Diseases Commons^™

Evaluating The Influence Of Trypanosomiasis On Murine Model Using Corchorus Olitorius Leaf Extract As A Trypanocidal Agent, Fatima M. Madaki, Adamu Y. Kabiru, Ogunrombi D. Clinton, Sakariyau A. Waheed, Yunusa O. Ibrahim

Chemistry & Biochemistry Faculty Publications

Trypanosomiasis, a parasitic disease caused by trypanosomes, which are flagellate protozoa transmitted through the bite of the tsetse fly, manifests with symptoms including substantial weight loss, anemia, fever, edema, adenitis, dermatitis, and nervous disorders. This research investigated the impact of trypanosomiasis on a murine model while utilizing Corchorus olitorius leaf extract as a potential trypanocidal agent. An acute toxicity analysis was conducted following Lorke's method, and the antitrypanosomal efficacy was assessed in rats at doses of 100, 200, and 400 mg/kg over three weeks, monitoring changes in parasitemia count, body weight, and hematological parameters. Additionally, lipid profile, electrolyte concentration, and …

Statins Are Rarely Prescribed For Incidentally Discovered Covert Cerebrovascular Disease: A Retrospective Cohort In A Large Electronic Health Record (Ehr) Identified Using Natural Language Processing, Lester Y Leung, Eric Puttock, David F Kallmes, Patrick Luetmer, Sunyang Fu, Chengyi X Zheng, Hongfang Liu, Wansu Chen, David M Kent

Faculty, Staff and Student Publications

Introduction: While incidentally discovered covert cerebrovascular diseases (id-CCD) are associated with future stroke, it is not known if patients with id-CCD are prescribed statins.

Methods: Patients age ≥50 with id-CCD on neuroimaging from 2009 to 2019 with no prior ischaemic stroke, transient ischaemic attack or dementia were identified using natural language processing in a large real-world cohort. Robust Poisson multivariable regression was used to assess statin prescription among patients without prior statins.

Results: Among 2 41 050 patients, 74 975 patients (31.1%; 4.7% with covert brain infarcts (CBI); 29.0% with white matter disease (WMD)) had id-CCD. 53.5% (95% CI 53.2 …

Advancing Clinical Bacterial Diagnosis: Gram-Stained Whole-Slide Image Classification With Attention-Based Deep Learning, Jack Mcmahon

Computer Science Senior Theses

We introduce a new method for the classification of Gram-stained WSIs. As a test for the diagnosis of blood infections, Gram stains are highly relevant to informing patient treatment. Rapid analysis of Gram stains has been shown to be positively associated with better clinical outcomes, indicating the need for better tools to aid in automatic Gram stain analysis. To date, this area of research has been underexplored, with previous studies relying on the manual patch-level annotation of WSIs to generate training data. This is the first application of a transformer-based model to Gram-stain WSI classification, an approach that is far …

Compton Scattering Of Mammographic Soft X-Ray Beams By Alkali And Transition Metal Salt Filters Produce X-Ray Interference Zones That May Have Treatment Potential For Localized Cancer Lesions, Subhendra N. Sarkar, Eric Lobel, Sabina Rakhmatova, Derbie Desir, Somdat Kissoon, Daler Djuraev, Katie Tam

Publications and Research

In breast x-ray imaging scattered radiation adds 50% of harmful radiation dose from anisotropic Compton scattering mechanism. We have been working with double layered inorganic salt materials that can induce Compton scattering to the incident mammographic x ray beams (in 20-30 kVp range) with adequate isotropy (angular control). Typically metal nitrates and alkali halide salt layers are shown here to cause low energy radiation interference zones with high and low photon intensities and local flux heterogeneity in terms of flux covariance. Spatial variation of low energy photon flux creates concentrated and sparse radiation zones that may be used to induce …

Integrated Machine Learning And Deep Learning Models For Cardiovascular Disease Risk Prediction: A Comprehensive Comparative Study, Shadman Mahmood Khan Pathan, Sakan Binte Imran

