Digital Commons Network^™

Informatics At The Frontier Of Cancer Research, Kathleen Noller, Malachi Griffith, Daniel Marcus, Et Al.

2020-Current year OA Pubs

Digitized healthcare data, high-throughput profiling technologies, and data repositories have facilitated the emergence of a new era of cancer research. Each data stream requires specialized analysis methods for interpretation. The data-driven era of cancer research requires the development, enhancement, and sustainment of informatics technology software infrastructure, including fundamental methodology development in artificial intelligence and data science. We review current and emerging informatics technology developments for cancer research and discovery, spanning molecular and cellular characterizations, image analysis, informatics, and therapeutics. Summarizing the diverse methods and applications of informatics throughout cancer research identifies themes and emerging areas for the next generation of …

Tracing Sars-Cov-2 Clusters Across Local Scales Using Genomic Data, Leke Lyu, Mandev Gill, Guppy Stott, Sachin Subedi, Cody Dailey, Gabriella Veytsel, Magdy Alabady, Kayo Fujimoto, Ryker Penn, Pamela Brown, Roger Sealy, Justin Bahl

Faculty, Staff and Student Publications

A quantitative understanding of local transmission dynamics is essential for designing effective prevention strategies. In this study, we developed a computational workflow to identify viral introductions and trace locally circulating clusters. We analyzed over 26,000 SARS-CoV-2 genomes and their associated metadata, collected between January and October 2021, to explore introduction and local dispersal patterns in Greater Houston, a major metropolitan area known for its demographic diversity. Our analysis identified more than 1,000 independent introduction events, resulting in clusters of varying sizes. The majority of introductions originated from domestic sources, while international introductions occurred earlier and were associated with larger cluster …

Impact Of A Multi-Strain L. Crispatus-Based Vaginal Synbiotic On The Vaginal Microbiome: A Randomized Placebo-Controlled Trial, Jacques Ravel, Sheri Simmons, Eleni Greenwood Jaswa, Sara Gottfried, Miriam Greene, Susan Kellogg-Spadt, Dirk Gevers, Diane M. Harper

Institute of Emerging Health Professions Faculty Papers

A clinical trial of a multi-strain vaginal synbiotic (NCT05659745, registered 12/19/2022 at clinicaltrials.gov) led to an optimal vaginal microbiome dominated by L. crispatus (CST I). The synbiotic led to a significant increase in L. crispatus compared to placebo (p <  0.05), and conversion to CST I was significantly higher with the vaginal synbiotic than with placebo (90 vs 11%; p <  0.002). Mechanistically, the synbiotic reduced Gardnerella vaginalis and Candida, clinically important microbes.

Development Of A Health Knowledge And Skill-Based Framework For The Digital Age, Evelyn Hovenga, Osama El-Hassan, Manal Almalki, Jawad Ahmed, Paul Barach, Mowafa Househ, Amr Jamal

College of Population Health Faculty Papers

The Gulf Cooperation Council (GCC) region is tackling a significant digital healthcare workforce skills gap by creating a computable unified digital health competency framework and repository. Digital technologies and global competency standards are leveraged to professionalize the digital health knowledge domain and facilitate the development of clear career pathways in digital health. A mixed-methods approach was employed to develop the framework. A standardized categorial structure and information model has been developed to support the creation of this computable framework for workforce evaluation and competency-based career development.

Association Between Allostatic Load And Accelerated White Matter Brain Aging: Findings From The Uk Biobank, Li Feng, Zhenyao Ye, Zewen Du, Yezhi Pan, Travis Canida, Hongjie Ke, Song Liu, Shuo Chen, L Elliot Hong, Peter Kochunov, Jie Chen, David K Y Lei, Edmond Shenassa, Tianzhou Ma

Faculty, Staff and Student Publications

White matter (WM) brain age, a neuroimaging-derived biomarker indicating WM microstructural changes, helps predict dementia and neurodegenerative disorder risks. The cumulative effect of chronic stress on WM brain aging remains unknown. In this study, we assessed cumulative stress using a multi-system composite allostatic load (AL) index based on inflammatory, anthropometric, respiratory, lipidemia, and glucose metabolism measures, and investigated its association with WM brain age gap (BAG), computed from diffusion tensor imaging data using a machine learning model, among 22 951 European ancestries aged 40 to 69 (51.40% women) from UK Biobank. Linear regression, Mendelian randomization, along with inverse probability weighting, …

