Medical Biomathematics and Biometrics Commons^™

Tumor–Immune Dynamics With Memory And Time Delay: A Fractional-Order Model With Ctla-4 Regulation, Mutaz Mohammad, Mohyeedden Sweidan, Alexander Trounev, Fathalla Rihan

Mathematical Modelling and Numerical Simulation with Applications

This study develops a fractional-order tumor-immune interaction model incorporating Caputo memory effects, delayed immune activation, and CTLA-4 checkpoint regulation. The model describes the coupled dynamics of tumor cells, CD4$^{+}$ T cells, IFN-$\gamma$, and CTLA-4, and extends classical integer-order tumor-immune models by accounting for hereditary immune responses and biologically motivated latency effects. Theoretical properties, including positivity, boundedness, equilibrium structure, and fractional-order stability, are examined to establish the biological and mathematical consistency of the model. The delayed fractional system is then investigated computationally by comparing several numerical methods, including finite difference discretization, Daubechies wavelet collocation, Euler wavelet collocation, and a predictor-corrector scheme. …

Network Analysis: An Application Of Graph Theory In Biology, Kiana Dunbar

Honors Theses

Graphs are simple, visual representations of entities as nodes connected by edges. They are used to convey relationships within a system. Networks are comprised of interrelated entities that are not easily separable, producing complex, structured data. These can be seen in social groups, highway systems, and even in biological systems. This paper surveys concepts in graph theory for application to the analysis of network data to understand disease. The features of graphs provide a useful framework for thinking about relationships between different genes or proteins. The structure of graphs is also compatible with a variety of machine learning tools. Especially …

A Probabilistic Modeling Analysis Of The Longitudinal Immune Response To Infection And Vaccination Across Demographic Groups And Pulmonary Symptoms, James O'Hanlon, Kaitlyn Sullivan, Lyndsey M. Muehling, Glenda Canderan, Jie Sun, Judith A. Woodfolk, Jeffrey M. Wilson, Rayanne A. Luke

Spora: A Journal of Biomathematics

Antibody and cytokine kinetics describe the dynamic response to immune events such as infection and vaccination. These dynamics are not fully understood, and mathematical characterization may help explain variability across demographic groups and pulmonary symptoms post-acute infection. We fit time-dependent probability models to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) data to obtain distributions of longitudinal antibody response and cytokine values. To assess differences between groups, an overlap metric is applied to the modeled response curves. Our antibody models suggest significant differences between male and female populations and demonstrate deficient antibody responses of less-healthy groups such as smokers. Our cytokine …

Managing Multi-Drug Resistance: An Evolutionary Game Theory And Optimal Control Approach, Shukhrat Nasrulloev

Theses and Dissertations

Multi-drug resistance is an evolutionary process in which treatment eliminates sensitive cells, allowing resistant clones to dominate. This thesis investigates this process using a framework integrating population dynamics, evolutionary game theory, and optimal control theory. We develop a two-population logistic growth model describing competition between drug-sensitive and drug-resistant cells under treatment, construct dose-dependent payoff matrices and replicator dynamics to characterize evolutionary competition, and derive a critical drug level D_crit = (r_S - rR)/(dS - d_R) at which resistant cells gain a fitness advantage. An optimal control problem is formulated via Pontryagin's Maximum Principle to identify schedules …

A Bayesian Late-Fusion Supportability Framework For Rare-Disease Severity Prediction In Glut1 Deficiency Syndrome, Jordan M. Rodriguez

Mathematics Dissertations

Glucose transporter type 1 deficiency syndrome (GLUT1-DS) is a rare neurometabolic disorder with heterogeneous neurological and developmental severity. Because patient-level severity is not observed as a single validated outcome, this dissertation develops a Bayesian late-fusion supportability framework for constructing and predicting an ordered latent severity phenotype from clinical, genetic, and EEG-derived evidence. The primary target was constructed in a larger clinical cohort using age-5 symptom burden and learning cognition, then assigned to an aligned multimodal prediction cohort. Target-defining variables were excluded from supervised predictors, and models were evaluated using patient-exclusive cross-validation with training-fold preprocessing and fold-wise EEG PCA.

