Physical Sciences and Mathematics Commons^™

The Prevalence Of Burnout In Saudi Arabia Dental Hygienists, Nouf Hamad Aldayel

Dental Hygiene Theses & Dissertations

Purpose: The purpose of this pilot study was to assess the prevalence of burnout in Saudi Arabian dental hygienists and identify risk factors associated with burnout. Methods: A descriptive survey design using the Copenhagen Burnout Inventory (CBI) assessed burnout among a convenience sample of n=123 Saudi dental hygienists. The survey was disseminated electronically to 1,000 Saudi Arabian dental hygienists. The CBI measures three subscales: personal, work-related, and client/patient-related burnout on a five-point Likert-type scale. The survey also included six demographic questions, two Likert-type, one “yes/no,” and one openended question, related to burnout. Descriptive statistics, one-way between subject’s ANOVA, independent samples …

Structural Insights Into The Cl-Par-4 Protein: Ionic Requirements, Conformational Transitions, And Interaction With Cisplatin, Krishna Kumar Raut

Chemistry & Biochemistry Theses & Dissertations

Cancer continues to be the leading global cause of death, with challenges in early diagnosis, drug resistance, non-specific drug targeting, and cancer recurrence and metastasis posing formidable obstacles in cancer therapy. In this context, Prostate Apoptosis Response-4 (Par-4), a pro-apoptotic tumor suppressor protein, emerged as a promising therapeutic target due to its ability to selectively induce apoptosis in cancer cells, thereby minimizing the drug-associated adverse effects. However, a comprehensive understanding of the structural features of Par-4, specifically the caspase-cleaved fragment (cl-Par-4), is crucial for therapeutic advancements.

This dissertation investigated the effects of various ions, both monovalent and divalent, on the …

Dental Hygiene Students Reported Physiological Symptoms Associated With Wearing An N95 Respirator Mask, Peyton Shea Butler

Dental Hygiene Theses & Dissertations

Purpose: Physiological symptoms and comfort levels while wearing an N95 respiratory mask has not been examined with dental hygienists. The purpose of this study was to investigate dental hygiene students reported physiological symptoms and comfort perception while wearing an N95 respirator mask during patient care appointments. Methods: After IRB approval (IRB #1987754-2), a 16-item questionnaire was distributed through email to a convenience sample of 65 dental hygiene students. Questions assessed respiratory, dermatologic, cardiac, mask mouth and general physiological symptoms, as well as comfort levels. Additionally, participants were asked to respond to demographic questions and one open ended question inquiring about …

Metals And Metal Complexes In Diseases With A Focus On Covid-19: Facts And Opinions, Agnieszka Ścibior, Manuel Aureliano, Alvin A. Holder, Juan Llopis

Chemistry & Biochemistry Faculty Publications

In the present Special Issue on “Metals and Metal Complexes in Diseases with a Focus on COVID-19: Facts and Opinions”, an attempt has been made to include reports updating our knowledge of elements considered to be potential candidates for therapeutic applications and certain metal-containing species, which are extensively being examined towards their potential biomedical use due to their specific physicochemical properties. The Special Issue compiles data on the role of metals in COVID-19 and focuses on other illnesses and biological processes that affect metal metabolism. It consists of eight manuscripts, including five review articles and three original research papers (Figure …

Enhancement Of Deep Learning Protein Structure Prediction, Ruoming Shen

Modeling, Simulation and Visualization Student Capstone Conference

Protein modeling is a rapidly expanding field with valuable applications in the pharmaceutical industry. Accurate protein structure prediction facilitates drug design, as extensive knowledge about the atomic structure of a given protein enables scientists to target that protein in the human body. However, protein structure identification in certain types of protein images remains challenging, with medium resolution cryogenic electron microscopy (cryo-EM) protein density maps particularly difficult to analyze. Recent advancements in computational methods, namely deep learning, have improved protein modeling. To maximize its accuracy, a deep learning model requires copious amounts of up-to-date training data.