Alternative To The Statistical Mass Confusion Of Testing For "No Effect", Josh L Morgan

2020-Current year OA Pubs

In cell biology, statistical analysis means testing the hypothesis that there was no effect. This weak form of hypothesis testing neglects effect size, is universally misinterpreted, and is disastrously prone to error when combined with high-throughput cell biology. The solution is for analysis of measurements to start and end with an interpretation of effect size. In this manuscript, I walk through some of the common critiques of significance testing and how they relate to experimental cell biology. I argue that careful consideration of effect size should be returned to its central position in the planning and discussion of cell biological …

Enhancing Patient Positioning Accuracy: Evaluating Daily Cone Beam Computed Tomography In The Halcyon System., Duong Thanh Tai, Luong Tien Phat, Tran Trung Kien, Nguyen Ngoc Anh, Nguyen Xuan Hai, Peter Sandwall, David Bradley, James C L Chow

Oncology Articles

BACKGROUND: Precise patient positioning is crucial for successful radiotherapy, ensuring accurate delivery of radiation to tumors while minimizing exposure to healthy tissues. Positional errors can significantly impact treatment efficacy and increase side effects. This study evaluates the effectiveness of daily cone beam computed tomography (CBCT) imaging in the Halcyon system for detecting and correcting patient misalignments across various cancer types and treatment sites.

METHODS: A retrospective analysis was conducted on 411 patients treated with the Varian Halcyon linear accelerator from August 2022 to August 2024. Patients were grouped based on tumor location: Head and Neck (118 patients), Chest (188 patients), …

Use Of Cognitive-Behavioral Therapy In A Nation-Wide Veterans Health Administration Sample: The Role Of Clinic, Therapist, And Patient Factors., Alan Mcguire, Mindy Flanagan, Madison E Stout, Jessica Coffing, Marina Kukla, Morgan Traylor, Laura Myers, Nancy Henry, Jessica Carter, Marianne Matthias

Health Services and Informatics Research

OBJECTIVE: To examine the use of CBT-CP (Cognitive-behavioral therapy for chronic pain) by CBT-CP-trained therapists to treat patients with pain over a five-year period (October 2015-February 2020).

DATA SOURCES AND STUDY SETTING: CBT-CP is a core evidence-based practice that is central to multidisciplinary chronic pain care. However, research suggests that CBT-CP is underused. The current study used national Veterans Health Administration data to examine the use of CBT-CP by CBT-CP-trained therapists to treat patients with pain over a five-year period.

STUDY DESIGN: Multilevel modeling was used to evaluate clinic, therapist, and patient-level factors as predictors of CBT-CP receipt.

DATA COLLECTION: …

Association Of Epigenetic Aging With Plasma Cbiomarkers Of Amyloid, Tau, Neurodegeneration, And Neuroinflammation In Hispanic/Latino Adults, Myriam Fornage, Wassim Tarraf, Martha L Daviglus, Charles Decarli, Kevin A Gonzalez, Carmen R Isasi, Sayaka Kuwayama, Melissa Lamar, Bonnie E Levin, Humberto Parada, Alberto R Ramos, Tatjana Rundek, Bharat Thyagarajan, Hector M González

The Brown Foundation: Institute of Molecular Medicine

Background: Blood-based biomarkers hold significant promise for the early detection and diagnosis of Alzheimer's disease (AD) and other dementias. Age-related changes in blood levels of AD biomarkers are well-documented but poorly understood. Epigenetic clocks are mathematical models based on DNA methylation patterns that reflect various aspects of the multidimensional aging process. We investigated the associations of epigenetic aging with five blood-based AD biomarkers in 2656 Hispanic/Latino adults (mean age 62.5 years; 65% females) from the Hispanic Community Health Study/Study of Latinos. We used multivariable linear regression models to estimate the associations of acceleration in each of five epigenetic clocks with …

Bayesian Counterfactual Machine Learning Individualizes Radiation Modality Selection To Mitigate Immunosuppression, Duo Yu, Michael J Kane, Yiqing Chen, Steven H Lin, Radhe Mohan, Brian P Hobbs

Faculty, Staff and Student Publications

Purpose: Lymphocytes play critical roles in cancer immunity and tumor surveillance. Radiation-induced lymphopenia (RIL) is a common side effect observed in patients with cancer undergoing chemoradiation therapy (CRT), leading to impaired immunity and worse clinical outcomes. Although proton beam therapy (PBT) has been suggested to reduce RIL risk compared with intensity-modulated radiation therapy (IMRT), this study used Bayesian counterfactual machine learning to identify distinct patient profiles and inform personalized radiation modality choice.

