Medicine and Health Sciences Commons^™

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 …

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, …

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 …

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, …

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 …

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 …

Homogeneity Test On Error Rates From Ordinal Scores And Application To Forensic Science, Ngoc Ty Nguyen

Graduate Thesis and Dissertation 2023-2024

The Receiver Operating Characteristic (ROC) curve is used to measure the classification accuracy of tests that yield ordinal or continuous scores. Ordinal scores are common in medical imaging studies and, more recently, in black-box studies on forensic identification accuracy (Phillips et al., 2018). To assess the accuracy of radiologists in medical imaging studies or the accuracy of forensic examiners in biometric studies, one needs to estimate the ROC curves from the ordinal scores and account for the covariates related to the radiologists or forensic examiners. In this thesis, we propose a homogeneity test to compare the performance of raters. We …

Lessons Learned From Interdisciplinary Efforts To Combat Covid-19 Misinformation: Development Of Agile Integrative Methods From Behavioral Science, Data Science, And Implementation Science, Sahiti Myneni, Paula Cuccaro, Sarah Montgomery, Vivek Pakanati, Jinni Tang, Tavleen Singh, Olivia Dominguez, Trevor Cohen, Belinda Reininger, Lara S Savas, Maria E Fernandez

Faculty, Staff and Student Publications

BACKGROUND: Despite increasing awareness about and advances in addressing social media misinformation, the free flow of false COVID-19 information has continued, affecting individuals' preventive behaviors, including masking, testing, and vaccine uptake.

OBJECTIVE: In this paper, we describe our multidisciplinary efforts with a specific focus on methods to (1) gather community needs, (2) develop interventions, and (3) conduct large-scale agile and rapid community assessments to examine and combat COVID-19 misinformation.

METHODS: We used the Intervention Mapping framework to perform community needs assessment and develop theory-informed interventions. To supplement these rapid and responsive efforts through large-scale online social listening, we developed a …

A Query Engine For Self-Controlled Case Series, With An Application To Covid-19 Ehr Data, Xiaojin Li, Yan Huang, Licong Cui, Guo-Qiang Zhang

Faculty, Staff and Student Publications

Self-controlled case series (SCCS) is a statistical method in epidemiological study design that uses individuals as their own controls, with comparisons made within the same individuals at different time points of observation. SCCS has been applied in settings where it is difficult to identify comparison or control groups. To provide computational support for SCCS, we introduce a query engine called Self-Controlled Case Query (SCCQ) and use it to extract cohorts of self-controlled case series from a large-scale COVID-19 Electronic Health Records (EHR) dataset. Visual summary of the queried population through the R-Shiny visualization framework offers SCCQ's query result dashboard to …

Federated Learning Based Futuristic Biomedical Big-Data Analysis And Standardization, Afifa Salsabil Fathima, Syed Muzamil Basha, Syed Thouheed Ahmed, Sandeep Kumar Mathivanan, Sukumar Rajendran, Saurav Mallik, Zhongming Zhao

Faculty, Staff and Student Publications

Medical data processing and analytics exert significant influence in furnishing dependable decision support for prospective biomedical applications. Given the sensitive nature of medical data, specialized techniques and frameworks tailored for application-centric processing are imperative. This article presents a conceptualization for the analysis and uniformitarian of datasets through the implementation of Federated Learning (FL). The realm of medical big data stems from diverse origins, necessitating the delineation of data provenance and attribute paradigms to facilitate feature extraction and dependency assessment. The architecture governing the data collection framework is intricately linked to remote data transmission, thereby engendering efficient customization oversight. The operational …

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 …

Enhancing The Conformational Stability Of The Cl-Par-4 Tumor Suppressor Via Site-Directed Mutagenesis, Samjhana Pandey, Krishna K. Raut, Antoine Baudin, Lamya Djemri, David S. Libich, Komala Ponniah, Steven M. Pascal

Chemistry & Biochemistry Faculty Publications

Intrinsically disordered proteins play important roles in cell signaling, and dysregulation of these proteins is associated with several diseases. Prostate apoptosis response-4 (Par-4), an approximately 40 kilodalton proapoptotic tumor suppressor, is a predominantly intrinsically disordered protein whose downregulation has been observed in various cancers. The caspase-cleaved fragment of Par-4 (cl-Par-4) is active and plays a role in tumor suppression by inhibiting cell survival pathways. Here, we employed site-directed mutagenesis to create a cl-Par-4 point mutant (D313K). The expressed and purified D313K protein was characterized using biophysical techniques, and the results were compared to that of the wild-type (WT). We have …

