Medicine and Health Sciences Commons^™

Engineered Plga Nanofibers For Drug Delivery, Andrew Mancuso

Dissertations, Theses, and Capstone Projects

Poly-lactic-co-glycolic acid (PLGA) polymers are rapidly gaining momentum as a platform for next-generation drug delivery systems due to their ease and low cost of synthesis, favorable biocompatibility and biodegradability, and lack of toxicity. In particular, the application of drug-loaded PLGA nanofibers directly to a target tissue may represent a promising alternative to traditional routes of drug administration (e.g., oral, injectable) as they offer the potential to greatly improve bioavailability, increase efficacy, and reduce off-target toxicity. Furthermore, the use of such a system may potentially allow for greater flexibility in clinical drug development, by enabling the use of compounds which have …

E Pluribus Unum: Prospective Acceptability Benchmarking From The Contouring Collaborative For Consensus In Radiation Oncology Crowdsourced Initiative For Multiobserver Segmentation, Diana Lin, Kareem A Wahid, Benjamin E Nelms, Renjie He, Mohammed A Naser, Simon Duke, Michael V Sherer, John P Christodouleas, Abdallah S R Mohamed, Michael Cislo, James D Murphy, Clifton D Fuller, Erin F Gillespie

Faculty, Staff and Student Publications

Purpose: Contouring Collaborative for Consensus in Radiation Oncology (C3RO) is a crowdsourced challenge engaging radiation oncologists across various expertise levels in segmentation. An obstacle to artificial intelligence (AI) development is the paucity of multiexpert datasets; consequently, we sought to characterize whether aggregate segmentations generated from multiple nonexperts could meet or exceed recognized expert agreement.

Approach: Participants who contoured ≥1 region of interest (ROI) for the breast, sarcoma, head and neck (H&N), gynecologic (GYN), or gastrointestinal (GI) cases were identified as a nonexpert or recognized expert. Cohort-specific ROIs were combined into single simultaneous truth and performance level estimation (STAPLE) consensus segmentations. …

Intelligent Health Care And Diseases Management System: Multi-Day-Ahead Predictions Of Covid-19, Ahed Abugabah, Farah Shahid

All Works

The rapidly growing number of COVID-19 infected and death cases has had a catastrophic worldwide impact. As a case study, the total number of death cases in Algeria is over two thousand people (increased with time), which drives us to search its possible trend for early warning and control. In this paper, the proposed model for making a time-series forecast for daily and total infected cases, death cases, and recovered cases for the countrywide Algeria COVID-19 dataset is a two-layer dropout gated recurrent unit (TDGRU). Four performance parameters were used to assess the model’s performance: mean absolute error (MAE), root …

Predicting Suicidal And Self-Injurious Events In A Correctional Setting Using Ai Algorithms On Unstructured Medical Notes And Structured Data, Hongxia Lu, Alex Barrett, Albert Pierce, Jianwei Zheng, Yun Wang, Chun Chiang, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

Suicidal and self-injurious incidents in correctional settings deplete the institutional and healthcare resources, create disorder and stress for staff and other inmates. Traditional statistical analyses provide some guidance, but they can only be applied to structured data that are often difficult to collect and their recommendations are often expensive to act upon. This study aims to extract information from medical and mental health progress notes using AI algorithms to make actionable predictions of suicidal and self-injurious events to improve the efficiency of triage for health care services and prevent suicidal and injurious events from happening at California's Orange County Jails. …

Determining The Proportionality Of Ischemic Stroke Risk Factors To Age, Elizabeth Hunter, John D. Kelleher

Articles

While age is an important risk factor, there are some disadvantages to including it in a stroke risk model: age can dominate the risk score and lead to over-or under-predictions in some age groups. There is evidence to suggest that some of these disadvantages are due to the non-proportionality of other risk factors with age, eg, risk factors contribute differently to stroke risk based on an individual’s age. In this paper, we present a framework to test if risk factors are proportional with age. We then apply the framework to a set of risk factors using Framingham heart study data …

Reducing Tracheal Complications In Endotracheal Intubation Patients Using Automated Cuff Pressure Modulation, Shrihan G. Babu