Electrical & Computer Engineering Faculty Publications

Cardiovascular Diseases (CVDs) pose a significant global health challenge, necessitating accurate risk prediction for effective preventive measures. This comprehensive comparative study explores the performance of traditional Machine Learning (ML) and Deep Learning (DL) models in predicting CVD risk, utilizing a meticulously curated dataset derived from health records. Rigorous preprocessing, including normalization and outlier removal, enhances model robustness. Diverse ML models (Logistic Regression, Random Forest, Support Vector Machine, K-Nearest Neighbor, Decision Tree, and Gradient Boosting) are compared with a Long Short-Term Memory (LSTM) neural network for DL. Evaluation metrics include accuracy, ROC AUC, computation time, and memory usage. Results identify the …

Enhancing Heart Disease Prediction With Reinforcement Learning And Data Augmentation, Gayathri R., Sangeetha S. K. B., Sandeep Kumar Mathivanan, Hariharan Rajadurai, Benjula Anbu Malar Mb, Saurav Mallik, Hong Qin

Computer Science Faculty Publications

The study presents a novel method to improve the prediction accuracy of cardiac disease by combining data augmentation techniques with reinforcement learning. The complex nature of cardiac data frequently presents challenges for traditional machine learning models, which results in subpar performance. In response, our fusion methodology improves predictive capabilities by augmenting data and utilizing reinforcement learning's skill at sequential decision-making. Our method predicts cardiac disease with an astounding 94 % accuracy rate, which is an outstanding result. This significant improvement outperforms existing techniques and shows a deeper comprehension of intricate data relationships. The amalgamation of reinforcement learning and data augmentation …

Regulation Of Mirnas In Obesity And Diabetes, Eva Maher, Ava O'Meara, Cathy Brougham

SURE Journal: Science Undergraduate Research Experience Journal

Introduction: The prevalence of obesity and obesity-related secondary disorders has increased dramatically in recent years. Dysregulated microRNA (miRNA) expression has been linked to the development of obesity and its associated disorders. Adipose derived stem cells (ADSCs) are promising cell models of obesity, obesity-related inflammation and diabetes. Furthermore, miRNA expression profiles have emerged as promising targets for the novel treatment of diseases such as obesity. In order to enhance miRNA-based therapies, the miRNA expression profile of obesity and its related disorders must be monitored to further understand the underlying mechanisms of obesity and to identify novel targets.

Aim: The aim of …

The Potential Of Stem Cell Therapy In Multiple Sclerosis Treatment: A Review, Sorina Amarculesei, Ava O'Meara Cushen, Cathy Brougham

SURE Journal: Science Undergraduate Research Experience Journal

Multiple Sclerosis is an autoimmune and neurodegenerative disease of the central nervous system. There are currently 2.8 million people living with Multiple Sclerosis worldwide, including 9000 people in Ireland, with a prevalence of 193 per 100,000 people. Symptoms of Multiple Sclerosis include sensory loss, fatigue, cognitive dysfunction, spasticity, depression, optic neuritis, gait ataxia, diplopia, and loss of bladder control. Currently, there is no standardised treatment or cure for Multiple Sclerosis with many strategies focusing on symptoms. Stem cells have emerged as promising approaches for Multiple Sclerosis therapeutics. Clinical trials primarily focus on mesenchymal stem cell-based therapies for Multiple Sclerosis. Furthermore, …

Deep Learning Uncertainty Quantification For Clinical Text Classification, Alina Peluso, Ioana Danciu, Hong-Jun Yoon, Jamaludin Mohd Yusof, Tanmoy Bhattacharya, Adam Spannaus, Noah Schaefferkoetter, Eric B. Durbin, Xiao-Cheng Wu, Antoinette Stroup, Jennifer Doherty, Stephen Schwartz, Charles Wiggins, Linda Coyle, Lynne Penberthy, Georgia D. Tourassi, Shang Gao

