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Osmosis Magazine - Spring 2024

Osmosis Magazine

Osmosis is a student read, led, and written publication from the University of Richmond, focusing on all aspects of healthcare and science.

Letter From The Editor, Andrew Watts

Osmosis Magazine

Dear Reader,

Thank you for opening Osmosis Magazine. We are excited to bring you more accessible, intriguing stories in science and technology spanning the disciplines of chemistry, environmental science, and mathematics. In addition to this edition’s science articles, we are excited to introduce faculty interviews, which chronicle select faculty members’ journeys into science and some of their passions outside of it. Interactive components such as crossword puzzles and word searches are also included. Our goal as a magazine is to share the joy of science with the UR community in an accessible and entertaining fashion. We hope that you …

The Origins Of Mathematics: Invented Or Discovered?, Andrew Watts

Osmosis Magazine

A divisive subject amongst students of all ages, Mathematics remains an integral part of each student’s educational journey. Why is that? you may wonder. The answer is that Mathematics lies at the center of the natural world.

Letter From The Editor, Lily Dickson

Osmosis Magazine

Dear Reader,

Thank you for picking up this semester’s issue of OSMOSIS. We are a student-run magazine filled with all things science! Inside these pages, you will find articles exploring all aspects of science, from straight scientific arguments to philosophical questions regarding mathematics and learning in a world of AI.

We have a talented group of writers, editors, and designers this year, and I cannot wait to share with you our spring issue. It is bittersweet to put together my final issue of OSMOSIS, and little makes me prouder than being a part of this team. Whatever article you choose …

Osmosis Magazine - Spring 2023

Osmosis Magazine

Osmosis is a student read, led, and written publication from the University of Richmond, focusing on all aspects of healthcare and science.

Hiv And Bacterial Lps Synergistically Activate Aim2 Inflammasome In Primary Human Oral Keratinocytes, Md Shafayat Jamil, Deepa Roy, Upal Roy, Hansapani Rodrigo, Nirakar Sahoo, Chun Xu

Research Symposium

Background: HIV infection profoundly disrupts the oral microbiome, increasing the presence of Gram-negative bacteria such as Porphyromonas gingivalis (P. gingivalis), which is detected in over 80% of cases. P. gingivalis secretes lipopolysaccharide (LPS), a potent immune stimulant that can damage primary human oral keratinocytes (HOK) even in antiretroviral therapy (cART) treated people with HIV (PWH). HOK cells respond to bacterial and viral stimuli by activating inflammasome complexes, including AIM2, a DNA-sensing inflammasome protein. While LPS alone is known to trigger canonical and non-canonical pathways, leading to inflammasome activation, our study investigates how HIV exposure synergizes with LPS to induce the …

Leveraging Large Language Models For Knowledge-Free Weak Supervision In Clinical Natural Language Processing, Enshuo Hsu, Kirk Roberts

Faculty, Staff and Student Publications

The performance of deep learning-based natural language processing systems is based on large amounts of labeled training data which, in the clinical domain, are not easily available or affordable. Weak supervision and in-context learning offer partial solutions to this issue, particularly using large language models (LLMs), but their performance still trails traditional supervised methods with moderate amounts of gold-standard data. In particular, inferencing with LLMs is computationally heavy. We propose an approach leveraging fine-tuning LLMs and weak supervision with virtually no domain knowledge that still achieves consistently dominant performance. Using a prompt-based approach, the LLM is used to generate weakly-labeled …

Unraveling Genetic Links Between Diabetes And Heart Failure-A Machine Learning Approach, Sunakhi Sahoo, Marzieh Ayati

Research Symposium

Background: Diabetic heart failure (DHF) is defined as a chronic and progressive disease which is associated with both diabetes and heart failure (HF). Even though there have been many developments in the knowledge of these diseases, there is still much to learn about the genetic crossovers between the two. In this study, we identified genes that are associated with diabetic heart failure and heart failure by using gene expression data from patients with DHF, HF, and a control group of patients who died of natural causes. We sought to identify genes that had altered expression levels which could possibly play …

Uca1 As A Key Regulator Of The Warburg Effect During Anoikis Resistance In Colorectal Cancer Metastasis, Ricardo Pequeno Bracho, Salique Hassan Shaham, Yamile Abuchard Anaya, Sophia Leslie, Kyle Doxtater, Subhash Chauhan, Bilal Hafeez, Tamer Oraby, Manish K. Tripathi