Journal of the South Carolina Academy of Science

Endotracheal tube intubation is the third most frequent procedure, performed approximately 13-20 million times yearly in the United States (Mosier et al., 2020). Despite the regularity of the procedure, intubation-related complications such as tracheal injuries, laryngeal injuries, and ventilator-associated pneumonia are ubiquitous due to improper cuff pressure management methods (Ganti et al., 2018). Current techniques, such as the pilot balloon and minimal leak technique, have proven ineffective and inconsistent in managing pressure. As a result, over 71.6% of intubation patients have abnormally high cuff pressures (Ramírez, 2014). Therefore, the purpose of this research was to design an endotracheal tube with …

Synthesize Heterogeneous Biological Knowledge Via Representation Learning For Alzheimer’S Disease Drug Repurposing, Kang-Lin Hsieh, German Plascencia-Villa, Ko-Hong Lin, George Perry, Xiaoqian Jiang, Yejin Kim

Faculty, Staff and Student Publications

Developing drugs for treating Alzheimer's disease has been extremely challenging and costly due to limited knowledge of underlying mechanisms and therapeutic targets. To address the challenge in AD drug development, we developed a multi-task deep learning pipeline that learns biological interactions and AD risk genes, then utilizes multi-level evidence on drug efficacy to identify repurposable drug candidates. Using the embedding derived from the model, we ranked drug candidates based on evidence from post-treatment transcriptomic patterns, efficacy in preclinical models, population-based treatment effects, and clinical trials. We mechanistically validated the top-ranked candidates in neuronal cells, identifying drug combinations with efficacy in …

Integrated Mrna Sequence Optimization Using Deep Learning, Haoran Gong, Jianguo Wen, Ruihan Luo, Yuzhou Feng, Jingjing Guo, Hongguang Fu, Xiaobo Zhou

Faculty, Staff and Student Publications

The coronavirus disease of 2019 pandemic has catalyzed the rapid development of mRNA vaccines, whereas, how to optimize the mRNA sequence of exogenous gene such as severe acute respiratory syndrome coronavirus 2 spike to fit human cells remains a critical challenge. A new algorithm, iDRO (integrated deep-learning-based mRNA optimization), is developed to optimize multiple components of mRNA sequences based on given amino acid sequences of target protein. Considering the biological constraints, we divided iDRO into two steps: open reading frame (ORF) optimization and 5' untranslated region (UTR) and 3'UTR generation. In ORF optimization, BiLSTM-CRF (bidirectional long-short-term memory with conditional random …

Ontologies Applied In Clinical Decision Support System Rules: Systematic Review, Xia Jing, Hua Min, Yang Gong, Paul Biondich, David Robinson, Timothy Law, Christian Nohr, Arild Faxvaag, Lior Rennert, Nina Hubig, Ronald Gimbel

Faculty, Staff and Student Publications

BACKGROUND: Clinical decision support systems (CDSSs) are important for the quality and safety of health care delivery. Although CDSS rules guide CDSS behavior, they are not routinely shared and reused.

OBJECTIVE: Ontologies have the potential to promote the reuse of CDSS rules. Therefore, we systematically screened the literature to elaborate on the current status of ontologies applied in CDSS rules, such as rule management, which uses captured CDSS rule usage data and user feedback data to tailor CDSS services to be more accurate, and maintenance, which updates CDSS rules. Through this systematic literature review, we aim to identify the frontiers …

Wrapper-Based Deep Feature Optimization For Activity Recognition In The Wearable Sensor Networks Of Healthcare Systems, Karam Kumar Sahoo, Raghunath Ghosh, Saurav Mallik, Arup Roy, Pawan Kumar Singh, Zhongming Zhao

Faculty, Staff and Student Publications

The Human Activity Recognition (HAR) problem leverages pattern recognition to classify physical human activities as they are captured by several sensor modalities. Remote monitoring of an individual's activities has gained importance due to the reduction in travel and physical activities during the pandemic. Research on HAR enables one person to either remotely monitor or recognize another person's activity via the ubiquitous mobile device or by using sensor-based Internet of Things (IoT). Our proposed work focuses on the accurate classification of daily human activities from both accelerometer and gyroscope sensor data after converting into spectrogram images. The feature extraction process follows …

Scalable Causal Structure Learning: Scoping Review Of Traditional And Deep Learning Algorithms And New Opportunities In Biomedicine, Pulakesh Upadhyaya, Kai Zhang, Can Li, Xiaoqian Jiang, Yejin Kim

Faculty, Staff and Student Publications

BACKGROUND: Causal structure learning refers to a process of identifying causal structures from observational data, and it can have multiple applications in biomedicine and health care.