School of Public Health Faculty Publications

INTRODUCTION: Machine learning algorithms are expected to work side-by-side with humans in decision-making pipelines. Thus, the ability of classifiers to make reliable decisions is of paramount importance. Deep neural networks (DNNs) represent the state-of-the-art models to address real-world classification. Although the strength of activation in DNNs is often correlated with the network's confidence, in-depth analyses are needed to establish whether they are well calibrated. METHOD: In this paper, we demonstrate the use of DNN-based classification tools to benefit cancer registries by automating information extraction of disease at diagnosis and at surgery from electronic text pathology reports from the US National …

Raman Spectroscopic Analysis Of Human Serum Samples Of Convalescing Covid-19 Positive Patients, Hugh Byrne, Naomi Jackson, Jaythoon Hassan

Articles

Rapid screening, detection and monitoring of viral infection is of critical importance, as exemplified by the rapid spread of SARS-CoV-2, leading to the worldwide pandemic of COVID-19. This is equally the case for the stages of patient convalescence as for the initial stages of infection, to understand the medium and long terms effects, as well as the efficacy of therapeutic interventions. Optical spectroscopic techniques potentially offer an alternative to currently employed techniques of screening for the presence, or the response to infection. In this study, the ability of Raman spectroscopy to distinguish between samples of the serum of convalescent COVID-19 …

Applications Of Causal Inference Methods For The Estimation Of Effects Of Bone Marrow Transplant And Prescription Drugs On Survival Of Aplastic Anemia Patients, Yesha M. Patel

Computational and Data Sciences (PhD) Dissertations

This dissertation provides an in-depth exploration into the treatment effectiveness for aplastic anemia using causal inference methods, structured around three pivotal research papers. Each paper contributes to a nuanced understanding of treatment impacts, specifically focusing on bone marrow transplantation (BMT) and prescription drugs, and the identification of optimal treatment strategies.

The first paper, "Causal Inference Analysis for Assessing the Effect of Bone Marrow Transplantation on the One-Year Survival of Adult and Pediatric Aplastic Anemia Patients," sets the foundation. It examines the short-term effectiveness of BMT in both adult and pediatric patients, providing crucial insights into how this treatment affects survival …

Transferability Of Tsetse Habitat Models Between Different Regions In Kenya And Rwanda, Stella Gachoki, Anton Vrieling, Thomas A. Groen, Andrew Skidmore, Daniel Masiga

All Peer-Reviewed Publications

Accurate and reliable information on the distribution of tsetse habitats is crucial for the effective management of African Trypanosomiasis in sub-Saharan Africa. However, conducting large-scale surveillance of tsetse flies to develop distribution maps is impractical due to vast areas infested and limited resources available. To address this challenge, we evaluated the applicability of tsetse habitat models developed in the intensively sampled Shimba Hills National Reserve in Kenya for both the wet and the dry season, to two other regions in Kenya (Ruma National Park and Nguruman Conservancy) and one region in Rwanda (Akagera National Park). The models utilized satellite-based estimates …

Usp38 Exacerbates Atrial Inflammation, Fibrosis, And Susceptibility To Atrial Fibrillation After Myocardial Infarction In Mice, Yang Gong, Tingting Yu, Wei Shuai, Tao Chen, Jingjing Zhang, He Huang

Faculty, Staff and Student Publications

BACKGROUND: Inflammation plays an important role in the pathogenesis of atrial fibrillation (AF) after myocardial infarction (MI). The role of USP38, a member of the ubiquitin-specific protease family, on MI-induced atrial inflammation, fibrosis, and associated AF is unclear.

METHODS: In this study, we surgically constructed a mouse MI model using USP38 cardiac conditional knockout (USP38-CKO) and cardiac-specific overexpression (USP38-TG) mice and applied biochemical, histological, electrophysiological characterization and molecular biology to investigate the effects of USP38 on atrial inflammation, fibrosis, and AF and its mechanisms.