Methods: A novel Bayesian causal inferential technique is introduced and applied to a matched retrospective cohort of 510 patients with esophageal cancer undergoing CRT to identify patient profiles …

Nature-Inspired Metaheuristics For Optimizing Dose-Finding And Computationally Challenging Clinical Trial Designs, Weng Kee Wong, Yevgen Ryeznik, Oleksandr Sverdlov, Ping-Yang Chen, Xinying Fang, Ray-Bing Chen, Shouhao Zhou, J Jack Lee

Faculty, Staff and Student Publications

Metaheuristics are commonly used in computer science and engineering to solve optimization problems, but their potential applications in clinical trial design have remained largely unexplored. This article provides a brief overview of metaheuristics and reviews their limited use in clinical trial settings. We focus on nature-inspired metaheuristics and apply one of its exemplary algorithms, the particle swarm optimization (PSO) algorithm, to find phase I/II designs that jointly consider toxicity and efficacy. As a specific application, we demonstrate the utility of PSO in designing optimal dose-finding studies to estimate the optimal biological dose (OBD) for a continuation-ratio model with four parameters …

Computed Tomography Radiomics-Based Cross-Sectional Detection Of Mandibular Osteoradionecrosis In Head And Neck Cancer Survivors, Serageldin Kamel, Laia Humbert-Vidan, Zaphanlene Kaffey, Sarah Mirbahaeddin, Abdulrahman Abusaif, David T A Fuentes, Kareem Wahid, Cem Dede, Mohamed A Naser, Renjie He, Ahmed W Moawad, Khaled M Elsayes, Melissa M Chen, Adegbenga O Otun, Jillian Rigert, Mark S Chambers, Andrew Hope, Erin Watson, Kristy K Brock, Katherine Hutcheson, Lisanne Van Dijk, Amy C Moreno, Stephen Y Lai, Clifton D Fuller, Abdallah S R Mohamed, Md Anderson Head And Neck Cancer Symptom Working Group

Faculty, Staff and Student Publications

Purpose: This study aims to identify radiomic features from contrast-enhanced CT (CECT) scans that differentiate osteoradionecrosis (ORN) from normal mandibular bone in head and neck cancer (HNC) patients treated with radiotherapy (RT).

Materials and methods: CECT images from 150 patients with confirmed ORN diagnosis (2008-2018) at MD Anderson Cancer Center (MDACC) were analyzed (80 % train, 20 % test). Radiomic features were extracted using PyRadiomics from manually segmented ORN regions and automated contralateral healthy mandible regions. Correlation analysis (r > 0.95) reduced features for model training. A random Forest (RF) classifier with Recursive Feature Elimination identified discriminative features. Explainability was assessed …

Rest-Activity Rhythm Phenotypes In Adults With Epilepsy And Intellectual Disability, Nandani Adhyapak, Grace E Cardenas, Mark A Abboud, Vaishnav Krishnan

Faculty, Staff and Students Publications

Objective: Rest-activity rhythms (RARs) are perturbed in many forms of neuropsychiatric illness. In this study, we applied wrist actigraphy to describe RAR perturbations in intellectually disabled adults with epilepsy ("E + ID"), using a cross-sectional case-control design. We examined whether RAR phenotypes correlated with epilepsy severity, deficits in adaptive function, and/or comorbid psychopathology.