The primary …

Probabilistic Modeling Of Antibody Kinetics Post Infection And Vaccination, Rayanne Luke, Prajakta Bedekar, Anthony J. Kearsley

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Corticobasal Syndrome With Mixed Pathology In The Absence Of Grn Mutation: A Clinico-Pathological Case Of Ftld-Tdp With Coexisting Alzheimer’S And Lewy Body Pathology, Hugo Zamarron, David Irwin, Jeffery Phillips, Edward Lee, Matthew Tisdall, Corey Mcmillan

Research Colloquium

Background: Corticobasal syndrome (CBS) is a neurodegenerative disorder characterized by often asymmetric fronto-pariteal and extra-pyramidal features that is traditionally associated with tauopathy, but pathological findings are heterogenous, including other forms of frontotemporal lobar degeneration (FTLD) and mixed pathologies of aging. We present clinical, radiographic, and histopathologic features of asymmetry in a unique patient with CBS and underlying FTLD with TDP-43 pathology (FTLD-TDP), co-occurring with other age-related pathologies.

Case Presentation: A 76-year-old man presented with progressive cognitive and motor dysfunction including asymmetric parkinsonism, left-sided dystonia and rigidity, apraxia, visuospatial impairment, and a subtle social disorder including apathy and social withdrawal. The …

An Exposition On Prostate Cancer Dynamics: A History And Exploration Of Cancer Growth Models, Walter Navarro

Electronic Theses, Projects, and Dissertations

The detection, diagnosis, and treatment of cancer are the primary objectives of the field of mathematical oncology. Our goal is to examine the history of mathematical oncology by introducing the models that have influenced it. From this vantage point, we examine five primary models that focus on the progression of prostate cancer and the development of treatment protocols at different stages. The Ideta model will be further elaborated upon by examining the effects of androgen deprivation therapy and the addition of chemotherapy on growth dynamics. Finally, clinical data will be utilized to verify the Vollmer and Humphrey model’s findings. We …

Analysis Of Rare Events In Healthcare Intervention Using Department Of Defense Data: Intravenous Immune Globulin Therapy For Bullous Pemphigoid, Onur Baser, Huseyin A. Yuce, Gabriela Samayoa

Publications and Research

Introduction

Rare events data have proven difficult to explain and predict. Standard statistical procedures can sharply underestimate the probability of rare events, such as intravenous immune globulin therapy (IVIg) for bullous pemphigoid.

Methods

This retrospective cross-sectional study used Department of Defense TRICARE data to determine factors associated with IVIg therapy among bullous pemphigoid patients. We used prior and weighted correction methods for logit regression to solve rare event bias.

Results

We identified 2,720 individuals diagnosed with bullous pemphigoid from 2019 to 2022, of which 14 were treated with IVIg. Patients who received IVIg therapy were younger (65.07 vs. 75.85, P …

Readiness To The Privatization Of The Health System In Saudi Arabia: Translation And Factor Analysis Of Readiness To Organizational Change (Roc) Scale, Ahmed Ali Alasiri, Qi Zhang

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Background

The Kingdom of Saudi Arabia (KSA) began a major transformation as a part of version 2030 for its health system. These reform initiatives aim to privatize health services and improve efficiency. Despite this meaningful change, there is a knowledge gap in how healthcare providers prepare for or perceive this shift. Specifically, there has been a lack of validation of Arabic instruments that gauge the individual readiness to this change. This study bridges the gap by localizing and validating the Readiness to Organizational Change scale (ROC) to provide empirical evidence and to understand adaptability for the KSA context.

Method

The …

An Overview Of Video Game Biometrics Collection And Considerations For Cyberbiosecurity, Lucas Potter, Christen Westberry, Xavier-Lewis Palmer

Electrical & Computer Engineering Faculty Publications

Over the past fifty years, the global cost of consumer electronics has significantly decreased, leading to greater accessibility to both biosensing systems and interactive entertainment platforms. This increased access has naturally resulted in higher usage of medical and entertainment electronics. However, the intersection of these technologies, combined with invasive data harvesting practices, has raised concerns about the potential misuse of biological signals to manipulate individuals' behavior both within and beyond the video game environment. Currently, biometric data in video games are employed in various ways, such as using Heart Rate Variability (HRV) as a performance metric and integrating eye tracking …

Assessing The Adequacy Of A Prediction Model, Abhaya Indrayan, Sakshi Mishra Ms

COBRA Preprint Series

No abstract provided.

