Digital Commons Network^™

Using Randomization To Compare Ai And Expert-Generated Formative Assessment Questions In Medical Education, Akshat Kumar, Katie Stinson, Litao Wang, Elizabeth Nugent, Yongsu Lee, Mark Hormann, Latanya Jones Love, Toufeeq Ahmed Syed

Faculty, Staff and Student Publications

Background: AI-generated content is being used across the education spectrum and is beneficial for creating complex multiple-choice questions, such as those used in medical education. However, evaluating AI-generated content is challenging, and existing testing and evaluation methods are falling short. This study uses randomization to compare medical students' performance on and subjective evaluation of AI versus expert-generated questions. We hypothesized that there would be no difference in student performance or subjective evaluation of AI vs expert-generated questions.

Methods: We designed a single-center, randomized study where medical student participants received either one AI- or expert-generated question per day over four weeks. …

Impact Of School Nurse Education On Factors Influencing Hpv Vaccine Communication With Parents, Jihye Choi, Efrat K Gabay, Jeanette Deason, Elizabeth Baumler, Diane Santa Maria, Daisy Mullassery, Lara S Savas, Erika Thompson, Sanghamitra M Misra, Paula M Cuccaro

Faculty, Staff and Student Publications

Human papillomavirus (HPV) can cause six cancer types but can be prevented with timely vaccination in early adolescence. However, despite the wide availability of the HPV vaccine, uptake remains suboptimal among US adolescents. School nurses are invaluable resources to students and their families regarding adolescent immunization needs. As part of the All for Them vaccination program, we assessed the impact of the continued nurse education (CNE) intervention on school nurses’ HPV vaccine communication with parents. Seventy-two school nurses and nurse administrators in Texas participated in the study. Using a single-arm study design, we measured participants’ potential barriers to and self-efficacy …

Lidocaine Combined With Low-Dose Esketamine For Movement-Evoked Pain After Hepatectomy: A Double-Blind Randomised Controlled Trial, Yan Xu, Li Zhou, Qianqian Tang, Feng Yu, Jingwen Wu, Siyu Yan, Min Cai, Jialu Wan, Yi Kang, Lajing Luowu, Mengmeng Zhou, Lulong Bo, Daniel I Sessler, Chunling Jiang

Faculty, Staff and Student Publications

Introduction: Pain following hepatectomy may delay recovery and increase opioid use. We tested the primary hypothesis that combining lidocaine and low-dose esketamine would reduce movement-evoked pain 24 h after hepatic resection. We also evaluated whether this approach reduced opioid consumption and improved quality of recovery.

Methods: Patients having elective hepatic resections were allocated randomly to receive lidocaine-esketamine or placebo from induction of anaesthesia until the end of surgery. After surgery, patients allocated to lidocaine-esketamine were given a continuous infusion of lidocaine with esketamine for 72 h. All patients received transversus abdominis plane blocks with ropivacaine 2 mg.kg-1 after induction of …

Hydroxyethyl Starch And Perioperative Complications: A Systematic Review And Meta-Analysis, Daniel I Sessler, Lorenzo Pradelli, Massimiliano Povero, Daniel Chappell, E Wang

Faculty, Staff and Student Publications

Background: Based on renal injury reported in critically ill and septic patients, the U.S. Food and Drug Administration issued a black box warning regarding hydroxyethyl starch (HES 130/0.4) use in 2013 and expanded the warning to surgical and trauma patients in 2021. Similarly, the European Medicines Agency initiated withdrawal of hydroxyethyl starch in 2022. This study was a new meta-analysis focused on renal injury designed to complement a 2021 meta-analysis of perioperative hydroxyethyl starch use, adding 45 trials and 6,895 patients. The focus was acute kidney injury and preoperative-to-postoperative change in creatinine concentration in surgical patients.

