Objectives/Goals: Alzheimer’s disease (AD) has limited treatments and an extremely high rate of clinical trial failure. Through a collaborative effort, Agomelatine (AGO) was identified as having repurposing potential for AD. This study sets out to evaluate the preclinical potential of AGO for the treatment of AD. Methods/Study Population: The TgF344-AD rat model (expresses human mutant “Swedish” amyloid-precursor protein and a Δ exon 9 presenilin 1) was used to test AGO’s potential to reduce cognitive deficits and neuropathology. The model was chosen due to its age-dependent progressive AD pathology and cognitive decline. Treatment with AGO at ~10 mg/kg body weight/day began at 5 months of age (pre-pathology) and continued until 11 months of age when cognitive testing (active place avoidance task) and tissue collection occurred. Immunohistochemistry was used to evaluate amyloid beta plaque burden and microglial response in the hippocampus. Results/Anticipated Results: AGO-treated female TgF344-AD rats showed reduced cognitive deficits with an increased latency to first entrance in aPAT testing compared to nontreated transgenic littermates. There were no differences between the cognitive performance of AGO treated and untreated male TgF344-AD rats. Interestingly, this reduced cognitive deficit did not correlate with decreased amyloid beta pathology in female AGO-treated rats yet male transgenic treated rats did have decreased amyloid burden in the dentate gyrus (DG) of the hippocampus. AGO modulated microglial activation in the DG of female transgenic rats. Discussion/Significance of Impact: AGO reduced cognitive deficits in females, but did not change their amyloid burden. This suggests that AGO could increase resilience to amyloid deposition in female rats. With the recent development of amyloid targeting drugs, novel non-amyloidogenic treatments have a large translational potential.

Objectives/Goals: Current popular scoring systems for evaluating facial nerve function are subjective and imprecise. This study aims to quantify speech and facial motor changes in patients suffering from facial palsy after cerebellopontine angle (CPA) tumor resection to lay the foundation for a scoring algorithm that is higher resolution and more objective. Methods/Study Population: We will obtain audio and video recordings from 20 adult patients prior to and after surgical resection of unilateral CPA tumors between October 2024 and February 2025. We will obtain preoperative recordings within two weeks prior to surgery and postoperative recordings following a preset schedule starting from the day after surgery up to one year. Audio recordings entail patient readings of standardized passages and phonations while video recordings entail patient performance of standardized facial expressions. We will analyze video data for key distance measurements, such as eye opening and wrinkle size, using DynaFace. We will process audio data using VoiceLab to extract metrics such as prominence and tonality. We will perform statistical tests such as t-tests and ANOVA to elucidate changes across time. Results/Anticipated Results: I expect to obtain 9 sets of audio and video recordings from each of the 20 participants. In terms of speech, I expect average speech duration to increase postoperatively. Similarly, I expect to find increases in time spent breathing, number of breaths taken, and mean breathing duration. In terms of facial movement, I expect nasolabial fold length to decrease postoperatively, as well as eye opening size and left-right symmetry at rest. For both audio and video, I expect these changes to revert towards their preoperative baseline as time passes. I also expect average House-Brackmann and Sunnybrook facial grading scores to increase postoperatively and then decrease with time, correlating strongly with the video and audio findings. I will use trajectory analysis and time point matching to handle any missing data. Discussion/Significance of Impact: This study will validate our analysis platform’s ability to automatically quantify measurable changes that occur to speech and facial movement which correlate strongly with existing scoring systems. Future work will synthesize these data streams to move towards establishing biomarkers for facial nerve function that aid clinical decision-making.

Objectives/Goals: The neighborhoods children grow up in are critical drivers of social, emotional, and cognitive development. This study utilized factor scores of environment, education, and socioeconomic variables in the Adolescent Brain Cognitive Development Study (ABCD) and its association with cognitive functioning in youth. Methods/Study Population: This study used ABCD (n  =  9,543) linked external data, cognitive performance, and self-reported data from youth (ages 9–10) and their caregivers. We utilized four factor scores of the Child Opportunity Index 2.0 (COI), including socioeconomic attainment, poverty, neighborhood enrichment, and child education. Furthermore, this study investigated the association between the COI factors and youth cognitive functioning via the NIH Toolbox. Covariates included age, sex, county level crime rates, perceptions of neighborhood threat, parent education, and family income; site and family relationship were held as random effects. Results/Anticipated Results: Increased Socioeconomic Attainment and Child Education factor scores were distinctly associated with increased cognitive performance across all subscales and composite scores that include aspects of overall cognitive ability, executive functioning, and learning and memory. Increased poverty factor scores were significantly associated with decreased cognitive performance across all substances and composite scores. Finally, increased neighborhood enrichment factor scores were significantly associated with increased oral reading recognition task scores only and no other cognitive task. Discussion/Significance of Impact: Findings suggest distinct dimensions of neighborhood opportunity associated with aspects of cognition. The present study can help to inform public health efforts and policy on improving modifiable built and natural environmental structures that may aid in supporting cognitive development.

