Medicine and Health Sciences Commons^™

Modeling An Infection Outbreak With Quarantine: The Sibkr Model, Mikenna Dew, Amanda Langosch, Theadora Baker-Wallerstein

Rose-Hulman Undergraduate Mathematics Journal

Influenza is a respiratory infection that places a substantial burden in the world population each year. In this project, we study and interpret a data set from a flu outbreak in a British boarding school in 1978 with mathematical modeling. First, we propose a generalization of the SIR model based on the quarantine measure in place and establish the long-time behavior of the model. By analyzing the model mathematically, we determine the analytic formulas of the basic reproduction number, the long-time limit of solutions, and the maximum number of infection population. Moreover, we estimate the parameters of the model based …

Arsenic Contamination Needs Serious Attention: An Opinion And Global Scenario, Abhijnan Bhat School Of Food Science And Environmental Health, Kamna Ravi Health, Engineering & Materials Sciences (Hems) Hub, Furong Tian Nanolab Research Centre, Baljit Singh Micra Biodiagnostics Technology Gateway

Articles

Arsenic (As) contamination is a serious global concern, polluting our natural resources, including water and soil, and posing a danger to the environment and public health. Arsenic is present in the groundwater of several countries and this contaminated water is used for irrigation, drinking, and food preparation, which poses the greatest threat to public health. Nearly 106 countries are affected by groundwater arsenic contamination and an estimated 230 million individuals worldwide are exposed to its adverse health effects, including increased cancer risks, associated cardiovascular disease and diabetes, skin lesions, neurological effects, kidney damage, and foetal or cognitive development-related complications. Arsenic …

04.08.2024 Orsp Connect, Liz Williamson

ORED Newsletter

Nature Masterclasses Overview, Mary Lea McMillan, Cost Transfer Policy, NSF Author and Allocation citing

Discourse- And Lesion-Based Aphasia Quotient Estimation Using Machine Learning, Nicholas Riccardi, Satvik Nelakuditi, Dirk B. Den Ouden, Chris Rorden, Julius Fridriksson, Rutvik H. Desai

Communication Sciences and Disorders Faculty Articles and Research

Discourse is a fundamentally important aspect of communication, and discourse production provides a wealth of information about linguistic ability. Aphasia commonly affects, in multiple ways, the ability to produce discourse. Comprehensive aphasia assessments such as the Western Aphasia Battery-Revised (WAB-R) are time- and resource-intensive. We examined whether discourse measures can be used to estimate WAB-R Aphasia Quotient (AQ), and whether this can serve as an ecologically valid, less resource-intensive measure. We used features extracted from discourse tasks using three AphasiaBank prompts involving expositional (picture description), story narrative, and procedural discourse. These features were used to train a machine learning model …

Green Oxidation Of Aromatic Hydrazide Derivatives Using An Oxoammonium Salt, Nidheesh Phadnis, Jessica A. Molen, Shannon M. Stephens, Shayne M. Weierbach, Kyle M. Lambert, John A. Milligan

College of Life Sciences Faculty Papers

Aromatic diazenes are often prepared by oxidation of the corresponding hydrazides using stoichiometric quantities of nonrecyclable oxidants. We developed a convenient alternative protocol for the oxidation of aromatic hydrazides using Bobbitt's salt (1), a metal-free, recyclable, and commercially available oxoammonium reagent. A variety of aryl hydrazides were oxidized within 75 min at room temperature using the developed protocol. Computational insight suggests that this oxidation occurs by a polar hydride transfer mechanism.

Leveraging Explainable Artificial Intelligence To Optimize Clinical Decision Support, Siru Liu, Allison B Mccoy, Josh F Peterson, Thomas A Lasko, Dean F Sittig, Scott D Nelson, Jennifer Andrews, Lorraine Patterson, Cheryl M Cobb, David Mulherin, Colleen T Morton, Adam Wright

Faculty, Staff and Student Publications

OBJECTIVE: To develop and evaluate a data-driven process to generate suggestions for improving alert criteria using explainable artificial intelligence (XAI) approaches.