Methods: Caregivers of E + ID subjects provided informed consent during routine ambulatory clinic visits and were asked to complete standardized surveys of overall epilepsy severity (GASE, Global Assessment of Severity of Epilepsy), adaptive function (ABAS-3, Adaptive Behavior Assessment System-3) and psychopathology (ABCL, Adult Behavior Checklist). Caregivers …

Effect Of Aerobic Or Resistance Exercise, Or Both On Insulin Secretion, Ciliary Neurotrophic Factor, And Insulin-Like Growth Factor-1 In Dieting Older Adults With Obesity, Georgia Colleluori, Viola Viola, Siresha Bathina, Reina Armamento-Villareal, Clifford Qualls, Antonio Giordano, Dennis T Villareal

Faculty, Staff and Students Publications

Background and aims: Obesity exacerbates age-related changes in metabolic and physical function. The effect of distinct exercise modalities combined with diet-induced weight loss on insulin secretion in older adults with obesity and frailty is unknown, and the potential mediators of the metabolic and functional improvements induced by lifestyle therapy still need to be identified. We aimed to assess the effects of various exercise therapies coupled with diet-induced weight loss on insulin secretion and sensitivity and on the levels of circulating Ciliary Neurotrophic Factor (CNTF), its receptor (CNTFRα), and Insulin-like Growth Factor-1 (IGF-1) in older adults with both obesity and frailty. …

Longer Scans Boost Prediction And Cut Costs In Brain-Wide Association Studies, Leon Qi Rong Ooi, Scott Marek, Nico U F Dosenbach, Timothy O Laumann, Evan M Gordon, Et Al.

2020-Current year OA Pubs

A pervasive dilemma in brain-wide association studies

A Data Assimilation Framework For Predicting The Spatiotemporal Response Of High-Grade Gliomas To Chemoradiation, Hugo J M Miniere, David A Hormuth, Ernesto A B F Lima, Maguy Farhat, Bikash Panthi, Holly Langshaw, Mihir D Shanker, Wasif Talpur, Sara Thrower, Jodi Goldman, Sophia Ty, Caroline Chung, Thomas E Yankeelov

Faculty, Staff and Student Publications

Background: High-grade gliomas are highly invasive and respond variably to chemoradiation. Accurate, patient-specific predictions of tumor response could enhance treatment planning. We present a novel computational platform that assimilates MRI data to continually predict spatiotemporal tumor changes during chemoradiotherapy.

Methods: Tumor growth and response to chemoradiation was described using a two-species reaction-diffusion model of enhancing and non-enhancing regions of the tumor. Two evaluation scenarios were used to test the predictive accuracy of this model. In scenario 1, the model was calibrated on a patient-specific basis (n = 21) to weekly MRI data during the course of chemoradiotherapy. A data assimilation …

A Novel Microdosimetry-Based Formalism For Cell Survival Modelling Applicable To Hypofractionated Radiotherapy, Oleg N Vassiliev, Radhe Mohan

Faculty, Staff and Student Publications

Objectives

Hypofractionated radiotherapy requires reliable cell survival models for doses much higher than the standard 2 Gy, for which the linear-quadratic (LQ) model is not applicable. We developed an alternative approach applicable to both low doses and high doses used in hypofractionated treatments and radiobiological experiments.

Approach.

We combined a standard microdosimetric technique with a recently introduced non-LQ cell survival model. Our formulation accounts for cell damage by multi-track events involving any number of particles. This is necessary for modelling cell survival at therapeutic doses. We characterise each cell type by the size �� of the sensitive volume (SV) and …

Replication Of Sensor-Based Categorization Of Upper-Limb Performance In Daily Life In People Post Stroke And Generalizability To Other Populations, Chelsea E Macpherson, Marghuretta D Bland, Christine Gordon, Allison E Miller, Caitlin Newman, Carey L Holleran, Christopher J Dy, Lindsay Peterson, Keith R Lohse, Catherine E Lang

2020-Current year OA Pubs

BACKGROUND: Wearable movement sensors can measure upper limb (UL) activity, but single variables may not capture the full picture. This study aimed to replicate prior work identifying five multivariate categories of UL activity performance in people with stroke and controls and expand those findings to other UL conditions.

