergo structural and functional changes during pregnancy and lactation, equipping them for motherhood. However, long-term cognitive health implications of these adaptations in women are poorly understood.

Methods: In the Women's Health Initiative (WHI) Memory Study (WHIMS; n = 7427) and WHI Study of Cognitive Aging (WHISCA; n = 2304), postmenopausal women completed reproductive history interviews, annual global cognitive assessment from mean age 70 for up to 13 years, and multi-domain cognitive testing for up to 8 years.

Results: Each additional month pregnant was associated with higher scores of global cognition. Each additional …

Artificial Light At Night Extends Pollen Season And Elevates Allergen Exposure, Brandt Geist, Lin Meng, Daniel S W Katz, Huidong Li, Franz Hölker, Qian Xiao

Faculty, Staff and Student Publications

Artificial light at night (ALAN), a growing environmental stressor in urban ecosystems, disrupts natural light-dark cycles and alters plant phenological events such as leaf-out and flowering. However, the extent to which ALAN influences airborne pollen season timing and exacerbates allergy-related health risks remains largely understudied. This study investigates how ALAN influences the timing and duration of the airborne pollen season across the Northeastern United States from 2012 to 2023 and the consequences of allergenic pollen exposure. Using daily pollen concentrations from the National Allergy Bureau, ALAN data from the Visible Infrared Imaging Radiometer Suite product, and gridded Daymet climate data, …

Plasma Proteomic Profile Of Dietary Potassium And Incident Ckd, Jiaqi Yang, Lauren Bernard, Jingsha Chen, Valerie K Sullivan, Bing Yu, Eugene P Rhee, Paul A Welling, Casey M Rebholz

Faculty, Staff and Student Publications

Background:: There is a need for objective biomarkers of dietary potassium. The mechanisms through which dietary potassium influences kidney health are incompletely understood.

Methods:: Atherosclerosis Risk in Communities study participants at visit 3 (1993–1995) with dietary and proteomics data were randomly divided into discovery (N=6,814) and replication (N=3,380) sets. We examined associations between dietary potassium and 4,955 aptamers using multivariable linear regression, adjusting for sociodemographic factors, health behaviors, and estimated glomerular filtration rate, with a false discovery rate of 0.05. Then, we tested the prospective associations between potassium-related proteins and incident chronic kidney disease (CKD).

Results:: …

Adapting A Smartphone-Based Auricular Point Acupressure Self-Management Program For Rural Chronic Musculoskeletal Pain: Qualitative Study, Jungkyung Min, Peiyin Hung, Jane N Bolin, Rupsikha Bora, Sarah Pace, Patricia Pitones, Hulin Wu, Jennifer Kawi

Faculty, Staff and Student Publications

Background: Chronic musculoskeletal pain is more prevalent in rural areas where access to pain interventions, including complementary approaches like Auricular Point Acupressure (APA), remains limited. APA is a non-invasive, needle-free approach, and its smartphone-based self-management delivery model has not been optimized for rural contexts.

Objectives: To explore the perspectives of rural partners on adapting a smartphone-based Auricular Point Acupressure-Self-Management (APA-SM) program to better meet rural needs. Study objectives were to: (1) refine the APA-SM program for rural adults, (2) identify implementation barriers, (3) understand practice workflows and engagement, and (4) identify strategies to integrate the APA-SM program into rural pain …

Subgroup Identification Of Disparities In Buprenorphine Discontinuation In Opioid-Use Disorder: A Virtual Twins Machine Learning Approach Using Nationwide United States Claims Data, 2006–2022, Kehe Zhang, Paula A Jaimes-Buitron, Wanru Guo, Yanmin Gong, Yuanxiong Guo, Carolina Vivas Valencia, Cici Bauer

Faculty, Staff and Student Publications

Buprenorphine retention is crucial for effective treatment of opioid use disorder (OUD), yet disparities in treatment discontinuation persist. This study aims to identify and quantify disparities in buprenorphine treatment retention using a machine learning framework adapted from Virtual Twins approach focusing on disparities related to sex, age, insurance type, geographic region, mental health status and community-level Social Vulnerability Index (SVI). Using a nationwide longitudinal cohort, we applied a two-stage machine learning approach. In Stage one, we trained classification models to estimate the counterfactual differences in treatment discontinuation across disparity types. Model performance was assessed using C-statistics and precision-recall curve. In …

