Disease Modeling Commons^™

Oropharyngeal Syphilis Presenting As Tongue Based Ulcer With Lymphadenopathy, Serena F. Pu, Kevin J. Carlson, Jonathan R. Mark, Benjamin J. Rubinstein

Department of Otolaryngology (ENT) Faculty Publications

Within the aerodigestive tract, syphilis presents with varied signs and symptoms, some of which may mimic malignancy or other disease processes. We present the case of a 29-year-old man with otalgia and odynophagia who was found on physical examination and office laryngoscopy to have a 4-cm ulcerative mass of the tongue base and cervical lymphadenopathy. While planning for tissue diagnosis, the patient’s serologies revealed positive treponemal antibody testing and elevated rapid plasma reagin (RPR) titers, confirming syphilitic infection, likely representing secondary syphilis. While awaiting operative biopsy, the patient received intramuscular penicillin with complete resolution of the mass and symptoms, and …

Paneugenesis: A Regenerative Systems Hypothesis For Advancing Health Promotion, Craig M. Becker, Leslie Hoglund, Beth Chaney, Joseph G. L. Lee, Michael Stellefson, Alex Davis

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Despite major advances in health promotion science, dominant approaches remain largely prevention-and risk-reduction-oriented. The prevailing orientation creates a substantial opportunity to advance generative, system-design strategies that intentionally produce well-being rather than merely prevent disease. This article proposes paneugenesis as a regenerative systems framework and a testable theoretical model for the intentional creation of net-positive outcomes, thereby extending health promotion beyond its traditional pathogenic emphasis. Paneugenesis integrates systems science, salutogenesis, behavioral science, complexity theory, and quality management principles into a unified four-function process: operationalizing idealized outcomes, identifying key precursors, optimizing processes, and continually plotting progress through feedback mechanisms. The central hypothesis …

A Scoping Review To Conceptualize Social Privilege For Studying Patients' Health Outcomes And Health Disparities, Elizabeth A. Brown, Priyanka Patel, Esther May B. Sarino, Vladimir Markovic, Carles Muntaner

Health Behavior, Policy & Management Faculty Publications

Background

The continued reliance on single-category self-reported demographic data (e.g., race/ethnicity) reflects conceptual limitations that hinder the study and understanding of health outcomes research. There is a pressing need for more precise measures of social privilege that conceptualize privilege and oppression while enabling the examination of their effects on health outcomes in the United States (US) healthcare system.

Objective

The purpose of this scoping review was to review the literature, determine how researchers have measured aspects of privilege and oppression, and develop a conceptual framework to study patients' social privilege in the US healthcare system and public health research.

Methods …

The Crucial Role Of Machine Learning Models In Predicting Current Childhood Asthma: Model Comparison, Calibration, And Shap-Based Interpretation, Aditya Chakraborty, A. K.M. Raquibul Bashar

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Background: Asthma is one of the most prominent chronic diseases in children and one of the most challenging ailments to diagnose in infants and preschoolers in the United States. Predictive models can be instrumental in improving early diagnosis, personalized treatment strategies, and disease progression. By utilizing nationalized data, this study focuses on building and comparing high-performing analytical predictive models based on the relevant risk factors and identifying the most influential predictors.

Methods: We analyzed cross-sectional BRFSS Asthma Call-Back Survey data (2011-2020; N = 9,813) and randomly split participants into training and testing sets. An XGBoost model (hyperparameters tuned via grid …

Enhancing The Accuracy Of Image Classification For Degenerative Brain Diseases With Cnn Ensemble Models Using Mel-Spectrograms, Sang-Ha Sung, Michael Pokojovy, Do-Young Kang, Woo-Yong Bae, Yeon-Jae Hong, Sangjin Kim

Mathematics & Statistics Faculty Publications

Alzheimer’s disease (AD) and Parkinson’s disease (PD) are prevalent neurodegenerative disorders among the elderly, leading to cognitive decline and motor impairments. As the population ages, the prevalence of these neurodegenerative disorders is increasing, providing motivation for active research in this area. However, most studies are conducted using brain imaging, with relatively few studies utilizing voice data. Using voice data offers advantages in accessibility compared to brain imaging analysis. This study introduces a novel ensemble-based classification model that utilizes Mel spectrograms and Convolutional Neural Networks (CNNs) to distinguish between healthy individuals (NM), AD, and PD patients. A total of 700 voice …

Lrtm Left-Right Transition Matrices For Molecular Interaction Prediction, Kaitlin Zheng, Guihua Duan, Mengyun Yang, Wei Wu, Yao-Hang Li, Jianxin Wang

Computer Science Faculty Publications

Molecular interactions are central to most biological processes. The discovery and identification of potential associations between molecules can provide insights into biological exploration, diagnostic and therapeutic interventions, and drug development. So far many relevant computational methods have been proposed, but most of them are usually limited to specific domains and rely on complex preprocessing procedures, which restricts the models’ ability to be applied to other tasks. Therefore, it remains a challenge to explore a generalized approach to accurately predicting potential associations. In this study, We propose Left-Right Transition Matrices (LRTM) for molecular interaction prediction. From the perspective on the diffusion …

Marineepi: A Gui-Based Matlab Toolbox To Simulate Marine Pathogen Transmission, Gorka Bidegain, Tal Ben-Horin, Eric N. Powell, John M. Klinck, Eileen E. Hofmann

