Digital Commons Network^™

Healthcare Administration Within Free Medical Clinics And The Impacts On The Sustainable Development Goals, Saneywongse Le Mar

Goal 3: Good Health and Well-Being

No abstract provided.

Analyzing Racial And Geographic Distribution In Clinical Trial Enrollment Among Women With Advanced Stage Ovarian Cancer, Paxton Gillispie, Dhruva Dave, Gerald Mcgwin, Ashwini Katre, Ashley Anderson, Teresa Boitano, Nneka Ijeli, Purva Pawar, Rebecca Arend

Expo Student Presentations

2025 Summer Expo Poster Presentation

• Physical & Applied Sciences
• Health Sciences & Health Professions

Machine Learning For Digital Biomarker-Based Detection Of Cognitive Decline, Seng Khoon The

Dissertations and Theses Collection (Open Access)

Dementia is a neurodegenerative disease with a prevalence rate expected to triple by 2050, posing a significant challenge for health services. To impede the increasing prevalence, medical professionals and scientists are actively investigating technology to detect cognitive decline at a reversible stage known as Mild Cognitive Impairment (MCI). Digital biomarker technology is an emerging pragmatic approach to permit objective, ecologically valid, and long-term continuous measurement of cognitive health status, rendering it as one of the promising technologies for early MCI detection. Despite its potential, it is nontrivial to encode, extract and combine predictive information from these digital biomarker technologies; advanced …

Effect Of The Cervical Lesion Severity On Procedural And Clinical Outcomes After Endovascular Treatment Of Acute Tandem Lesions: A Multicenter Study, Milagros Galecio-Castillo, Mudassir Farooqui, Ameer E Hassan, Mouhammad A Jumaa, Afshin A Divani, Marc Ribo, Michael Abraham, Nils H Petersen, Johanna T Fifi, Waldo R Guerrero, Amer M Malik, Thanh N Nguyen, Sunil A Sheth, Albert J Yoo, Guillermo Linares, Nazli Janjua, Michael Dubinsky, Darko Quispe-Orozco, Wondwossen Tekle, Syed F Zaidi, Sara Y Sabbagh, Marta Olive-Gadea, Tiffany Barkley, Reade A De Leacy, Mohamad Abdalkader, Sergio Salazar-Marioni, Jazba Soomro, Weston Gordon, Charoskhon Turabova, Leonardo Cruz-Criollo, Piyush Kalakoti, Maxim Mokin, Dileep R Yavagal, Tudor G Jovin, Santiago Ortega-Gutierrez

Faculty, Staff and Student Publications

Background: Tandem lesions pose unique challenges in the endovascular treatment of acute ischemic stroke. We aimed to compare the clinical and procedural outcomes of patients with tandem lesions and extracranial internal carotid artery (ICA) complete occlusion versus those with moderate to severe stenosis.

Methods: This is a subanalysis of a multicenter cohort of patients with acute anterior circulation tandem lesions treated with intracranial mechanical thrombectomy and carotid artery stenting, between January 2015 and December 2020. The patients were categorized into 2 groups: extracranial ICA stenosis >70% to 99% and complete occlusion. Outcomes included successful and excellent recanalization, functional independence, symptomatic …

The Effect Of Individual Variation On Epidemiological Dynamics: From Super-Spreaders To Landscapes Of Risk, Alexis Shannon Beagle

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Individuals that make up a population always display some level of variation between members. At the smallest scale, individuals always maintain genetic variation, but variation continues to arise at other scales of biological organization from physiological or immunological variation within individuals to variation in behavior between individuals that can be both genetically and environmentally mediated. The role of individual variation is particularly important in the context of infectious diseases because there is strong evidence that infections are highly heterogenous, indicating that patterns of individual variation drive a significant portion of the epidemiological patterns we observe. Individual variation leads to heterogeneity …

Use Of High-Throughput Phenomics With And Without Fungicide As A Wheat Breeding Tool, Gerardo Ivan Rivera Collazo

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Wheat (Triticum aestivum) is an important food staple for many countries around the world and current consumption and production data demonstrate a production deficit. Breeders are challenged to help close this gap in production by selecting better cultivars with improved yields. Several methods aim to accelerate the breeding process to reduce the time required for releasing an elite variety. One of the main breeding bottlenecks is the lack of fast and reliable phenotypic data acquisition that could dissect physiological and morphological plant data. High-throughput remote sensing could have the potential to reduce this bottleneck by streamlining data acquisition, …

Pengaruh Vaksinasi Covid-19 Terhadap Kesehatan Dan Kondisi Ekonomi Masyarakat Di Indonesia, Ayu Lestari, Fauziah Zen