Methods: This study searched …

Spcc: Inferring Spatial Cell-Cell Interaction By Integrating Single-Cell And Spatial Transcriptomics, Tiangang Wang, Yu Zhou, Xi Liu, Sijia Wu, Liyu Huang, Kexin Huang, Xiaobo Zhou

Faculty, Staff and Student Publications

Study of single-cell spatial biology reveals the importance of integrating single-cell and spatial data for capturing spatial structure at individual cell resolution in various fields. With the lack of cellular-level information in most spatial data, it is necessary to integrate single-cell and spatial data. Here, we developed a deep learning computational framework for alignment and mapping of unpaired single-cell and the spatial data by using adversarial joint-variational autoencoder and Random Forest model (SPCC). SPCC will generate a mapping matrix for single-cell and spatial positions that can transfer spatial location to individual cells. SPCC can be used to perform downstream analysis, …

An Online Epilepsy Self-Management Tool For Patients With Epilepsy: A Formative Usability Study, Katarzyna Czerniak, Ross Shegog, Refugio Sepulveda, Robert Addy, Youngran Kim, Sahiti Myneni, Alejandra Garcia-Quintana, Kimberly Martin, David M Labiner

Faculty, Staff and Student Publications

Background: Epilepsy is a serious chronic neurological condition with no permanent cure. Continual self-management is important to mitigate seizure frequency and optimize quality of life in people with epilepsy who have greater disparities in accessing epilepsy care. The Management Information & Decision Support Epilepsy Tool (MINDSET [UTHealth, University of Arizona, and Radiant Digital]) was developed to enhance accessibility to epilepsy self-management (ESM) assessment and treatment. The purpose of this formative usability pilot study was to assess the user experience and functionality of MINDSET 2.0, an enhanced cross-platform online version of MINDSET, among a sample of patients with epilepsy prior to …

Prescription Opioid Misuse Among High School Athletes During The Opioid Prescribing Limit Law Era: Yrbss 2017-2023, Francine R Vega, Andrea J Yatsco, Audrey Sarah Cohen, James R Langabeer, Tiffany Champagne-Langabeer, Rakshitha Vijendra, Christine Bakos-Block

Faculty, Staff and Student Publications

Background/Objectives: School-age athletes occupy a paradoxical position in the adolescent opioid crisis, combining health-oriented activity with elevated risk of sports-related injury and prescription opioid exposure. In response to the opioid epidemic, states enacted opioid prescribing limit laws (OPLLs) beginning in 2016-2017, yet whether these supply-side policies reached high-risk youth subgroups remains unclear. This study evaluated national temporal trends in prescription opioid misuse among U.S. high school students during the period of OPLL implementation and examined differences across athletic participation, concussion history, sex, grade, race/ethnicity, and substance-use profiles.

Methods: Using four biennial waves of the Youth Risk Behavior Surveillance System with …

Conceptual Framework And Key Considerations For Field-Based Infrastructure In Food Is Medicine Research, Shreela V Sharma, Colleen Tewksbury, Christopher R Long, Colleen Spees, Ronit A Ridberg, Reshma Gupta, Erin P Ferranti, Naomi Tice, Eric Peterson, Brian Levine

Faculty, Staff and Student Publications

In 2023, the American Heart Association launched the Healthcare by Food (HCXF) initiative to establish a rigorous evidence base for Food Is Medicine (FIM) programs, so that patients with acute or chronic disease could access FIM programs as a covered benefit under their health insurance. The HCXF initiative is engaging in research, advocacy, and education to support the development and testing of interventions that improve health outcomes. The HCXF initiative launched 9 task forces aligned with research progress, including the Field-Based Infrastructure task force designed to examine broader questions to help support either earlier or later stages of the HCXF …

Computable Phenotypes For Research Using Real-World Data: Experiences From The Nih Pragmatic Trials Collaboratory, Marisa L Conte, Judith M Schlaeger, Guilherme Del Fiol, James R Campbell, Andrea L Cheville, Keith Marsolo, Kari A Stephens, Miriam O Ezenwa, Andrew D Boyd, Juanita E Darby, Nadine S Matthie, P Michael Ho, Alice Pressman, Morgan Justice, Carol Reynolds Geary, Keturah R Faurot, Alex Fist, Karen Staman, Hulin Wu, Rachel L Richesson

Faculty, Staff and Student Publications

Objectives: Embedded pragmatic clinical trials (ePCTs) are conducted as part of routine clinical care and therefore use data collected from real-world data sources, such as electronic health record systems and administrative claims. A common approach for using these types of data across all phases of trial conduct is to create a computable phenotype (an explicitly defined data query data, including specified data types, data codes, and logical parameters) to capture patients with a clinical condition, exposure, symptom, characteristic, treatment, or outcome of interest.