Improving Overall Risk Ranking Via Subgroup-Level Information Borrowing In Survival Risk Stratification, Tia S Thomas, Jing Ning, Ruosha Li

Faculty, Staff and Student Publications

Effective risk stratification is essential for providing tailored therapies, improving patient outcomes, and optimizing healthcare resources by identifying sub-populations with similar health risks. However, accurate risk ranking is challenging in the presence of heterogeneous subgroups. Under these instances, subgroup-level information can be leveraged to refine the overall risk ranking. We propose a novel approach that integrates within-subgroup risk ranking percentiles to enhance the overall cohort risk stratification. This method uses both a global model and subgroup-specific models along with optimized weights to improve discriminatory performance across the entire cohort. The proposed method is validated through extensive simulations and applied to …

Ai Privacy And Security In Healthcare: A Systematic Literature Review, Diane Dolezel, Karima Lalani, Valerie Watzlaf, Kerryn Butler-Henderson, Elise V Z Lambert, Mary Morton, Jamie Sand, David Gibbs, Susan Fenton

Faculty, Staff and Student Publications

Background: Artificial intelligence is expanding into telemedicine and telerehabilitation, yet significant privacy and security concerns persist.

Scope: To synthesize empirical evidence on privacy and security approaches in health care, particularly those relevant to distributed home care.

Methodology: A systematic review identified 80 studies (2019 to 2025), and Latent Dirichlet Allocation (LDA) topic modeling characterized the privacy and security themes.

Results: Sixty-six studies addressed privacy, only seventeen addressed security, and three studies addressed both. LDA identified four themes: patient data privacy, federated learning for medical imaging, encrypted training and secure computation, and healthcare data governance. Most studies emphasized privacy-preserving approaches, like …

Advancing Virus-Associated Lymphoma Research In Latin America: A Global Opportunity For Cancer Science, Irene Tamí-Maury, Bryan Valcarcel, Maria Alejandra Torres, Arlett Hernandez Chavez, Luis Malpica

Faculty, Staff and Student Publications

No abstract provided.

Nasal Cavity Microbial Makeup And The Influence On Psychiatric Symptoms Following Fire Exposure In Firefighters, Paul Grunsted, Chao Xu, Amanda Janitz, Jessica Reese, Janis Campbell, Tasha M Santiago-Rodriguez, Sara J Javornik Cregeen, Joseph F Petrosino, Jooyeon Hwang

Faculty, Staff and Student Publications

Background: Firefighters experience high levels of occupational stress and trauma, increasing their risk of depression, anxiety, and post-traumatic stress disorder (PTSD). Although microbial communities may influence brain function and behavior through neural pathways, the nasal microbiome remains understudied. This study examined associations between nasal microbiome characteristics and psychiatric symptoms among firefighters.

Methods: We conducted a cross-sectional study of 34 firefighters recruited from Texas fire stations. Participants completed validated questionnaires assessing depression, anxiety, and PTSD. Nasal swabs were collected before and after fire suppression and 16S rRNA sequencing was used to characterize microbial communities. Alpha and beta diversity, relative abundance, and …

An Integrated Lifestyle-, Genetic- And Metabolomics-Based Prediction Model For Mild Cognitive Aging In The Hchs/Sol, Annah B Wyss, Yana Hrytsenko, Linfeng Hu, Iris J Broce, Robert C Kaplan, Wassim Tarraf, Bing Yu, Eric Boerwinkle, Qibin Qi, Myriam Fornage, Charles Decarli, Hector M González, Tamar Sofer

Faculty, Staff and Student Publications

Prediction models for cognitive aging measures have largely evaluated demographic variables and APOE carrier status in populations of European ancestry. To comprehensively assess prediction models among Hispanic/Latinos, we considered 12 models (6 predictor sets and 2 methods) for global cognitive score change (GCSC) and mild cognitive impairment (MCI) in the Study of Latinos-Investigation of Neurocognitive Aging (SOL-INCA) (N = 5856). Based on the average mean squared error (MSE) for GCSC or average area under the curve (AUC) for MCI across 100 randomly split testing and training sets, performance was similar across models, but slightly better for the following models: …