Jurnal Ekonomi dan Pembangunan Indonesia

The COVID-19 vaccination is considered crucial for controlling the pandemic and accelerating economic recovery. However, empirical evidence on the impact of vaccination on health and the economy at the district/city level in Indonesia remains limited. This study aims to analyze the impact of vaccination on health outcomes and economic conditions. The methodology used is a fixed effect model with monthly panel data on vaccination and health outcomes (positivity rate and recovery), as well as annual data on per capita expenditure in 514 districts/cities from January 2021 to December 2022. The results show that the first dose of vaccination significantly reduces …

Graduate School Blog - July 2025 Volume 1, Cynthia Haynes

UofM Grad School Blog

The July 2025 UofM Graduate School Blog – Volume 1 continues the Cost of Graduate School Guide with a deep dive into hidden and variable expenses such as residency-based tuition differences, program-specific fees, and differential tuition. The blog provides practical tips for prospective students on how to ask the right financial questions when comparing programs. It also features a student spotlight on Billy Brooks, a dual MHA/MBA candidate motivated to transform healthcare access and equity. Upcoming events include a Virtual Fall 2025 Open House with Financial Aid and USBS, a Dissertation Writers Retreat, and both in-person and virtual Graduate Student …

Biocomputing Approach To Modeling And Modulating Calcium Signaling, Sehee Sun

School of Computing: Dissertations, Theses, and Student Research

Biocomputing is an emerging field that seeks to perform computational tasks using biological substrates and processes. Unlike conventional computing systems based on silicon hardware, biocomputing leverages the parallelism, energy efficiency, and complex dynamics of living systems. Among various cellular mechanisms, calcium (Ca2+) signaling stands out as a central regulator of diverse biological functions, offering a promising basis for programmable logic and control in living cells.

This thesis introduces a novel framework for modeling and modulating Ca2+ dynamics using biologically inspired Boolean logic circuits. Specifically, we propose the Ca2+ Boolean Logic (CaBL) model, in which Ca2+ fluxes and interactions are abstracted …

Characterization Of Lactobacilli-Containing Catheter Segments Developed By Using Selective Laser Sintered Mold., Caden Maners

Master of Engineering Theses

Catheter-associated urinary tract infections (CAUTIs) are a major healthcare burden with current prevention strategies offering limited success. This study presents a novel, self-coating biomaterial approach using a silicone-based bioink embedded with thermally sensitive probiotic strains (L. crispatus, L. rhamnosus, and L. reuteri). Catheter segments were fabricated via bio-injection molding using 3D-printed CAD molds. These Lactobacilli, selected for their probiotic and antimicrobial potential, serve as a non- antibiotic strategy to reduce infection risk. These segments were evaluated for mechanical strength (Shore A hardness), thermal stability (TGA/DSC), porosity and bacterial presence (SEM), biofilm formation (crystal-violet assay), as well as mass retention in …

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 …

Amyloid Accumulation, Brain Atrophy, And Cognitive Decline In Emergent Alzheimer's Disease, Ying Xia, Pierrick Bourgeat, Vincent Doré, Jurgen Fripp, Yen Ying Lim, Simon M. Laws, Christopher Fowler, Christopher C. Rowe, Colin L. Masters, Elizabeth J. Coulson, Paul Maruff

Research outputs 2022 to 2026

Introduction : Emergent Alzheimer's disease (AD) represents a transitional stage where cognitively unimpaired (CU) individuals exhibit subthreshold but increasing amyloid-β (Aβ) levels. The impact of Aβ accumulation on brain volume loss and cognition during this early stage remains unclear. Methods: This retrospective cohort study analyzed data from 408 CU participants who were initially Aβ− (< 15 Centiloids) and followed for up to 15 years. Changes in basal forebrain and hippocampal volume, along with domain-specific cognitive performance, were compared between those who progressed to Aβ+ (≥20 Centiloids) and those who remained Aβ−. Results: Sixty-five CU participants progressed to Aβ+, indicating emergent AD, and showed faster Aβ accumulation and subtle memory decline. However, no significant differences in rate of BF and hippocampal atrophy were observed between groups. Discussion: The results suggest that during this emergent phase of AD, Aβ accumulation is associated with episodic memory loss, in the absence of detectable accelerated brain atrophy. Highlights: Identified cognitively unimpaired individuals in the emergent stage of Alzheimer's disease (AD). Emergent AD exhibits a greater rate of amyloid-β (Aβ) accumulation. No accelerated volume loss detected in the basal forebrain or hippocampus. Emergent AD is also associated with a subtle decline in memory. Early Aβ accumulation may impair cognitive function before structural atrophy.