Materials and methods: The Electronic Health Record (EHR) Core Working Group of the NIH Pragmatic Trials Collaboratory …

Fuimos Olvidados Y Descuidados [Forgotten And Neglected]: Lessons Learned And Findings From On-Farm Covid-19 Education And Vaccine Clinics For Agricultural Workers And Their Multigenerational Families In Texas, Anabel Rodriguez, David I Douphrate, Ana L Pineda Reyes, Susana Zavala, Lus Chavez, Sofia Nicole Lopez, Andrea V Cabrera Cruz, Annie J Keeney, Nora Hernandez, Brenda Berumen-Flucker, Eva M Shipp, Matthew W Nonnenmann, Shannon P Guillot-Wright, Bethany Boggess Alcauter, G Lopez Ixta, Paula M Cuccaro, Higinio Fernandez-Sanchez, David Gimeno Ruiz De Porras

Faculty, Staff and Student Publications

Background: Despite being deemed essential non-healthcare workers, agricultural workers were excluded from COVID-19 vaccine prioritization in Texas. This professional practice report describes the multifaceted worker health and safety approaches to protecting agricultural workers and their families during the COVID-19 pandemic.

Methods: Between March 2020 and January 2025, several outreach, education, and training grants from various funding agencies were leveraged to deliver training, personal protective equipment, vaccines, and economic relief to agricultural workers in partnership with community-based organizations, industry, local public health departments, and academic institutions.

Findings: Timely funding efforts led to the distribution of 1,000 PPE kits, with more than …

Spae: Deciphering Cell Cycle Dynamics And Cell States In Single-Cell Rna-Seq Data, Jiahao Yi, Jiajia Liu, Peng Guo, Yuan-Nong Ye, Xiaobo Zhou

Faculty, Staff and Student Publications

Rapid advances in single-cell RNA sequencing (scRNA-seq) technology have enabled the investigation of gene expression changes at the single-cell level, particularly for elucidating the heterogeneity among cells and complex biological processes. This technique reveals subtle molecular differences within individual cells, thereby offering a unique viewpoint for the investigation of cell cycle progression, cellular differentiation, and disease pathogenesis. However, accurately identifying and analyzing cell cycle dynamics in scRNA-seq data remains challenging due to the complexity of the data and the subtle differences between cell states. To address this challenge, we developed the integrated Sinusoidal and Piecewise AutoEncoder (SPAE), an autoencoder-based piecewise …

Effects Of Non-Surgical Periodontal Therapy On Dental Plaque Microbiome, Qingguo Wang, Bing-Yan Wang, Derek Wilus, Hua Xie

Faculty, Staff and Student Publications

Periodontitis, a chronic inflammatory disease affecting approximately 40% of U.S. adults aged 30 years and older, is characterized by dysbiosis of the dental plaque microbiome. However, although scaling and root planing (SRP) is the cornerstone of periodontal treatment, its effects on the taxonomic composition and functional potential of the dental plaque microbiome remain incompletely understood. In this study, we used whole-metagenome shotgun sequencing to characterize taxonomic composition and functional potential in dental plaque microbiomes collected from 39 patients with Stage II or III generalized periodontitis before and 3–4 months after SRP. Consistent with clinical improvement, periodontal therapy significantly reduced probing …

Loss Of Atp-Dependent Citrate Lyase Drives Left Ventricular Dysfunction By Metabolic Remodeling, Shijie Liu, Seth T Gammon, Lin Tan, Yaqi Gao, Kyoungmin Kim, Mahmoud H Elbatreek, Adrian Arrieta, Ian K Williamson, Rebecca L Salazar, Janet Pham, Angela Davidian, Radhika Khanna Neicheril, Benjamin D Gould, Heidi Vitrac, Alia Sadiq, An Q Dinh, Evan C Lien, Francisca N De Luna Vitorino, Joanna M Gongora, Sara A Martinez, Melanie T Odenkirk, Anna K Boatman, Jessie R Chappel, Lawrence S C Czer, Evan P Kransdorf, David J Lefer, Blake M Hanson, Benjamin A Garcia, Erin M Baker, Matthew G Vander Heiden, Philip L Lorenzi, Heinrich Taegtmeyer, David Piwnica-Worms, James F Martin, Anja Karlstaedt