Research Symposium

Colorectal carcinoma (CRC) is the second leading cause of cancer-related mortality in the United States. While localized CRC has a 90% five-year survival rate, this drops sharply to 14% upon metastasis. Metastasis occurs in approximately 40–50% of CRC cases and requires cancer cells to acquire anoikis resistance—a critical adaptation allowing survival after detachment from the extracellular matrix, enabling migration and colonization of secondary sites. Understanding the molecular mechanisms driving anoikis resistance, particularly those linked to altered glucose metabolism, is essential for developing targeted therapies for metastatic CRC.

Cancer cells frequently exhibit the Warburg Effect, a metabolic adaptation favoring glycolysis over …

Late! I’M Late For A Very Important Physics Update I’M Late! I’M Late For A Very Important Physics Update, Caterina Erdas

Osmosis Magazine

Modern physics is my only class where half the students are consistently late. It’s not a forgivable one or two minutes late, but five to fifteen. I say this as a culprit myself; I slept in late on the third day of class and didn’t go. It’s ironic, considering we spend a good portion of lecture re-defining time.

Osmosis Magazine - Fall 2021

Osmosis Magazine

Osmosis is a student read, led, and written publication from the University of Richmond, focusing on all aspects of healthcare and science.

Future Applications Of Fluorescence Lifetime Imaging Ophthalmoscopy In Neuro-Ophthalmology, Neurology, And Neurodegenerative Conditions, Daniel M. Markowitz, Elizabeth Affel, György Hajnóczky, Robert C. Sergott

Farber Institute for Neuroscience Faculty Papers

Fluorescence lifetime imaging ophthalmoscopy (FLIO) has emerged as an innovative advancement in retinal imaging, with the potential to provide in vivo non-invasive insights into the mitochondrial metabolism of the retina. Traditional retinal imaging, such as optical coherence tomography (OCT) and fundus autofluorescence (FAF) intensity imaging, focus solely on structural changes to the retina. In contrast, FLIO provides data that may reflect retinal fluorophore activity, some of which may indicate mitochondrial metabolism. This review builds upon the existing literature to describe the principles of FLIO and established uses in retinal diseases while introducing the potential for FLIO in neurodegenerative conditions.

Designing Accessible Ui/Ux For Epileptic Patients: A Scalable Solution For Music Therapy Delivery, Amethyst G.H. Mckenzie

Computer Science Senior Theses

How can we design an accessible, scalable UI/UX system tailored to the cognitive, visual, and motor impairments of epileptic patients, that ensures safe and effective interactions with music therapy applications? This research explores the intersection of accessibility, user-centred design, and digital health, using an iterative design process to develop and refine the SONATA app—a clinically deployable music therapy platform.

Through two prototype iterations, usability testing, and quantitative event logging, this study compares the effectiveness of structured versus flexible navigation in improving user experience. Key findings reveal that structured navigation reduces unintended detours, while progressive disclosure techniques enhance instructional clarity. Additionally, …

Editorial: Machine Learning Advancements In Pharmacology: Transforming Drug Discovery And Healthcare, Moom Rahman Roosan, Ramgopal Mettu

Pharmacy Faculty Articles and Research

"In recent years, the integration of machine learning (ML) into pharmacology has revolutionized how we approach drug discovery, disease modeling, and therapeutic development. By leveraging vast datasets and computational power, ML has enabled researchers to uncover patterns, predict outcomes, and accelerate drug development processes that were previously unimaginable. This Research Topic on 'Machine Learning Advancements in Pharmacology' features five impactful studies that highlight the diverse applications and potential of ML in this field. These contributions, encompassing original research and a systematic review, exemplify the transformative role of ML in addressing some of the most pressing challenges in pharmacology."

Evolving Trends In Retinoblastoma Management: A 16-Year Clinicopathological Analysis Of Enucleated Eyes, Ari H. August, Darcy Curtis, Maya Eiger-Moscovich, Antonio Yaghy, Sara E. Lally, Jerry A. Shields, Carol L. Shields, Ralph C. Eagle, Tatyana Milman

Wills Eye Hospital Papers

PURPOSE: New treatments for advanced retinoblastoma (RB) have offered alternatives to primary enucleation. We assessed the impact of these therapies on the indications for enucleation and the histopathological findings in enucleated eyes with RB.