METHODS: We extracted data on alerts generated from January 1, 2019 to December 31, 2020, at Vanderbilt University Medical Center. We developed machine learning models to predict user responses to alerts. We applied XAI techniques to generate global explanations and local explanations. We evaluated the generated suggestions by comparing with alert's historical change logs and stakeholder interviews. Suggestions that either matched (or partially matched) changes already made to the alert or were considered clinically correct were classified as helpful. …

Effects Of Sars-Cov-2 Variants On Cd8+ T Cell Epitope Diversity: Estimating Clinical Severity In The United States, Grace Kim, Jacob Elnaggar, Maya Sevalia, Najah Nicholas, Mallory Varnado, Judy Crabtree, Lucio Miele

School of Medicine Faculty Publications

Association for Clinical and Translational Science 2024; April 3 - April 5, 2024; Las Vegas, NV

Ai Is A Viable Alternative To High Throughput Screening: A 318-Target Study, Izhar Wallach, Denzil Bernard, Kong Nguyen, Gregory Ho, Adrian Morrison, Adrian Stecula, Andreana Rosnik, Ann Marie O’Sullivan, Aram Davtyan, Ben Samudio, Bill Thomas, Brad Worley, Brittany Butler, Christian Laggner, Desiree Thayer, Ehsan Moharreri, Greg Friedland, Ha Truong, Henry Van Den Bedem, Ho Leung Ng, Kate Stafford, Krishna Sarangapani, Kyle Giesler, Lien Ngo, Michael Mysinger, Mostafa Ahmed, Nicholas J. Anthis, Niel Henriksen, Arthur L. Haas, Et Al

School of Medicine Faculty Publications

High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, …

Associations Between Sleep Duration, Sleep Disturbance And Cardiovascular Disease Biomarkers Among Adults In The United States, Prince Nii Ossah Addo, Paddington T. Mundagowa, Longgang Zhao, Mufaro Kanyangarara, Monique J. Brown Ph.D., Mph, Jihong Liu Sc.D.

Faculty Publications

Background

Sleep problems are associated with abnormal cardiovascular biomarkers and an increased risk of cardiovascular diseases (CVDs). However, studies investigating associations between sleep problems and CVD biomarkers have reported conflicting findings. This study examined the associations between sleep problems and CVD biomarkers in the United States.

Methods

Data were from the National Health and Nutrition Examination Survey (NHANES) (2007–2018) and analyses were restricted to adults ≥ 20 years (n = 23,749). CVD biomarkers [C-reactive Protein (CRP), low-density lipoproteins, high-density lipoproteins (HDL), triglycerides, insulin, glycosylated hemoglobin (HbA1c), and fasting blood glucose] were categorized as abnormal or normal using standardized cut-off …

Cardiogpt: An Ecg Interpretation Generation Model, Guohua Fu, Jianwei Zheng, Islam Abudayyeh, Chizobam Ani, Cyril Rakovski, Louis Ehwerhemuepha, Hongxia Lu, Yongjuan Guo, Shenglin Liu, Huimin Chu, Bing Yang

Mathematics, Physics, and Computer Science Faculty Articles and Research

Numerous supervised learning models aimed at classifying 12-lead electrocardiograms into different groups have shown impressive performance by utilizing deep learning algorithms. However, few studies are dedicated to applying the Generative Pre-trained Transformer (GPT) model in interpreting electrocardiogram (ECG) using natural language. Thus, we are pioneering the exploration of this uncharted territory by employing the CardioGPT model to tackle this challenge. We used a dataset of ECGs (standard 10s, 12-channel format) from adult patients, with 60 distinct rhythms or conduction abnormalities annotated by board-certified, actively practicing cardiologists. The ECGs were collected from The First Affiliated Hospital of Ningbo University and Shanghai …

A Systematic Review: Mirror Neurons & Schizophrenia, Yashesvi Sharma, Surajit Dey

Annual Research Symposium

This research project establishes a link between Mirror Neuron System (MNS) activity and this information's implications in treating and understanding schizophrenia, specifically, schizophrenic patients with negative symptoms.