Genetic Analysis Of Hereditary Gingival Fibromatosis Associated Sos1 Missense Variants Of Uncertain Significance In Caenorhabditis Elegans, Himani Patel

Theses

Hereditary gingival fibromatosis (HGF) is a disease that can present as benign overgrowth of gingival tissue in the mouth. The overgrowth can enclose the entire mouth and teeth in severe cases or present itself in a concentrated area. Researchers have identified that mutations in the SOS1 gene can be responsible for HGF. This disease can impair basic functions related to the mouth. Eating, smiling, speaking can all be affected. Additionally, excess inflammation can cause periodontal disease because of the difficulty in maintaining proper oral health. Periodontal disease can lead to severe bone loss which can lead to complete loss of …

Fbpp: Software To Design Pcr Primers And Probes For Nucleic Acid Base Detection Of Foodborne Pathogens, Mohamed A Soliman, Mohamed S Azab, Hala A Hussein, Mohamed M Roushdy, Mohamed N Abu El-Naga

Faculty, Staff and Student Publications

Foodborne pathogens can be found in various foods, and it is important to detect foodborne pathogens to provide a safe food supply and to prevent foodborne diseases. The nucleic acid base detection method is one of the most rapid and widely used methods in the detection of foodborne pathogens; it depends on hybridizing the target nucleic acid sequence to a synthetic oligonucleotide (probes or primers) that is complementary to the target sequence. Designing primers and probes for this method is a preliminary and critical step. However, new bioinformatics tools are needed to automate, specific and improve the design sets to …

Energy Harvesting Face Mask Using A Thermoelectric Generator For Powering Wearable Health Monitoring Sensors, Ugur Erturun, Cansu Yalim, James E. West

Engineering Management & Systems Engineering Faculty Publications

A wearable energy harvester (EH) incorporating a face mask with a thermoelectric generator is demonstrated. The function of this device is to generate electrical power from the heat produced by the human body, particularly breath, with the specific aim of powering wearable sensor applications. A prototype was built using a commercially available N95 face mask, a thermoelectric generator, and a heatsink. The performance of this EH device was assessed using experimental and numerical methodologies. The experimentally tested power output of the prototype was found to be ≈100 µW, with a corresponding power density of ≈30 µW/cm3, for a temperature difference …

Effect Of Specific Data Variations On Automated Speaker Recognition, Ethan David Meighen

Graduate Theses, Dissertations, and Problem Reports (ETD)

Speaker recognition is not a new biometric modality but there are still many obstacles in the way in order for it to become as used as fingerprint recognition, facial recognition, and iris recognition. Many real-world environmental conditions, hardware device variations, and human behavior present serious challenges to the use of opportunistic voice or speaker samples for identification purposes. Non-idealities, identified as nuisance factors, include environmental noise, input device quality, length of utterance, sample rate variation, and unscripted data are common nuisance factors that can impact speaker recognition match score performance. The impact of the nuisance factors listed above were evaluated …

A Class Of Game-Theoretic And Fokker-Planck Optimal Control Frameworks In Colon And Esophageal Cancer, Mesfer Alajmi Phd

Mathematics Dissertations - Archive

In this dissertation, we first present a new stochastic framework for parameter estimation and uncertainty quantification in colon cancer-induced immune responses. A stochastic process that captures the system's inherent randomness determines the dynamics of colon cancer. The stochastic framework is based on the Fokker-Planck equation, which represents the evolution of the probability density function corresponding to the stochastic process. We formulate an optimization problem that takes individual patient data with randomness present and solves it to obtain the unknown parameters corresponding to the individual tumor characteristics. Furthermore, we perform a sensitivity analysis of the optimal parameter set to identify the …

Utilizing Ai Integrated Neuroimaging Technology To Expand Upon Machine Learning In Positron Emission Tomography Technology With The Aim Of Detecting Amyloid Beta Biomarkers Early In The Onset Of Alzheimer's., Ethan S. Terman

Undergraduate Research Posters

Early intervention in Alzheimer's is vital for treatment. The earlier a professional can detect symptoms and make a diagnosis the earlier a prognosis can be implemented. With the prevalence of data in our day-to-day world combined with Artificial intelligence (AI), utilizing both for machine learning can pave the way for more accurate and efficient detection of Alzheimer's and other neurodegenerative diseases. AI combined with Machine learning (ML) increases diagnostic efficiency and reduces human errors, making it a valuable resource for physicians and clinicians alike. With the increasing amount of data processing and image interpretation required, the ability to use AI …