MATERIALS AND METHODS: Eyes of all patients who underwent enucleation for RB at a single institution between January 2005 and August 2021 were included. Data collected retrospectively included demographics, clinical and pathologic staging, pathologic findings, and management. Statistical analysis included Kendall’s τb, Pearson χ², and Cramér’s V.

RESULTS: There were 254 eyes from 252 patients with information available for review. Annual enucleations decreased between …

Pre-Exposure Prophylaxis Uptake Among Black/African American Men Who Have Sex With Other Men In Midwestern, United States: A Systematic Review, Oluwafemi Adeagbo, Oluwaseun Abdulganiyu Badru, Prince Addo, Amber Hawkins, Monique J. Brown Ph.D., Mph, Xiaoming Li, Rima Afifi

Faculty Publications

Introduction: Black/African American men who have sex with other men (BMSM) are disproportionately affected by HIV, experience significant disparities in HIV incidence, and face significant barriers to accessing HIV treatment and care services, including pre-exposure prophylaxis (PrEP). Despite evidence of individual and structural barriers to PrEP use in the Midwest, no review has synthesized this finding to have a holistic view of PrEP uptake and barriers. This review examines patterns of, barriers to, and facilitators of PrEP uptake among BMSM in the Midwest, United States (US).

Methods: Five databases (CINAHL Plus, PUBMED, PsycINFO, SCOPUS, and Web of Science) were searched …

Factors Driving Adolescent Tuberculosis Incidence By Age And Sex In 30 High-Tuberculosis Burden Countries: A Mathematical Modelling Study, Silvia S Chiang, Megan B Murray, Alexander W Kay, Peter J Dodd

Faculty, Staff and Students Publications

INTRODUCTION: During adolescence, tuberculosis incidence rises, with a greater increase in males compared with females. Tuberculosis notifications and estimates infrequently disaggregate adolescent age groups. Moreover, the factors that drive the increases in overall incidence and the male-to-female (MF) ratio remain unclear.

METHODS: We constructed a mechanistic model to estimate cumulative Mycobacterium tuberculosis infection and tuberculosis disease incidence in the WHO’s 30 high-tuberculosis burden countries (HBCs), which represent 86%–90% of global tuberculosis incidence. We derived infection risk from tuberculosis prevalence and assortative social mixing based on sex and age (10–14 years vs 15–19 years old). We adjusted age subgroup-specific risks of …

Heart Disease Prediction Using Ensemble Tree Algorithms: A Supervised Learning Perspective, Enoch Sakyi-Yeboah, Edmund F. Agyemang, Vincent Agbenyeavu, Akua Osei- Nkwantabisa, Priscilla Kissi-Appiah, Lateef Moshood, Lawrence Agbota, Ezekiel N.N. Nortey

School of Mathematical & Statistical Sciences Faculty Publications

Heart disease stands as a leading cause of morbidity and mortality globally, presenting a significant public health challenge. Therefore, early prediction and detection are critical, leading to timely and appropriate interventions at early stages. Four ensemble tree-based algorithms were used in this study: adaptive boosting, extreme gradient boosting, random forest, and extremely randomized trees, investigating their ability to predict heart disease. Data related to heart disease clinical features was obtained from the open Kaggle Machine Learning Dataset repository. Adaptive Boosting stands out as the highest performer, achieving an average testing accuracy of 93.70%, precision of 93.71%, recall of 93.70%, and …

A Bland–Altman Comparison Of The Lead Care® System And Inductively Coupled Plasma Mass Spectrometry For Detecting Low-Level Lead In Child Whole Blood Samples, Christina Sobin, Tanner Schaub, Natali Parisi, Eva De La Riva

Departmental Papers (PH)

Chronic childhood lead exposure, yielding blood lead levels consistently below 10 μg/dL, remains a major public health concern. Low neurotoxic effect thresholds have not yet been established. Progress requires accurate, efficient, and cost-effective methods for testing large numbers of children. The LeadCare® System (LCS) may provide one ready option. The comparability of this system to the “gold standard” method of inductively coupled plasma mass spectrometry (ICP-MS) for the purpose of detecting blood lead levels below 10 μg/dL has not yet been examined. Paired blood samples from 177 children ages 5.2–12.8 years were tested with LCS and ICP-MS. Triplicate repeat tests …