Enhancing Data Compatibility In An Evolving Landscape: Medical Cannabis And Polysubstance Use Protocols In The Phenx Toolkit, Anne Buu, Johannes Thrul, Amanda Bunting, Tamara Haegerich, Wayne Huggins, Christian Hopfer, Denise Vidot, Cataia Ives, Ryan Mcneil, Sarah Zemore, Corrie Vilsaint, Elizabeth Fallon, Christine Hill, Carol Hamilton, John Kelly

Faculty, Staff and Student Publications

Introduction: With increasing legalization of medical cannabis and prevalence of polysubstance use in the United States comes the need for standard psychometrically validated measures to study these substances' health effects in the population. The PhenX (consensus measures for Phenotypes and eXposures) Toolkit (www.phenxtoolkit.org) is a freely accessible catalog of recommended measurement protocols to promote data compatibility across studies, but this extensive catalog did not include measures in these important areas.

Methods: In 2024, a PhenX Working Group of experts followed a well-established consensus process to identify and recommend measurement protocols suitable for inclusion in studies on medical cannabis and polysubstance …

Intra-Coronary Imaging And Transcriptomics Of Calcified Nodules Before And After Intensive Lipid-Lowering Therapy: A Yellow Iii Substudy, Pruthvi C Revaiah, Yuliya Vengrenyuk, Jiajia Liu, Keisuke Yasumura, Vemuri Krishna Santosh, Monika Karki, Ishani Bansal, Amit Hooda, Joseph K Sweeny, Sahil Khera, Vishal Kapur, Prakash Krishnan, Pedro R Moreno, Roxana Mehran, Xiaobo Zhou, Jagat Narula, Samin K Sharma, Annapoorna S Kini

Faculty, Staff and Student Publications

Aims: Calcified nodules (CNs) contribute to 3-5% of acute coronary syndromes (ACS). Identifying peri-calcific lipid-rich areas is challenging with conventional imaging but feasible using near-infrared spectroscopy (NIRS). This YELLOW III substudy investigated the impact of maximal lipid-lowering on CN morphology and lipid content over 26 weeks.

Methods and results: Patients with stable CAD and lipid-rich, non-obstructive plaques (lipid arc >90°, FCT < 120 µm on OCT) received Evolocumab (140 mg biweekly) plus maximally tolerated statins. Lesions were evaluated at baseline and 26 weeks using combined NIRS-IVUS and OCT. Exploratory endpoints were the maximum 4 mm lipid core burden index (LCBI) in segments containing CNs (maxLCBI4mm-CN) and morphological changes in CN. Linear mixed-effects models were used to evaluate temporal changes and group interactions. Peripheral blood mononuclear cell (PBMC) transcriptomics were analysed. Among 110 patients, 43 (39.1%) had CNs. A total of 73 paired CNs were analysed for morphology, of which 65 CNs were ≥4 mm. CNs with lipid signal (CNLS) demonstrated a significant reduction in maxLCBI4mm-CN from 176.8 to 113.3 (β = -63.51 ± 17.63; P < 0.001), whereas no change was observed in dense CNs (P = 0.317). Morphological parameters remained largely unchanged in both groups. A modest increase in the surrounding calcium arc was observed in CNLS (P = 0.018), while depth showed a differential change …

Enhancing Inter-Institutional Ai Research Collaboration Across Multidisciplinary Teams To Increase The National Ai Workforce In Healthcare, Toufeeq Ahmed Syed, Sarah Popal, D'Laney Kernan, Deevakar Rogith, Zulfiia Ditto, Paul Warhurst, Jay Johnson, Jamboor K Vishwanatha

Faculty, Staff and Student Publications

Inter-institutional team collaboration is critical for impactful multidisciplinary AI research in healthcare. The goal of our project (AIM-AHEAD Connect) is to increase multidisciplinary collaborations by connecting AI/ML experts and healthcare researchers, trainees and professionals to enhance research and improve health for all Americans. As of February 2026, AIM-AHEAD Connect has over 10,100 AI/ML and healthcare experts from across 2,400 institutions, has made more than 7,800 connections and facilitated 194 collaborative online groups. We conducted a unique study to understand collaboration, and analyzed profile, connection, and platform engagement metrics to determine if AI experts and healthcare researchers with more inter-institutional connections …

