Digital Commons Network^™

Alpha-Synuclein Seed Amplification Assays: Data Sharing, Standardization Needed For Clinical Use, Hilal A Lashuel, D James Surmeier, Tanya Simuni, Kalpana Merchant, Byron Caughey, Claudio Soto, Mohamed-Bilal Fares, Roland G Heym, Ronald Melki

Faculty, Staff and Student Publications

Alpha-synuclein seed amplification assays can improve neurodegenerative disease diagnosis and care, but widespread use depends on a framework that standardizes protocols and encourages data sharing.

Normalized And Directional Interplay Scoring For The Interrogation Of Proteoform Data, Karl F Poncha, Alyssa T Paparella, Nicolas L Young

Faculty, Staff and Students Publications

Histone proteoforms, often presenting multiple co-occurring post-translational modifications (PTMs), are central to chromatin regulation and gene expression. A proteoform is a specific form of a protein that includes variations arising from genetic changes, alternative RNA splicing, proteolytic processing, and PTMs. Genome-indexed histone proteoforms define the histone code, influencing cellular phenotype by dictating DNA interacting partners. Understanding the dynamics of histone proteoforms is essential for elucidating chromatin-based regulatory mechanisms. Advances in middle-down and top-down proteomics enable accurate identification and quantitation of thousands of proteoforms in a single run. However, the resulting data complexity presents significant challenges for analysis and visualization. Here, …

De Novo Variants In Cdkl1 And Cdkl2 Are Associated With Neurodevelopmental Symptoms, Ali H Bereshneh, Jonathan C Andrews, Daniel F Eberl, Guney Bademci, Nicholas A Borja, Stephanie Bivona, Wendy K Chung, Shinya Yamamoto, Michael F Wangler, Shane Mckee, Mustafa Tekin, Hugo J Bellen, Oguz Kanca

Duncan NRI Faculty and Staff Publications

The CDKL (cyclin-dependent kinase-like) family consists of five members in humans, CDKL1-5, that encode serine-threonine kinases. The only member that has been associated with a Mendelian disorder is CDKL5, and variants in CDKL5 cause developmental and epileptic encephalopathy type 2 (DEE2). Here, we study four de novo variants in CDKL2 identified in five individuals, including three unrelated probands and monozygotic twins. These individuals present with overlapping symptoms, including global developmental delay, intellectual disability, childhood-onset epilepsy, dyspraxia, and speech deficits. We also identified two individuals with de novo missense variants in CDKL1 in the published Deciphering Developmental Disorders (DDD) and GeneDx …

Widespread Variation In Molecular Interactions And Regulatory Properties Among Transcription Factor Isoforms, Luke Lambourne, Kaia Mattioli, Clarissa Santoso, Gloria Sheynkman, Sachi Inukai, Babita Kaundal, Anna Berenson, Kerstin Spirohn-Fitzgerald, Anukana Bhattacharjee, Elisabeth Rothman, Shaleen Shrestha, Florent Laval, Brent S Carroll, Stephen P Plassmeyer, Ryan J Emenecker, Zhipeng Yang, Deepa Bisht, Jared A Sewell, Guangyuan Li, Anisa Prasad, Sabrina Phanor, Ryan Lane, Devlin C Moyer, Toby Hunt, Dawit Balcha, Marinella Gebbia, Jean-Claude Twizere, Tong Hao, Alex S Holehouse, Adam Frankish, Josh A Riback, Nathan Salomonis, Michael A Calderwood, David E Hill, Nidhi Sahni, Marc Vidal, Martha L Bulyk, Juan I Fuxman Bass

Faculty, Staff and Students Publications

Most human transcription factor (TF) genes encode multiple protein isoforms differing in DNA-binding domains, effector domains, or other protein regions. The global extent to which this results in functional differences between isoforms remains unknown. Here, we systematically compared 693 isoforms of 246 TF genes, assessing DNA binding, protein binding, transcriptional activation, subcellular localization, and condensate formation. Relative to reference isoforms, two-thirds of alternative TF isoforms exhibit differences in one or more molecular activities, which often could not be predicted from sequence. We observed two primary categories of alternative TF isoforms: "rewirers" and "negative regulators," both of which were associated with …