Functional Time Transformation Model With Applications To Digital Health, Rahul Ghosal Ph.D., Marcos Matabuena, Sujit K. Ghosh

Faculty Publications

The advent of wearable and sensor technologies now leads to functional predictors which are intrinsically infinite dimensional. While the existing approaches for functional data and survival outcomes lean on the well-established Cox model, the proportional hazard (PH) assumption might not always be suitable in real-world applications. Motivated by physiological signals encountered in digital medicine, we develop a more general and flexible functional time-transformation model for estimating the conditional survival function with both functional and scalar covariates. A partially functional regression model is used to directly model the survival time on the covariates through an unknown monotone transformation and …

Clinically Validated Graphical Approaches Identify Hepatosplenic Multimorbidity In Individuals At Risk Of Schistosomiasis, Yin-Cong Zhi, Simon Mpooya, Narcis Kabatereine, Betty Nabatte, Christopher Opio, Narcis Kabatereine, Goylette Chami

Internal Medicine, East Africa

The global burden of multimorbidity is increasing yet poorly understood, owing to insufficient methods for modelling complex systems of conditions. In particular, hepatosplenic multimorbidity has been inadequately investigated. From 17 January to 16 February 2023, we examined 3186 individuals aged 5–92 years from 52 villages across Uganda within the SchistoTrack Cohort. Point-of-care B-mode ultrasound was used to assess 45 hepatosplenic conditions within the context of schistosomiasis (Schistosoma mansoni). Three graph learning methods for representing hepatosplenic multimorbidity were compared. Thresholds for including graph edges were found using graph kernels and tested with graph neural networks to assess predictive utility for unobserved …

Reaction Control Mechanism In Deoxyuridine 5'-Triphosphate Nucleotidohydrolase, Aaron Delay

School of Biological Sciences: Dissertations, Theses, and Student Research

Deoxyuridine 5'-triphosphate nucleotidohydrolase (dUTPase) is an enzyme involved in the pyrimidine biosynthesis pathway, a key component of cellular DNA metabolism. It regulates intracellular uracil carrying triphosphate levels by hydrolyzing dUTP, thereby providing a substrate for thymidylate synthase (TS). The effective inhibition of dUTPase is expected to enhance TS-targeted chemotherapy by promoting thymine-less apoptosis.

Although the reaction mechanism of dUTPase has been studied, the human nuclear homotrimeric form remains complex, as all three subunits cooperatively form a single active site. As a result, the detailed molecular dynamics of its catalysis are still not fully understood. In this study, I investigated the …

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 …

1d Thermoembolization Model Using Ct Imaging Data For Porcine Liver, Rohan Amare, Danielle Stolley, Steve Parrish, Megan Jacobsen, Rick R Layman, Chimamanda Santos, Beatrice Riviere, Natalie Fowlkes, David Fuentes, Erik Cressman

Faculty, Staff and Student Publications

Innovative therapies such as thermoembolization are expected to play an important role in improving care for patients with diseases such as hepatocellular carcinoma. Thermoembolization is a minimally invasive strategy that combines thermal ablation and embolization in a single procedure. This approach exploits an exothermic chemical reaction that occurs when an acid chloride is delivered via an endovascular route. However, comprehension of the complexities of the biophysics of thermoembolization is challenging. Mathematical models can aid in understanding such complex processes and assisting clinicians in making informed decisions. In this study, we used a Hagen-Poiseuille 1D blood flow model to predict the …

Extubation Decisions With Predictive Information For Mechanically Ventilated Patients In Icu, Guang Cheng, Jingui Xie, Zhichao Zheng, Haidong Luo, Oon Cheong Ooi

Research Collection Lee Kong Chian School Of Business

Weaning patients from mechanical ventilators is a crucial decision in intensive care units (ICUs), significantly affecting patient outcomes and the throughput of ICUs. This study aims to improve the current extubation protocols by incorporating predictive information on patient health conditions. We develop a discrete-time, finite-horizon Markov decision process with predictions of future state to support extubation decisions. We characterize the structure of the optimal policy and provide important insights into how predictive information can lead to different decision protocols. We demonstrate that adding predictive information is always beneficial, even if physicians place excessive trust in the predictions, as long as …

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 …

Digital Stress Scale (Dsc): Development And Psychometric Validation Of A Measure Of Stress In The Digital Age, Agathi Argyriadi, Dimitra Katsarou, Athina Patelarou, Kalliopi Megari, Evridiki Patelarou, Stiliani Kotrotsiou, Konstantinos Giakoumidakis, Shabnam Abdoola, Evangelos Mantsos, Efthymia Efthymiou, Alexandros Argyriadis

