Life Sciences Commons^™

Beyond Strong: A Phenomenology Of Women Executives And The Connection Between Leadership And Fitness, Nozomi Bullock

Antioch University Dissertations & Theses

Senior-level executive leaders’ work in a dynamic, competitive, 24/7 business environment can be physically rigorous, mentally demanding, and emotionally isolating. The same holds true for women pursuing senior-level leadership roles in corporate America. Women who achieve and succeed in such roles remain the minority: Outsiders in elite spaces who are held to higher standards and overly scrutinized. Among senior-level executive women leaders, those committed to a fitness and training regimen including weightlifting constitute an even smaller minority. Senior-level executive roles require stamina, resilience, and courage—qualities that make up the foundation of the mindset of fitness and strength training (Foyster et …

Pick Up A Frog, Or Pet A Dog; Animals Are Our First Teachers, Allison Ratner

Antioch University Dissertations & Theses

This dissertation’s goal was an attempt to answer the question: What are the emotional, cognitive, and/or spiritual effects of children’s relationships/interactions with animals that potentially impact their development? By utilizing autoethnography, I analyzed instances from my own life where interacting with animals changed me permanently; my thinking, my knowing, my feeling, my judgement, my empathy, my attitude, and my ethics. With a standpoint rooted in the research of experts from the fields of psychology and education, I combined my personal knowledge gained over a lifetime, to grant merit to the profundity of children’s relationships with animals. With the analyzed data, …

Becoming The Donkey Derby’S ‘Karen’: A Humane Educator’S Autoethnographic Journey Toward Anti-Speciesist Communication, Jesika Keener

Antioch University Dissertations & Theses

Language not only carries oppression as an educative force, but research indicates that language is inherently speciesist and highly pervasive (Ethical Globe, 2021; Guevara Labaca, 2017; Hamlett, 2024; Leach et al., 2023). However, the ontological commitment to speciesism is historically foundational, which makes the total eradication of speciesist communication only viable through an unemerged hypothetical future society (Kahn, 2011). For the possibilities of such a world to come into being, pivotal steps must first be taken to critically engage with the communicated forms of speciesism in order to better understand it and actively resist its reproduction—with the aspiration for this …

Resilience Of Food Sovereignty Organizations To The Covid-19 Pandemic, Rachel M. Brice

Antioch University Dissertations & Theses

This sequential explanatory mixed methods study explored the organizational resilience of food sovereignty organizations (FSOs) in the northeastern United States during the COVID-19 pandemic. Using a novel “open structural learning approach” that integrates structural contingency theory, open systems theory, and organizational learning theory, this research examined how FSOs’ structural attributes, resource flows, and organizational culture shaped their ability to navigate crisis. The study engaged FSO leaders through surveys (n = 13) and in-depth interviews (n = 7), supplemented by archival data analysis, to explore factors that strengthened or diminished FSO resilience. Findings revealed that FSOs navigated COVID-19 with multiple concurrent …

Fire History, Ecological History, And Historical Human-Environment Interactions In The Northern Great Plains, James Victor Benes

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation explores the spatiotemporal signatures of fire in North American grassland ecosystems. In three chapters, I explore different aspects of fire history in the northern Great Plains. Chapter 1 is an introduction. Chapter 2 focuses on the Euro-American Settlement Period (ca. 1850–1950 C.E.). Fire histories from six different lakes in the Nebraska Sandhills are compared with two periods of historic drought and the establishment of United States Post Offices. Five of the six records show increased levels of biomass burning during the initial phases of Euro-American Settlement. Chapter 3 is a long-term (ca. 15,000 years), high-resolution fire history and …

Food Finding Ability Does Not Predict Annual Survival In Winter Resident Birds, Aidan Hand

Honors Program: Senior Projects (Public)