OBJECTIVE: This paper provides a practical review and tutorial on scalable causal structure learning models with examples of real-world data to help health care audiences understand and apply them.

METHODS: We reviewed traditional (combinatorial and score-based) methods for causal structure discovery and machine learning-based schemes. Various traditional approaches have been studied to tackle this problem, the most important among these being the Peter Spirtes and Clark Glymour algorithms. This was followed by analyzing the …

A Deep Learning Based Dual Encoder–Decoder Framework For Anatomical Structure Segmentation In Chest X-Ray Images, Ihsan Ullah, Farman Ali, Babar Shah, Shaker El-Sappagh, Tamer Abuhmed, Sang Hyun Park

All Works

Automated multi-organ segmentation plays an essential part in the computer-aided diagnostic (CAD) of chest X-ray fluoroscopy. However, developing a CAD system for the anatomical structure segmentation remains challenging due to several indistinct structures, variations in the anatomical structure shape among different individuals, the presence of medical tools, such as pacemakers and catheters, and various artifacts in the chest radiographic images. In this paper, we propose a robust deep learning segmentation framework for the anatomical structure in chest radiographs that utilizes a dual encoder–decoder convolutional neural network (CNN). The first network in the dual encoder–decoder structure effectively utilizes a pre-trained VGG19 …

Potential Of Biduri Fiber (Calotropis Gigantea) As Material For Oil Spill Absorbent, Anne Sukmawati, Wulan Septiani

Journal of Materials Exploration and Findings

Biduri fiber (Calotropis gigantea) is a natural hollow fiber with hydrophobic and oleophilic properties potentially used as oil spilled sorbent from seawater. This study aims to determine the absorption capacity and efficiency of the Biduri fiber and membrane to fuel oil. Measurement of oil absorption to seawater was carried out at various fiber weights (0.5-1.5 g), fiber composition (50-95%), contact time (10-90 minutes), temperature (30 and 50°C), and compared with commercial products. The results showed that the fiber weight variation of 0.5-1.5 g has an average absorption efficiency of 96.67%, and the highest absorption was obtained in a weight of …

An Efficient Hash-Based Assessment And Recovery Algorithm For Distributed Healthcare Systems, Sanaa Kaddoura, Ramzi Haraty, Sultan Al Jahdali, Mohamad Jaber

All Works

The enhancement of the information technology in many domains has had a positive impact on the healthcare sector. The ability to share medical data is one of the positive outcomes. However, this improvement comes with a number of threats. Although many threat preventive measures have been applied yet, no one can be confident that the system is safe from attacks. Thus, an algorithm needs to assess the damage occurring as a result of an attack before recovering the database. In this work, we present a distributed algorithm that uses hash tables to deal with the “information warfare” problem in healthcare …

Not A Waste: Wastewater Surveillance To Enhance Public Health, Anna Gitter, Jeremiah Oghuan, Anuja Rajendra Godbole, Carlos A. Chavarria, Carlos Monserrat, Tao Hu, Yun Wang, Anthony W. Maresso, Blake M. Hanson, Kristina D. Mena, Fuqing Wu

Pharmacy Faculty Articles and Research

Domestic wastewater, when collected and evaluated appropriately, can provide valuable health-related information for a community. As a relatively unbiased and non-invasive approach, wastewater surveillance may complement current practices towards mitigating risks and protecting population health. Spurred by the COVID-19 pandemic, wastewater programs are now widely implemented to monitor viral infection trends in sewersheds and inform public health decision-making. This review summarizes recent developments in wastewater-based epidemiology for detecting and monitoring communicable infectious diseases, dissemination of antimicrobial resistance, and illicit drug consumption. Wastewater surveillance, a quickly advancing Frontier in environmental science, is becoming a new tool to enhance public health, improve …

Divergent Directionality Of Immune Cell-Specific Protein Expression Between Bipolar Lithium Responders And Non-Responders Revealed By Enhanced Flow Cytometry, Keming Gao, Nicholas M. Kaye, Marzieh Ayati, Mehmet Koyuturk, Joseph R. Calabrese, Eric Christian, Hillard M. Lazarus, David Kaplan