Faculty, Staff and Student Publications

Background: Metabolic adaptation and maladaptation are hallmarks of the failing heart and may be a target for therapeutic interventions. For example, sustained glucose oxidation during cardiac stress is associated with increased activity and abundance of ACL (ATP-dependent citrate lyase, Acly), which produces acetyl-coenzyme A (CoA) from citrate and CoA and supports de novo lipid synthesis. However, our understanding of how ACL supports cardiac metabolic adaptation and its potential to modulate disease pathophysiology has not yet been investigated.

Methods: We used human heart tissue samples from healthy donors and patients with nonischemic cardiomyopathy. Next, we used CRISPR (clustered, regularly interspaced …

Molecular Mechanism Leading To Human Coronary Atherosclerosis Assessed By Proteomic Analysis And Rna Sequences, Sarah J Parker, Chunhong Mao, David L Caudell, Austin Lyle Seals, Yizhi Wang, Thomas D Green, Joseph M Mcclung, Joshua T Maxwell, Jacolby T Roddey, Kiarash Shakeriastani, Chiung-Ting Wu, Yingzhou Lu, Do-Kyun Kim, Justyna Fert-Bober, Dongping Du, Archana Bhat, Niveda Sundararaman, Matthew Ayres, Rakhi Pandey, Saurabh Bhardwaj, Genesio M Karere, Dana Troxclair, Fannie Jackson, Gordon L Love, Richard Vander Heide, James Hixson, Jennifer E Van Eyk, Yue Wang, David Herrington

Faculty, Staff and Student Publications

Background and aims: Atherosclerosis results from cellular and extracellular changes in the arterial wall, preceded by molecular shifts that initiate disease and drive tissue conversion, yet these changes are not yet fully described. More data are needed concerning these early changes in the coronary artery molecular landscape that signify the initiation of atherosclerosis and the subsequent tissue pheno-conversion to atherosclerotic plaque. This report summarizes results from a large biorepository of human coronary artery tissue, applying state-of-the-art omics technology, advanced data analytic methods, and an arterial organoid model system to predict molecular dynamics and identify potential regulatory mechanisms that could interrupt …

Tau Seeds Induce Neurofibrillary Tangle Formation Across Brain Regions Via Individual-Specific Connectivity, Audrey J Weber, Bernard Ng, Kelsey M Greathouse, David A Bennett, Shinya Tasaki, Chris Gaiteri, Jeremy H Herskowitz

Faculty, Staff and Student Publications

The spread of tau pathology across the cerebral cortex is closely tied to cognitive decline in Alzheimer's disease (AD). To investigate mechanisms underlying tau spread, we measured bioactivity of tau seeds from inferior temporal gyrus (ITG) and superior frontal gyrus (SFG) synaptosomes in 128 individuals and demonstrated that tau seed bioactivity associates with tau phosphorylation, neurofibrillary tangles (NFTs), and cognitive impairment. Incorporating genotype data from the same individuals within a Mendelian randomization framework showed that tau seeds in ITG induce NFTs locally as well as drive tau seeds and NFTs in SFG. Integrating antemortem functional magnetic resonance imaging data from …

Longitudinal Genomic Surveillance Of Sars-Cov-2 In A University Microcosm Reflects Global Evolutionary Trends, Sankar Prasad Chaki, Melissa M Kahl-Mcdonagh, Benjamin W Neuman, Loni A Taylor, Rebecca S B Fischer, Blake M Hanson, Marlisa S Hardy, Jo Ann Culpepper, Eric Boerwinkle, Kurt A Zuelke