METHODS: Demographic, self-report, and wearable sensor-based UL activity performance variables were collected from 324 participants (stroke

RESULTS: Two PCs explained 70-90% variance: PC1 (overall UL activity performance) and PC2 (preferred-limb use). A five-variable, five-cluster model was optimal across samples. In comparison to clusters, two PCs and individual accelerometry variables showed higher convergent …

Image-Based Inference Of Tumor Cell Trajectories Enables Large-Scale Cancer Progression Analysis, Yang Liu, Ling Cai, Ruichen Rong, Shidan Wang, Liwei Jia, Peiran Quan, Qin Zhou, Guanghua Xiao, Yang Xie

Faculty, Staff and Student Publications

Current approaches to estimating cell trajectories, tumor progression dynamics, and cell population diversity of tumor microenvironment often depend on single-cell RNA sequencing, which is costly and resource intensive. To address this limitation, we developed an artificial intelligence (AI) model that leverages cell morphology features and histological spatial organization to classify tumor cell differentiation status, infer cell dynamic trajectories, and quantify tumor progression from hematoxylin and eosin (H&E)-stained whole-slide images. In three independent lung adenocarcinoma cohorts, our AI-based model accurately predicted cell differential status and provided quantifiable measures of tumor progression that were prognostic of patient survival. Spatial transcriptomic integrative analyses …

Networked Behaviors Associated With A Large-Scale Secure Messaging Network: Cross-Sectional Secondary Data Analysis, Laura Rosa Baratta, Linlin Xia, Daphne Lew, Elise Eiden, Y Jasmine Wu, Noshir Contractor, Bruce L Lambert, Sunny S Lou, Thomas Kannampallil

2020-Current year OA Pubs

BACKGROUND: Communication among health care professionals is essential for effective clinical care. Asynchronous text-based clinician communication-secure messaging-is rapidly becoming the preferred mode of communication. The use of secure messaging platforms across health care institutions creates large-scale communication networks that can be used to characterize how interaction structures affect the behaviors and outcomes of network members. However, the understanding of the structure and interactions within these networks is relatively limited.

OBJECTIVE: This study investigates the characteristics of a large-scale secure messaging network and its association with health care professional messaging behaviors.

METHODS: Data on electronic health record-integrated secure messaging use from …

Hikikomori Risk In The Uk, Gregory Gorman, Alison Bacon, Jon May, Stephen Minton

School of Psychology

Background: Hikikomori syndrome involves voluntary withdrawal from social life, school and work, with onset typically in young adulthood. Hikikomori risk has not been examined in the UK, and these studies aimed to validate and refine the Hikikomori Risk Inventory-24 (HRI-24) screening tool in UK young adults. Methods/Results: In Study 1, participants (n = 341) completed the HRI-24. Item analysis and confirmatory factor analysis resulted in a shorter 13-item HRI (HRI-13), which demonstrated a perfect correlation with the full HRI-24. Both the HRI-13 and HRI-24 showed strong convergent and divergent validity, correlating with depression, anxiety, avoidant coping and negative early life …

Transcripts With High Distal Heritability Mediate Genetic Effects On Complex Metabolic Traits., Anna L. Tyler, J Matthew Mahoney, Mark P Keller, Candice N Baker, Margaret Gaca, Anuj Srivastava, Isabela Gerdes Gyuricza, Madeleine J Braun, Nadia Rosenthal, Alan D Attie, Gary Churchill, Gregory W. Carter

Faculty Research 2025

Although many genes are subject to local regulation, recent evidence suggests that complex distal regulation may be more important in mediating phenotypic variability. To assess the role of distal gene regulation in complex traits, we combine multi-tissue transcriptomes with physiological outcomes to model diet-induced obesity and metabolic disease in a population of Diversity Outbred mice. Using a novel high-dimensional mediation analysis, we identify a composite transcriptome signature that summarizes genetic effects on gene expression and explains 30% of the variation across all metabolic traits. The signature is heritable, interpretable in biological terms, and predicts obesity status from gene expression in …

Bayesian Inference Of Fitness Landscapes Via Tree-Structured Branching Processes, Xiang Ge Luo, Jack Kuipers, Kevin Rupp, Koichi Takahashi, Niko Beerenwinkel

Faculty, Staff and Student Publications

Motivation: The complex dynamics of cancer evolution, driven by mutation and selection, underlies the molecular heterogeneity observed in tumors. The evolutionary histories of tumors of different patients can be encoded as mutation trees and reconstructed in high resolution from single-cell sequencing data, offering crucial insights for studying fitness effects of and epistasis among mutations. Existing models, however, either fail to separate mutation and selection or neglect the evolutionary histories encoded by the tumor phylogenetic trees.

