Medical Sciences Commons^™

Scopolamine-Induced Modulation Of Serotonin And Dopamine Transporters Activity: Behavioral And Molecular Insights Into Rapid Antidepressant Action, Deepak Karunakaran

Theses and Dissertations

Major depressive disorder (MDD) affects over 350 million individuals worldwide and is characterized by profound dysregulation of serotonin (5-HT) and dopamine (DA) systems that govern mood, reward processing, and motivation. The serotonin transporter (SERT) and dopamine transporter (DAT), both dynamically regulated through phosphorylation, serve as critical determinants of synaptic monoamine signaling. Despite decades of therapeutic development, current antidepressants require 4-6 weeks to achieve efficacy, and approximately one-third to half of patients develop treatment-resistant depression. The emergence of rapid-acting antidepressants like ketamine represents a paradigmatic shift, demonstrating symptom relief within hours; however, ketamine's therapeutic potential remains constrained by abuse liability, dissociative …

Benchmarking And Improving Foundation Model Dietary Estimates From Meal Images, Yongcheng Mu, Jiangwen Sun, Jing He

Computer Science Faculty Publications

Accurate quantifying dietary contents, such as calories, proteins, carbohydrates, and fats, from an image of a meal plate is vital for managing diabetes. Recently, Large Multimodal Models (LMMs) have excelled in complex vision-language tasks due to their use of very large, highly diverse data. This study benchmarked the use of seven LMMs that include full and lightweight models of GPT, Gemini, and Llama for nutrition estimation based on Google's Nutrition5k dataset and our own phone-collected DonateAndLearn dataset. We analyzed the performance of LMMs and the RGB-D fusion model, in which the RGB-D model was specifically trained using Nutrition5k data. On …

Igf-1 Impacts Neocortical Interneuron Connectivity In Epileptic Spasm Generation And Resolution, Carlos J Ballester-Rosado, John T Le, Trang T Lam, Anne E Anderson, James D Frost, John W Swann

Faculty, Staff and Students Publications

Little is known about the mechanisms that generate epileptic spasms following perinatal brain injury. Recent studies have implicated reduced levels of Insulin-like Growth Factor 1 (IGF-1) in these patients' brains. Other studies have reported low levels of the inhibitory neurotransmitter, GABA. In the TTX brain injury model of epileptic spasms, we undertook experiments to evaluate the impact of IGF-1 deficiencies on neocortical interneurons and their role in spasms. Quantitative immunohistochemical analyses revealed that neocortical interneurons that express glutamic acid decarboxylase, parvalbumin, or synaptotagmin 2 co-express IGF-1. In epileptic rats, expression of these three interneuron markers were reduced in the neocortex. …

Comparative Analysis Of Aav Serotypes For Transduction Of Olfactory Sensory Neurons, Benjamin D W Belfort, Johnathan D Jia, Alexandra R Garza, Anthony M Insalaco, J P Mcginnis, Brandon T Pekarek, Joshua Ortiz-Guzman, Burak Tepe, Hu Chen, Ascent-Pd Investigators, Zhandong Liu, Benjamin R Arenkiel

Faculty, Staff and Students Publications

Olfactory sensory neurons within the nasal epithelium detect volatile odorants and relay odor information to the central nervous system. Unlike other sensory inputs, olfactory sensory neurons interface with the external environment and project their axons directly into the central nervous system. The use of adeno-associated viruses to target these neurons has garnered interest for applications in gene therapy, probing olfactory sensory neuron biology, and modeling disease. To date, there is no consensus on the optimal AAV serotype for efficient and selective transduction of olfactory sensory neurons

Survey And Improvement Strategies For Gene Prioritization With Large Language Models, Matthew B Neeley, Guantong Qi, Guanchu Wang, Ruixiang Tang, Dongxue Mao, Chaozhong Liu, Sasidhar Pasupuleti, Bo Yuan, Fan Xia, Pengfei Liu, Zhandong Liu, Xia Hu

Duncan NRI Faculty and Staff Publications

Motivation: Rare diseases remain difficult to diagnose due to limited patient data and genetic diversity, with many cases remaining undiagnosed despite advances in variant prioritization tools. While large language models have shown promise in medical applications, their optimal application for trustworthy and accurate gene prioritization downstream of modern prioritization tools has not been systematically evaluated.

Results: We benchmarked various language models for gene prioritization using multi-agent and Human Phenotype Ontology classification approaches to categorize patient cases by phenotype-based solvability levels. To address language model limitations in ranking large gene sets, we implemented a divide-and-conquer strategy with mini-batching and token limiting …

Glutamatergic Lateral Habenula Neurons Modulate Consolidation Of Associative Memories, Snigdha Srivastava, I-Ching Wang, Mikhail Y Kochukov, Jessica L Swanson, Mauro Costa-Mattioli, Benjamin R Arenkiel

Duncan NRI Faculty and Staff Publications

INTRODUCTION: Despite the rise in psychiatric disorders worldwide, the underlying brain circuits responsible for these devastating conditions remain elusive. The lateral habenula (LHb) has emerged as a key brain structure in depression studies due to its hyperactive state in both patients and animal models. While this aligns with known roles in driving aversive states and regulating serotonin release, it is still unclear how acute and transient activity changes in the LHb can influence higher order cognitive processes such as learning, memory, and behavioral adaptation. Given the importance of these processes to psychiatric conditions, understanding how LHb activity impacts cognitive function …

Resort Enhances Reference-Based Cell Type Deconvolution For Spatial Transcriptomics Through Regional Information Integration, Linhua Wang, Ling Wu, Guantong Qi, Chaozhong Liu, Wanli Wang, Xiang H-F Zhang, Zhandong Liu

Duncan NRI Faculty and Staff Publications

Motivation: Spatial transcriptomics (ST) captures positional gene expression within tissues but lacks single-cell resolution. Reference-based cell type deconvolution methods were developed to understand cell type distributions for ST. However, batch/platform discrepancies between references and ST impact their accuracy.

Results: We present Region-based Cell Sorting (ReSort), which utilizes ST's region-level data to lessen reliance on reference data and alleviate these technical issues. In simulation studies, ReSort enhances reference-based deconvolution methods. Applying ReSort to a mouse breast cancer model highlights macrophages M0 and M2 enrichment in the epithelial clone, revealing insights into epithelial-mesenchymal transition and immune infiltration.

Availability and implementation: Source codes …