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 …

Using Wastewater-Based Epidemiology To Study Chlamydia Occurrence On A College Campus, Jessie E. Chin Quee

Honors Undergraduate Theses

Chlamydia is a sexually transmitted disease caused by Chlamydia trachomatis, commonly affecting sexually active college-aged adults. Presently, opportunistic testing, self-testing, and information campaigns are methods to screen vulnerable populations and raise awareness about chlamydia. Chlamydia remains underdiagnosed and undertested due to a lack of participation by individuals who may have been exposed to it. Wastewater-based epidemiology is a rising biomonitoring tool that detects the presence of disease- and drug-specific biomarkers in a community's wastewater. In this study, wastewater-based epidemiology was used to detect the presence of C. trachomatis on the University of Central Florida campus. Wastewater samples were collected …

Nutrient Pollution And Chlorophyll-A As A Precursor To Harmful Algal Blooms And Cyanotoxins In Rehabilitated Machado Lake, California, Michael E. Shiang

Walden Dissertations and Doctoral Studies

Algal blooms result in the formation of cyanotoxic conditions in a freshwater lake causing severe detrimental impacts to community and public health. Nitrogen, phosphorous, and ammonia stimulate the growth of phytoplankton biomass and algae, as measured by chlorophyll. This retrospective quantitative research study, grounded in the socioecological model, examined the relationship between nutrient pollutants and chlorophyll-a (Chl-a) that forecast harmful algal blooms, a precursor to cyanotoxins. A former impaired lake, Machado Lake in California, provided an ideal setting to assess relationships among nutrient indicators and Chl-a post-lake rehabilitation. Correlation and multiple regression analyses were performed to determine if a relationship …

Striving For Appropriate Antibiotic Use: A Biomarker Initiative, And Outcomes Associated With Azithromycin Exposure, Amanda Gusovsky

Theses and Dissertations--Pharmacy

The introduction of antibiotics into clinical practice is considered the greatest medical breakthrough of the 20^thcentury. However, the use of antibiotics can contribute to the development of resistance. In the United States (U.S.), approximately 2.8 million people are infected with antibiotic-resistant bacteria each year, and more than 35,000 people die as a result. Moreover, some antibiotics are known to cause cardiac side effects including QT prolongation, hypotension, and ventricular arrythmias. The U.S. Centers for Disease Control and Prevention (CDC) defines appropriate antibiotic use as the effort to use “the right antibiotic, at the right dose, for the right …

Clustering Hospital Performance Using Group-Based Multi-Trajectory Modeling With Singular Bayesian Information Criterion, Gaixin Du

Theses and Dissertations--Epidemiology and Biostatistics

Hospital performance is complex and patient-experience oriented. Currently, the Centers for Medicare and Medicaid Services (CMS) evaluate hospitals yearly with a single score of one to five ("Star Rating") using composite measures from five domains. However, a single composite score cannot fully describe it, and alternative measures should be considered. Healthcare quality improvement needs long-term data to validate effectiveness. Group-based multi-trajectory modeling (GBMTM) estimates probabilities of latent group membership based on longitudinal profiles from multiple outcomes. We use GBMTM to identify groups of hospitals with similar performance in SAS PROC TRAJ.

We downloaded Medicare-eligible hospitals (N=5,111) that provided patient care …

Potential Alzheimer's Disease Plasma Biomarkers, Taylor Estepp

Theses and Dissertations--Epidemiology and Biostatistics

In this series of studies, we examined the potential of a variety of blood-based plasma biomarkers for the identification of Alzheimer's disease (AD) progression and cognitive decline. With the end goal of studying these biomarkers via mixture modeling, we began with a literature review of the methodology. An examination of the biomarkers with demographics and other health factors found evidence of minimal risk of confounding along the causal pathway from biomarkers to cognitive performance. Further study examined the usefulness of linear combinations of biomarkers, achieved via partial least squares (PLS) analysis, as predictors of various cognitive assessment scores and clinical …

The Effect Of Land-Cover/Land-Use And Habitat Fragmentation On Spatial Patterns Of Lyme Disease In The Eastern United States, Maria Elizabeth Topmiller