Hif Regulates Multiple Translated Endogenous Retroviruses: Implications For Cancer Immunotherapy, Qinqin Jiang, David A Braun, Karl R Clauser, Vijyendra Ramesh, Nitin H Shirole, Joseph E Duke-Cohan, Nancy Nabilsi, Nicholas J Kramer, Cleo Forman, Isabelle E Lippincott, Susan Klaeger, Kshiti M Phulphagar, Vipheaviny Chea, Nawoo Kim, Allison P Vanasse, Eddy Saad, Teagan Parsons, Melissa Carr-Reynolds, Isabel Carulli, Katarina Pinjusic, Yijia Jiang, Rong Li, Sudeepa Syamala, Suzanna Rachimi, Eva K Verzani, Jonathan D Stevens, William J Lane, Sabrina Y Camp, Kevin Meli, Melissa B Pappalardi, Zachary T Herbert, Xintao Qiu, Paloma Cejas, Henry W Long, Sachet A Shukla, Eliezer M Van Allen, Toni K Choueiri, L Stirling Churchman, Jennifer G Abelin, Cagan Gurer, Gavin Macbeath, Richard W Childs, Steven A Carr, Derin B Keskin, Catherine J Wu, William G Kaelin

Faculty, Staff and Student Publications

Clear cell renal cell carcinoma (ccRCC), despite having a low mutational burden, is considered immunogenic because it occasionally undergoes spontaneous regressions and often responds to immunotherapies. The signature lesion in ccRCC is inactivation of the VHL tumor suppressor gene and consequent upregulation of the HIF transcription factor. An earlier case report described a ccRCC patient who was cured by an allogeneic stem cell transplant and later found to have donor-derived T cells that recognized a ccRCC-specific peptide encoded by a HIF-responsive endogenous retrovirus (ERV), ERVE-4. We report that ERVE-4 is one of many ERVs that are induced by HIF, translated …

Biochemical Profiling And Structural Basis Of Adar1-Mediated Rna Editing, Xiangyu Deng, Lina Sun, Min Zhang, Rashmi Basavaraj, Jin Wang, Yi-Lan Weng, Yang Gao

Faculty, Staff and Students Publications

ADAR1 regulates RNA-induced immune responses by converting adenosine to inosine in double-stranded RNA. Mutations in ADAR1 are associated with human autoimmune disease, and targeting ADAR1 has been proposed for cancer immunotherapy. However, the molecular mechanisms underlying ADAR1-mediated editing remain unclear. Here, we provide detailed biochemical and structural characterizations of human ADAR1. Our biochemical profiling reveals that ADAR1 editing is both sequence and RNA-duplex-length dependent but can well tolerate mismatches near the editing site. High-resolution ADAR1-RNA complex structures, combined with mutagenesis, elucidate RNA binding, substrate selection, dimerization, and the essential role of RNA-binding domain 3. The ADAR1 structures also help explain …

Breaking The Synaptic Vesicle Cycle: Mechanistic Insights Into Presynaptic Dysfunctions In Epilepsy, Kevin Jiang, Lu-Tang Yang, Mingshan Xue

Duncan NRI Faculty and Staff Publications

Synaptic dysfunction is a hallmark of many neurological disorders including epilepsy. An increasing number of epilepsy-causing pathogenic variants are being identified in genes encoding presynaptic proteins that affect every step of the synaptic vesicle cycle, from vesicle loading, tethering, docking, priming, calcium sensing, fusing, to recycling. These different molecular dysfunctions result in converging impairment of presynaptic neurotransmitter release, yet lead to diverse epileptic disorders. This review focuses on representative monogenic epileptic disorders caused by pathogenic variants of key presynaptic proteins involved in different stages of the synaptic vesicle cycle: SYN1 (vesicle pool regulation), STXBP1 (vesicle docking, priming, and fusion), and …

A Mapping Review And Critique Of The Literature On Translation, Dissemination, And Implementation Capacity Building Initiatives For Different Audiences, Sara Malone, Kathleen R Stevens, Maria E Fernandez, Sunil Kripalani

Faculty, Staff and Student Publications

Background: Capacity building is critical for research and practice as the fields of dissemination, implementation and translation science continue to grow. Some scholars state that capacity building should be grounded in competencies. However, the fields are unclear in determining which competencies are relevant for whom, including the content and appropriate level of information and skills for different roles. The goal of this study was to catalogue competencies across current D&I capacity building initiatives.