RESULTS: Our results revealed that USP38-CKO attenuates atrial inflammation, thereby ameliorating fibrosis, and abnormal electrophysiologic properties, …

Long-Acting Cabotegravir And The Emergence Of Drug-Resistant Hiv, Katharine Gurski

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

An Ode Model For Investigating The Sleep-Pain Relationship In Sickle Cell Disease, Quindel Jones, Angela Reynolds, Rebecca Segal, Reginald Mcgee

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Predicting Dengue Incidence In Central Argentina Using Google Trends Data, Sahil Chindal

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Physics-Informed Neural Networks For Agent-Based Epidemiological Model Calibration, Alvan C. Arulandu, Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Braf Inhibitors In Metastatic Colorectal Cancer And Mechanisms Of Resistance: A Review Of The Literature, Patricia Guerrero, Víctor Albarrán, María San Román, Carlos González-Merino, Coral García De Quevedo, Jaime Moreno, Juan Carlos Calvo, Guillermo González, Inmaculada Orejana, Jesús Chamorro, Íñigo Martínez-Delfrade, Blanca Morón, Belén De Frutos, María Reyes Ferreiro

Faculty, Staff and Students Publications

Metastatic colorectal cancer (mCRC) with mutated BRAF exhibits distinct biological and molecular features that set it apart from other subtypes of CRC. Current standard treatment for these tumors involves a combination of chemotherapy (CT) and VEGF inhibitors. Recently, targeted therapy against BRAF and immunotherapy (IT) for cases with microsatellite instability (MSI) have been integrated into clinical practice. While targeted therapy has shown promising results, resistance to treatment eventually develops in a significant portion of responsive patients. This article aims to review the available literature on mechanisms of resistance to BRAF inhibitors (BRAFis) and potential therapeutic strategies to overcome them.

Braf D594a Mutation Defines A Unique Biological And Immuno-Modulatory Subgroup Associated With Functional Cd8+ T Cell Infiltration In Colorectal Cancer, Wenjing Li, Chenyi Zhao, Wenhui Li, Yang Gong, Kaili Ma, Yujie Lu, Xiaowei Liu, Lianjun Zhang, Feng Guo

Faculty, Staff and Student Publications

BACKGROUND: BRAF non-V600 mutation occupies a relatively small but critical subset in colorectal cancer (CRC). However, little is known about the biological functions and impacts of BRAF class III mutation in CRC. Here, we aim to explore how D594A mutation impacts on biological behaviors and immune related signatures in murine CRC cells.

METHODS: BRAF V600E (class I), G469V (class II) and D594A (class III) mutant cell lines were established based on MC38 cells. The biological behaviors of cells were evaluated in respect of cell growth, cell proliferation, cell apoptosis, cell migration and invasion by the methods of colony-forming assay, CCK-8 …

Assessment Of First-Phase Covid-19 Pandemic In Europe Using Hierarchical Clustering Based On Principal Components Analysis, Sanjay Kumar, Evrim Oral

School of Public Health Faculty Publications

It is of great interest for researchers to assess the COVID-19 pandemic in Europe. Grouping of COVID-19-affected regions is an effective way to monitor and optimize planning to combat the disease. This paper applied hierarchical clustering based on principal components analysis (HCPCA) to COVID-19 data from affected European countries. Considering several attribute indices, we obtained a new set of indicators using principal components analysis to aggregate and reduce the dimension of attribute indices of affected countries. Further, we obtained groups of affected countries subject to their similarity using hierarchical clustering to the reduced observations of new attributes indices of these …

Surveillance Systems In Western Kenya: Methods, Perceptions, And Effectiveness, Marissa Duffy

Independent Study Project (ISP) Collection

Surveillance is an important tool in monitoring and evaluating infectious disease patterns and trends. Surveillance is vital because it aids public health officials and medical professionals in creating better prevention methods and efficiently managing outbreaks. Kenya is home to many noncommunicable diseases making it an important location to conduct disease surveillance. Within Kenya, each county has its own surveillance unit which tracks and controls outbreaks. In addition, government run surveillance systems were established to determine disease burden, incidence, and patterns in specific at-risk communities around Kenya. One of these major surveillance systems is Population-Based Infectious Disease Surveillance (PBIDS) which has …