Faculty, Staff and Student Publications

SARS-CoV-2 transmission has declined, yet ongoing viral evolution continues to pose public health challenges. This study conducted long-term (2020-2024) genomic surveillance within a large and globally diverse university community. Viral genomes obtained from clinical (n = 1,786) and surveillance (n = 888) testing samples were classified under clade, lineage, and variant systems, and compared with global genomic data sets. Local patterns broadly paralleled global evolutionary trends, including the phased emergence of major variants, episodic introductions of new lineages, and shifts in dominant clades. Lineage diversity peaked during fall semesters and was highest among undergraduate-aged individuals, with similar distributions …

Advancing Bioinformatics With Language Models: Components, Applications, And Perspectives, Jiajia Liu, Mengyuan Yang, Yankai Yu, Haixia Xu, Tiangang Wang, Kang Li, Xiaobo Zhou

Faculty, Staff and Student Publications

Large language models (LLMs) are deep learning-based artificial intelligence models that have achieved remarkable success in natural language processing. Typically composed of neural networks with billions of parameters, they are trained on massive unlabeled datasets using self-supervised or semi-supervised learning. Beyond language, LLMs hold immense potential for addressing complex bioinformatics challenges. This review provides a comprehensive overview of transformer-based model applications in genomics, transcriptomics, proteomics, drug discovery, and single-cell analysis. We discuss critical components, including tokenization strategies for diverse biological data, transformer architectures, attention mechanisms, and pretraining approaches. We also survey currently available foundation models and their downstream applications across …

The Effects Of Abstinence Status And Sleep Quality On Resting State Alpha Power In Cocaine Use Disorder, Heather E Webber, Danielle A Kessler, Joy M Schmitz, Scott D Lane, Robert Suchting

Faculty, Staff and Student Publications

Rationale

Substance use disorders are associated with notable sleep disturbances. Electroencephalogram (EEG) alpha power occurs during wakeful rest, is associated with sleepiness, and indicates neural deactivation.

Objectives

The goal of the current study was to assess the effects of abstinence on the relationship between alpha power and subjective sleep quality in participants with cocaine use disorder (CUD).

Methods

Participants with CUD (n = 32) who were recently or non-abstinent completed a resting-state EEG paradigm (90 s eyes open/closed). Absolute alpha power was calculated using the fast Fourier transform and by averaging within the power spectra of the alpha band (8–13 …

Qualitative Evaluation Of The Seated Physical Activity Intervention (Spin) Randomized Controlled Trial For Wheelchair Users With Multiple Sclerosis (Ms): Formative Feedback And Future Directions, Angela J Piasecki, Robert W Motl, Katherine Froehlich-Grobe, Stephanie L Silveira

Faculty, Staff and Student Publications

Background/objectives: Wheelchair users with multiple sclerosis (MS) often face barriers that restrict participation in physical activity and exercise training. This manuscript reports on participant feedback to guide evaluating and refining a novel exercise training program, Seated Physical activity INtervention (SPIN). SPIN was adapted from the Guidelines for Exercise in MS (GEMS) approach using a three-step community-engaged research framework based on meeting the needs of wheelchair users with MS.

Methods: Semi-structured interviews were conducted with 9 participants who completed the 16-week SPIN intervention. The key SPIN intervention components were the exercise prescription, exercise equipment, and behavioral coaching grounded in Social Cognitive …

Qeith: Quantifies Tumor Ecosystem Heterogeneity To Predict Cancer Progression And Treatment Benefit, Qiqi Liu, Jiangti Luo, Jiawei Wang, Bangqi Zhao, Xiaosheng Wang, Linjun You

Faculty, Staff and Student Publications

Intratumor heterogeneity (ITH) is a fundamental driver of therapeutic failure and disease progression. However, the complexity of the tumor ecosystem is a critical yet underexplored aspect, making its precise quantification essential for fully deciphering ITH and its clinical implications. To address this, we developed Quantifying Ecosystem Intratumor Heterogeneity (QeITH), a computational framework that applies Shannon entropy to quantify ecosystem heterogeneity by measuring the diversity and distributional entropy of cellular compositions and functional states across single-cell, bulk, and spatial transcriptomics. At the single-cell resolution, QeITH identifies elevated ITH as intrinsic markers of malignant transformation, yet enhanced sensitivity to therapy. Pan-cancer bulk …