This project explores DeepSSETracer, a …

Review Of Nighttime Temperature Effects On Long-Term Health Condition Through Sleep Studies, Sydnie Matkins

Modeling, Simulation and Visualization Student Capstone Conference

Over the past 40 years, there has been increasing interest in human sleep quality and duration. This nonsystematic review looked at over 80 peer-reviewed papers on the association among sleep, temperature, and long-term health conditions. Generally, warmer temperatures lend to poorer sleep quality, and poor sleep quality lend to mental illness and a higher risk of coronary heart disease and mortality. Future research should be to conduct a study that relies more on health records rather than questionnaires to accurately map current and future health quality.

An Efficient Lightweight Provably Secure Authentication Protocol For Patient Monitoring Using Wireless Medical Sensor Networks, Garima Thakur, Sunil Prajapat, Pankaj Kumar, Ashok Kumar Das, Sachin Shetty

VMASC Publications

The refurbishing of conventional medical network with the wireless medical sensor network has not only amplified the efficiency of the network but concurrently posed different security threats. Previously, Servati and Safkhani had suggested an Internet of Things (IoT) based authentication scheme for the healthcare environment promulgating a secure protocol in resistance to several attacks. However, the analysis demonstrates that the protocol could not withstand user, server, and gateway node impersonation attacks. Further, the protocol fails to resist offline password guessing, ephemeral secret leakage, and gateway-by-passing attacks. To address the security weaknesses, we furnish a lightweight three-factor authentication framework employing the …

Architectural Design Of A Blockchain-Enabled, Federated Learning Platform For Algorithmic Fairness In Predictive Health Care: Design Science Study, Xueping Liang, Juan Zhao, Yan Chen, Eranga Bandara, Sachin Shetty

VMASC Publications

Background: Developing effective and generalizable predictive models is critical for disease prediction and clinical decision-making, often requiring diverse samples to mitigate population bias and address algorithmic fairness. However, a major challenge is to retrieve learning models across multiple institutions without bringing in local biases and inequity, while preserving individual patients' privacy at each site.

Objective: This study aims to understand the issues of bias and fairness in the machine learning process used in the predictive health care domain. We proposed a software architecture that integrates federated learning and blockchain to improve fairness, while maintaining acceptable prediction accuracy and minimizing overhead …

The Use Of Artificial Intelligence To Detect Students Sentiments And Emotions In Gross Anatomy Reflections, Krzysztof J. Rechowicz, Carrie A. Elzie

VMASC Publications

Students' reflective writings in gross anatomy provide a rich source of complex emotions experienced by learners. However, qualitative approaches to evaluating student writings are resource heavy and timely. To overcome this, natural language processing, a nascent field of artificial intelligence that uses computational techniques for the analysis and synthesis of text, was used to compare health professional students' reflections on the importance of various regions of the body to their own lives and those of the anatomical donor dissected. A total of 1365 anonymous writings (677 about a donor, 688 about self) were collected from 132 students. Binary and trinary …

The Shortfalls Of Vulnerability Indexes For Public Health Decision-Making In The Face Of Emergent Crises: The Case Of Covid-19 Vaccine Uptake In Virginia, Lydia Cleveland Sa, Erika Frydenlund

VMASC Publications

Equitable and effective vaccine uptake is a key issue in addressing COVID-19. To achieve this, we must comprehensively characterize the context-specific socio-behavioral and structural determinants of vaccine uptake. However, to quickly focus public health interventions, state agencies and planners often rely on already existing indexes of "vulnerability." Many such "vulnerability indexes" exist and become benchmarks for targeting interventions in wide ranging scenarios, but they vary considerably in the factors and themes that they cover. Some are even uncritical of the use of the word "vulnerable," which should take on different meanings in different contexts. The objective of this study is …

Multipatch Stochastic Epidemic Model For The Dynamics Of A Tick-Borne Disease, Milliward Maliyoni, Holly D. Gaff, Keshlan S. Govinder, Faraimunashe Chirove

Biological Sciences Faculty Publications

Spatial heterogeneity and migration of hosts and ticks have an impact on the spread, extinction and persistence of tick-borne diseases. In this paper, we investigate the impact of between-patch migration of white-tailed deer and lone star ticks on the dynamics of a tick-borne disease with regard to disease extinction and persistence using a system of Itô stochastic differential equations model. It is shown that the disease-free equilibrium exists and is unique. The general formula for computing the basic reproduction number for all patches is derived. We show that for patches in isolation, the basic reproduction number is equal to the …