Rewiring The Immune Response In Lung Cancer: Current Progress In Bispecific Antibodies, Car-T Therapy, And The Rise Of In Vivo Car-T Platforms, Lei He, Yi Sun, Bowen Ma, Guojun Lang, Jianguo Wen, George R Blumenschein, Hong Ma

Faculty, Staff and Student Publications

Lung cancer remains the leading cause of cancer mortality worldwide and continues to impose a major clinical burden, particularly in advanced non-small cell lung cancer (NSCLC) and small-cell lung cancer (SCLC). Although targeted therapies, antiangiogenic agents, immune checkpoint inhibitors, and antibody-drug conjugates have improved outcomes in selected patients, durable responses remain limited by primary and acquired resistance. Here, we comprehensively review recent progress in immunologically oriented therapeutic strategies for lung cancer, focusing on bispecific antibodies, chimeric antigen receptor (CAR) T-cell therapy, and emerging in vivo CAR-engineering modalities. We further elaborate on the clinical rationale, latest translational and early clinical evidence, …

Deep Learning To Predict Future Cognitive Decline: A Multimodal Approach Using Brain Mri And Clinical Data, Tamoghna Chattopadhyay, Pavithra Senthilkumar, Rahul H Ankarath, Christopher Patterson, Emma J Gleave, Sophia I Thomopoulos, Heng Huang, Li Shen, Lei You, Degui Zhi, Paul M Thompson

Faculty, Staff and Student Publications

Predicting the trajectory of clinical decline in aging individuals is a pressing challenge, especially for people with mild cognitive impairment, Alzheimer's disease, Parkinson's disease, or vascular dementia. Accurate predictions can guide treatment decisions, identify risk factors, and optimize clinical trials. In this study, we compared two deep learning approaches for forecasting changes, over a 2-year interval, in the Clinical Dementia Rating scale 'sum of boxes' score (sobCDR), as a continuous outcome (regression). This is a key metric in dementia research and clinical trials, and scores range from 0 (no impairment) to 18 (severe impairment). To predict decline, we trained a …

Genetic Variants Associated With Sjögren’S Disease Subtypes Stratified By Clinical Feature, Nitesh Enduru, Chihiro Iwaya, Akiko Suzuki, Zhongming Zhao, Junichi Iwata

Faculty, Staff and Student Publications

Introduction: Sjögren's disease (SjD) is a chronic autoimmune disorder characterized by dry mouth (xerostomia) and dry eyes (xerophthalmia) due to inflammation in exocrine glands, particularly the salivary and lacrimal glands. The condition presents a wide variety of clinical features, suggesting that it may involve heterogeneous conditions without a clear boundary. Although genome-wide association studies (GWAS) have identified several genetic variants associated with SjD, their roles in SjD pathogenesis remain unclear.

Methods: In this study, we aimed to identify single-nucleotide polymorphisms (SNPs) associated with SjD by categorizing patients based on four diagnostic markers: anti-Ro/SSA and anti-La/SSB antibodies, IgG levels, and lymphocyte …

Isolated Immune-Mediated Enteritis In Patients Treated With Immune Checkpoint Inhibitor Therapy, Sharada Wali, Rohan Srinivas Patel, Maria Julia Moura Nascimento Santos, Anirudha Chatterjee, Sophia Chenyu Fan, Sean Ngo, Tanvi Gupta, Kian Abdul Baki, Lucie Heinzerling, Bryan J Schneider, Kathryn Bollin, Jessica Philpott, Anusha Thomas, Yinghong Wang

Faculty, Staff and Student Publications

Background: Immune checkpoint inhibitors (ICIs) commonly cause colitis, but isolated immune-mediated enteritis (IMEN) is poorly characterized. This study describes the clinical features, diagnostic findings, and outcomes of IMEN.

Method: We retrospectively identified adults with cancer who developed IMEN within one year of ICI initiation, confirmed as duodenitis, ileitis, or both.

