Medicine and Health Sciences Commons^™

Excitation Power Dependence Of Blinking In Copper-Indium-Sulfide Quantum Dots, Nicholas Chambers

Physics Undergraduate Honors Theses

Under continuous excitation, quantum dots exhibit random transitions between fluorescent ON states and non-fluorescent OFF states --- a phenomenon known as blinking. A physical description of the mechanism responsible for blinking that applies broadly to many types of quantum dots remains under debate. We study the blinking behavior of the non-toxic CuInS2 quantum dot, a system that has seen little investigation at the single-particle level. In particular, the optical properties of CuInS2 quantum are often improved by adding ZnS to the nanoparticles, but this addition leads to complex structural-optical property relationships that are even less understood. To probe the relationship …

Fragment Based Drug Development Based On 6,7-Dimethoxyquinazoline As A Core Scaffold, Cody M. Orahoske

ETD Archive

The work entitled “Fragment Based Drug Design based on 6,7- Dimethoxyquinazoline core structure” presents a unique approach to drug discovery, specifically focusing on the pharmacophore 6,7-dimethoxyquinazoline. This study explores the structural diversity of 6,7-Dimethoxyquinazoline derivatives to identify other pharmacologically relevant targets, with evidence indicating that this core structure possesses intrinsic properties that make it suitable as a base structure of small molecule drugs. Furthermore, this pharmacophore has been observed in various approved therapeutics or drug candidates under investigation, highlighting its importance in drug discovery. My research showcases of 6,7-dimethoxyquinazoline core structure been derivatized to generate an anti-trypanosomiasis drug candidates and …

Peripheral Blood Mononuclear Cell Mitochondrial Dysfunction In Acute Alcohol-Associated Hepatitis, Annette Bellar, Nicole Welch, Jaividhya Dasarathy, Amy Attaway, Ryan Musich, Avinash Kumar, Jinendiran Sekar, Saurabh Mishra, Yana I. Sandlers, Et. Al

Chemistry Faculty Publications

Background: Patients with acute alcohol-associated hepatitis (AH) have immune dysfunction. Mitochondrial function is critical for immune cell responses and regulates senescence. Clinical translational studies using complementary bioinformatics-experimental validation of mitochondrial responses were performed in peripheral blood mononuclear cells (PBMC) from patients with AH, healthy controls (HC), and heavy drinkers without evidence of liver disease (HD).
Methods: Feature extraction for differentially expressed genes (DEG) in mitochondrial components and telomere regulatory pathways from single-cell RNAseq (scRNAseq) and integrated 'pseudobulk' transcriptomics from PBMC from AH and HC (n = 4 each) were performed. After optimising isolation and processing protocols for functional studies in …

Multiple Sequence Alignment Guided By Clam, Emily Light

Senior Honors Projects

For my honors project, I am continuing my research with my academic advisor, Dr. Daniels on creating an approach to the Multiple Sequence Alignment problem in the Rust programming language. This approach will be attached to Dr. Daniels’ CLAM (Clustered Learning for Approximate Manifolds) to enable it to globally and locally align DNA sequences. This research was divided into three separate parts: building the algorithms, implementing them into CLAM’s metric, and measuring and improving the performance of the algorithms. This project includes two separate but related algorithms; Needleman-Wunsch algorithm and the Smith-Waterman algorithm.

The Needleman-Wunsch algorithm takes in two DNA …

Program And Proceedings: Nebraska Academy Of Sciences 1880–2023, 143rd Anniversary Year, One Hundred-Thirty-Third Annual Meeting, April 21, 2023

Nebraska Academy of Sciences: Programs and Proceedings

Program

Aeronautics and Space Science

Humans Past and Present

Applied Science and Technology Section

Biology

Biomedical Sciences

Chemistry

Earth Sciences

Environmental Science

Physics

Science Education

2023 Maiben Lecture: Jason Bartz

2023 Friend of Science Award: Ray Ward and Jim Lewis

Characterization Of Public Opinion On Severity Of Mental Illness And Hiv Based On Individual Traits Using Hierarchical Multi-Category Probit Models, Md Moinul Ahsan

Graduate Theses and Dissertations

In this thesis, we focus on modeling categorical response variables from public opinion datasets. A hierarchical probit model was used to analyze these different variables. Particularly for multinomial data, we tried different covariate settings to see the model’s performance. For that purpose, we tried two different estimation techniques. The first algorithm uses identified parameters by fixing the first diagonal element of the covariance matrix at 1. The second algorithm uses one unidentifiable parameter and subsequently identifies the parameters by fixing the trace of the covariance matrix. The results from the simulation study confirm that the trace-restricted algorithm performs better with …