Theses and Dissertations--Forestry and Natural Resources

Lyme disease has been of national concern for the past few decades. As our understanding of the role of landscape structure in epidemiology expands, it is essential to apply the principles of landscape ecology to the research of vector-borne and zoonotic disease. This study examined the strength of the relationship between land-cover class, degree of habitat fragmentation and county-level Lyme disease cases. Forest, agricultural, and urban land cover types were the categories of interest, while percent cover, edge density, and patch density were the landscape metric used to measure habitat amount and fragmentation. The general linear trends were modelled with …

Covidanno, Covid-19 Annotation In Human, Yuzhou Feng, Mengyuan Yang, Zhiwei Fan, Weiling Zhao, Pora Kim, Xiaobo Zhou

Faculty, Staff and Student Publications

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiologic agent of coronavirus disease 19 (COVID-19), has caused a global health crisis. Despite ongoing efforts to treat patients, there is no universal prevention or cure available. One of the feasible approaches will be identifying the key genes from SARS-CoV-2-infected cells. SARS-CoV-2-infected in vitro model, allows easy control of the experimental conditions, obtaining reproducible results, and monitoring of infection progression. Currently, accumulating RNA-seq data from SARS-CoV-2 in vitro models urgently needs systematic translation and interpretation. To fill this gap, we built COVIDanno, COVID-19 annotation in humans, available at http://biomedbdc.wchscu.cn/COVIDanno/. The aim …

Syllable-Pbwt For Space-Efficient Haplotype Long-Match Query, Victor Wang, Ardalan Naseri, Shaojie Zhang, Degui Zhi

Faculty, Staff and Student Publications

MOTIVATION: The positional Burrows-Wheeler transform (PBWT) has led to tremendous strides in haplotype matching on biobank-scale data. For genetic genealogical search, PBWT-based methods have optimized the asymptotic runtime of finding long matches between a query haplotype and a predefined panel of haplotypes. However, to enable fast query searches, the full-sized panel and PBWT data structures must be kept in memory, preventing existing algorithms from scaling up to modern biobank panels consisting of millions of haplotypes. In this work, we propose a space-efficient variation of PBWT named Syllable-PBWT, which divides every haplotype into syllables, builds the PBWT positional prefix arrays on …

Use Gpt-J Prompt Generation With Roberta For Ner Models On Diagnosis Extraction Of Periodontal Diagnosis From Electronic Dental Records, Yao-Shun Chuang, Xiaoqian Jiang, Chun-Teh Lee, Ryan Brandon, Duong Tran, Oluwabunmi Tokede, Muhammad F Walji

Faculty, Staff and Student Publications

This study explored the usability of prompt generation on named entity recognition (NER) tasks and the performance in different settings of the prompt. The prompt generation by GPT-J models was utilized to directly test the gold standard as well as to generate the seed and further fed to the RoBERTa model with the spaCy package. In the direct test, a lower ratio of negative examples with higher numbers of examples in prompt achieved the best results with a F1 score of 0.72. The performance revealed consistency, 0.92-0.97 in the F1 score, in all settings after training with the RoBERTa model. …

Towards Fair Patient-Trial Matching Via Patient-Criterion Level Fairness Constraint, Chia-Yuan Chang, Jiayi Yuan, Sirui Ding, Qiaoyu Tan, Kai Zhang, Xiaoqian Jiang, Xia Hu, Na Zou

Faculty, Staff and Student Publications

Clinical trials are indispensable in developing new treatments, but they face obstacles in patient recruitment and retention, hindering the enrollment of necessary participants. To tackle these challenges, deep learning frameworks have been created to match patients to trials. These frameworks calculate the similarity between patients and clinical trial eligibility criteria, considering the discrepancy between inclusion and exclusion criteria. Recent studies have shown that these frameworks outperform earlier approaches. However, deep learning models may raise fairness issues in patient-trial matching when certain sensitive groups of individuals are underrepresented in clinical trials, leading to incomplete or inaccurate data and potential harm. To …

Energy Content Of Grasshoppers (Orthoptera: Acrididae) In The Diet Of Scaled Quail (Callipepla Squamata) In Southeastern New Mexico, J.L. Hunt, M.E. Grilliot, T.L. Best, C.M. Wilkerson, A.F. Huitt