Web-Grading-A Tool To Test Personal Grading Of Renal And Prostate Cancer, Glen Kristiansen, Matthias Schmid, Lars Egevad, Hemamali Samaratunga, Murali Varma, Kaan Inam, Hans-Jürgen Thiesen, Brett Delahunt, Yulin Dai

Faculty, Staff and Student Publications

Only a few pathologists have the opportunity to verify their personal grading through objective assessment. This study introduces a web-based grading platform to facilitate and validate the grading of renal cell carcinoma and prostate cancer. Two representative images of two clinically annotated cohorts of 100 cases each of prostate and renal cell carcinoma were used. Each participant was asked to grade a tumor series utilizing a three tiered grading system. Finally, a Kaplan-Meier curve was drawn, and the log-rank test was used for statistical testing of the p-value. The grading of 22 participants (68%) achieved prognostic significance. Further analysis highlighted …

Climate Change, Malnutrition, And Hiv: The Impact Of Food Insecurity On Hiv Response In Sub-Saharan Africa, Olivia Walshak

Independent Study Project (ISP) Collection

Climate change is a key driver of an unprecedented global food crisis, exacerbated by rising temperatures and the vulnerability of crop yields. Sub-Saharan Africa is particularly susceptible, and case studies demonstrate the fragility of food systems in the region, leading to severe food insecurity and famine in the face of climate shocks.

There are a variety of health implications, particularly the syndemic relationship between malnutrition and HIV. HIV interacts bidirectionally with malnutrition, creating a vicious cycle of poor clinical outcomes. Expanding access to antiretroviral therapy in Sub-Saharan Africa is hindered by rampant food insecurity, including inadequate food intake, reduced dietary …

A Case Report: A Patient Rescued By Va-Ecmo After Cardiac Arrest Triggered By Trigeminocardiac Reflex After Nasal Surgery, Xu Zhang, Bin Sun, Chen Pac-Soo, Daqing Ma, Liwei Wang

Faculty, Staff and Student Publications

Rationale:

Cardiac arrest (CA) caused by trigeminocardiac reflex (TCR) after endoscopic nasal surgery is rare. Hence, when a patient suffers from TCR induced CA in the recovery room, most doctors may not be able to find the cause in a short time, and standard cardiopulmonary resuscitation and resuscitation measures may not be effective. Providing circulatory assistance through venous-arterial extracorporeal membrane oxygenation (VA-ECMO) can help healthcare providers gain time to identify the etiology and initiate symptom-specific treatment.

Patient concerns:

We report a rare case of CA after endoscopic nasal surgery treated with VA-ECMO.

Diagnoses:

We excluded myocardial infarction, pulmonary embolism, allergies, …

Sugar-Sweetened Beverages And Artificially Sweetened Beverages Consumption And The Risk Of Nonalcoholic Fatty Liver (Nafld) And Nonalcoholic Steatohepatitis (Nash), Tung Sung Tseng, Wei Ting Lin, Peng Sheng Ting, Chiung Kuei Huang, Po Hung Chen, Gabrielle V. Gonzalez, Hui Yi Lin

School of Public Health Faculty Publications

Nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) are fast becoming the most common chronic liver disease and are often preventable with healthy dietary habits and weight management. Sugar-sweetened beverage (SSB) consumption is associated with obesity and NAFLD. However, the impact of different types of SSBs, including artificially sweetened beverages (ASBs), is not clear after controlling for total sugar intake and total caloric intake. The aim of this study was to examine the association between the consumption of different SSBs and the risk of NAFLD and NASH in US adults. The representativeness of 3739 US adults aged ≥20 years …

Individual Difference Correlates Of Being Sexually Unrestricted Yet Declining An Hiv Test, Nicholas S. Holtzman, Stephen W. Carden, Stacy W. Smallwood, Janice Steirn, S. Mason Garrison