Methods: We conducted a mapping review to examine to what extent are theories or frameworks used to guide capacity building, who is being trained, to what extent …

Long-Term Patient-Reported Bowel And Urinary Quality Of Life In Patients Treated With Intensity-Modulated Radiotherapy Versus Intensity-Modulated Proton Therapy For Localized Prostate Cancer, Kimberly R Gergelis, Miao Bai, Jiasen Ma, David M Routman, Bradley J Stish, Brian J Davis, Thomas M Pisansky, Thomas J Whitaker, Richard Choo

Faculty, Staff and Student Publications

Purpose: This study aimed to compare long-term patient-reported outcomes in bowel and urinary domains between intensity-modulated radiotherapy (IMRT) and intensity-modulated proton therapy (IMPT) for localized prostate cancer.

Methods and materials: Patients with clinical T1-T2 prostate cancer receiving IMRT or IMPT at a tertiary cancer center from 2015-2018 were analyzed to determine the changes in the prospectively collected bowel function (BF), urinary irritative/obstructive symptoms (UO), and urinary incontinence (UI) domains of EPIC-26. The mean changes in EPIC-26 scores were evaluated from pretreatment to 24 months post-radiotherapy for each modality. A score change >50% of the baseline standard deviation was considered a …

Chronic Viral Mimicry Induction Following P53 Loss Promotes Immune Evasion, Charles A Ishak, Sajid A Marhon, Naïri Tchrakian, Anjelica Hodgson, Helen Loo Yau, Isabela M Gonzaga, Melanie Peralta, Ilinca M Lungu, Stephanie Gomez, Sheng-Ben Liang, Shu Yi Shen, Raymond Chen, Jocelyn Chen, Biji Chatterjee, Kevin N Wanniarachchi, Junwoo Lee, Nicholas Zehrbach, Amir Hosseini, Parinaz Mehdipour, Siyu Sun, Alexander Solovyov, Ilias Ettayebi, Kyle E Francis, Aobo He, Taiyi Wu, Shengrui Feng, Tiago Da Silva Medina, Felipe Campos De Almeida, Jane Bayani, Jason Li, Spencer Macdonald, Yadong Wang, Sarah S Garcia, Elisa Arthofer, Noor Diab, Aneil Srivastava, Paul Tran Austin, Peter J B Sabatini, Benjamin D Greenbaum, Catherine A O'Brien, Trevor G Shepherd, Ming Sound Tsao, Katherine B Chiappinelli, Amit M Oza, Blaise A Clarke, Robert Rottapel, Stephanie Lheureux, Daniel D De Carvalho

Faculty, Staff and Student Publications

Epigenetic therapies facilitate transcription of immunogenic repetitive elements that cull cancer cells through ‘viral mimicry’ responses. Paradoxically, cancer-initiating events also facilitate transcription of repetitive elements. Contributions of repetitive element transcription towards cancer initiation, and the mechanisms by which cancer cells evade lethal viral mimicry responses during tumor initiation remain poorly understood. In this report, we characterize premalignant lesions of the fallopian tube along with syngeneic epithelial ovarian cancer models to explore the earliest events of tumorigenesis following loss of the p53 tumor suppressor protein. We report that p53 loss permits transcription of immunogenic repetitive elements and chronic viral mimicry activation …

General Characteristics Of Patients With Primary Biliary Cholangitis From Türkiye And Denmark, Cumali Efe, Ersin Batıbay, Tugrul Purnak

Faculty, Staff and Student Publications

No abstract provided.