Health And Healthcare: Designing For The Social Determinants Of Health And Blue Zones In North Nashville, Rebecca Tonguis, Honor Thomas, Olivia Hobbs

[Archive] Belmont University Research Symposium (BURS)

Owned by North Nashville’s First Community Church, a now empty site in the Osage-North Fisk neighborhood of North Nashville has been identified as a potential site for a new location of The Store, in addition to a community-centric architectural development based on the social determinants of health and informed by the principles behind Blue Zones, the locations with the highest lifespans in the world. Opened by Brad Paisley and Kimberly Williams-Paisley, The Store is a free grocery store that “allow[s] people to shop for their basic needs in a way that protects dignity and fosters hope”, for which North Nashville …

Santa Clara Magazine, Volume 65 Number 1, Spring 2024, Santa Clara University

Santa Clara Magazine

14 - A CAMPUS ON THE RISE Six new buildings on campus aren’t the only changes brought by a successful $1 billion fundraising campaign. Lauren Loftus & Leslie Griffy

20 - HUMAN AT HEART How Santa Clara University is distinguishing itself as a leader in human-focused health care innovation. Lauren Loftus

26 - SHEPHERDING INNOVATION How wonder, and God, can make us better scientists. Brother Guy Consolmagno, S.J.

30 - THE CO-OP Santa Clara University has long been a bastion of interdisciplinary learning. A new fund is taking cross-collaboration to new heights. SCM Staff

34 - MAKE AI THE BEST …

2024- The Twenty-Eighth Annual Symposium Of Student Scholars

Symposium of Student Scholars Program Books

The full program book from the 28th Annual Symposium of Student Scholars, held on April 17-19, 2024. Includes abstracts from the presentations and posters.

Increased Perceived Confidence In Professional Role Skills Among Undergraduate Dietetic Students Following Simulation-Based Learning Experiences, Makenzie Barr-Porter, Elizabeth Combs, Lauren Batey, Dawn Brewer, Aaron Kyle Schwartz, Tammy Stephenson

UK CARES Faculty Publications

Simulation-based learning experiences (SBLEs) are effective for teaching healthcare students clinical and communication skills. The current study assessed self-perceived clinical and communication confidence among dietetics students completing a series of four SBLEs (3 group, 1 individual) across nine months. Dietetics students were recruited in February 2023 prior to their first SBLE. Simultaneously through the academic year, students completed clinical and communication courses. Students were invited to complete an online, anonymous self-reported survey regarding confidence with nutrition care and communication prior to their first SBLE (Time 1), prior to their third SBLE (Time 2), and following their final SBLE (Time 3). …

Predicting Biomolecular Properties And Interactions Using Numerical, Statistical And Machine Learning Methods, Elyssa Sliheet

Mathematics Theses and Dissertations

We investigate machine learning and electrostatic methods to predict biophysical properties of proteins, such as solvation energy and protein ligand binding affinity, for the purpose of drug discovery/development. We focus on the Poisson-Boltzmann model and various high performance computing considerations such as parallelization schemes.

Short-Term Larval Surveys Reveal Rainy Season Breeding Site Preferences Of Malaria Vector Anopheles Spp. In Zanzibar City, Kaeden K. Hill

Independent Study Project (ISP) Collection

Malaria is a serious illness that causes over 500,000 deaths annually worldwide, with Tanzania alone contributing to approximately 4% of those deaths. Malaria is caused by Plasmodium spp. parasites, and it is vectored by mosquitoes in the Anopheles genus. In Zanzibar City, the incidence of malaria has decreased over the past few decades due to standardized treatment protocols and public health interventions targeting adult mosquitoes. However, the incidence remains between 1-2%, with an increasing trend observed over the past few years likely stemming from continued exchange of Plasmodium spp. from other malaria-endemic areas. Because larvicidal strategies can be useful in …

A Literature Review On The Use Of Ai Technology For Medical Diagnosis, Olivia Maddock

Senior Honors Projects

The integration of technology like artificial intelligence (AI) in medical diagnosis offers a unique solution to the growing demands of healthcare providers across all fields of medicine. The purpose of the literature review is to examine current and future applications of artificial intelligence in healthcare, as well as associated challenges to implementing AI in medical decision-making and care access. The literature review was organized into sections examining current applications, limitations, and future directions. From the literature review conducted, I found that AI technology like machine learning (ML) and deep learning (DL) have the potential to optimize fields like medical diagnostics, …

Mediating Effect Of Bmi On The Association Of Economic Status And Coexistence Of Hypertension And Diabetes In Bangladesh: A Counterfactual Framework-Based Weighting Approach, Foyez , Md. Jamal Hossain Ahmmed, Md. Jamal Hossain, Md Tareq Ferdous Khan, Muhammad Mahabub Rahaman Manik, Saimon Shahriar, Dulal Chandra Nandi, Md Parvej Hussain

Mathematics and Statistics Faculty Publications

Background and Aims

Non-communicable diseases such as hypertension and diabetes are matters of huge concern worldwide, with an increasing trend in prevalence over the previous decade. First of all, this study aimed to evaluate the association between economic status (ES) and body mass index (BMI), ES and comorbidity of hypertension and diabetes, and BMI and comorbidity independently. Second, it explored the mediating role of BMI in the association between ES and comorbidity of hypertension and diabetes. Finally, it investigated whether the mediating effect differs with the place of residence, gender, and education levels.