Mathematical Sciences: Faculty Publications

Which individual differences accurately predict one’s decision to get tested for human immunodeficiency virus (HIV), and do individuals who have regular short-term sex get tested at higher rates? Two studies—one lab study (total valid N = 69, with n = 20 who were tested) and one involving a student health center (valid N = 250, n = 4 who were tested)—involved participants (total valid N = 319, with n = 24 who got tested) taking a number of personality and individual difference measures, including the dark triad (Machiavellianism, narcissism, and psychopathy). Then, in both studies, participants had the opportunity to …

Design, Analysis, And Interpretation Of Treatment Response Heterogeneity In Personalized Nutrition And Obesity Treatment Research, Roger S. Zoh, Bridget H. Esteves, Xiaoxin Yu, Amanda J. Fairchild, Ana I. Vazquez, Andrew G. Chapple, Andrew W. Brown, Brandon George, Derek Gordon, Douglas Landsittel, Gary L. Gadbury, Greg Pavela, Gustavo De Los Campos, Luis M. Mestre, David B. Allison

School of Public Health Faculty Publications

It is increasingly assumed that there is no one-size-fits-all approach to dietary recommendations for the management and treatment of chronic diseases such as obesity. This phenomenon that not all individuals respond uniformly to a given treatment has become an area of research interest given the rise of personalized and precision medicine. To conduct, interpret, and disseminate this research rigorously and with scientific accuracy, however, requires an understanding of treatment response heterogeneity. Here, we define treatment response heterogeneity as it relates to clinical trials, provide statistical guidance for measuring treatment response heterogeneity, and highlight study designs that can quantify treatment response …

Low Pitch Significantly Reduces Helical Artifacts In Abdominal Ct, Moiz Ahmad, Peng Sun, Christine B Peterson, Marcus R Anderson, Xinming Liu, Ajaykumar C Morani, Corey T Jensen

Faculty, Staff and Student Publications

Purpose: High helical pitch scanning minimizes scan times in CT imaging, and thus also minimizes motion artifact and mis-synchronization with contrast bolus. However, high pitch produces helical artifacts that may adversely affect diagnostic image quality. This study aims to determine the severity and incidence of helical artifacts in abdominal CT imaging and their relation to the helical pitch scan parameter.

Methods: To obtain a dataset with varying pitch values, we used CT exam data both internal and external to our center. A cohort of 59 consecutive adult patients receiving an abdomen CT examination at our center with an accompanying prior …

Forecasting Stock Indices With The Covid-19 Infection Rate As An Exogenous Variable, Mohammad Saha A. Patwary

School of Computing and Informatics

Forecasting stock market indices is challenging because stock prices are usually nonlinear and non- stationary. COVID-19 has had a significant impact on stock market volatility, which makes forecasting more challenging. Since the number of confirmed cases significantly impacted the stock price index; hence, it has been considered a covariate in this analysis. The primary focus of this study is to address the challenge of forecasting volatile stock indices during Covid-19 by employing time series analysis. In particular, the goal is to find the best method to predict future stock price indices in relation to the number of COVID-19 infection rates. …

Additive Effects Of Cyclic Peptide [R4w4] When Added Alongside Azithromycin And Rifampicin Against Mycobacterium Avium Infection, Melissa Kelley, Kayvan Sasaninia, Arbi Abnousian, Ali Badaoui, James Owens, Abrianna Beever, Nala Kachour, Rakesh Kumar Tiwari, Vishwanath Venketaraman

Pharmacy Faculty Articles and Research

Mycobacterium avium (M. avium), a type of nontuberculous mycobacteria (NTM), poses a risk for pulmonary infections and disseminated infections in immunocompromised individuals. Conventional treatment consists of a 12-month regimen of the first-line antibiotics rifampicin and azithromycin. However, the treatment duration and low antibiotic tolerability present challenges in the treatment of M. avium infection. Furthermore, the emergence of multidrug-resistant mycobacterium strains prompts a need for novel treatments against M. avium infection. This study aims to test the efficacy of a novel antimicrobial peptide, cyclic [R4W4], alongside the first-line antibiotics azithromycin and rifampicin in reducing M. avium survival. Colony-forming unit (CFU) …