Results: Among 20,991 ICI-treated patients, 30 (0.143%) developed isolated IMEN. Median age was 69.5 years; 73.3% were male, and 80% white. The most common malignancies were gastrointestinal/hepatobiliary (26.7%) and melanoma (23.3%). Presenting symptoms included nausea (66.7%), diarrhea (53.3%), and vomiting (46.7%); 62.5% of patients with diarrhea had grade ≥2 severity. …

Mitochondrial Dysfunction In Alzheimer’S Disease And Related Sex Differences, Afzal Misrani, Conelius Ngwa, Fudong Liu

Faculty, Staff and Student Publications

Alzheimer's disease (AD), the most common form of dementia, accounts for 70% of cases and remains a major healthcare challenge due to its rising prevalence and lack of disease-modifying treatments. Clinically, AD is a sexually dimorphic disease. Women exhibit more rapid cognitive decline and accelerated brain atrophy during mild cognitive impairment and early dementia, whereas men more frequently present cardiovascular comorbidities, earlier mitochondrial dysfunction, and greater neuropsychiatric symptoms. AD is marked by amyloid-β (Aβ) plaques, neurofibrillary tangles, neuroinflammation, and neuronal loss, with mitochondrial dysfunction emerging as a key early contributor that exhibits sex specific phenotypes. Mitochondria are vital for neuronal …

Retrospective Longitudinal Analysis Of Blood Microrna-7-5p As A Possible Progression Biomarker In People With Parkinson’S Disease, Shayan Abdollah Zadegan, Corrine Hutchinson, Chiamaka Onuigbo, Juan D Martinez-Lemus, Laura Talbot, E Jeffrey Metter, Marie-Francoise Doursout, Emily Tharp, Jessika Suescun, Mohammad Shahnawaz, Timothy M Ellmore, Mya Schiess, Christopher Adams

Faculty, Staff and Student Publications

Background: MicroRNA-7-5p (miR-7-5p) may play a neuroprotective role in people with Parkinson's disease (PwP), as it has been found to regulate α-synuclein (α-syn) and the NLRP3 inflammasome in animal models of Parkinson's disease (PD).

Objective: The study aimed to investigate the use of miR-7-5p as a potential biomarker for disease progression in PwP by correlating it with time, clinical measures, and neurofilament light chain (NfL).

Methods: We performed a longitudinal retrospective analysis of blood miR-7-5p levels in 303 de novo PwP and 159 healthy controls (HCs) from the Parkinson's Progression Markers Initiative (PPMI) cohort. In PwP, a linear mixed-effects …

Spatial Evolution In Temporal Dynamics Of Hemodynamic Response Function In Human Superior Colliculi With Ultra-High-Resolution Mri At 9.4t, Nooshin J Fesharaki, Artemy Vinogradov, David Ress, Jung Hwan Kim

Faculty, Staff and Student Publications

The superior colliculus (SC) plays a crucial role in multisensory integration, visual information processing, saccadic target selection, visual selective attention, and decision making. In particular, the SC has a key role in oculomotor coordination, following a rostro-caudal organization. The rostral SC, which corresponds to foveal representation, is linked to fixation, microsaccades, smooth pursuit, and vergence adjustments. In contrast, the caudal SC, representing more peripheral visual field, is associated with the large gaze shifts (saccades). However, evidence regarding whether this functional gradient is preserved in the human SC remains limited. In this study, we employed a sequence-following visual-motor task to specifically …

The Effects Of Measurement Errors On Minimum Ablative Margins After Thermal Ablation Of Liver Tumors: A Simulation Study, Iwan Paolucci, Jessica Albuquerque, Noreen S Siddiqi, A Kyle Jones, Kristy K Brock, Bruno C Odisio

Faculty, Staff and Student Publications

Purpose: To develop a mathematical framework to estimate the in silico A0 threshold based on the technical specifications of a specific ablation confirmation software package for thermal ablation of liver tumors that can then be used to identify the impact of different sources of error.

Methods: To estimate in silico A0 thresholds, we developed a simulation framework incorporating technical parameters and biological effects. Technical parameters were segmentation error, registration error, and slice thickness, and biological effects were tissue shrinkage and microscopic satellite lesions; these parameters and effects were all modeled using statistical distributions. For each permutation of parameters, a logistic …