Methods

A total of 11,291 complete cases …

04.01.2024 Orsp Connect, Liz Williamson

ORED Newsletter

NSF Conference, Jennifer Baumbaugh, Sustainable Food Packaging research, Export Control Policy Update

An Investigation On The Intricacies Of Epigenetic Modulations In The Pathogenesis Of Human Papillomavirus-Associated Cervical Cancer: A Comprehensive Meta-Narrative Synthesis, Jade Carolina Cabello, Marcella Victoria Ras, Katelyn Thy Nhung Tran, Athit Voytas

Research Methods Poster Session 2024

Abstract

Objective: To conduct a meta-analysis of the available and relevant literature on E1/E2 genes and their affect on the epigenetics of Human Papillomavirus caused uterine cervical cancer.

Background/Significance: Human Papillomavirus is strongly linked to cervical cancer, and cervical cancer is the fourth most common type of cancer in women. 99.7% of patients with cervical cancer have a “high risk HPV genotype” which factors greatly into the causation if their diagnosis. The HPV vaccine that came out in 2006 has greatly decreased cervical cancer in the population as well as increased the preventative chances of highly susceptible individuals.

Methods: To …

2024 Research Day Program, Lincoln Memorial University

Research Day

This program contains abstracts and presentation summaries from LMU's 2024 Annual Research Day conference.

Introduction To The Special Centennial Issue, Woodward S. Bousquet, Christopher Osgood

Virginia Journal of Science

This special issue of the Virginia Journal of Science (VJS) is dedicated to the 2023 Centennial of the Virginia Academy of Science (VAS). It includes congratulations from Commonwealth leaders, a proclamation by the Virginia General Assembly Senate, Academy members’ personal reflections, several historical papers and summaries, and portions of the program for the May 25-26, 2023 Annual Meeting in Williamsburg on the William & Mary campus.

Reflections About The Academy And Its Centennial, Marco Aldi, Woodward S. Bousquet

Virginia Journal of Science

Brief reflective essays from members of the Virginia Academy of Science were solicited as part of the Academy's centennial commemoration in 2023. The essays received demonstrate the many and varied ways in which the Academy has fostered collegiality, encouraged research, supported science education, and shaped the course of science in Virginia during the organization's 100-year history.

Transcriptional Signature Of Durable Effector T Cells Elicited By A Replication Defective Hcmv Vaccine, Xiaohua Ye, David J H Shih, Zhiqiang Ku, Junping Hong, Diane F Barrett, Richard E Rupp, Ningyan Zhang, Tong-Ming Fu, W Jim Zheng, Zhiqiang An

Faculty, Staff and Student Publications

Human cytomegalovirus (HCMV) is a leading infectious cause of birth defects and the most common opportunistic infection that causes life-threatening diseases post-transplantation; however, an effective vaccine remains elusive. V160 is a live-attenuated replication defective HCMV vaccine that showed a 42.4% efficacy against primary HCMV infection among seronegative women in a phase 2b clinical trial. Here, we integrated the multicolor flow cytometry, longitudinal T cell receptor (TCR) sequencing, and single-cell RNA/TCR sequencing approaches to characterize the magnitude, phenotype, and functional quality of human T cell responses to V160. We demonstrated that V160 de novo induces IE-1 and pp65 specific durable polyfunctional …

Learning From Data In Dentistry: Summary Of The Third Annual Openwide Conference, Elsbeth Kalenderian, Kawtar Zouaidi, Jan Yeager, Janelle Urata, Alfa Yansane, Bunmi Tokede, D Brad Rindal, Heiko Spallek, Joel White, Muhammad Walji