Computer Science Faculty Publications

Background and Objectives: There is no biomarker to predict lithium response. This study used CellPrint™ enhanced flow cytometry to study 28 proteins representing a spectrum of cellular pathways in monocytes and CD4+ lymphocytes before and after lithium treatment in patients with bipolar disorder (BD). Materials and Methods: Symptomatic patients with BD type I or II received lithium (serum level ≥ 0.6 mEq/L) for 16 weeks. Patients were assessed with standard rating scales and divided into two groups, responders (≥50% improvement from baseline) and non-responders. Twenty-eight intracellular proteins in CD4+ lymphocytes and monocytes were analyzed with CellPrint™, an enhanced flow …

Ageanno: A Knowledgebase Of Single-Cell Annotation Of Aging In Human, Kexin Huang, Hoaran Gong, Jingjing Guan, Lingxiao Zhang, Changbao Hu, Weiling Zhao, Liyu Huang, Wei Zhang, Pora Kim, Xiaobo Zhou

Faculty, Staff and Student Publications

Aging is a complex process that accompanied by molecular and cellular alterations. The identification of tissue-/cell type-specific biomarkers of aging and elucidation of the detailed biological mechanisms of aging-related genes at the single-cell level can help to understand the heterogeneous aging process and design targeted anti-aging therapeutics. Here, we built AgeAnno (https://relab.xidian.edu.cn/AgeAnno/#/), a knowledgebase of single cell annotation of aging in human, aiming to provide comprehensive characterizations for aging-related genes across diverse tissue-cell types in human by using single-cell RNA and ATAC sequencing data (scRNA and scATAC). The current version of AgeAnno houses 1 678 610 cells from 28 healthy …

Spascer: Spatial Transcriptomics Annotation At Single-Cell Resolution, Zhiwei Fan, Yangyang Luo, Huifen Lu, Tiangang Wang, Yuzhou Feng, Weiling Zhao, Pora Kim, Xiaobo Zhou

Faculty, Staff and Student Publications

In recent years, the explosive growth of spatial technologies has enabled the characterization of spatial heterogeneity of tissue architectures. Compared to traditional sequencing, spatial transcriptomics reserves the spatial information of each captured location and provides novel insights into diverse spatially related biological contexts. Even though two spatial transcriptomics databases exist, they provide limited analytical information. Information such as spatial heterogeneity of genes and cells, cell-cell communication activities in space, and the cell type compositions in the microenvironment are critical clues to unveil the mechanism of tumorigenesis and embryo differentiation. Therefore, we constructed a new spatial transcriptomics database, named SPASCER (https://ccsm.uth.edu/SPASCER), …

Intro To Primary Sources, Katie Strand, Jen Kirk, Dan Davis, Lara Petersen

All E-Learning Resources

Attention: As of 2026 updated versions of this item will no longer be available on Digital Commons. Please contact [email protected] for more information.

The Identifying Primary Sources tutorial teaches students how they find, evaluate, and use primary sources in their own research. Along the way, they'll learn about some great places to start researching when looking for primary sources.

Chacahoula 2022, Tram Phan

Chacahoula

Chacahoula 2022 includes the people and events that made the 2021-2022 school year at University of Louisiana at Monroe unique. Staff included

Tram Phan, Editor-in-Chief

Feature Writers:

Amir Alnajjar

Hanna Flynn

Alayna Pellegrin

Tram Phan

Evan Ranjitkar

Koshish Shrestha

Zoe Sissac

Tia Smith

Sports Writers:

Jonah Bostick

Cameron Jett

Designers:

Hanna Flynn

Tram Phan

Photographers:

Lanaya Bolden

Skylar Henry

Jeanette Robinson

Saugat Shrestha

Calli Sinclair

Paul Ware

Characterization Of Food Chain Clostridioides Difficile Isolates In Terms Of Ribotype And Antimicrobial Resistance, Pilar Marcos, Aoife Doyle, Paul Whyte, Thomas R. Rogers, Maire Mcelroy, Seamus Fanning, Jesus Maria Frias, Declan Bolton

Articles

The aim of this study was to characterize C. difficile isolates from the farm, abattoir, and retail outlets in Ireland in terms of ribotype and antibiotic resistance (vancomycin, erythromycin, metronidazole, moxifloxacin, clindamycin, and rifampicin) using PCR and E-test methods, respectively. The most common ribotype in all stages of the food chain (including retail foods) was 078 and a variant (RT078/4). Less commonly reported (014/0, 002/1, 049, and 205) and novel (RT530, 547, and 683) ribotypes were also detected, but at lower frequencies. Approximately 72% (26/36 tested) of the isolates tested were resistant to at least one antibiotic, with the majority …

Gamelan Gong Directivity Dataset, Samuel D. Bellows, Dallin T. Harwood, Kent L. Gee, Micah R. Shepherd

Directivity

No abstract provided.