Scalar-On-Function Regression: Estimation And Inference Under Complex Survey Designs, Ekaterina Smirnova, Erjia Cui, Lucia Tabacu, Andrew Leroux

Mathematics & Statistics Faculty Publications

Increasingly, large, nationally representative health and behavioral surveys conducted under a multistage stratified sampling scheme collect high dimensional data with correlation structured along some domain (eg, wearable sensor data measured continuously and correlated over time, imaging data with spatiotemporal correlation) with the goal of associating these data with health outcomes. Analysis of this sort requires novel methodologic work at the intersection of survey statistics and functional data analysis. Here, we address this crucial gap in the literature by proposing an estimation and inferential framework for generalizable scalar-on-function regression models for data collected under a complex survey design. We propose to: …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Modeling Biphasic, Non-Sigmoidal Dose-Response Relationships: Comparison Of Brain- Cousens And Cedergreen Models For A Biochemical Dataset, Venkat D. Abbaraju, Tamaraty L. Robinson, Brian P. Weiser

Rowan-Virtua School of Osteopathic Medicine Departmental Research

Biphasic, non-sigmoidal dose-response relationships are frequently observed in biochemistry and pharmacology, but they are not always analyzed with appropriate statistical methods. Here, we examine curve fitting methods for “hormetic” dose-response relationships where low and high doses of an effector produce opposite responses. We provide the full dataset used for modeling, and we provide the code for analyzing the dataset in SAS using two established mathematical models of hormesis, the Brain-Cousens model and the Cedergreen model. We show how to obtain and interpret curve parameters such as the ED50 that arise from modeling, and we discuss how curve parameters might change …

Relative Burden Of Cancer And Noncancer Mortality Among Long-Term Survivors Of Breast, Prostate, And Colorectal Cancer In The Us, Madhav Kc, Jane Fan, Terry Hyslop, Sirad Hassan, Michael Cecchini, Shi-Yi Wang, Andrea Silber, Michael S. Leapman, Ira Leeds, Stephanie B. Wheeler, Lisa P. Spees, Cary P. Gross, Maryam Lustberg, Rachel A. Greenup, Amy C. Justice, Kevin C. Oeffinger, Michaela A. Dinan

Kimmel Cancer Center Faculty Papers

IMPORTANCE: Improvements in cancer outcomes have led to a need to better understand long-term oncologic and nononcologic outcomes and quantify cancer-specific vs noncancer-specific mortality risks among long-term survivors.

OBJECTIVE: To assess absolute and relative cancer-specific vs noncancer-specific mortality rates among long-term survivors of cancer, as well as associated risk factors.

DESIGN, SETTING, AND PARTICIPANTS: This cohort study included 627 702 patients in the Surveillance, Epidemiology, and End Results cancer registry with breast, prostate, or colorectal cancer who received a diagnosis between January 1, 2003, and December 31, 2014, who received definitive treatment for localized disease and who were alive 5 …

Modeling The Immune Response To Immunotherapy And Triple Negative Breast Cancer In Mice, Dayton J. Syme, Angelica Davenport, Yun Lu, Anna G. Sorace, Nicholas G. Cogan

Biology and Medicine Through Mathematics Conference

No abstract provided.

Optimizing Tumor Xenograft Experiments Using Bayesian Linear And Nonlinear Mixed Modelling And Reinforcement Learning, Mary Lena Bleile

Statistical Science Theses and Dissertations

Tumor xenograft experiments are a popular tool of cancer biology research. In a typical such experiment, one implants a set of animals with an aliquot of the human tumor of interest, applies various treatments of interest, and observes the subsequent response. Efficient analysis of the data from these experiments is therefore of utmost importance. This dissertation proposes three methods for optimizing cancer treatment and data analysis in the tumor xenograft context. The first of these is applicable to tumor xenograft experiments in general, and the second two seek to optimize the combination of radiotherapy with immunotherapy in the tumor xenograft …

Development Of A Novel Mathematical Model That Explains Sars-Cov-2 Infection Dynamics In Caco-2 Cells, Vladimir Staroverov, Stepan Nersisyan, Alexei Galatenko, Dmitriy Alekseev, Sofya Lukashevich, Fedor Ployakov, Nikita Anisimov, Alexander Tonevitsky