Small non-migratory birds in temperate locations face many challenges to survive the winter. They must be able to find enough food, which is in decreased supply, to fuel the energetic demands of staying warm. Prior work has demonstrated that birds show individual variation in their foraging behaviors that could contribute to the discovery of new foraging patches, such as novel environment exploration. A better ability to discover new food sources could increase a bird’s chance of surviving the winter by increasing its access to new food patches. To test this hypothesis, we used radio frequency identification (RFID)-enabled bird feeders to …

Strolling The Lingnan Garden, 2022-2024 = 涓流彩園錄, 第二卷 : 下冊, Lingnan Gardeners, Centre For Cultural Research And Development, Lingnan University

Lingnan Gardeners Publications 嶺南彩園刊物

No abstract provided.

Building Patient-Facing Technology: A Redcap-Based Approach, Yuheng Shi, Eric Yang, Katie Gahn, Heidi Mason, Yun Jiang, Yang Gong

Faculty, Staff and Student Publications

This work describes the architecture design of a patient-facing technology (PFT) based on the Research Electronic Data Capture (REDCap) platform and other tools to support cancer patients in self-tracking and managing medication concerns and symptoms during transitions of care. The design is guided by the Chronic Care Model (CCM) and User-Centered Design (UCD) principles for a personalized application to inform, engage, and empower patients. We describe the evolutional details of four major versions, which represent milestones of our PFT, highlighting how specific objectives were achieved and the barriers encountered. Additionally, patient representatives were involved in the evaluation of prototypes, and …

Generalizable Self-Supervised Learning For Brain Cta In Acute Stroke, Yingjun Dong, Samiksha Pachade, Kirk Roberts, Xiaoqian Jiang, Sunil A Sheth, Luca Giancardo

Faculty, Staff and Student Publications

Acute stroke management involves rapid and accurate interpretation of CTA imaging data. However, generalizable models for multiple acute stroke tasks able to learn from unlabeled data do not exist. We propose a linear probed self-supervised contrastive learning utilizing 3D CTA images and the findings section of radiologists' reports for pretraining. Subsequently, the pretrained model was applied to four disparate tasks: large vessel occlusion (LVO) detection, acute ischemic stroke detection, acute ischemic stroke, intracerebral hemorrhage classification, and ischemic core volume prediction. The tasks chosen are particularly challenging as they cannot be directly extracted from the radiology reports findings with keywords. The …

Unraveling Complex Temporal Patterns In Ehrs Via Robust Irregular Tensor Factorization, Ren Yifei, Linghui Zeng, Jian Lou, Li Xiong, Joyce C Ho, Xiaoqian Jiang, Sivasubramanium V Bhavani

Faculty, Staff and Student Publications

Electronic health records (EHRs) contain diverse patient data with varying visit frequencies. While irregular tensor factorization techniques such as PARAFAC2 have been used for extracting meaningful medical concepts from EHRs, existing methods fail to capture non-linear and complex temporal patterns and struggle with missing entries. In this paper, we propose REPAR, an RNN REgularized Robust PARAFAC2 method to model complex temporal dependencies and enhance robustness in the presence of missing data. Our approach employs Recurrent Neural Networks (RNNs) for temporal regularization and a low-rank constraint for robustness, enabling precise patient subgroup identification and improved clinical decision-making in noisy EHR data. …

Pain Phenotyping Indicators In Older Adults With Chronic Low Back Pain: A Secondary Analysis Of A Randomized Controlled Trial, Katrina R Hamilton, Nada Lukkahatai, Wanqi Chen, Hulin Wu, Jennifer Kawi, Constance M Johnson, Paul J Christo, Claudia M Campbell

Faculty, Staff and Student Publications

Purpose: A multimodal approach to clinical care is often recommended for chronic low back pain (cLBP); however, treatment responses are highly variable. Phenotyping could help determine subgroups of patients, allowing for targeted and tailored interventional approaches.