CCPO Publications

The Graphical User Interface (GUI) MarineEpi is presented as a Matlab toolbox for easily (i) constructing disease transmission models for different marine host-pathogen systems, (ii) running simulations by specifying initial conditions and model parameters, and (iii) interpreting the resulting time series of the host and pathogen population dynamics. MarineEpi users can generate models for systems in which pathogen transmission occurs through contact with infected individuals (SI), contact with dead infected individuals (SID), contact with environmental pathogens released by infected individuals (SIP), and contact with environmental pathogens released by dead infected individuals (SIPD). MarineEpi is a freely available GUI that provides …

Heart Disease Prediction Using Stacking Model With Balancing Techniques And Dimensionality Reduction, Ayesha Noor, Nadeem Javaid, Nabil Alrajeh, Babar Mansoor, Ali Khaqan, Safdar Hussain Bouk

School of Cybersecurity Faculty Publications

Heart disease is a serious worldwide health issue with wide-reaching effects. Since heart disease is one of the leading causes of mortality worldwide, early detection is crucial. Emerging technologies like Machine Learning (ML) are currently being actively used by the biomedical, healthcare, and health prediction industries. PaRSEL, a new stacking model is proposed in this research, that combines four classifiers, Passive Aggressive Classifier (PAC), Ridge Classifier (RC), Stochastic Gradient Descent Classifier (SGDC), and eXtreme Gradient Boosting (XGBoost), at the base layer, and LogitBoost is deployed for the final predictions at the meta layer. The imbalanced and irrelevant features in the …

A Unified Health Information System Framework For Connecting Data, People, Devices, And Systems, Wu He, Justin Zuopeng Zhang, Huanmei Wu, Wenzhuo Li, Sachin Shetty

Information Technology & Decision Sciences Faculty Publications

The COVID-19 pandemic has heightened the necessity for pervasive data and system interoperability to manage healthcare information and knowledge. There is an urgent need to better understand the role of interoperability in improving the societal responses to the pandemic. This paper explores data and system interoperability, a very specific area that could contribute to fighting COVID-19. Specifically, the authors propose a unified health information system framework to connect data, systems, and devices to increase interoperability and manage healthcare information and knowledge. A blockchain-based solution is also provided as a recommendation for improving the data and system interoperability in healthcare.

Predictive Modeling And Estimation Of The Doubling Time Of Confirmed Cases Of Covid-19 In Niger, Ibrahim Sidi Zakari, Hadiza Galadima

Community & Environmental Health Faculty Publications

Modeling is increasingly used to assess scenarios and make projections on the future course of new coronavirus disease. This allows for better planning of care as well as a relaxation or tightening of the restrictive measures decreed by the government and the health authorities. The data analyzed in this study covers the period from March 19 to June 05, 2020 and allowed predictions of new cases of COVID-19 based on a growth model with a growth rate that changes linearly over time. In addition, we calculated and predicted the doubling time of the number of positive cases in each region …

Functionality Of Membrane Proteins Overexpressed And Purified From E. Coli Is Highly Dependent Upon The Strain, Khadija Mathieu, Waqas Javed, Sylvain Vallet, Christian Lesterlin, Marie-Pierre Candusso, Feng Ding, Xiaohong Nancy Xu, Christine Ebel, Jean-Michel Jault, Cédric Orelle

Chemistry & Biochemistry Faculty Publications

Overexpression of correctly folded membrane proteins is a fundamental prerequisite for functional and structural studies. One of the most commonly used expression systems for the production of membrane proteins is Escherichia coli. While misfolded proteins typically aggregate and form inclusions bodies, membrane proteins that are addressed to the membrane and extractable by detergents are generally assumed to be properly folded. Accordingly, GFP fusion strategy is often used as a fluorescent proxy to monitor their expression and folding quality. Here we investigated the functionality of two different multidrug ABC transporters, the homodimer BmrA from Bacillus subtilis and the heterodimer PatA/PatB …

Selective Mutation Accumulation: A Computational Model Of The Paternal Age Effect, Eoin C. Whelan, Alexander C. Nwala, Christopher Osgood, Stephan Olariu

Biological Sciences Faculty Publications

Motivation: As the mean age of parenthood grows, the effect of parental age on genetic disease and child health becomes ever more important. A number of autosomal dominant disorders show a dramatic paternal age effect due to selfish mutations: substitutions that grant spermatogonial stem cells (SSCs) a selective advantage in the testes of the father, but have a deleterious effect in offspring. In this paper we present a computational technique to model the SSC niche in order to examine the phenomenon and draw conclusions across different genes and disorders.

Results: We used a Markov chain to model the probabilities of …

Analyzing The Effects Of Policy Options To Mitigate The Effect Of Sea Level Rise On The Public Health And Medically Fragile Population: A System Dynamics Approach, Rafael Diaz, Joshua Behr, Anna Jeng, Hua Liu, Franceso Longo

VMASC Publications

A critical question related to climate change concerns to how rising sea level will affect underserved populations and medically fragile population in coastal zones and floodplains. As sea levels rise, coastal waters will regain near-tidal areas and co-mingle with human-made pollutants, resulting from decades of industrial and commercial activity. This poses potential threat and risks to public health and the environment. It is critical that decision makers will initiate a process of parsing resources to the mitigation and management of these issues. The purpose of this research is to model the inherent dynamics of this process and understand how near-term …