COVID-19 Papers, Posters, and Presentations

Mathematical modeling is widely used to study within-host viral dynamics. However, to the best of our knowledge, for the case of SARS-CoV-2 such analyses were mainly conducted with the use of viral load data and for the wild type (WT) variant of the virus. In addition, only few studies analyzed models for in vitro data, which are less noisy and more reproducible. In this work we collected multiple data types for SARS-CoV-2-infected Caco-2 cell lines, including infectious virus titers, measurements of intracellular viral RNA, cell viability data and percentage of infected cells for the WT and Delta variants. We showed …

Adaptive Critic Network For Person Tracking Using 3d Skeleton Data, Joseph G. Zalameda, Alex Glandon, Khan M. Iftekharuddin, Mohammad S. Alam (Ed.), Vijayan K. Asari (Ed.)

Electrical & Computer Engineering Faculty Publications

Analysis of human gait using 3-dimensional co-occurrence skeleton joints extracted from Lidar sensor data has been shown a viable method for predicting person identity. The co-occurrence based networks rely on the spatial changes between frames of each joint in the skeleton data sequence. Normally, this data is obtained using a Lidar skeleton extraction method to estimate these co-occurrence features from raw Lidar frames, which can be prone to incorrect joint estimations when part of the body is occluded. These datasets can also be time consuming and expensive to collect and typically offer a small number of samples for training and …

Population Variations Of Cheiloscopy Patterns: A Cross-Sectional Observation Pilot Study, Emily Smith Regan, Brenda T. Bradshaw, Ann M. Bruhn, Walter Melvin, Sinjini Sikdar

Dental Hygiene Faculty Publications

Purpose Lip prints are unique and have potential for use as a human identifier. The purpose of this study was to observe possible cheiloscopy differences of individuals with and without parafunctional oral habits such as smoking, vaping, playing a wind instrument or using an asthma inhaler.

Methods This IRB approved blinded cross-sectional observation pilot study collected lip prints from sixty-six individuals, three of which were excluded. Participants cleansed their lips, then lipstick was applied to the vermillion zones of the upper and lower lips. Adhesive tape was applied to the lips and prints were transferred to white bond paper for …

Computer-Aided Drug Discovery For Helicobacter Pylori, Nicole Ann Vita

Theses and Dissertations (ETD)

Helicobacter pylori is a high-priority drug-resistant pathogen and is currently the only bacteria considered to be a class I carcinogen and there is a critical need to identify novel chemical matter to treat H. pylori infections. Hp is responsible for greater than 60% of gastric cancer related deaths and 89% of all gastric cancer morbidities. In a previous study, our lab identified novel Hp thienopyrmidine inhibitors that target respiratory complex I, an essential enzyme in respiration. Respiratory complex I is a large asymmetric multidomain and membrane bound enzyme and due to these innate features, it is not practical for biophysical …

A Bayesian Phase I/Ii Biomarker-Based Design For Identifying Subgroup-Specific Optimal Dose For Immunotherapy, Beibei Guo, Yong Zang

Faculty Publications

Immunotherapy is an innovative treatment that enlists the patient's immune system to battle tumors. The optimal dose for treating patients with an immunotherapeutic agent may differ according to their biomarker status. In this article, we propose a biomarker-based phase I/II dose-finding design for identifying subgroup-specific optimal dose for immunotherapy (BSOI) that jointly models the immune response, toxicity, and efficacy outcomes. We propose parsimonious yet flexible models to borrow information across different types of outcomes and subgroups. We quantify the desirability of the dose using a utility function and adopt a two-stage dose-finding algorithm to find the optimal dose for each …

Modeling Of Patient-Specific Periaortic Mechanics And Pulmonary Artery Hemodynamics Based On Phase-Contrast Magnetic Resonance Imaging Sequences., Johane H. Bracamonte

Theses and Dissertations

Inverse modeling in cardiovascular medicine is a collection of methodologies that can provide non-invasive patient-specific estimations of clinical risk factors using medical imaging as inputs. Its incorporation into clinical practice has the potential to improve diagnosis and treatment planning with low associated risks and costs.

Herein, three different phase contrast magnetic resonance imaging (MRI) modalities were implemented as input data, displacement encoding with stimulated echoes (DENSE MRI) applied, and time-resolved velocity encoding phase-contrast MRI, in 1D and 3D, applied to pulmonary artery (PA) hemodynamics.

A model to account for the effect of periaortic interactions due to static and dynamic structures …