Joint Involvement In A Psoriasis Affected Population In A Medically Underrepresented Region, Blake C. Martin, Jared Hensley, Manoj Peiris

Research Symposium

Background: Psoriatic arthritis is an aggressive condition that may be characterized by compromised quality of life and significant morbidity. The prevalence of psoriatic arthritis in patients with psoriasis is around 1.7% at 5 years, 3.1% at 10 years, 5.1% at 20 years, and 20.5% at 30 years which shows an increase in joint involvement with increasing age, at least until the age of 30. The objective of this study was to explore joint involvement in psoriatic patients in this region and determine what are the demographic disparities in Psoriatic patients regarding joint involvement. We hypothesized that individuals with psoriasis between …

Gout Versus Pseudogout In The Medically Underserved Rio Grande Valley, Blake C. Martin, Fernando Cisneros, Kristina Vatcheva

Research Symposium

Background: Gout and pseudogout are inflammatory joint conditions, with gout being one of the most prevalent etiologies of chronic inflammatory arthritis in the United States. The patient population in the Rio Grande Valley (RGV) has a distinct demographic profile that warrants exploration of various health conditions. The primary objective of this study is to compare the frequencies of gout and pseudogout in the Rio Grande Valley to national frequencies and determine if there were demographic disparities between Gout and Pseudogout in this community. We hypothesized that the frequency gout and pseudogout would be higher in the RGV compared to the …

Bone And Joint Infections: A Retrospective Chart Review Of The Medically Underserved Rio Grande Valley, Blake C. Martin, Chloe Harris, Manoj Peiris

Research Symposium

Background: The Rio Grande Valley (RGV) is a demographically unique region that is impoverished and medically underserved. Because of its unique patient population, this community may be at increased risk for bone and joint infections and the morbidity and mortality that follows. The goal of this study was to analyze individuals with osteomyelitis, septic arthritis, and periprosthetic joint infections and determine which infectious bone or joint conditions are most prevalent in the Rio Grande Valley and determine if there were any demographic disparities between the various types of bone and joint infections and healthy individuals. We hypothesized that age and …

Addressing Health Disparities In Hematologic Malignancies: From Genes To Outreach, Christopher R Flowers, Rachel W Anantha, Veronica Leautaud, Pinkal Desai, Chancellor E Donald, Michelle A T Hildebrandt, Jean L Koff, Rulla M Tamimi, Wendy Cozen, Chijioke Nze, Ari M Melnick

Faculty, Staff and Student Publications

This review underscores our shared responsibility to champion multidimensional strategies rooted in basic and translational science, community involvement, and societal responsiveness for a meaningful impact. Unifying themes include the need to enhance collaborative infrastructure to engage laboratory researchers, epidemiologists, data scientists, clinicians, patients, community leaders, and policymakers; patient-level support services; outreach, education, and navigation for patients at the community level; recruitment and retention of underrepresented groups in the healthcare and research workforce; and funding for these efforts.

Learning Directed Acyclic Graphs For Ligands And Receptors Based On Spatially Resolved Transcriptomic Data Of Ovarian Cancer, Shrabanti Chowdhury, Sammy Ferri-Borgogno, Peng Yang, Wenyi Wang, Jie Peng, Samuel C Mok, Pei Wang

Faculty, Staff and Student Publications

To unravel the mechanism of immune activation and suppression within tumors, a critical step is to identify transcriptional signals governing cell-cell communication between tumor and immune/stromal cells in the tumor microenvironment. Central to this communication are interactions between secreted ligands and cell-surface receptors, creating a highly connected signaling network among cells. Recent advancements in in situ-omics profiling, particularly spatial transcriptomic (ST) technology, provide unique opportunities to directly characterize ligand-receptor signaling networks that power cell-cell communication. In this paper, we propose a novel statistical method, LRnetST, to characterize the ligand-receptor interaction networks between adjacent tumor and immune/stroma cells based on ST …