Outside, Looking In: A Dissertation On Mindful Walking And How Green Exercise Affects State Mindfulness And Connectedness To Nature, Dustin Wyatt Davis

UNLV Theses, Dissertations, Professional Papers, and Capstones

INTRODUCTION: Mindfulness, green exercise, and connectedness to nature are increasingly popular topics among academics and the public. These three topics overlap in the underexplored area called mindful green exercise. Mindful green exercise is a blend of mindful exercise and green exercise. Mindful exercise is physical exercise during which people pay attention on purpose without judgment to each new present moment. The person applies an accepting awareness to internal phenomena (thoughts, emotions, and bodily sensations) and external phenomena (objects and events in the environment). Green exercise is exercise performed outdoors in natural environments. Despite its name, green exercise does not only …

Enhanced Iot-Based Electrocardiogram Monitoring System With Deep Learning, Jian Ni

UNLV Theses, Dissertations, Professional Papers, and Capstones

Due to the rapid development of computing and sensing technologies, Internet of Things (IoT)-based cardiac monitoring plays a crucial role in providing patients with cost-efficient solutions for long-term, continuous, and pervasive electrocardiogram (ECG) monitoring outside a hospital setting. In a typical IoT-based ECG monitoring system, ECG signals are picked up by sensors located on the edge, and then uploaded to the remote cloud servers. ECG interpretation is performed for the collected ECGs in the cloud servers and the analysis results can be made instantly available to the patients as well as their healthcare providers.In this dissertation, we first examine the …

Spatial Metabolomics Reveals Glycogen As An Actionable Target For Pulmonary Fibrosis, Lindsey R. Conroy, Harrison A. Clarke, Derek B. Allison, Samuel Santos Valenca, Qi Sun, Tara R. Hawkinson, Lyndsay E. A. Young, Juanita E. Ferreira, Autumn V. Hammonds, Jaclyn B. Dunne, Robert J. Mcdonald, Kimberly J. Absher, Brittany Dong, Ronald C. Bruntz, Kia H. Markussen, Jelena A. Juras, Warren J. Alilain, Jinze Liu, Matthew S. Gentry, Peggi M. Angel, Christopher M. Waters, Ramon C. Sun

Saha Cardiovascular Research Center Faculty Publications

Matrix assisted laser desorption/ionization imaging has greatly improved our understanding of spatial biology, however a robust bioinformatic pipeline for data analysis is lacking. Here, we demonstrate the application of high- dimensionality reduction/spatial clustering and histopathological annotation of matrix assisted laser desorption/ionization imaging datasets to assess tissue metabolic heterogeneity in human lung diseases. Using metabolic features identified from this pipeline, we hypothesize that metabolic channeling between glycogen and N-linked glycans is a critical metabolic process favoring pulmonary fibrosis progression. To test our hypothesis, we induced pulmonary fibrosis in two different mouse models with lysosomal glycogen utilization deficiency. Both mouse models displayed …

Development Of A Cost-Constrained Intelligent Prosthetic Knee With Real-Time Machine Learning, Predictive Stumble Control, Lucas Jonathan Galey

Open Access Theses & Dissertations

The field of biomechatronics is evolving quickly with advances in computer science, biology, and electrical and mechanical engineering. Coupled with increased interests in machine learning (ML) across all industry sectors, there are opportunities to leverage advanced analytics in uniquely complex problems. This study aimed to deploy real-time ML predictions in a novel microprocessor-controlled prosthetic knee (MPK) device capable of identifying and responding to stumble-events to reduce amputee fall prevalence. Innately, stumbling is a chaotic event. Current MPKs operate by detecting gait characteristics and reacting to preprogrammed states. While these systems are beneficial in significant ways, such as energy expenditure and …

Data Science For Hospital Antibiotic Stewardship, Saikou Jawla

Theses and Dissertations

Antibiotics are widely used to treat bacterial infections, but their misuse leads to antibiotic resistance. Antibiotic resistance is one of the biggest threats to global health, food security, and development today. Antibiotic resistance leads to higher medical costs, prolonged hospital stays, and increased mortality. Antimicrobial stewardship is an approach to measure and improve the appropriate use of antibiotics in healthcare settings. Data science has the potential to support these programs by providing insights into antibiotic prescribing patterns, identifying areas for improvement, and predicting patient outcomes. We explored the role of data science in hospital antibiotic stewardship programs, including statistical methods …

The Safe And Effective Clinical Deployment Of Artificial Intelligence To Ols, Kelly Nealon

Dissertations and Theses (Open Access)