Objectives/Goals: The standard care for malignant gliomas includes maximal tumor resection, but challenges arise near functional (speech) areas. Direct cortical stimulation (DCS) identifies functional (nonresectable) cortex. We aim to identify electrophysiologic (via subdural electrode recordings [ECOG]) biomarkers of DCS-positive (functional) areas. Methods/Study Population: Our lab maintains one of the largest datasets of electrophysiology analysis of glioma infiltrated brain cortex in the USA. Recordings of intraoperative brain mapping were analyzed to identify cortical sites that were found to be positive (functional) during DCS. DCS positive and negative (nonfunctional) sites were aligned to corresponding subdural electrodes. Future analysis: We plan to compare the temporal and spectral electrophysiologic variations associated with cortical sites found to be DCS positive versus negative during brain mapping. We plan to train machine learning classifiers that utilize these electrophysiologic biomarkers to discriminate between DCS positive and negative sites. Results/Anticipated Results: In total, our database comprised of 110 resections with brain mapping (DCS) and ECOG, including 4 patients who underwent a second procedure for resection. Eight patients were excluded as their resections were for brain metastases, not glioma. Our final cohort was comprised of 98 glioma resections, including 4 patients who underwent surgery twice for recurrence. During these resections, a total of 1393 sites were mapped via DCS for language function (including picture naming, word reading, and sentence syntax tasks). Of these 1393 sites, 100 sites were found to be DCS positive (7.1% positivity rate). (Currently in the process of conducting analysis comparing electrophysiologic features and biomarkers of DCS positive versus negative sites.) Discussion/Significance of Impact: This research is ongoing. Identifying electrophysiologic biomarkers of critical DCS-positive regions may provide a durable alternative to stimulation mapping. Due to its resource intensity, DCS has access barriers. Future neurosurgeons may use biomarkers from subdural electrode recordings to plan safer cortical resections.

Objectives/Goals: This project (1) assesses provider behavior at the Galveston Secure Against the Fentanyl Epidemic (G-SAFE) Clinic in providing evidence-based care for underserved patients in our community and (2) implements evidence-based anti-stigma intervention in local health care. Methods/Study Population: The efficacy and impact of G-SAFE on healthcare utilization, health outcomes, and patient satisfaction will be determined. Evaluations assessing provider behavior will be made across at least 25 clinic patient visits, taking note of medical students, clinicians, and health providers’ interactions with patients related to decision-making, care plan creation, and communication. Health provider discussion groups will provide essential data in understanding the successful management of SUDs, management of safety and risk, and how best to pilot and assess interventions that promote greater trust-building and a harm-reduction approach to clinical care for patient empowerment and positive outcomes. Results/Anticipated Results: Observations in the clinic will be turned into interventions to improve diagnostics and therapeutics for SUD medical care and behavioral change. We will recruit 40 medical students (with/without exposure to UTMB’s free clinics) as well as 20 clinicians in the G-SAFE Clinic, Emergency Medicine, and Primary Care. Baseline stigma will be measured with the Medical Condition Regard Scale and the Drug and Drug Problems Questionnaire alongside measures of care approaches. The data collected and the educational intervention for medical students and clinicians will make a positive impact on the lives of those affected by SUDs and serve as a model for future interventions on a larger scale. Discussion/Significance of Impact: Health provider’s SUDs stigma undermines both care quality, patient empowerment, and recovery success. Addressing provider stigma is crucial for necessitating a shift toward collaborative, responsive, and creative clinical decision-making to tackle the ethical challenges posed by the opioid crisis.