Publisher Correction: Whole Genome Sequence Analysis Of Pulmonary Function And Copd In 44,287 Multi-Ancestry Participants, Wonji Kim, Xiaowei Hu, Kangjin Kim, Sung Chun, Peter Orchard, Dandi Qiao, Ingo Ruczinski, Aabida Saferali, Francois Aguet, Lucinda Antonacci-Fulton, Pallavi P Balte, Traci M Bartz, Wardatul Jannat Anamika, Xiaobo Zhou, Junyi Duan, Jennifer A Brody, Brian E Cade, Martha L Daviglus, Harshavadran Doddapaneni, Shannon Dugan-Perez, Susan K Dutcher, Christian D Frazar, Stacey B Gabriel, Sina A Gharib, Namrata Gupta, Brian D Hobbs, Silva Kasela, Laura R Loehr, Ginger A Metcalf, Donna M Muzny, Elizabeth C Oelsner, Laura J Rasmussen-Torvik, Colleen M Sitlani, Joshua Smith, Tamar Sofer, Hanfei Xu, Bing Yu, David Zhang, John Ziniti, R Graham Barr, April P Carson, Myriam Fornage, Lifang Hou, Ravi Kalhan, Robert Kaplan, Tuuli Lappalainen, Stephanie J London, Alanna C Morrison, George T O'Connor, Bruce M Psaty, Laura M Raffield, Susan Redline, Stephen S Rich, Jerome I Rotter, Edwin K Silverman, Ani Manichaikul, Michael H Cho

Faculty, Staff and Student Publications

This corrects the article "Whole genome sequence analysis of pulmonary function and COPD in 44,287 multi-ancestry participants", 28.

Auricular Point Acupressure Self-Management (Apa-Sm) Program For Chronic Musculoskeletal Pain Among Rural Populations: A Protocol For A Pragmatic, Randomized Controlled Trial, Jennifer Kawi, Jane Bolin, Hulin Wu, Jungkyung Min, Rupsikha Bora, Sarah Pace, Idara N Akpan, Alee Lockman, Tonychris Nnaka

Faculty, Staff and Student Publications

Introduction: Chronic musculoskeletal pain (CMP) is a leading cause of incurred personal healthcare costs and disability in the USA. It disproportionately affects rural populations, who are more likely to be uninsured, lack access to a regular healthcare provider and experience a higher prevalence of CMP. As a result of reduced access to non-pharmacological care, there is greater reliance on opioids. The Auricular Point Acupressure - Self-Management (APA-SM) program is a simple, needleless, evidence-based therapy that empowers individuals to self-manage their pain. Preliminary studies, including a recent UG3 pilot testing, demonstrated feasibility, safety and significant improvements in pain and function. Guided …

From Performance To Practice: Knowledge-Distilled Segmentator For On-Premises Clinical Workflows, Qizhen Lan, Aaron Choi, Jun Ma, Bo Wang, Zhongming Zhao, Xiaoqian Jiang, Yu-Chun Hsu

Faculty, Staff and Student Publications

Deploying medical image segmentation models in routine clinical workflows is often constrained by on-premises infrastructure, where computational resources are fixed and cloud-based inference may be restricted by governance and security policies. While high-capacity models achieve strong segmentation accuracy, their computational demands hinder practical deployment and long-term maintainability in hospital environments. We present a deployment-oriented framework that leverages knowledge distillation to translate a high-performing segmentation model into a scalable family of compact student models without modifying the inference pipeline. The framework is primarily evaluated on nnU-Net, with additional validation across transformer and heterogeneous teacher–student architectures. The proposed approach preserves architectural compatibility …

Exploring Racial And Ethnic Diversity Trajectories And Diabetes Prevalence In The United States, Jiue-An Yang, Calvin P Tribby, Anna Dmowska, Qian Xiao, Marta M Jankowska

Faculty, Staff and Student Publications

This study investigates whether long-term changes in neighborhood racial and ethnic diversity are associated with adult diabetes prevalence across the contiguous United States. We calculated diversity indexes for US census tracts (n = 72,033) using decennial census data from 1990 to 2020. Five diversity trajectory clusters were identified using K-means clustering. Diabetes prevalence in 2019 was obtained from the CDC's PLACES dataset. Linear mixed models (LMMs) assessed global associations between diversity trajectories and diabetes prevalence, adjusting for age, sex, poverty, marital status, and public insurance. Geographically weighted regression (GWR) examined local variations in these associations. Compared to the reference group …