18 million new cancer cases are diagnosed each year. Roughly half of these patients will be treated with radiation therapy, a complex technique that requires an interdisciplinary team of clinical staff and expensive equipment to be delivered safely. Cancer centers in Low- and Middle-Income Countries (LMIC) have an especially difficult time meeting the demands of radiation therapy as the complexity of treatment techniques increase, with only 37% of patients in these regions having access to the care they need. Artificial Intelligence (AI) based tools are being developed to simplify the treatment planning and quality assurance processes to increase the number …

Optimal R&D Investment In The Management Of Invasive Species, William Haden Chomphosy, Dale T. Manning, Stephanie A. Shwiff, Stephan Weiler

United States Department of Agriculture Wildlife Services: Staff Publications

Invasive alien species (IAS) threaten world biodiversity, ecosystem services, and economic welfare. While existing literature has characterized the optimal control of an established IAS, it has not considered how research and development (R&D) into new removal methods or technologies can affect management decisions and costs over time. R&D can lower the costs of control in a management plan and creates an intertemporal trade-off between quick but costly control and gradual but cheaper removal over time. In this paper, we develop and solve a continuous time dynamic optimization model to study how investment in R&D influences the optimal control of an …

Design And Synthesis Of Peripherally Selective Endocannabinoid Enzyme Inhibitors For Ocular Indications, Kezia Reji Thomas

Senior Honors Theses

Peripherally selective compounds have been found to stimulate endocannabinoid receptor activity, which has been observed to have positive physiological effects such as ocular wound healing and inflammation control. The activation of the cannabinoid 1 receptor via binding of the endogenous ligands, anandamide and 2-arachidonoylglycerol, has been indicated to elicit these effects. Both ligands are controlled by two hydrolase enzymes, fatty acid amide hydrolase (FAAH) and monoacylglycerol lipase (MAGL), which can be targeted for therapeutic inhibition. Sulfonamide derivatives of JZL195 containing carbamate functionalities in the southern region of the inhibitor compounds were produced using novel carbamate exchange reactions. Polar functionalities were …

Multiparametric Magnetic Resonance Imaging Artificial Intelligence Pipeline For Oropharyngeal Cancer Radiotherapy Treatment Guidance, Kareem Wahid

Dissertations and Theses (Open Access)

Oropharyngeal cancer (OPC) is a widespread disease and one of the few domestic cancers that is rising in incidence. Radiographic images are crucial for assessment of OPC and aid in radiotherapy (RT) treatment. However, RT planning with conventional imaging approaches requires operator-dependent tumor segmentation, which is the primary source of treatment error. Further, OPC expresses differential tumor/node mid-RT response (rapid response) rates, resulting in significant differences between planned and delivered RT dose. Finally, clinical outcomes for OPC patients can also be variable, which warrants the investigation of prognostic models. Multiparametric MRI (mpMRI) techniques that incorporate simultaneous anatomical and functional information …

Treatment Planning Automation For Rectal Cancer Radiotherapy, Kai Huang

Dissertations and Theses (Open Access)

Background

Rectal cancer is a common type of cancer. There is an acute health disparity across the globe where a significant population of the world lack adequate access to radiotherapy treatments which is a part of the standard of care for rectal cancers. Safe radiotherapy treatments require specialized planning expertise and are time-consuming and labor-intensive to produce.

Purpose:

To alleviate the health disparity and promote the safe and quality use of radiotherapy in treating rectal cancers, the entire treatment planning process needs to be automated. The purpose of this project is to develop automated solutions for the treatment planning process …

Bayesian Semi-Mechanistic Dose-Finding Designs For Phase I Oncology Trials, Chao Yang

Dissertations and Theses (Open Access)

Bayesian adaptive designs are getting more popular in research and in practice because they are flexible and efficient in evaluating an experimental drug. In oncology, despite the great advances in novel dose-finding designs, the high failure rates of clinical cancer drug development from phase I to III trials call for further improvements on novel designs, in addition to the need to promote and adopt novel designs in practice. Because anticancer agents often have a narrow therapeutic index, an accurate identification of the maximum tolerated dose (MTD) in a phase I trial is crucial for identifying a tolerable and efficacious dose …

Automating The Radiation Therapy Treatment Planning Process For Pediatric Patients With Medulloblastoma, Soleil Hernandez

Dissertations and Theses (Open Access)

Over the past 50 years, pediatric cancer 5-year survival rates increased from 20% to 80% in high-income countries, however, these trends have not been mirrored in low-and-middle-income countries (LMICs). This is due in part to delayed diagnosis, higher rates of advanced disease at presentation and a growing lack of access to high quality medical personnel and technology necessary to deliver complex treatments.