Patients and methods: 263 (Mage=69.8 (7.2); 64.6% female) individuals with cLBP participated in the parent study, a 3-arm, randomized clinical trial examining auricular point acupressure treatment outcomes. Parent study participants were randomized (1:1:1) to APA ear points targeted to cLBP (T-APA, n=92), non-targeted to cLBP (NT-APA, n=91), or education control (n=89). The current study used latent class analysis to identify clustering for pain severity …

Explainable Diagnosis Prediction Through Neuro-Symbolic Integration, Qiuhao Lu, Rui Li, Elham Sagheb, Andrew Wen, Jinlian Wang, Liwei Wang, Jungwei W Fan, Hongfang Liu

Faculty, Staff and Student Publications

Diagnosis prediction is a critical task in healthcare, where timely and accurate identification of medical conditions can significantly impact patient outcomes. Traditional machine learning and deep learning models have achieved notable success in this domain but often lack interpretability which is a crucial requirement in clinical settings. In this study, we explore the use of neuro-symbolic methods, specifically Logical Neural Networks (LNNs), to develop explainable models for diagnosis prediction. Essentially, we design and implement LNN-based models that integrate domain-specific knowledge through logical rules with learnable weights and thresholds. Our models, particularly Mmulti-pathway and Mcomprehensive, demonstrate superior performance over traditional models …

Reusable Generic Clinical Decision Support System Module For Immunization Recommendations In Resource-Constraint Settings, Samuil Orlioglu, Akash Shanmugan Boobalan, Kojo Abanyie, Richard D Boyce, Hua Min, Yang Gong, Dean F Sittig, Paul Biondich, Adam Wright, Christian Nøhr, Timothy Law, David Robinson, Arild Faxvaag, Nina Hubig, Ronald Gimbel, Lior Rennert, Xia Jing

Faculty, Staff and Student Publications

Clinical decision support systems (CDSS) are routinely employed in clinical settings to improve quality of care, ensure patient safety, and deliver consistent medical care. However, rule-based CDSS, currently available, do not feature reusable rules. In this study, we present CDSS with reusable rules. Our solution includes a common CDSS module, electronic medical record (EMR) specific adapters, CDSS rules written in the clinical quality language (CQL) (derived from CDC immunization recommendations), and patient records in fast healthcare interoperability resources (FHIR) format. The proposed CDSS is entirely browser-based and reachable within the user's EMR interface at the client-side. This helps to avoid …

Session Introduction: Translating Big Data Imaging Genomics Findings To The Individual: Prediction Of Risks And Outcomes In Neuropsychiatric Illnesses, Peter Kochunov, Li Shen, Zhongming Zhao, Paul M Thompson

Faculty, Staff and Student Publications

This PSB 2025 session is focused on opportunities, challenges and solutions for translating Big Data Imaging Genomic findings toward powering decision making in personalized medicine and guiding individual clinical decisions. It combines many of the scientific directions that are of interest to PSB members including Big Data analyses, pattern recognition, machine learning and AI, electronic health records and others.

Leveraging Gpt-4o For Automated Extraction Of Neural Projections From Scientific Literature, Rashmie Abeysinghe, Gorbachev Jowah, Licong Cui, Samden D Lhatoo, Guo-Qiang Zhang

Faculty, Staff and Student Publications

Sudden Unexpected Death in Epilepsy (SUDEP) is a major cause of death for epilepsy patients having uncontrolled seizures. Understanding the complex neural circuits within the central nervous system is crucial for understanding the mechanisms underlying cardiorespiratory regulation, particularly in the context of SUDEP. This study explores the potential of GPT-4o, a cutting-edge language model, to automate the extraction of neural projections from scientific literature. We developed prompts to extract neuroscientific structures, extract projections, and perform synonym harmonization. Applying the approach to four neuroscientific articles, the method extracted 205 projections. A random sample of 100 projections identified was handed over to …