Trust In Cancer Information Sources And Awareness Of Human Papillomavirus As A Cause Of Cervical Cancer Among Us Adults, Olajumoke Ope Oladoyin, Paula Cuccaro, Lara S Savas, Robert Yu, Joel Fokom Domgue, Sheryl Mccurdy, Sanjay Shete

Faculty, Staff and Student Publications

Importance: Religiosity, trust in physicians, and trust in government health agencies influence individual decision-making and behavior toward public health programs. However, trust in information about cancer from these sources and their association with public awareness of human papillomavirus (HPV) as a cause of cervical cancer remain understudied.

Objective: To assess the association of trust in cancer information sources with awareness that HPV causes cervical cancer among US adults.

Design, setting, and participants: This cross-sectional study used the nationally representative 2022 Health Information National Trends Survey (HINTS) data on noninstitutionalized US adults aged 18 years or older collected between March 7 …

Association Of Insulin Resistance And Fracture Risk In The Osteoporotic Fractures In Men (Mros) Cohort, Jeonghoon Ha, Li-Yung Lui, Kristine Ensrud, Qian Xiao, Andrew R Hoffman, Joy Y Wu

Faculty, Staff and Student Publications

Context: Insulin resistance (IR) is more prevalent in men than in women, but evidence directly linking IR to fracture risk in older men remains limited.

Objective: To evaluate the association between insulin resistance (IR), estimated using the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) and the triglyceride-glucose (TyG) index, and fracture risk in older men.

Methods: Data from 5994 men (≥65 years) in the MrOS cohort were analyzed. A total of 5416 participants were included in the HOMA-IR analysis and 5384 in the TyG index analysis. Fractures were self-reported and confirmed radiographically. Participants were grouped into quartiles based on IR …

Brain Age Prediction In Generalized Anxiety Disorder Using A Convolutional Neural Network, Corey Richier, André Zugman, Anita Harrewijn, Elise M Cardinale, Parmis Khosravi, Moji Aghajani, Willem B Bruin, Kevin Hilbert, Narcis Cardoner, Daniel Porta-Casteràs, Marta Cano, Savannah Gosnell, Ramiro Salas, Andrea P Jackowski, Pedro M Pan, Giovanni A Salum, Karina S Blair, James R Blair, Mohammed R Milad, Katie L Burkhouse, K Luan Phan, Heidi K Schroeder, Jeffrey R Strawn, Katja Beesdo-Baum, Neda Jahanshad, Sophia I Thomopoulos, Jared A Nielsen, Jordan W Smoller, Jair C Soares, Benson Mwangi, Mon-Ju Wu, Giovana B Zunta-Soares, Michal Assaf, Gretchen J Diefenbach, Paolo Brambilla, Eleonora Maggioni, David Hofmann, Thomas Straube, Carmen Andreescu, Rebecca B Price, Gisele G Manfro, Federica Agosta, Elisa Canu, Camilla Cividini, Massimo Filippi, Milutin Kostić, Ana Munjiza Jovanovic, Brenda Benson, Gabrielle F Freitag, Ellen Leibenluft, Grace V Ringlein, Kathryn Werwath, Hannah Zwiebel, Hans J Grabe, Sandra Van Der Auwera, Katharina Wittfeld, Henry Völzke, Robin Bülow, Nicholas L Balderston, Monique Ernst, Lilianne R Mujica-Parodi, Helena Van Nieuwenhuizen, Hugo D Critchley, Elena Makovac, Matteo Mancini, Frances Meeten, Cristina Ottaviani, Gregory A Fonzo, Martin P Paulus, Murray B Stein, Raquel E Gur, Ruben C Gur, Antonia N Kaczkurkin, Bart Larsen, Theodore D Satterthwaite, Jennifer Harper, Michael T Perino, Chad M Sylvester, Qiongru Yu, Patrick Mcclure, Francisco Pereira, Ulrike Lueken, Dick J Veltman, Paul M Thompson, Nynke A Groenewold, Janna Marie Bas-Hoogendam, Dan J Stein, Nic J A Van Der Wee, Anderson M Winkler, Daniel S Pine, Chelsea K Sawyers