Journal of the Arkansas Academy of Science

Grasshoppers (Orthoptera: Acrididae) are common insects that are important food items for many kinds of wildlife, including many species of upland game birds such as scaled quail (Callipepla squamata). We analyzed the energy content of grasshoppers obtained from the crops of scaled quail collected from plainsmesa sand-scrub in Lea and Eddy counties, New Mexico. Grasshoppers were removed from crops and dried for 48 hours at 60°C to remove moisture and standardize masses. Grasshoppers were then pulverized and analyzed for gross caloric value (i.e., energy content) in an oxygen bomb calorimeter. Energy content of grasshoppers from New Mexico averaged 19.2 J/kg …

The Potential And Limitations Of Conversational Agents For Chronic Conditions And Well-Being, Ekaterina Uetova, Lucy Hederman, Robert J. Ross, Dympna O'Sullivan

Articles

Conversational agents are becoming more common in the health and wellness domains in part due to assumptions regarding potential improvements in individuals’ outcomes. This paper presents initial findings from a review of conversational agent use in healthcare for chronic conditions and well-being. A search of the literature was performed on electronic databases PubMed, ACM Digital Library, Scopus and IEEE Xplore. Studies were included if they were focused on chronic disorder management, disease prevention or lifestyle change and if systems were tested on target user groups. This paper investigates the health domains, the user profiles and reasons why conversational agents may …

Enhancing Health Data Representation For Older Adults: Unlocking Opportunities, Peterson Jean

Academic Posters Collection

The prevalence of off-the-shelf wearable devices increases the monitoring and measurement of critical physiological parameters like activity, sleep, heart rate, and blood pressure. However, the accessibility of health data representations poses challenges for older adults, who often struggle to understand the criticality of their own health data without assistance. This poster highlights the challenges older adults face in accessing their health data from wearable technologies, specifically focusing on data representations.

To address these challenges, it proposes a methodology that involves a heuristic evaluation of existing data representations with experts and accessibility studies with older adults using a mixed methods approach …

Knowledge Discovery On The Integrative Analysis Of Electrical And Mechanical Dyssynchrony To Improve Cardiac Resynchronization Therapy, Zhuo He

Dissertations, Master's Theses and Master's Reports

Cardiac resynchronization therapy (CRT) is a standard method of treating heart failure by coordinating the function of the left and right ventricles. However, up to 40% of CRT recipients do not experience clinical symptoms or cardiac function improvements. The main reasons for CRT non-response include: (1) suboptimal patient selection based on electrical dyssynchrony measured by electrocardiogram (ECG) in current guidelines; (2) mechanical dyssynchrony has been shown to be effective but has not been fully explored; and (3) inappropriate placement of the CRT left ventricular (LV) lead in a significant number of patients.

In terms of mechanical dyssynchrony, we utilize an …

Machine Learning Framework For Real-World Electronic Health Records Regarding Missingness, Interpretability, And Fairness, Jing Lucas Liu

Theses and Dissertations--Computer Science

Machine learning (ML) and deep learning (DL) techniques have shown promising results in healthcare applications using Electronic Health Records (EHRs) data. However, their adoption in real-world healthcare settings is hindered by three major challenges. Firstly, real-world EHR data typically contains numerous missing values. Secondly, traditional ML/DL models are typically considered black-boxes, whereas interpretability is required for real-world healthcare applications. Finally, differences in data distributions may lead to unfairness and performance disparities, particularly in subpopulations.

This dissertation proposes methods to address missing data, interpretability, and fairness issues. The first work proposes an ensemble prediction framework for EHR data with large missing …

New Records Of Distribution And Natural History Of Vertebrates In Arkansas: 2020-2023, R. Tumlison, H.W. Robison, M.B. Connior, D.B. Sasse, T.S. Risch, K. Edmonds, J.D. Wilhide, C.R. Allen

Journal of the Arkansas Academy of Science

Small details of natural history often go undocumented to science if those details are not parts of larger studies. However, knowledge of small details can provide insights that lead to interesting questions about ecological relationships or environmental change. We have compiled recent important observations of natural history of vertebrates, including several distributional and size records of fishes, atypical carapace shape in a common snapping turtle, an unusual support structure for a bird nest, healed damage to a broken jaw of a young deer, and numerous distributional records of bats.