Epidemiologic Investigation Of Protozoa And Soil-Transmitted Helminths In Starr County, Texas, Lauren M Leining, Timothy A Erickson, Craig L Hanis, Cici Bauer, Maya D Murry, Eric L Brown, Rojelio Mejia, Sarah M Gunter

Faculty, Staff and Students Publications

The burden of pathogenic enteric protozoa and soil-transmitted helminths among impoverished populations living on the Texas-Mexico border is unclear. We conducted a cross-sectional study on an ongoing longitudinal cohort of 616 adults residing in Starr County, Texas. A total of 359 adults were screened for four protozoa and five soil-transmitted helminths by using real-time polymerase chain reaction. This analysis identified 48 (13.4%) participants who tested positive for Blastocystis sp., three (0.8%) who tested positive for Giardia intestinalis, and one (0.3%) who tested positive for Strongyloides stercoralis and was also coinfected with Blastocystis sp. Infection was significantly associated with age, a …

Bone-Induced Her2 Promotes Secondary Metastasis In Hr+/Her2- Breast Cancer, Rahat Alam, Anna Reva, David G Edwards, Bree M Lege, Laura S Munoz-Arcos, Carolina Reduzzi, Swarnima Singh, Xiaoxin Hao, Yi-Hsuan Wu, Zeru Tian, Laura M Natalee, Gargi Damle, Deniz Demircioglu, Yixian Wang, Ling Wu, Elisabetta Molteni, Dan Hasson, Bora Lim, Zbigniew Gugala, Jerry E Chipuk, Julie E Lang, Joseph A Sparano, Chonghui Cheng, Massimo Cristofanilli, Han Xiao, Xiang H-F Zhang, Igor L Bado

Faculty, Staff and Students Publications

Bone metastases can disseminate to secondary sites and promote breast cancer progression creating additional clinical challenges. The mechanisms contributing to secondary metastasis are barely understood. Here, we evaluate the prediction power of Her2-expressing (Her2E) circulating tumor cells (CTCs) after analyzing over 13,000 CTCs from a cohort of 137 metastatic breast cancer (MBC) patients with initial HR+/Her2− status and employ preclinical models of bone metastasis (BM) to validate the role of Her2E CTCs in multi-organ metastases. While Her2 expression was higher in patients with bone metastasis, experimental analyses revealed that Her2E CTCs derived from bone lesions were more dependent on Her2 …

Zp4: A Novel Target For Car-T Cell Therapy In Triple Negative Breast Cancer, Lauren K Somes, Jonathan T Lei, Xinpei Yi, Diego F Chamorro, Paul Shafer, Ahmed Z Gad, Lacey E Dobrolecki, Emily Madaras, Nabil Ahmed, Michael T Lewis, Bing Zhang, Valentina Hoyos

Faculty, Staff and Students Publications

Triple-negative breast cancer (TNBC) remains one of the most challenging subtypes of breast cancer to treat due to a lack of effective targeted therapies. Chimeric antigen receptor (CAR)-T cells hold promise, but their efficacy in solid tumors is often limited by on-target/off-tumor toxicities. Through comprehensive bioinformatic analysis of public RNA and proteomic data, we identified zona pellucida glycoprotein 4 (ZP4) as a novel target for TNBC. ZP4 RNA and protein were detected in a subset of TNBC patient samples and patient-derived xenograft (PDX) models, with expression otherwise restricted to oocytes. We generated 89 ZP4-specific novel monoclonal antibodies and used the …

Improving The Oral Pathology Referral Process In An Academic Dental Institution, Gregory Olson

Translational Projects (Open Access)

Introduction: Inefficiencies in the oral cancer referral process pose serious risks, including delayed diagnoses and poor patient outcomes. This project aimed to improve the reliability and efficiency of referrals between dental students and oral pathology residents for patients with suspected oral cancer. Although early detection is widely acknowledged as critical, significant process breakdowns were identified, including the absence of a standardized workflow, inconsistent follow-up practices, and a lack of accountability and tracking mechanisms. As a result, approximately half of the patients recommended for biopsy did not undergo the procedure, leading to delayed diagnoses and potentially worse prognoses.