Design Of Robust Blockchain-Envisioned Authenticated Key Management Mechanism For Smart Healthcare Applications, Siddhant Thapiyal, Mohammad Wazid, Devesh Pratap Singh, Ashok Kumar Das, Sachin Shetty

VMASC Publications

The healthcare sector is a very crucial and important sector of any society, and with the evolution of the various deployed technologies, like the Internet of Things (IoT), machine learning and blockchain it has numerous advantages. However, in this section, the data is much more vulnerable than others, because the data is strictly private and confidential, and it requires a highly secured framework for the transmission of data between entities. In this article, we aim to design a blockchain-envisioned authentication and key management mechanism for the IoMT-based smart healthcare applications (in short, we call it SBAKM-HS). We compare the various …

Unttangling Irregular Actin Cytoskeleton Architectures In Tomograms Of The Cell With Struwwel Tracer, Salim Sazzed, Peter Scheible, Jing He, Willy Wriggers

Computer Science Faculty Publications

In this work, we established, validated, and optimized a novel computational framework for tracing arbitrarily oriented actin filaments in cryo-electron tomography maps. Our approach was designed for highly complex intracellular architectures in which a long-range cytoskeleton network extends throughout the cell bodies and protrusions. The irregular organization of the actin network, as well as cryo-electron-tomography-specific noise, missing wedge artifacts, and map dimensions call for a specialized implementation that is both robust and efficient. Our proposed solution, Struwwel Tracer, accumulates densities along paths of a specific length in various directions, starting from locally determined seed points. The highest-density paths originating …

Sound The (Smaller) Alarm: The Triphosphate Magic Spot Nucleotide Pgpp, Areej Malik, Megan A. Hept, Erin B. Purcell

Chemistry & Biochemistry Faculty Publications

It has recently become evident that the bacterial stringent response is regulated by a triphosphate alarmone (pGpp) as well as the canonical tetra- and pentaphosphate alarmones ppGpp and pppGpp [together, (p)ppGpp]. Often dismissed in the past as an artifact or degradation product, pGpp has been confirmed as a deliberate endpoint of multiple synthetic pathways utilizing GMP, (p)ppGpp, or GDP/GTP as precursors. Some early studies concluded that pGpp functionally mimics (p)ppGpp and that its biological role is to make alarmone metabolism less dependent on the guanine energy charge of the cell by allowing GMP-dependent synthesis to continue when GDP/GTP has been …

Halogen Bonding Interactions Of Haloaromatic Endocrine Disruptors And The Potential For Inhibition Of Iodothyronine Deiodinases, Craig A. Bayse

Chemistry & Biochemistry Faculty Publications

Halogen bonding (XB) is a potential mechanism for the inhibition of the thyroid-activating/deactivating iodothyronine deiodinase family of selenoproteins through interactions with halogenated endocrine disrupting compounds (EDCs). Trends in XB interactions were examined using density functional theory for a series of polyhalogenated dibenzo-1,4-dioxins, biphenyls, and other EDCs with methylselenolate, a simple model of the Dio active site selenocysteine. The strengths of the interactions depend upon the halogen (Br>Cl), the degree of substitution, and the position of the acceptor. In terms of donor-acceptor energies, interactions at the meta position are often the strongest, suggesting a link to the topology of THs, …

Synthesis Of A Series Of Trimeric Branched Glycoconjugates And Their Applications For Supramolecular Gels And Catalysis, Jonathan Bietsch, Anji Chen, Dan Wang, Guijun Wang

Chemistry & Biochemistry Faculty Publications

Carbohydrate-derived molecular gelators have found many practical applications as soft materials. To better understand the structure and molecular gelation relationship and further explore the applications of sugar-based gelators, we designed and synthesized eight trimeric branched sugar triazole derivatives and studied their self-assembling properties. These included glucose, glucosamine, galactose, and maltose derivatives. Interestingly, the gelation properties of these compounds exhibited correlations with the peripheral sugar structures. The maltose derivative did not form gels in the tested solvents, but all other compounds exhibited gelation properties in at least one of the solvents. Glucose derivatives showed superior performance, followed by glucosamine derivatives. They …