Emerging Technologies For Forensic Genetic Identification, Lilly Llanos

Senior Honors Theses

There are many new innovations in forensic science that are being developed for the identification of biological evidence. These techniques include next-generation DNA sequencing, DNA phenotyping, and forensic genetic genealogy. This thesis will explore each, as well as newer applications of proteomics. The methodologies, reliability, practicality of cost and training, moral implications, and past research of each will be discussed. Finally, some ideas for future research and steps to drive growth and greater understanding will be suggested. This will encourage further innovations and the increased acceptance of forensic evidence in court. Each method was found to have both advantages and …

A Novel Sensitivity Maximization At A Given Specificity Method For Binary Classifications, Seyyed Mahmood Ghasemi, Chunhui Gu, Johannes F Fahrmann, Samir Hanash, Kim-Anh Do, James P Long, Ehsan Irajizad

Faculty, Staff and Student Publications

In the cancer early detection field, logistic regression (LR) is a frequently used approach to establish a combination rule that differentiates cancer from noncancer. However, the application of LR relies on a maximum likelihood approach, which may not yield optimal combination rules for maximizing sensitivity at a clinically desirable specificity and vice versa. In this article, we have developed an improved regression framework, sensitivity maximization at a given specificity (SMAGS), for binary classification that finds the linear decision rule, yielding the maximum sensitivity for a given specificity or the maximum specificity for a given sensitivity. We additionally expand the framework …

Analysis Of Systematic Trade-Offs Between Military And Healthcare Expenditure Alongside Gdp Growth Of Select Asian And Western Exporting Economies In The 21st Century, Rahul Balamurugan, Carlos Gershenson, Preethi Nanjundan, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

This study explores the complexity in the trade-offs between military expenditure, healthcare expenditure, and GDP growth across select Asian nations and major weapon-exporting countries, examining how nations allocate finite resources between national security and human well-being over the past two decades. Using a systems science approach, the research integrates Granger causality testing to analyze temporal and directional relationships among GDP growth, military expenditure, and healthcare expenditure, uncovering their dynamic interdependencies. The methodology includes trend and slope analysis, Granger causality testing, outlier detection, and clustering to identify heterogeneity in resource allocation strategies. Developed, weapon-exporting nations exhibit complementary trends, with strong causality …

Children Suspected For Developmental Coordination Disorder In Hong Kong And Associated Health-Related Functioning: A Survey Study, Kathlynne F. Eguia, Sum Kwing Cheung, Kevin K.H. Chung, Catherine M. Capio

Health Sciences Faculty Publications

Children with developmental coordination disorder (DCD) have motor difficulties that interfere with their daily functions. The extent to which DCD affects children in Hong Kong has not been established. In this study, we aimed to estimate the prevalence of children suspected of DCD (sDCD) in Hong Kong and to examine the relationship between motor performance difficulties and health-related functioning. We conducted a cross-sectional survey of parents of children aged 5 to 12 years across Hong Kong (N = 656). The survey consisted of the Developmental Coordination Disorder Questionnaire (DCDQ) and short forms on global health, physical activity, positive affect, and …

The Present And Future Of Ai: Ethical Issues And Research Opportunities, Ankita Srivastava, Marco Marabelli, Danielle Blanch-Hartigan, Jeffrey Moriarty, Evan Carey

Philosophy Faculty Publications

Healthcare is currently a fast-changing industry with AI and generative AI (GenAI) playing a prominent role in the transformation of clinical as well as managerial practices. Clinical practices involve AI to diagnose diseases and develop new drugs and compounds, while managerial practices concern AI-supporting processes such as billing patients and insurance companies, handling electronic medical records, and supporting remote connections with patients, increasingly using virtual and augmented reality. Yet, all these opportunities offered by AI come with challenges involving potential ethical issues, such as discrimination, bias, lack of accessibility, and privacy issues. In March 2024, we organized a panel with …

Preserving Privacy In Senior Care At Home Monitoring Systems, Sam Russel, Ryan Benton, Amy Campbell, Scott Sittig

Shelby Hall Graduate Research Forum Posters

Many seniors prefer to live at home which necessitates research into the application of technologies to provide a safer environment with less caregiver resources. However, the application of home health care (HHC) monitoring for seniors is still in an evolutionary stage. Present HHC systems are produced by private companies with general regulatory guidelines lacking specific care of the elderly. As such, each company that produces such a system claims to have better safety, privacy, and security that their competitors. A pressing issues is devising and applying a general framework for the application of technologies that delivers safety while preserving privacy. …