Methodology: …

An Examination Of Ambulatory Care Code Specificity Utilization In Icd-10-Cm Compared To Icd-9-Cm: Implications For Icd-11 Implementation, Susan H Fenton, Cassandra Ciminello, Vickie M Mays, Mary H Stanfill, Valerie Watzlaf

Faculty, Staff and Student Publications

Objective: The ICD-10-CM classification system contains more specificity than its predecessor ICD-9-CM. A stated reason for transitioning to ICD-10-CM was to increase the availability of detailed data. This study aims to determine whether the increased specificity contained in ICD-10-CM is utilized in the ambulatory care setting and inform an evidence-based approach to evaluate ICD-11 content for implementation planning in the United States.

Materials and methods: Diagnosis codes and text descriptions were extracted from a 25% random sample of the IQVIA Ambulatory EMR-US database for 2014 (ICD-9-CM, n = 14 327 155) and 2019 (ICD-10-CM, n = 13 062 900). Code …

Adoptively Transferred Tumor-Specific Il-9-Producing Cytotoxic Cd8+ T Cells Activate Host Cd4+ T Cells To Control Tumors With Antigen Loss, Liuling Xiao, Rui Duan, Wendao Liu, Chuanchao Zhang, Xingzhe Ma, Miao Xian, Qiang Wang, Qi Guo, Wei Xiong, Pan Su, Lingqun Ye, Yabo Li, Ling Zhong, Jianfei Qian, Yong Lu, Zhongming Zhao, Qing Yi

Faculty, Staff and Student Publications

Host effector CD4+ T cells emerge as critical mediators for tumor regression but whether they can be activated by adoptively transferred CD8+ T cells remains unknown. We previously reported that adoptive transfer of interleukin 9 (IL-9)-producing cytotoxic CD8+ T (Tc9) cells achieved long-term control of tumor growth. Here, we demonstrate that murine tumor-specific Tc9 cells control the outgrowth of antigen-loss relapsed tumors by recruiting and activating host effector CD4+ T cells. Tc9 cells secreted IL-24 and recruited CCR7-expressing conventional type 2 dendritic cells (cDC2 cells) into tumor-draining lymph nodes to prime host CD4+ T cells against relapsed tumors. Host CD4+ …

Llm-Ie: A Python Package For Biomedical Generative Information Extraction With Large Language Models, Enshuo Hsu, Kirk Roberts

Faculty, Staff and Student Publications

Objectives: Despite the recent adoption of large language models (LLMs) for biomedical information extraction (IE), challenges in prompt engineering and algorithms persist, with no dedicated software available. To address this, we developed LLM-IE: a Python package for building complete IE pipelines.

Materials and methods: The LLM-IE supports named entity recognition, entity attribute extraction, and relation extraction tasks. We benchmarked it on the i2b2 clinical datasets.

Results: The sentence-based prompting algorithm resulted in the best 8-shot performance of over 70% strict F1 for entity extraction and about 60% F1 for entity attribute extraction.

Discussion: We developed a Python package, LLM-IE, …

Leveraging Observational And Rct Data For Understanding Interventions’ Efficacy: Applications In Progressive And Acute Neurological Diseases, Yaobin Ling

Dissertations and Theses (Open Access)

The advancement of drug repurposing for progressive and acute neurological diseases is hampered by the limitations of randomized clinical trials (RCTs) and observational data. This dissertation presents a comprehensive framework to integrate data-driven insights from multiple sources, including observational studies, RCTs, and synthetic data generation, to overcome these challenges.

The first study focuses on estimating treatment effects on the population level, which investigates the effects of routine and high-dose influenza vaccines on the risk of Alzheimer’s Disease and Related Dementias (ADRD) through a trial emulation framework applied to health claims data, addressing biases inherent in observational studies. The second study …

The Structural Inequality Of Status Quo Clinical Communication, Joelle Robertson-Preidler

Faculty and Staff Publications

No abstract provided.