Objectives/Goals: Evaluate the effectiveness of ChatGPT as a complementary tool for addressing the mental health needs of Hispanic LGBTTQI+ young adult patients. We will also explore the experience of clinical healthcare providers with the integration of ChatGPT as a complementary tool in psychotherapy with Hispanic LGBTTQI+ young adults. Methods/Study Population: In this mixed-method study, we will create hypothetical clinical cases that reflect common mental health challenges experienced by LGBTTQI+ Hispanic population. These cases will be presented to three groups: 1) ChatGPT app, 2) clinical mental health care providers, and 3) clinical mental health care providers collaborating with ChatGPT. Each group will provide a diagnosis and a treatment plan based on the case information. A panel of experts will evaluate each plan using a standardized rubric to provide a score on clinical accuracy and on the ability to address specific needs of Hispanic LGBTTQI+ patients. Statistical analysis will be used to evaluate the differences in the scores of each domain and qualitative content analysis to evaluate the experience of clinical mental health care providers using ChatGPT. Results/Anticipated Results: The results will provide evidence of the effectiveness of ChatGPT as a supportive tool in mental health care. We anticipated that the combination of a clinical mental health care provider and ChatGPT to develop a diagnosis and treatment plan would produce better outcomes than either ChatGPT or the clinical mental health care provider working independently. We will also expect to find a positive attitude toward the integration of ChatGPT applications, viewing them as useful tools that complement traditional psychological interventions for Hispanic LGBTTQI+ young adults. The study will provide evidence of the effectiveness of ChatGPT to complementing clinical practice involving Hispanic LGBTTQI+ young adults. Those results in a preclinical phase are preconditions to a more applied intervention. Discussion/Significance of Impact: We aim to improve the quality of life for LGBTTQI+ Hispanics by developing innovative psychological treatments enhanced by AI apps. By developing innovative treatments, we are addressing and mitigating health disparities within the LGBTTQI+ Hispanic community in Puerto Rico and contributing to a broader effort of inclusivity and health equity.

Objectives/Goals: We aim to enhance risk prediction in kidney transplantation outcomes by improving models of peptide antigen presentation of mismatched HLA molecules. HLA-derived peptides presented by HLA Class II to T-cells can activate an immune response, ultimately leading to graft failure. We aim to improve peptide prediction by modeling antigen processing. Methods/Study Population: T-cell epitope models for HLA mismatching struggle to predict which peptides are presented because antigen processing by proteases is not well modeled. We model antigen processing of HLA Class II proteins using 3D HLA structures (crystallography data) to create an HLA-specific antigen processing likelihood (APL) model. APL uses conformational stability measurements such as b-factor, COREX, solvent accessible surface area, and sequence entropy to predict cleavage sites from proteolysis. We will integrate APL into a T-cell epitope prediction tool for HLA-derived peptides based on donor and recipient HLA genotypes. Finally, we will associate the risk of graft failure with counts of these peptides derived from APL-integrated prediction models using a historical kidney transplant cohort from 2000 to 2023. Results/Anticipated Results: We expect that applying APL could reduce false-positive peptide binders influencing risk prediction scores. We anticipate improved peptide prediction accuracy compared to existing tools such as NetMHCIIPan, which assumes all possible peptides are equally likely to emerge from antigen processing. NetMHCIIPan is currently used by PIRCHE-II HLA mismatch risk algorithm. We expect that merging antigen processing (APL) and peptide-binding (NetMHCIIPan) models into a unified model would enhance risk stratification for graft failure. Current risk stratification still leads to poor outcomes post-transplant, especially for minority population groups. Our model can identify an alternative pool of well-matched donors and has the potential to improve equity for non-White minority candidates. Discussion/Significance of Impact: Improving the understanding of how HLA matching contributes to kidney transplant outcomes can better stratify risks for kidney transplant recipients, enable personalized treatment, and ultimately improve outcomes for those undergoing kidney transplantation to treat renal diseases.

Objectives/Goals: pT217-tau is a novel fluid biomarker that predicts onset of Alzheimer’s disease (AD) symptoms, but little is known about how pT217-tau arises in brain, as soluble pT217-tau is dephosphorylated postmortem in the humans. Aging macaques naturally develop tau pathology with the same qualitative pattern and sequence as humans, including cortical pathology. Methods/Study Population: The etiology of pT217-tau in aging brains can be probed in rhesus macaques, where perfusion fixation allows capture of phosphorylated proteins in their native state. We utilized multi-label immunofluorescence and immunoperoxidase and immunogold immunoelectron microscopy to examine the subcellular localization of early-stage pT217-tau in entorhinal cortex (ERC) and dorsolateral prefrontal cortex (dlPFC) of aged rhesus macaques with naturally occurring tau pathology and assayed pT217-tau levels in blood plasma using an ultrasensitive nanoneedle approach. Results/Anticipated Results: pT217-tau labeling is primarily observed in postsynaptic compartments, accumulating in: 1) dendritic spines on the calcium-storing smooth endoplasmic reticulum spine apparatus near asymmetric glutamatergic-like synapses and 2) in dendritic shafts, where it aggregated on microtubules, often “trapping” endosomes associated with Aβ42. The dendrites expressing pT217-tau were associated with autophagic vacuoles and dysmorphic mitochondria, indicative of early neurite degeneration. We observed trans-synaptic pT217-tau trafficking between neurons within omega-shaped bodies and endosomes, specifically near excitatory, but not inhibitory synapses. We also examined pT217-tau in blood plasma in macaques across age-span and observed a statistically significant age-related increase in pT217-tau. Discussion/Significance of Impact: We provide direct evidence of pT217-tau trafficking between neurons near synapses to “seed” tau pathology in higher brain circuits, interfacing with the extracellular space to become accessible to CSF and blood. The expression of pT217-tau in dendrites with early signs of degeneration may help to explain why this tau species can herald future diseases.