Results: We introduce FiTree, a tree-structured multi-type branching process model with epistatic fitness parameterization and a Bayesian inference scheme to learn fitness landscapes from single-cell …

Βiv Spectrin Abundancy, Cellular Distribution And Sensitivity To Akt/Gsk3 Regulation In Schizophrenia, Jessica Di Re, Michela Marini, Syed Ibrar Hussain, Aditya K Singh, Akshaya Venkatesh, Musaad A Alshammari, Tahani K Alshammari, Abdul-Rizaq Ali Hamoud, Ali Sajid Imami, Zahra Haghighijoo, Nickolas Fularcyzk, Laura Stertz, Derek Hawes, Angela Mosebarger, Jordan Jernigan, Claire Chaljub, Ralda Nehme, Consuelo Walss-Bass, Anton Schulmann, Marquis P Vawter, Robert Mccullumsmith, Robert D Damoiseaux, Agenor Limon, Demetrio Labate, Michael F Wells, Fernanda Laezza

Faculty, Staff and Student Publications

Schizophrenia (SCZ) is a complex psychiatric disorder with unclear biological mechanisms. Spectrins, cytoskeletal proteins linked to neurodevelopmental disorders, are regulated by the AKT/GSK3 pathway, which is implicated in SCZ. However, the impact of SCZ-related dysregulation of this pathway on spectrin expression and distribution remains unexplored. Here, we show that βIV spectrin protein levels were reduced in neurons of the dorsolateral prefrontal cortex in SCZ postmortem samples compared to healthy control (HC) from the Human Brain Collection Core (HBCC). To investigate potential links between βIV spectrin and the AKT/GSK3 pathway, we analyzed the PsychEncode dataset, revealing elevated SPTBN4 and AKT2 mRNA …

Adtnorm: Robust Integration Of Single-Cell Protein Measurement Across Cite-Seq Datasets, Ye Zheng, Daniel P Caron, Ju Yeong Kim, Seong-Hwan Jun, Yuan Tian, Florian Mair, Kenneth D Stuart, Peter A Sims, Raphael Gottardo

Faculty, Staff and Student Publications

Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) enables paired measurement of surface protein and mRNA expression in single cells using antibodies conjugated to oligonucleotide tags. Due to the high copy number of surface protein molecules, sequencing antibody-derived tags (ADTs) allows for robust protein detection, improving cell-type identification. However, variability in antibody staining leads to batch effects in the ADT expression, obscuring biological variation, reducing interpretability, and obstructing cross-study analyses. Here, we present ADTnorm, a normalization and integration method designed explicitly for ADT abundance. Benchmarking against 14 existing scaling and normalization methods, we show that ADTnorm accurately aligns populations …

Powerest: Statistical Power Estimation For Spatial Transcriptomics Experiments To Detect Differentially Expressed Genes Between Two Conditions, Lan Shui, Anirban Maitra, Ying Yuan, Ken Lau, Harsimran Kaur, Liang Li, Ziyi Li

Faculty, Staff and Student Publications

Recent advancements in spatial transcriptomics (ST) have significantly enhanced biological research in various domains. However, the high cost for current ST data generation techniques restricts the large-scale application of ST. Consequently, maximization of the use of available resources to achieve robust statistical power for ST data is a pressing need. One fundamental question in ST analysis is detection of differentially expressed genes (DEGs) under different conditions using ST data. Such DEG analyses are performed frequently, but their power calculations are rarely discussed in the literature. To address this gap, we developed PoweREST, a power estimation tool designed to support the …

Novel Validation Of Hdr Brachy Therapy Dosimetry For Cervical Cancer Using Egs_Brachy Monte Carlo Simulations: A Comparative Analysis With Oncentra Treatment Planning System., Duong Thanh Tai, Nguyen Thi Anh Thu, Tran Thien Thanh, Pham Anh Tuan, Marc J P Chamberland, Peter Sandwall, David Bradley, James C L Chow

Oncology Articles

PURPOSE: This study aims to validate HDR brachytherapy dosimetry for cervical cancer patients utilizing the egs_brachy Monte Carlo (MC) simulation.