Standardizing Social Determinants Of Health Factors From Heterogeneous Sources To Improve Data Fairness, Yifang Dang

Dissertations and Theses (Open Access)

Social Determinants of Health (SDoH) significantly influence health outcomes, yet their representation in computational models remains fragmented. This dissertation addresses this gap by constructing an SDoH ontology (SDoHO), leveraging it to improve large language model (LLM) performance, and using LLMs to extract new knowledge and enrich the ontology. The overarching goal is to establish a feedback loop where ontology development enhances LLM-based extraction, and LLM-derived insights refine and expand the ontology. The methodology is structured across three aims: (1) ontology construction, (2) ontology-assisted LLM enhancement, and (3) LLM-driven ontology enrichment, with a focus on Alzheimer’s Disease and Related Dementias (ADRD). …

Computer-Aided Integrated Rehabilitation For Post-Stroke Patients Using Deep Learning Techniques, Kaichen Tang

Dissertations and Theses (Open Access)

Stroke is a leading cause of long-term disability, often requiring intensive rehabilitation and frequent clinical assessments such as the Fugl-Meyer Assessment. However, traditional in-person evaluations are resource-heavy and difficult to scale, limiting access for many patients. Additionally, monitoring vital signs like blood pressure and oxygen saturation typically depends on specialized equipment, leading to fragmented care and incomplete recovery insights. Even when assessments and monitoring are available, patients often struggle to maintain high-quality, intensive exercise routines without supervision, further limiting rehabilitation outcomes.

To address these challenges, this dissertation proposes an AI-driven, smartphone-based framework that integrates automated motor function assessment, non-invasive vital …

Acute Kidney Injury In Severe Alcohol-Associated Hepatitis Treated With Anakinra Plus Zinc Or Prednisone, Kavish R Patidar, Wanzhu Tu, Thomas G Cotter, Douglas A Simonetto, Amon Asgharpour, Muhammad Y Jan, Qing Tang, Yunpeng Yu, Yang Li, Moyinoluwa Taiwo, Prashanth Thevkar Nagesh, Srinivasan Dasarathy, Patrick S Kamath, Craig J Mcclain, Naga Chalasani, Gyongyi Szabo, Ramon Bataller, Mack Mitchell, Wajahat Z Mehal, Laura E Nagy, Vijay H Shah, Samer Gawrieh, Arun J Sanyal

Faculty, Staff and Students Publications

Background and aims: In a recent trial, patients with severe alcohol-associated hepatitis treated with anakinra plus zinc (A+Z) had lower survival and higher acute kidney injury (AKI) rates versus prednisone (PRED). We characterize the clinical factors and potential mechanisms associated with AKI development in that trial.

Approach and results: Data from 147 participants in a multicenter randomized clinical trial (74 A+Z, 73 PRED) were analyzed. AKI, AKI phenotypes, and kidney injury biomarkers were compared between participants who did/did not develop AKI in the 2 treatment arms. Multivariable competing risk analyses were performed to identify baseline risk factors for incident AKI, …

The Relationship Between Physical Activity And Telomere Length In Women: A Systematic Review, Jeni Page, Catherine Stephens, Melissa Richard, Elizabeth Lyons, Elizabeth Baumler, M Terese Verklan, Elizabeth Lorenzo

Faculty, Staff and Student Publications

Telomere length (TL) is a biomarker of cellular aging with variations observed by sex, age, race, and ethnicity. Prior studies have suggested that physical activity (PA) may positively impact TL by potentially elongating telomeres and slowing cellular aging. However, research examining the optimal type and intensity of PA needed to elicit these changes specific to women remains limited. This systematic review aimed to investigate variations in TL in response to PA among women, exploring how these effects differ by age, race, or ethnicity. Following PRISMA guidelines, searches across five databases identified 17 relevant studies published from 2008 to 2022. A …

Precision Drug Dosing And Disease Risk Prediction: Advanced Deep Learning Artificial Intelligence Approaches For Precision Medicine Using Structured Electronic Health Records Data, Bingyu Mao

Dissertations and Theses (Open Access)

Advancements in precision medicine increasingly rely on data-driven approaches to improve clinical decision-making. This work presents three interconnected studies that leverage deep learning, reinforcement learning, and comparative modeling to address key challenges in precision drug dosing and disease risk prediction. Together, these contributions offer novel computational frameworks that enhance model performance, improve dosing strategies, and guide model selection for clinical predictive tasks.