Gene Expression Changes In Human Cerebral Arteries Following Hemoglobin Exposure: Implications For Vascular Responses In Sah, Chathathayil M Shafeeque, Arif O Harmanci, Sithara Thomas, Ari C Dienel, Devin W Mcbride, Kumar T Peeyush, Spiros L Blackburn

Faculty, Staff and Student Publications

Subarachnoid hemorrhage (SAH), characterized by the presence of hemoglobin (Hb) in the subarachnoid space, significantly impacts cerebral vessels, leading to various pathological outcomes. The toxicity of cell-free Hb released from erythrocytes and its metabolites after SAH causes vasoconstriction and neuronal damage, and correlates with delayed ischemic neurological deficits (DIND). While animal models have provided substantial and invaluable data in the research of aneurysmal SAH, the specific effects of subarachnoid blood on cerebral arteries remain greatly understudied. Here, we describe the changes in the genetic profile of human cerebral arteries exposed to free Hb for 48 h. We performed an ex …

A Bayesian Deep Segmentation Framework For Glioblastoma Tumor Segmentation Using Follow-Up Mris, Tanjida Kabir, Kang-Lin Hsieh, Luis Nunez, Yu-Chun Hsu, Juan C Rodriguez Quintero, Octavio Arevalo, Kangyi Zhao, Jay-Jiguang Zhu, Roy F Riascos, Mahboubeh Madadi, Xiaoqian Jiang, Shayan Shams

Faculty, Staff and Student Publications

Background: Glioblastoma (GBM) is the most common malignant brain tumor with an abysmal prognosis. Since complete tumor cell removal is impossible due to the infiltrative nature of GBM, accurate measurement is paramount for GBM assessment. Preoperative magnetic resonance images (MRIs) are crucial for initial diagnosis and surgical planning, while follow-up MRIs are vital for evaluating treatment response. The structural changes in the brain caused by surgical and therapeutic measures create significant differences between preoperative and follow-up MRIs. In clinical research, advanced deep learning models trained on preoperative MRIs are often applied to assess follow-up scans, but their effectiveness in this …

Examining Educational And Career Transition Points Among A Diverse, Virtual Mentoring Network, Erika L Thompson, Toufeeq Ahmed Syed, Zainab Latif, Katie Stinson, Damaris Javier, Gabrielle Saleh, Jamboor K Vishwanatha

Faculty, Staff and Student Publications

Given the differences in trajectory for under-represented minorities in biomedical careers, we sought to explore how a virtual mentoring program, the National Research Mentoring Network (NRMN), and its platform (MyNRMN), may facilitate transitions in the science, technology, engineering, mathematics, and medicine (STEMM) pipeline. The purpose of this study was to describe how the size of an MyNRMN member’s mentoring network and level of engagement correlate with academic and career transitions. We examined MyNRMN platform user data from March 2020 to May 2021 (n = 2993). Logistic regression estimated the odds of a career or academic transition related to NRMN …

Intelligent Biology And Medicine: Accelerating Innovative Computational Approaches, Fuhai Li, Li Liu, Kai Wang, Xiaoming Liu, Zhongming Zhao

Faculty, Staff and Student Publications

In this editorial, we summarize the 2023 International Conference on Intelligent Biology and Medicine (ICIBM 2023) conference which was held on July 16-19, 2023 in Tampa, Florida, USA. We then briefly describe the nine research articles included in this special issue. ICIBM 2023 scientific program included four tutorials and workshops, four keynote lectures, four eminent scholars' presentations, 11 concurrent scientific sessions, and a poster session. We had total of 88 scientific oral presentations, including 62 regular oral presentations and 26 flash talks, as well as 46 poster presentations. The topics of these presentations covered artificial intelligence (AI), data sciences, bioinformatics, …

Scientific Writing: A Guide From Data To Draft, Kristin M. Klucevsek

Open Education Materials

Textbook for ENGL302W (Scientific Writing)

CC BY-NC-SA (2025)