Extracting High-Molecular Weight Dna From Cyanobacteria Using Promega's Wizard® Hmw Dna Extraction Kit With A Modified Protocol, Metis, Megan A. Hept, Lesley H. Greene

Chemistry & Biochemistry Faculty Publications

Extraction of high molecular weight (HMW) DNA for long read sequencing with little to no fragmentation and high purity is difficult to acquire from cyanobacterial species. Here we describe a modified method of extraction using Promega's Wizard® HMW DNA Extraction Kit to acquire high molecular weight DNA from cyanobacterial species. The protocol used in the kit is the “3.D. Isolating HMW DNA from Gram-Positive and Gram-Negative Bacteria” protocol. During a key step in the protocol, the lingering remnants of the mucilage layer of the cyanobacterial species is removed, preventing it from sticking to the DNA pellet produced. This customized modification …

Detection And Quantification Of Antiviral Drug Tenofovir Using Silver Nanoparticles And Surface Enhanced Raman Spectroscopy (Sers) With Spatially Resolved Hotspot Selection, Marguerite R. Butler, Jana Hrncirova, Terry A. Jacot, Sucharita Dutta, Meredith R. Clark, Gustavo F. Doncel, John B. Cooper

Chemistry & Biochemistry Faculty Publications

This study introduces a convenient and ultra-sensitive method of detection and quantification of the antiviral drug, tenofovir (TFV), by surface-enhanced Raman spectroscopy (SERS). Novel spatially resolved instrumentation for spectral acquisition and subsequent statistical analysis for hot spot selection was developed for convenient quantification of TFV in an aqueous matrix. Methods of statistical analysis include the use of partial least squares (PLS) regression vector analysis and spectral ranking by quality indices computed using CHAOS theory. Hydroxylamine-reduced Ag colloidal nanoparticles evaporated to dryness on an aluminum well-plate were used as the SERS substrate. To our knowledge, quantification of TFV down to 25 …

Para-Methoxybenzylidene Acetal-Protected D-Glucosamine Derivatives As Ph-Responsive Gelators And Their Applications For Drug Delivery, Jonathan Bietsch, Logan Baker, Anna Duffney, Alice Mao, Mary Foutz, Cheandri Ackermann, Guijun Wang

Chemistry & Biochemistry Faculty Publications

Carbohydrate-based low molecular weight gelators (LMWGs) are compounds with the capability to self-assemble into complex molecular networks within a solvent, leading to solvent immobilization. This process of gel formation depends on noncovalent interactions, including Van der Waals, hydrogen bonding, and π–π stacking. Due to their potential applications in environmental remediation, drug delivery, and tissue engineering, these molecules have emerged as an important area of research. In particular, various 4,6-O-benzylidene acetal-protected D-glucosamine derivatives have shown promising gelation abilities. In this study, a series of C-2-carbamate derivatives containing a para-methoxy benzylidene acetal functional group were synthesized and characterized. These compounds exhibited good …

The Effect Of Metalation On Antimicrobial Piscidins Imbedded In Normal And Oxidized Lipid Bilayers, Ana Dreab, Craig A. Bayse

Chemistry & Biochemistry Faculty Publications

Metalation of the N-terminal Amino Terminal Cu(II)- and Ni(II)-binding (ATCUN) motif may enhance the antimicrobial properties of piscidins. Molecular dynamics simulations of free and nickelated piscidins 1 and 3 (P1 and P3) were performed in 3 : 1 POPC/POPG and 2.6 : 1 : 0.4 POPC/POPG/aldo-PC bilayers (POPC, 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine: POPG, 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoglycerol; aldo-PC, 1-palmitoyl-2-(9′-oxo-nonanoyl)-sn-glycero-3-phosphocholine) bilayer models. Nickel(II) binding decreases the conformation dynamics of the ATCUN motif and lowers the charge of the N-terminus to allow it to embed deeper in the bilayer without significantly changing the overall depth due to interactions of the charged half-helix …