To improve individualized vancomycin therapeutic drug monitoring (TDM), the first study introduces PKRNN-2CM, a novel deep learning framework that integrates a two-compartment pharmacokinetic (PK) model with recurrent neural networks (RNNs). While one-compartment models are commonly used in clinical …

Computational Methods For Enhancing The Quality And Interoperability Of Biomedical Terminologies, Xubing Hao

Dissertations and Theses (Open Access)

Biomedical ontologies or terminologies not only serve as a part of the metadata standards for describing data in the FAIR Data Principles (Findable, Accessible, Interoperable, Reusable), but also play a vital role in downstream applications such as cohort identification from electronic health records (EHR). However, there are two critical barriers that may lead to ambiguity, complexity, and inaccuracies in such ontology-based downstream applications. The first barrier is the quality of the ontology. Despite efforts by ontology curators to ensure ontology accuracy and comprehensiveness, errors and inconsistencies are unavoidable. The second barrier is the semantic heterogeneity since human experts may use …

Advancing Genetic Association Discovery In Brain Mri Using Unsupervised And Self-Supervised Deep Learning: Exploring Learning Dynamics, Region-Specific Features, And Spatially Resolved Representations, Sheikh Muhammad Saiful Islam

Dissertations and Theses (Open Access)

Deep learning has unlocked significant potential for advancing the discovery of genetic associations in imaging genetics, particularly in brain imaging using T1-weighted Magnetic Resonance Imaging (MRI). Traditional methods for this task often relied on hand-crafted or semi-automated feature extraction, followed by genetic association studies utilizing these features. While effective, these approaches are limited by their lack of data-driven exploration and the generation of features with limited informativeness.

Unsupervised deep learning, in particular, has emerged as a powerful alternative, addressing some of these limitations by enabling automated and data-driven feature discovery. Recent research in this domain has primarily focused on adapting …

Accelerating Drug Repurposing And Target Discovery Using Deep Learning, Kohong Lin

Dissertations and Theses (Open Access)

Drug discovery is a long-lasting and expensive process. Computational approaches, particularly deep learning techniques, offer the potential to accelerate this process by integrating diverse perspectives from drug discovery theories and capturing intricate patterns within large, multimodal datasets. This dissertation explores deep learning methodologies to accelerate drug repurposing and genetic target discovery. The first aim focuses on integrating multimodal data, including chemical structures, disease genetics, and systems biology, into comprehensive disease knowledge graphs, followed by applying graph neural networks (GNNs) to prioritize repurposable drug candidates. The second aim is to develop a heterogeneous GNN-based approach capable of modelling distinct semantic relationships …

Defining The Transcriptional Basis Of Organ-Specific Endothelial Cell Specialization, Joshua D. Wythe, James F. Martin

Faculty, Staff and Students Publications

Blood vessels feature extensive phenotypic and functional differences that help them meet the unique nutritive and energetic demands of the specific organ they reside in. Profiling the chromatin and transcriptional landscape of several organs identified novel gene regulatory networks that determine endothelial cell organ specialization in mammals.

Differentiation Stage Predicts Radiosensitivity In Mesenchymal-Like Pancreatic Cancer, Tingshi Su, Xinjian Yu, Mojtaba Hoseini-Ghahfarokhi, David B Flint, Scott J Bright, Joana I D S Antunes, David K J Martinus, Mandira Manandhar, Mariam Ben Kacem, Poliana C Marinello, Eurico J G Pereira, Hua-Sheng Chiu, Uwe Titt, David R Grosshans, Jan Schuemann, Henning Willers, Harald Paganetti, Pavel Sumazin, Gabriel O Sawakuchi

Faculty, Staff and Student Publications

Purpose: To derive a genomic classifier to predict radiosensitivity of pancreatic cancer cell lines and patients with pancreatic cancer to allow genomic-guided radiation therapy.

Methods and materials: We collected a comprehensive data set of full clonogenic cell survival curves of 45 pancreatic cancer cell lines irradiated with clinical photon and proton beams. We derived classifiers based on data from human embryonic and fetal pancreas single-cell RNA-sequencing to distinguish between epithelial and mesenchymal cells and to predict pancreas cell-line differentiation stage. Independent testing was done with an embryonic mouse pancreas single-cell RNA-sequencing data set. We then used bulk RNA-seq profiles from …