Rank Aggregation Methods And Tools In Genomic Data Analysis, Wenping Zou, Savannah Mwesigwa, Sayed-Rzgar Hosseini, Zhongming Zhao

Faculty, Staff and Student Publications

Rank aggregation (RA) is the process of consolidating disparate rankings into a single unified ranking. It holds immense potential in the field of genomics. RA has applications in diverse research areas, such as gene expression analysis, meta-analysis, gene prioritization, and biomarker discovery. However, there are many challenges in the application of the RA approach to biological data, such as dealing with heterogeneous data sources, rankings of mixed quality, and evaluating the consolidated rankings. In this review, we present an overview of the existing RA methods with an emphasis on those that have been tailored to the complexities of genomics research. …

Deep5mc: Predicting 5-Methylcytosine (5mc) Methylation Status Using A Deep Learning Transformer Approach, Evan Kinnear, Houssemeddine Derbel, Zhongming Zhao, Qian Liu

Faculty, Staff and Student Publications

DNA methylations, such as 5-methylcytosine (5mC), are crucial in biological processes, and aberrant methylations are strongly linked to various human diseases. Genomic 5mC is not randomly distributed but exhibits a strong association with genomic sequences. Thus, various computational methods were developed to predict 5mC status based on DNA sequences. These methods generated promising achievements and overcome the limitations of experimental approaches. However, few studies have comprehensively investigated the dependency of 5mC on genomic sequences, and most existing methods focus on specific genomic regions. In this work, we introduce Deep5mC, a deep learning transformer-based method designed to predict 5mC methylations. Deep5mC …

Enhancing The Utility Of Polygenic Scores In Alzheimer’S Disease Through Systematic Curation And Annotation, Savannah Mwesigwa, Yulin Dai, Nitesh Enduru, Zhongming Zhao

Faculty, Staff and Student Publications

Introduction: Polygenic Scores (PGSs) assess cumulative genetic risk variants that contribute to the association with complex diseases like Alzheimer's Disease (AD). The PGS Catalog is a valuable repository of PGSs of various complex diseases, but it lacks standardized annotations and harmonization, making the information difficult to integrate for a specific disease.

Methods: In this study, we curated 44 PGS datasets for AD from the PGS Catalog, categorized them into five methodological groups, and annotated 813,257 variants to nearby genes. We aligned the scores based on the "GWAS significant variants" (GWAS-SV) method with the GWAS Catalog and flagged redundant files and …

Investigating The Impact Of Social Determinants Of Health On Diagnostic Delays And Access To Antifibrotic Treatment In Idiopathic Pulmonary Fibrosis, Rui Li, Qiuhao Lu, Andrew Wen, Jinlian Wang, Sunyang Fu, Xiaoyang Ruan, Liwei Wang, Hongfang Liu

Faculty, Staff and Student Publications

Idiopathic pulmonary fibrosis (IPF) is a rare disease that is challenging to diagnose. Patients with IPF often spend years awaiting a diagnosis after the onset of initial respiratory symptoms, and only a small percentage receive antifibrotic treatment. In this study, we examine the associations between social determinants of health (SDoH) and two critical factors: time to IPF diagnosis following the onset of initial respiratory symptoms, and whether the patient receives antifibrotic treatment. To approximate individual SDoH characteristics, we extract demographic-specific averages from zip code-level data using the American Community Survey (via the U.S. Census Bureau API). Two classification models are …

Epidemiology Of Patient Record Duplication, Onur Sahin, Audrey Zhao, Reuben Joseph Applegate, Todd R Johnson, Elmer V Bernstam

Faculty, Staff and Student Publications

Objectives: Duplicate patient records can increase costs and medical errors. We assessed the association between demographic factors, comorbidities, health care usage, and duplicate electronic health records.