Synthesis And Self-Assembling Properties Of Carbohydrate- And Diarylethene-Based Photoswitchable Molecular Gelators, Pramod Aryal, Joedian Morris, Surya B. Adhikari, Jonathan Bietsch, Guijun Wang

Chemistry & Biochemistry Faculty Publications

Carbohydrate-based low-molecular-weight gelators are interesting new materials with many potential applications. These compounds can be designed to include multiple stimuli-responsive functional groups. In this study, we designed and synthesized several chemically responsive bola-glycolipids and dimeric carbohydrate- and diarylethene-based photoswitchable derivatives. The dimeric glycolipids formed stable gels in a variety of solvent systems. The best performing gelators in this series contained decanedioic and dithienylethene (DTE) spacers, which formed gels in eight and nine of the tested solvents, respectively. The two new DTE-containing esters possessed interesting photoswitching properties and DTE derivative 7 was found to have versatile gelation properties in many solvents, …

Identifying The Serious Clinical Outcomes Of Adverse Reactions To Drugs By A Multi-Task Deep Learning Framework, Haochen Zhao, Peng Ni, Qichang Zhao, Xiao Liang, Di Ai, Shannon Erhardt, Jun Wang, Yaohang Li, Jiianxin Wang

Computer Science Faculty Publications

Adverse Drug Reactions (ADRs) have a direct impact on human health. As continuous pharmacovigilance and drug monitoring prove to be costly and time-consuming, computational methods have emerged as promising alternatives. However, most existing computational methods primarily focus on predicting whether or not the drug is associated with an adverse reaction and do not consider the core issue of drug benefit-risk assessment-whether the treatment outcome is serious when adverse drug reactions occur. To this end, we categorize serious clinical outcomes caused by adverse reactions to drugs into seven distinct classes and present a deep learning framework, so-called GCAP, for predicting the …

Enabling Customization Of Discussion Forums For Blind Users, Mohan Sunkara, Yash Prakash, Hae-Na Lee, Sampath Jayarathna, Vikas Ashok

Computer Science Faculty Publications

Online discussion forums have become an integral component of news, entertainment, information, and video-streaming websites, where people all over the world actively engage in discussions on a wide range of topics including politics, sports, music, business, health, and world affairs. Yet, little is known about their usability for blind users, who aurally interact with the forum conversations using screen reader assistive technology. In an interview study, blind users stated that they often had an arduous and frustrating interaction experience while consuming conversation threads, mainly due to the highly redundant content and the absence of customization options to selectively view portions …

Msdrp: A Deep Learning Model Based On Multisource Data For Predicting Drug Response, Haochen Zhao, Xiaoyu Zhang, Qichang Zhao, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Motivation: Cancer heterogeneity drastically affects cancer therapeutic outcomes. Predicting drug response in vitro is expected to help formulate personalized therapy regimens. In recent years, several computational models based on machine learning and deep learning have been proposed to predict drug response in vitro. However, most of these methods capture drug features based on a single drug description (e.g. drug structure), without considering the relationships between drugs and biological entities (e.g. target, diseases, and side effects). Moreover, most of these methods collect features separately for drugs and cell lines but fail to consider the pairwise interactions between drugs and cell …

An Approach To Developing Benchmark Datasets For Protein Secondary Structure Segmentation From Cryo-Em Density Maps, Thu Nguyen, Yongcheng Mu, Jiangwen Sun, Jing He

Computer Science Faculty Publications

More and more deep learning approaches have been proposed to segment secondary structures from cryo-electron density maps at medium resolution range (5--10Å). Although the deep learning approaches show great potential, only a few small experimental data sets have been used to test the approaches. There is limited understanding about potential factors, in data, that affect the performance of segmentation. We propose an approach to generate data sets with desired specifications in three potential factors - the protein sequence identity, structural contents, and data quality. The approach was implemented and has generated a test set and various training sets to study …