Prevention Research Center For Healthy Neighborhoods, Madeline Panus

Celebration of Scholarship 2023

No abstract provided.

Modification Of Hyaluronic Acid To Enable Click Chemistry Photo-Crosslinking Of Hydrogels With Tailorable Degradation Profiles, Ciara Buckley

Articles

Hyaluronic acid (HA) is a naturally occurring mucopolysaccharide that, due to its inherent bioactivity and extracellular matrix-like structure, has the potential to be utilised extensively in tissue engineering. However, this glycosaminoglycan lacks the properties required for cellular adhesion and photo-crosslinking by UV light, which significantly hinders this polymers applicability. This research presents a method for modifying hyaluronic acid via thiolation and methacrylation to generate a novel photo-crosslinkable polymer with improved physicochemical properties, biocompatibility and the potential to customize biodegradability according to the ratio of monomers used. A decrease in stiffness proportional to increasing thiol concentration was observed when testing the …

The Clinical Transferability Of Raman Micro-Spectroscopic Systems For Cervical Cytopathology, Rubina Shaikh Dr, Sarah Loughlin, Alison Malkin, John J. O'Leary, Cara M. Martin, Fiona Lyng

Conference papers

The clinical potential for Raman microscopic systems is well established for early diagnosis via cytology. Although Raman systems offer a complementary diagnostic tool providing molecular information, it is not yet utilised substantially in clinics. A few challenges for the clinical implementation of Raman spectroscopy are system and user variability. In this study, we asked how much variability occurs due to different Raman systems or users. To address these questions, we measured the same set of cells using two different Raman microscopes and by two different users. And classification models were generated using multivariate partial least squares discriminant analysis (PLS-DA) and …

Third Arkansas Record Of Mountain Bluebird (Sialia Currucoides), With Notes On Habitat And Behavior, G. R. Graves

Journal of the Arkansas Academy of Science

Mountain Bluebird (Sialia currucoides) breeds in western North America and winters east to the Great Plains from Nebraska to Texas (Johnson and Dawson 2020). Vagrants are occasionally reported in eastern North America, mostly from November through March, but relatively few wintering records have been documented in the lower Mississippi Valley east of 96° W longitude and south of 37° N latitude.

Academy Presidents And Institutional Members, Academy Editors

Journal of the Arkansas Academy of Science

No abstract provided.

Tolle Lege Works Published In 2023, Mcquade Library

Bibliographies

Compiled Tolle Lege bibliography of works published by members of the Merrimack College Community in 2023. Works include journal articles, books, book chapters, conference presentations and posters, and more.

The Impact Of Big Data Utilization On Quality Improvement In Inpatient Facilities, Lakyn Hare

Theses, Dissertations and Capstones

Introduction: Poor quality in healthcare has resulted in avoidable patient complications, including readmission rates. Big data in healthcare can be analyzed and built into a tools, with machine learning, to aid in reduced readmission rates and overall positive patient outcomes.

Purpose of the Study: The intention of this study was to evaluate the ways that big data can be analyzed to improve healthcare, specifically readmissions, patient outcomes, and show cost savings. This study examined different ways that big data could be used in concordance with machine learning, including predictive analysis, to make these improvements.

Methodology: The hypothesis was the …

Helminth Parasites Of Northern Cottonmouth, Agkistrodon Piscivorus (Ophidia: Viperidae), From Arkansas, C.T. Mcallister, C.R. Bursey, H.W. Robison

Journal of the Arkansas Academy of Science

The Northern cottonmouth, Agkistrodon piscivorus is a large, semiaquatic viperid snake found statewide in Arkansas. Although a great deal has been published on helminth parasites of A. piscivorus from other parts of its range, little (outside of its cestodes) is known about those other helminths occurring in cottonmouths of the state. In our survey, we examined seven adult A. piscivorus from Polk County and a single specimen from Calhoun County. Several helminth parasites were found, including three trematodes, Styphlodora magna, Renifer ellipticus, and Paralechriorchis syntomentera, two nematodes, an unknown larval ascarid and Physaloptera abjecta, an oligacanthorhynchid acanthocephalan cystacanth, and a …