Methods: We analyzed the association between duplicate patient records and multiple demographic variables (race, Hispanic ethnicity, sex, and age) as well as the Charlson Comorbidity Index (CCI), number of diagnoses, and number of health care encounters. The study population included 3,018,413 patients seen at a large urban academic medical center with at least one recorded diagnosis. Duplication of patient medical records was determined by using a previously validated enterprise Master Person Index.

Results: Unknown …

Parallel Inquiries: Investigation Of Social Resource Use In Early Career Stem Teachers And Impacts Of Metal Pollution On Fingernail Clam Microbiome, Emily Hamada

EWU Masters Thesis Collection

No abstract provided.

The Effects Of Salinity On The Cutaneous Microbiome And Pathogen Infection On The Pacific Tree Frog (Pseudacris Regilla) In Monterey Bay, California, Usa, Hannah Eunhae Kim

EWU Masters Thesis Collection

Global climate change and infectious diseases are considered a leading cause of amphibian population declines worldwide. Changes in precipitation and salinity have altered watershed systems and microbial communities, reducing habitat availability and physiological performances for amphibian survival. The salt refuge hypothesis, however, is a proposed explanation that higher saline environments may reduce susceptibility to pathogens such as Batrachochytrium dendrobatidis (Bd). The Moro Cojo Slough State Marine Reserve (MCSSMR) (California, USA) is known as an abundant breeding ground for endangered/threatened amphibian species. To test and expand the salt refuge hypothesis, I evaluated Bd prevalence and intensity and the cutaneous microbiome of …

Bridging Prairie Restoration And Regenerative Agriculture With Compost Tea / The Rocket Incident: Post-Fire Soil Microbe Recovery On The Eastern Washington University Restoration Site, April Hersey

EWU Masters Thesis Collection

Inland Pacific Northwest prairie is an endangered ecosystem that has been reduced by conversion to agriculture. There is growing interest in the role of soil microorganisms in prairie ecosystems, which may be crucial for restoration of the plant community through interspecies interactions within the rhizosphere. One method for improving soil microorganism community composition is compost tea: enriched liquid compost extract. Compost tea is used in regenerative agriculture to improve crop yields and protect against pathogens. While research has supported compost tea application in regenerative agriculture, it has not been widely studied in the context of ecosystem restoration. After beginning a …

Shrubsteppe Birds Under Fire: Guiding Post-Wildfire Habitat Restoration In The Whiskey Dick And Quilomene Units, Washington, Kevin Clements

All Master's Theses

Bird species, globally, are declining at an alarming rate. Birds of the shrubsteppe are particularly vulnerable to habitat loss caused by agricultural development, invasive vegetation, and heightened wildfire frequency and severity. Fire and invasive vegetation create a positive feedback cycle that threatens complete conversion of shrubsteppe to grasslands. Restoring habitat following wildfire is a top priority for land managers. As bioindicators of ecosystem health, bird populations reflect landscape changes and restoration efficacy. I analyzed bird populations in the Whiskey Dick and Quilomene units of the L.T. Murray Wildlife Area in Kittitas County, Washington following the 2022 Vantage Highway fire. Using …

More Than One Way To Be A Planktivore: The Vast Morphospace Of Plankton-Feeding Reef Fishes, Isabelle Ng, David R. Bellwood, Jan M. Strugnell, Sergio R. Floeter, Alexandre C. Siqueira

Research outputs 2022 to 2026

Planktivorous reef fishes are thought to possess unique morphological traits to feed on small, evasive prey. Despite the multitude of family-level studies addressing this hypothesis, results remain inconclusive. Our goal, therefore, was to determine whether specialised traits and patterns of morphological convergence are congruent across a comprehensive phylogeny of reef-associated fishes. We measured 15 morphological traits from 815 images of 299 species in 12 globally distributed families. Using phylogenetic comparative methods, we mapped the evolution of plankton-feeding across lineages; assessed the effect of planktivory on body shape; and tested for the presence of morphological convergence among planktivores. We demonstrate that …