Progenitor Cell Isolation From Mouse Epididymal Adipose Tissue And Sequencing Library Construction, Qianglin Liu, Chaoyang Li, Yuxia Li, Leshan Wang, Xujia Zhang, Buhao Deng, Peidong Gao, Mohammad Shiri, Fozi Alkaifi, Junxing Zhao, Jacqueline M. Stephens, Constantine A. Simintiras, Joseph Francis, Jiangwen Sun, Xing Fu

Computer Science Faculty Publications

Here, we present a protocol to isolate progenitor cells from mouse epididymal visceral adipose tissue and construct bulk RNA and assay for transposase-accessible chromatin with sequencing (ATAC-seq) libraries. We describe steps for adipose tissue collection, cell isolation, and cell staining and sorting. We then detail procedures for both ATAC-seq and RNA sequencing library construction. This protocol can also be applied to other tissues and cell types directly or with minor modifications.

For complete details on the use and execution of this protocol, please refer to Liu et al. (2023).¹

*¹ Liu, Q., Li, C., Deng, B., Gao, P., …

Detecting Deceptive Dark-Pattern Web Advertisements For Blind Screen-Reader Users, Satwick Ram Kodandaram, Mohan Sunkara, Sampath Jayarathna, Vikas Ashok

Computer Science Faculty Publications

Advertisements have become commonplace on modern websites. While ads are typically designed for visual consumption, it is unclear how they affect blind users who interact with the ads using a screen reader. Existing research studies on non-visual web interaction predominantly focus on general web browsing; the specific impact of extraneous ad content on blind users' experience remains largely unexplored. To fill this gap, we conducted an interview study with 18 blind participants; we found that blind users are often deceived by ads that contextually blend in with the surrounding web page content. While ad blockers can address this problem via …

Autodesc: Facilitating Convenient Perusal Of Web Data Items For Blind Users, Yash Prakash, Mohan Sunkara, Hae-Na Lee, Sampath Jayarathna, Vikas Ashok

Computer Science Faculty Publications

Web data items such as shopping products, classifieds, and job listings are indispensable components of most e-commerce websites. The information on the data items are typically distributed over two or more webpages, e.g., a ‘Query-Results’ page showing the summaries of the items, and ‘Details’ pages containing full information about the items. While this organization of data mitigates information overload and visual cluttering for sighted users, it however increases the interaction overhead and effort for blind users, as back-and-forth navigation between webpages using screen reader assistive technology is tedious and cumbersome. Existing usability-enhancing solutions are unable to provide adequate support in …

Intergenic Transcription In In Vivo Developed Bovine Oocytes And Pre-Implantation Embryos, Saurav Ranjitkar, Mohammad Shiri, Jiangwen Sun, Xiuchun Tian

Computer Science Faculty Publications

Background

Intergenic transcription, either failure to terminate at the transcription end site (TES), or transcription initiation at other intergenic regions, is present in cultured cells and enhanced in the presence of stressors such as viral infection. Transcription termination failure has not been characterized in natural biological samples such as pre-implantation embryos which express more than 10,000 genes and undergo drastic changes in DNA methylation.

Results

Using Automatic Readthrough Transcription Detection (ARTDeco) and data of in vivo developed bovine oocytes and embryos, we found abundant intergenic transcripts that we termed as read-outs (transcribed from 5 to 15 kb after TES) and …

Cellbrf: A Feature Selection Method For Single-Cell Clustering Using Cell Balance And Random Forest, Yunpei Xu, Hong-Dong Li, Cui-Xiang Lin, Ruiqing Zheng, Yaohang Li, Jinhui Xu, Jianxin Wang

Computer Science Faculty Publications

Motivation

Single-cell RNA sequencing (scRNA-seq) offers a powerful tool to dissect the complexity of biological tissues through cell sub-population identification in combination with clustering approaches. Feature selection is a critical step for improving the accuracy and interpretability of single-cell clustering. Existing feature selection methods underutilize the discriminatory potential of genes across distinct cell types. We hypothesize that incorporating such information could further boost the performance of single cell clustering. Results

We develop CellBRF, a feature selection method that considers genes’ relevance to cell types for single-cell clustering. The key idea is to identify genes that are most important for discriminating …