Objectives/Goals: This study aims to evaluate diversity of participants in GLP-1 T2DKM clinical research with regard to sex, race, and ethnicity by using results data available through the ClinicalTrials.gov database. Sample population estimates for studies were calculated using the 2020 Census and compared within groups with respect to sex, race, and ethnicity. Methods/Study Population: The public ClinicalTrials.gov database was searched for interventional studies with GLP1 inclusion as treatment (n = 2,397). This search was then filtered to studies where results were reported (n = 772). From these studies, 466 studies focused on type 2 diabetes as a condition and thus became the analysis dataset. Participant and protocol information for these 466 studies were obtained from the clinical trials transformation initiative (CTTI) as an AACT data download. Observed to expected ratios were calculated for each subgroup-based population estimates from the 2020 Census and using the baseline counts of participants for studies where sex, race, and ethnicity were provided. In addition to within group comparisons, study characteristics (e.g. phase) were included in models to assess influence of covariates. Results/Anticipated Results: Of the 466 studies, 430 (92%) reported sex, 171 (37%) reported race, and 145 (31%) reported Hispanic ethnicity. Among those found to be underrepresented in studies (defined as a ratio < 1): females (mean  =  0.89, median  =  0.92); Black/African Americans (mean  =  0.88, median  =  0.39). Hispanic or Latinos mean ratio was 1.16 (95% CL: 0.97, 1.35) but had the least available data. When including covariates in the models, there were statistically significant differences in ratios with respect to sex as females had significantly lower odds compared to males (ratio > =  1), with the odds being about 21% of those for males. With respect to race, Black or African American individuals had significantly lower odds (about 32% of those of White individuals) (ratio > =  1). Discussion/Significance of Impact: This study reveals significant underrepresentation of females (mean ratio 0.89) and Black/African Americans (mean ratio 0.88) in clinical trials for GLP-1 drugs in type 2 diabetes. These disparities highlight the need for more inclusive research to ensure diverse populations benefit equally from medical advancements.

Objectives/Goals: This study aims to explore the relationship between plasma biomarkers (GFAP, NF-L, and IL-1β) and cognitive impairment in moderate to severe TBI patients. We will assess biomarker levels and their link to neurocognitive outcomes at acute and chronic stages of injury. Methods/Study Population: We will recruit 100 patients aged 21 years and older with moderate to severe TBI (Glasgow Coma Score 3–12) from a trauma hospital. Blood samples will be collected at 24–72 hours post-injury and again at 3 and 6 months. Plasma levels of GFAP, NF-L, and IL-1β will be measured using multiplex ELISA. Neurocognitive tests will be administered at 3 and 6 months to assess cognitive function. Correlations will be made between biomarker levels, neurocognitive performance, and disability scores (Disability Rating Scale and Glasgow Outcome Scale). Exosome isolation from plasma will allow for detailed analysis of astrocyte-derived biomarkers and their association with long-term cognitive impairment and recovery. Results/Anticipated Results: We anticipate that plasma levels of GFAP, NF-L, and IL-1β will be elevated in the acute phase of moderate to severe TBI and will correlate with injury severity. At 3 and 6 months, higher levels of IL-1β, in particular, are expected to be strongly associated with cognitive deficits. We also anticipate that biomarkers in astrocyte-derived exosomes will provide more specific insights into long-term neuroinflammation and its impact on cognitive function. These findings could pave the way for targeted, personalized interventions to improve recovery in TBI patients. Discussion/Significance of Impact: This research focuses on inflammation’s role in cognitive impairment and disability in TBI patients. We propose using multiple biomarkers – GFAP, IL-1β, NF-L – paired with advanced techniques like exosomes and multiplex analyses to identify novel therapeutic targets, aiming for personalized treatment strategies, as well as prognosis.