METHODS: Three cervical cancer patients treated with

RESULTS: TPS-calculated doses were greater than those obtained from MC simulations. For the CTV, the median percentage differences were 7.9% (Q1: 6.4%, Q3: 9.8%; range: 0.4%-10.4%) for D

CONCLUSION: CTV and critical organ doses calculated by the TPS were consistently greater than those obtained from MC simulations. This suggests that the TPS may overestimate dose distributions, especially in heterogeneous regions like the pelvis. These results emphasize the need for continued validation of TPS …

Where Should The Cancer Control Interventions Target: A Geospatial Hotspot Analysis For Major Cancer Mortality 2018 To 2022 In The United States, Chongliang Luo, Saira Khan, Liyan Jin, Aimee S James, Graham A Colditz, Bettina F Drake

2020-Current year OA Pubs

BACKGROUND: Identifying changes in geographic disparities of cancer mortality reveals locations where cancer prevention and control efforts should be focused/targeted. We use recent cancer surveillance data to demonstrate the geographic disparity of major cancer mortality rates in the United States and its shift compared with previous data.

METHODS: This cross-sectional study used the 2018 to 2022 county-level mortality rates of colorectal, lung, breast, and prostate cancers from the Centers for Disease Control mortality data. Counties with suppressed death counts were imputed by spatial regression models. Getis-Ord Gi* statistics were used to evaluate the spatial clustering of county mortality. Identified hotspot …

Automated Assignment Grading With Large Language Models: Insights From A Bioinformatics Course, Pavlin G Poličar, Martin Špendl, Tomaž Curk, Blaž Zupan

Faculty, Staff and Students Publications

Motivation: Providing students with individualized feedback through assignments is a cornerstone of education that supports their learning and development. Studies have shown that timely, high-quality feedback plays a critical role in improving learning outcomes. However, providing personalized feedback on a large scale in classes with large numbers of students is often impractical due to the significant time and effort required. Recent advances in natural language processing and large language models (LLMs) offer a promising solution by enabling the efficient delivery of personalized feedback. These technologies can reduce the workload of course staff while improving student satisfaction and learning outcomes. Their …

Clonal Evolution Of Hematopoietic Stem Cells After Autologous Stem Cell Transplantation, Hidetaka Uryu, Koichi Saeki, Hiroshi Haeno, Chiraag Deepak Kapadia, Ken Furudate, Jyoti Nangalia, Michael Spencer Chapman, Linda Zhang, Jennifer Padilla, Li Zhao, Joanne I Hsu, Chong Zhao, Shujuan Chen, Tomoyuki Tanaka, Zongrui Li, Satoko Ogata, Sarah Hanache, Hui Yang, Courtney Dinardo, Naval Daver, Naveen Pemmaraju, Nitin Jain, Farhad Ravandi, Jianhua Zhang, Xingzhi Song, Erika Thompson, Hongli Tang, Latasha Little, Curtis Gumbs, Robert Z Orlowski, Muzaffar Qazilbash, Kapil Bhalla, Simona Colla, Hagop Kantarjian, Rashmi Kanagal-Shamanna, Carlos Bueso-Ramos, Daisuke Nakada, Gheath Al-Atrash, Jeffery Molldrem, P Andrew Futreal, Elizabeth Shpall, Margaret Goodell, Guillermo Garcia-Manero, Koichi Takahashi

Faculty, Staff and Student Publications

The impact of exogenous stressors, such as cancer chemotherapies, on the genomic integrity and clonal dynamics of normal hematopoiesis is not well defined. We conducted whole-genome sequencing on 1,276 single-cell-derived hematopoietic stem and progenitor cell (HSPC) colonies from ten patients with multiple myeloma treated with chemotherapies and six normal donors. Melphalan treatment significantly increased the mutational burden, producing a distinctive mutation signature, whereas other chemotherapeutic agents had minimal effects. Consequently, the clonal diversity and architecture of post-treatment HSPCs resemble those observed in normal elderly individuals, particularly through the progression of oligoclonal hematopoiesis, thereby suggesting that chemotherapy accelerates clonal aging. Integrated …