Faculty, Staff and Student Publications

Higher predicted brain age difference has been associated with several psychiatric disorders. Generalized anxiety disorder (GAD) is associated with markers of accelerated aging. In this study, we determined brain predicted age difference (PAD) in individuals with GAD and healthy controls (HC) as well as group differences in PAD variability using voxel-wise structural MRI. The training dataset included 3511 controls, and the testing dataset included 1595 individuals with GAD and 4552 HC from the ENIGMA-Anxiety GAD Working Group. A convolutional neural network model using four input modalities per subject and a model ensemble approach was used to predict brain age. The …

Smart Pediatric Oncology Tracker Of Symptoms (Spots), A Web-Based Interface For The Pediatric Pro-Ctcae: Development And Usability Study, Stacey Crane, Deevakar Rogith, Melody Hellsten, Andrew D Miller, Jacqueline Castillo, Brandy Boeger, Susan Vidaurre, Stefanie Pieper, Cecile Nguyen, Duc Anh Thanh Huynh, Jessica Wooden, Amy Franklin, Karen Moody, Wenyaw Chan, Pamela S Hinds, Constance Johnson

Faculty, Staff and Student Publications

Background: Children undergoing cancer treatment experience a range of treatment-related toxicities that significantly affect quality of life and adherence to therapy. Current methods for symptom reporting rely heavily on clinician interpretation of caregiver or child verbal reports, which can result in incomplete or inaccurate records. The Pediatric Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (Pediatric PRO-CTCAE; National Cancer Institute) provides a validated mechanism for direct symptom reporting by children and caregivers, yet its traditional administration and preselection of questions limit the breadth of symptom capture.

Objective: This research aimed to co-design and conduct formative usability testing …

Correction: Berezowski Et Al. Biomarkers In Renal Cell Carcinoma: A Systematic Review And Immunohistochemical Validation Study, Brett Berezowski, Robert Boothe, Billy Chaplin, Sharon J Del Vecchio, Zakariya Fares, Tyrone L R Humphries, Keng Lim Ng, Taylor Noonan, Hemamali Samaratunga, Aaron Urquhart, David A Vesey, Simon T Wood, Glenda C Gobe, Robert J Ellis

Faculty, Staff and Student Publications

This corrects the article "Biomarkers in Renal Cell Carcinoma: A Systematic Review and Immunohistochemical Validation Study" in volume 17, 2588.

Identifying Novel Gene Dysregulation Associated With Opioid Overdose Death: A Meta-Analysis Of Differential Gene Expression In Human Prefrontal Cortex, Javan K Carter, Bryan C Quach, Caryn Willis, Melyssa S Minto, Dana B Hancock, Janitza Montalvo-Ortiz, Olivia Corradin, Ryan W Logan, Consuelo Walss-Bass, Brion S Maher, Eric Otto Johnson

Faculty, Staff and Student Publications

Only recently have human postmortem brain studies of differential gene expression (DGE) associated with opioid overdose death (OOD) been published; sample sizes from these studies have been modest (N = 40-153). To increase statistical power to identify OOD-associated genes, we leveraged human prefrontal cortex RNA-seq data from four independent OOD studies and conducted a transcriptome-wide DGE meta-analysis (N = 272). Using a unified gene expression data processing and analysis framework across studies, we meta-analyzed 20, 098 genes and found 335 significant differentially expressed genes (DEGs) by OOD status (false discovery rate <  0.05). Of these, 66 DEGs were among the list of 303 genes reported as OOD-associated in prior prefrontal cortex molecular studies (e.g., genes/gene families OPRK1, NPAS4, DUSP, EGR). The remaining 269 DEGs were not previously reported (e.g., NR4A2, SYT1, HCRTR2, BDNF). There was little evidence of genetic drivers for the observed differences in gene expression between opioid addiction cases and controls. Enrichment analyses for the DEGs across molecular pathway and biological process databases highlight an interconnected set of genes and pathways linked to orexin and tyrosine kinase receptors through MEK/ERK/MAPK signaling to affect neuronal plasticity.