The long-term goal of this study was to alleviate demanding workflows and increase global access to high-quality pediatric radiation therapy by harnessing the power of artificial intelligence to automate the radiation therapy treatment planning process for pediatric patients …

Risk Assessment Framework For Evaluation Of Cybersecurity Threats And Vulnerabilities In Medical Devices, Maureen S. Van Devender

Graduate Theses and Dissertations (2019 - present)

Medical devices are vulnerable to cybersecurity exploitation and, while they can provide improvements to clinical care, they can put healthcare organizations and their patients at risk of adverse impacts. Evidence has shown that the proliferation of devices on medical networks present cybersecurity challenges for healthcare organizations due to their lack of built-in cybersecurity controls and the inability for organizations to implement security controls on them. The negative impacts of cybersecurity exploitation in healthcare can include the loss of patient confidentiality, risk to patient safety, negative financial consequences for the organization, and loss of business reputation. Assessing the risk of vulnerabilities …

An Investigation On The Effect Of Conserved Hinge Histidine On Influenza Hemagglutinin(Ha2) Protein Conformation Using Md Simulations, Nada Tolba

Chemistry & Biochemistry Undergraduate Honors Theses

Hemagglutinin is a protein on the surface of Human Influenza Viruses.¹ It is composed of two glycopolypeptide domains, the HA1 and HA2 domains. Previous studies have found that across different strains of Influenza viruses, HIS435 residues remain conserved.⁴ In studies where mutations occurred in hinge-site histadine residues, the Influenza virus was inactive.⁴ These investigations indicated a significant role of HIS435 (hinge-site histadines) in virulence. Four systems were created using Molecular dynamics (MD) simulations. Each system was composed of an Isolated HA2 trimer solvated in a 150 mM NaCl rectangular water box at 310 K under isobaric and …

Sexual Dimorphism Of Glomerular Capillary Morphology In Rats, Zackarias Coker

Undergraduate Honors Theses

Chronic kidney disease (CKD) progresses faster in males than females; however, the underlying mechanisms remain poorly understood. Sex differences in glomerular capillary morphology has been hypothesized to contribute, in part, to the increased susceptibility to hypertension-induced renal injury and CKD progression in males, but this has not been investigated. The goal of the present study was to assess glomerular capillary morphology in male vs. female rats with intact kidneys and after uninephrectomy (UNX). We hypothesized that glomerular capillary radii (R_CAP) and length (L_CAP) would be greater in male rats.

Male (n=4) and female (n=4) with intact …

Online Dashboards For Sars-Cov-2 Wastewater Data Need Standard Best Practices: An Environmental Health Communication Agenda., Colleen C. Naughton, Rochelle H. Holm, Nancy J. Lin, Brooklyn P. James, Ted Smith

Faculty and Staff Scholarship

The COVID-19 pandemic has highlighted the benefits of wastewater surveillance to supplement clinical data. Numerous online information dashboards have been rapidly, and typically independently, developed to communicate environmental surveillance data to public health officials and the public. In this study, we review dashboards presenting SARS-CoV-2 wastewater data and propose a path toward harmonization and improved risk communication. A list of 127 dashboards representing 27 countries was compiled. The variability was high and encompassed aspects including the graphics used for data presentation (e.g., line/bar graphs, maps, and tables), log versus linear scale, and 96 separate ways of labeling SARS-CoV-2 wastewater concentrations. …

Modeling Antihypertensive Therapeutic Inertia And Intensification To Support Clinical Action Toward Hypertension Control, Benjamin Martin

All Dissertations

Background

Hypertension is the leading modifiable risk factor for cardiovascular disease and consequent mortality worldwide. In the U.S., more than half of hypertension cases remain uncontrolled, despite availability of effective pharmaceutical treatment options. Evidence suggests that therapeutic inertia, defined as clinician failure to initiate or increase therapy when treatment goals are unmet, is the most influential barrier to improving hypertension control. Substantial rates of therapeutic inertia have been reported in ambulatory primary care settings where hypertension is typically treated and managed. Understanding and overcoming the forces driving therapeutic inertia in hypertension management is a critical strategy to reach population health …

Synthesis, Radiolabeling And Evaluation Of A Suite Of Tracers With 44Sc For Detecting Extracellular Dna, Zhiyao Li

