Digital Commons Network^™

Improved Radiation Expression Profiling In Blood By Sequential Application Of Sensitive And Specific Gene Signatures, Eliseos J. Mucaki, Ben C. Shirley, Peter K. Rogan

Biochemistry Publications

Purpose. Combinations of expressed genes can discriminate radiation-exposed from normal control blood samples by machine learning based signatures (with 8 to 20% misclassification rates). These signatures can quantify therapeutically-relevant as well as accidental radiation exposures. The prodromal symptoms of Acute Radiation Syndrome (ARS) overlap those present in Influenza and Dengue Fever infections. Surprisingly, these human radiation signatures misclassified gene expression profiles of virally infected samples as false positive exposures. The present study investigates these and other confounders, and then mitigates their impact on signature accuracy.

Methods. This study investigated recall by previous and novel radiation signatures independently derived …

Random Forest-Integrated Analysis In Ad And Late Brain Transcriptome-Wide Data To Identify Disease-Specific Gene Expression, Xinxing Wu, Chong Peng, Peter T. Nelson, Qiang Cheng

Sanders-Brown Center on Aging Faculty Publications

Alzheimer's disease (AD) is a complex neurodegenerative disorder that affects thinking, memory, and behavior. Limbic-predominant age-related TDP-43 encephalopathy (LATE) is a recently identified common neurodegenerative disease that mimics the clinical symptoms of AD. The development of drugs to prevent or treat these neurodegenerative diseases has been slow, partly because the genes associated with these diseases are incompletely understood. A notable hindrance from data analysis perspective is that, usually, the clinical samples for patients and controls are highly imbalanced, thus rendering it challenging to apply most existing machine learning algorithms to directly analyze such datasets. Meeting this data analysis challenge is …

Characterization Of The Growth Factor Receptor Network Oncogenes In Lung Cancer, Ashley Duche

Pharmaceutical Sciences (MS) Theses

Lung cancer remains the leading cause of cancer related deaths worldwide, reportedly contributing to 1.8 million of the 10.0 million mortalities documented in the year 2020. Although advancements have been made in therapeutics and diagnostic methods, formulation of effective treatments and development of drug resistance continues to be a challenge. These challenges arise from our lack of understanding of intricate signaling pathways, such as the Growth Factor Receptor Network (GFRN), which contributes to complex lung tumor heterogeneity allowing for drug resistance development. In this study, gene expression signatures of six GFRN oncogenes overexpressed in human mammary epithelial cells (HMECs) were …

Elucidating The Evolution And Function Of Srnas That Facilitate Bacterial Stress Tolerance, Madeline Claire Krieger

Dissertations and Theses

Non-coding small RNAs (sRNAs) are ubiquitous post-transcriptional regulators found in both gram-negative and gram-positive bacteria. Despite their integral role in many regulatory pathways, including those that facilitate stress-tolerance, little is known about the evolutionary forces that drive the emergence of novel sRNAs, how prevalent sRNAs are within bacterial species, or the functions of a majority of these transcripts. In this work, I first describe the evolution of OxyS, a well-characterized sRNA in gram-negative Enterobacteriaceae that is involved in coordinating the bacterial response to oxidative stress. Next, I identify novel sRNAs differentially produced by the gram-positive oral pathogen Streptococcus mutans in …