All Works

(1) Background: The integration of digital technologies such as electronic health records (EHRs), telepsychiatry, and communication platforms has transformed the mental health sector a lot compared to in previous years. While these tools enhance service delivery, they also introduce unique stressors. Despite growing concerns, there is no validated instrument specifically designed to measure the digital stress experienced by mental health professionals. (2) Methods: This study involved the development and psychometric validation of the Digital Stress Scale (DSC). The process included item generation through a literature review and qualitative interviews, expert panel validation, and a two-phase statistical evaluation. Exploratory Factor Analysis …

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 …

Evaluating The Predictive Value Of Basc-3 Anxiety Scale And Working Memory Index Scores For Clinically Significant Test Anxiety: A Comprehensive Analysis Of Non-Classifiable Cases, Des'tiana S. Williams

Electronic Theses and Dissertations

This dissertation will explore how test anxiety (TA) affects working memory (WM) and whether certain factors can help predict higher levels of test anxiety. Anxiety has been defined as a common experience that can show up in various forms—like general worry, social fears, panic attacks, and specific phobias (APA, 2022). It was described as often triggering our natural “fight-or-flight” response, which can impact our ability to focus, think clearly, and remember things. For students, test anxiety has been especially challenging, affecting how they perform in high-stakes academic settings. Using data from a university based psychological assessment center, this study will …

Evaluating The Predictive Value Of Basc-3 Anxiety Scale And Working Memory Index Scores For Clinically Significant Test Anxiety: A Comprehensive Analysis Of Non-Classifiable Cases, Des'tiana S. Williams

Electronic Theses and Dissertations

This dissertation will explore how test anxiety (TA) affects working memory (WM) and whether certain factors can help predict higher levels of test anxiety. Anxiety has been defined as a common experience that can show up in various forms—like general worry, social fears, panic attacks, and specific phobias (APA, 2022). It was described as often triggering our natural “fight-or-flight” response, which can impact our ability to focus, think clearly, and remember things. For students, test anxiety has been especially challenging, affecting how they perform in high-stakes academic settings. Using data from a university based psychological assessment center, this study will …

Metabolic Clearance Rate Of Insulin Across The Glucose Tolerance Spectrum By Race And Ethnicity In Youth With Obesity, Wonhee Cho, Fida Bacha, Hala Tfayli, Sojung Lee, Sara F Michaliszyn, Joon Young Kim, Silva Arslanian

Children’s Nutrition Research Center Staff Publications

Objective: Despite β-cell failure in youth with dysglycemia (i.e., impaired glucose tolerance [IGT] and type 2 diabetes), fasting insulin (FI) concentrations are elevated. Herein, we examined the following: 1) metabolic clearance rate of insulin (MCRI) in youth with obesity and normal glucose tolerance (NGT) versus those with IGT versus those with type 2 diabetes; 2) racial and ethnic differences in insulin dynamics; and 3) metabolic/adiposity correlates of MCRI.

Methods: A total of 206 youth underwent assessment of fasting glucose, FI, MCRI and peripheral insulin sensitivity (PIS), first-phase insulin secretion, disposition index, body composition, and abdominal adiposity.

Results: In type 2 …

Individualized Functional And Structural Language Lateralities In Temporal Lobe Epilepsy And Their Impact On Memory, Ankeeta Ankeeta, Qirui Zhang, Sam Sharifzadeh Javidi, Shilpi Modi, Michael R. Sperling, Joseph I. Tracy

Department of Neurology Faculty Papers

The basis and impact of functional asymmetries in the brain, particularly language lateralization, are not fully understood, and the relationship between functional and structural asymmetries remains largely untested. This study investigated the degree to which asymmetries in hemispheric language laterality are concordant with asymmetries in gray matter (GM) structure and whether the hemispheric organization of memory is influenced by functional language asymmetries. Structural and functional MR data was acquired from 261 individuals, including those with unilateral temporal lobe epilepsy (LTLE = 96, RTLE = 69) and matched with healthy participants (HPs = 96). Functional language laterality indices (LIs) were calculated …

Multiple Subcortical And Subcortico-Cortico Dynamic Network Reconfigurations Characterize Focal-To-Bilateral Tonic-Clonic Seizures, Shilpi Modi, A. Ankeeta, Walter Hinds, Michael R. Sperling, Xiaosong He, Joseph I. Tracy

Department of Neurology Faculty Papers

Temporal lobe epilepsy (TLE) is the most common focal epilepsy, with focal to bilateral tonic-clonic seizures (FBTCS+) a more severe form of the disorder. Evidence has underscored the critical role of the thalamus, mesial temporal region, basal ganglia and cerebellum, along with the cortex, in the propagation, termination, and modulation of seizure activity. We examined time variant patterns of interaction within and between 7 cortical and 4 subcortical systems in 55 healthy controls and 56 patients with TLE (n = 40 with FBTCS+ and 15 without), isolating those patterns most distinctive of FBTCS+ utilizing tools from dynamic network neuroscience on …

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 …