McKelvey School of Engineering Graduate Student Theses & Dissertations

Neutrophil extracellular traps involve the rapid translocation of DNA to the outside of the cell under certain stimuli. This structure forms a fibrous network that is able to limit the spread of pathogens and to kill microorganisms. It has also been shown to be present in various pathological processes such as inflammation, autoimmune diseases, and cancer metastasis. Currently, the formation process of NETs in vivo is being extensively studied. However noninvasive detection and quantitation has yet to be achieved. A class of PET tracers are described here that consists of a DNA dye as the backbone that is labeled with …

Exploring A Gradient-Based Explainable Ai Technique For Time-Series Data: A Case Study Of Assessing Stroke Rehabilitation Exercises, Min Hun Lee, Yi Jing Choy

Research Collection School Of Computing and Information Systems

Explainable artificial intelligence (AI) techniques are increasingly being explored to provide insights into why AI and machine learning (ML) models provide a certain outcome in various applications. However, there has been limited exploration of explainable AI techniques on time-series data, especially in the healthcare context. In this paper, we describe a threshold-based method that utilizes a weakly supervised model and a gradient-based explainable AI technique (i.e. saliency map) and explore its feasibility to identify salient frames of time-series data. Using the dataset from 15 post-stroke survivors performing three upper-limb exercises and labels on whether a compensatory motion is observed or …

Inaugural Artificial Intelligence For Public Health Practice (Ai4php) Retreat: Ontario, Canada, Jacqueline K. Kueper, Laura C. Rosella, Richard G. Booth, Brent D. Davis, Sarah Nayani, Maxwell J. Smith, Dan Lizotte

Computer Science Publications

The Artificial Intelligence (AI) for Public Health Practice Retreat was a hybrid event held in October 2022 in London, Ontario to achieve three main goals: 1) Identify both the goals of public health practitioners and the tasks that they undertake as part of their practice to achieve those goals that could be supported by AI, 2) Learn from existing examples and the experience of others about facilitators and barriers to AI for public health, and 3) Support new and strengthen existing connections between public health practitioners and AI researchers. The retreat included a keynote presentation, group brainstorming exercises, breakout group …

Toward A Neural Semantic Parsing System For Ehr Question Answering, Sarvesh Soni, Kirk Roberts

Faculty, Staff and Student Publications

Clinical semantic parsing (SP) is an important step toward identifying the exact information need (as a machine-understandable logical form) from a natural language query aimed at retrieving information from electronic health records (EHRs). Current approaches to clinical SP are largely based on traditional machine learning and require hand-building a lexicon. The recent advancements in neural SP show a promise for building a robust and flexible semantic parser without much human effort. Thus, in this paper, we aim to systematically assess the performance of two such neural SP models for EHR question answering (QA). We found that the performance of these …

Head And Neck Tumor Histopathological Image Representation With Pre- Trained Convolutional Neural Network And Vision Transformer, Ranny Rahaningrum Herdiantoputri, Daisuke Komura, Tohru Ikeda, Shumpei Ishikawa

Journal of Dentistry Indonesia

Image representation via machine learning is an approach to quantitatively represent histopathological images of head and neck tumors for future applications of artificial intelligence-assisted pathological diagnosis systems. Objective: This study compares image representations produced by a pre-trained convolutional neural network (VGG16) to those produced by a vision transformer (ViT-L/14) in terms of the classification performance of head and neck tumors. Methods: W hole-slide images of five oral t umor categories (n = 319 cases) were analyzed. Image patches were created from manually annotated regions at 4096, 2048, and 1024 pixels and rescaled to 256 pixels. Image representations were …

On Cox Proportional Hazards Model Performance Under Different Sampling Schemes, Hani Samawi, Lili Yu, Jingjing Yin

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

Cox’s proportional hazards model (PH) is an acceptable model for survival data analysis. This work investigates PH models’ performance under different efficient sampling schemes for analyzing time to event data (survival data). We will compare a modified Extreme, and Double Extreme Ranked Set Sampling (ERSS, and DERSS) schemes with a simple random sampling scheme. Observations are assumed to be selected based on an easy-to-evaluate baseline available variable associated with the survival time. Through intensive simulations, we show that these modified approaches (ERSS and DERSS) provide more powerful testing procedures and more efficient estimates of hazard ratio than those based on …

Employee Attrition: Analyzing Factors Influencing Job Satisfaction Of Ibm Data Scientists, Graham Nash

Symposium of Student Scholars

Employee attrition is a relevant issue that every business employer must consider when gauging the effectiveness of their employees. Whether or not an employee chooses to leave their job can come from a multitude of factors. As a result, employers need to develop methods in which they can measure attrition by calculating the several qualities of their employees. Factors like their age, years with the company, which department they work in, their level of education, their job role, and even their marital status are all considered by employers to assist in predicting employee attrition. This project will be analyzing a …