Faculty, Staff and Student Publications

The overarching goal of the third scientific oral health symposium was to introduce the concept of a learning health system to the dental community and to identify and discuss cutting-edge research and strategies using data for improving the quality of dental care and patient safety. Conference participants included clinically active dentists, dental researchers, quality improvement experts, informaticians, insurers, EHR vendors/developers, and members of dental professional organizations and dental service organizations. This report summarizes the main outputs of the third annual OpenWide conference held in Houston, Texas, on October 12, 2022, as an affiliated meeting of the American Dental Association (ADA) …

Evaluating And Improving The Usability Of A Mhealth Platform To Assess Postoperative Dental Pain, Ana M Ibarra-Noriega, Alfa Yansane, Joanna Mullins, Kristen Simmons, Nicholas Skourtes, David Holmes, Joel White, Elsbeth Kalenderian, Muhammad F Walji

Faculty, Staff and Student Publications

OBJECTIVES: The use of interactive mobile health (mHealth) applications to monitor patient-reported postoperative pain outcomes is an emerging area in dentistry that requires further exploration. This study aimed to evaluate and improve the usability of an existing mHealth application.

MATERIALS AND METHODS: The usability of the application was assessed iteratively using a 3-phase approach, including a rapid cognitive walkthrough (Phase I), lab-based usability testing (Phase II), and

RESULTS: The rapid cognitive walkthrough identified 23 potential issues that could negatively impact user experience, with the majority classified as system issues. The lab-based usability testing yielded 141 usability issues.; 43% encountered by …

Unveiling Gene Interactions In Alzheimer's Disease By Integrating Genetic And Epigenetic Data With A Network-Based Approach, Keith L Sanders, Astrid M Manuel, Andi Liu, Boyan Leng, Xiangning Chen, Zhongming Zhao

Faculty, Staff and Student Publications

Alzheimer’s Disease (AD) is a complex disease and the leading cause of dementia in older people. We aimed to uncover aspects of AD’s pathogenesis that may contribute to drug repurposing efforts by integrating DNA methylation and genetic data. Implementing the network-based tool, a dense module search of genome-wide association studies (dmGWAS), we integrated a large-scale GWAS dataset with DNA methylation data to identify gene network modules associated with AD. Our analysis yielded 286 significant gene network modules. Notably, the foremost module included the BIN1 gene, showing the largest GWAS signal, and the GNAS gene, the most significantly hypermethylated. We conducted …

Digital Health Technologies For High-Risk Pregnancy Management: Three Case Studies Using Digilego Framework, Sahiti Myneni, Alexandra Zingg, Tavleen Singh, Angela Ross, Amy Franklin, Deevakar Rogith, Jerrie Refuerzo

Faculty, Staff and Student Publications

OBJECTIVE: High-risk pregnancy (HRP) conditions such as gestational diabetes mellitus (GDM), hypertension (HTN), and peripartum depression (PPD) affect maternal and neonatal health. Patient engagement is critical for effective HRP management (HRPM). While digital technologies and analytics hold promise, emerging research indicates limited and suboptimal support offered by the highly prevalent pregnancy digital solutions within the commercial marketplace. In this article, we describe our efforts to develop a portfolio of digital products leveraging advances in social computing, data science, and digital health.

METHODS: We describe three studies that leverage core methods from

RESULTS: Scalable social computing models using deep learning classifiers …

Identification Of Novel F2-Isoprostane Metabolites By Specific Udp-Glucuronosyltransferases, Ginger L Milne, Marina S Nogueira, Benlian Gao, Stephanie C Sanchez, Warda Amin, Sarah Thomas, Camille Oger, Jean-Marie Galano, Harvey J Murff, Gong Yang, Thierry Durand

Faculty, Staff and Student Publications

UDP-glucuronosyltransferases (UGTs) catalyze the conjugation of glucuronic acid with endogenous and exogenous lipophilic small molecules to facilitate their inactivation and excretion from the body. This represents approximately 35 % of all phase II metabolic transformations. Fatty acids and their oxidized eicosanoid derivatives can be metabolized by UGTs. F2-isoprostanes (F2-IsoPs) are eicosanoids formed from the free radical oxidation of arachidonic acid. These molecules are potent vasoconstrictors and are widely used as biomarkers of endogenous oxidative damage. An increasing body of evidence demonstrates the efficacy of measuring the β-oxidation metabolites of F2-IsoPs rather than the unmetabolized F2-IsoPs to quantify oxidative damage in …