Objectives/Goals: To assess theory of mind and empathy in adolescents with Tourette syndrome (TS) and examine their association with social problems. This study aims to extend research in social cognition to an adolescent cohort with TS and identify a potential modifiable risk factor for social problems in TS that may serve as a novel intervention target. Methods/Study Population: We will enroll 50 adolescents with TS (ages 11–17) and 50 demographically matched controls along with one parent to complete a single in-person study visit. Adolescents with TS will be recruited through the Vanderbilt Center for TS and other Tic disorders. Controls will be recruited using university listservs and flyers posted in community and primary care settings. Adolescents will complete the NEPSY-II to assess theory of mind abilities and the Multifaceted Empathy Test – Juvenile to assess empathy with negative emotions. Parents will complete the Child Behavior Checklist to assess adolescent social problems. Results/Anticipated Results: Based on evidence of low self-other distinction in TS, we hypothesize TS adolescents will make more errors about the mental states of others (theory of mind) and report greater emotional reactions to faces (empathy) compared to controls. Further, greater social problems will be associated with greater disturbances in social cognition. To date, 15 adolescents with TS and 15 matched controls have completed the assessment (67% male; Mage  =  14.33 in both groups). Within this sample, adolescents with TS experienced more social problems than controls (Cohen’s d  =  .74, p  = .03). There were no between-group differences in theory of mind or empathy in this pilot sample. However, higher levels of both theory of mind and empathy were linked to experiencing greater social problems in the TS sample only (p’s < .05). Discussion/Significance of Impact: Preliminary findings suggest that while social cognition did not differ between groups, TS adolescents exhibiting high levels of theory of mind and empathy appear to struggle socially. This work could inform future interventions by highlighting the need to focus on social cognition and how these skills translate into social behaviors.

Objectives/Goals: Digital recruitment can improve participant engagement in medical research, but its potential to introduce demographic and socioeconomic biases is unclear. This study investigates pathways participants took during a digital recruitment workflow in neurology, examining potential associations with socioeconomic and demographic factors. Methods/Study Population: As part of an ongoing study aiming to remotely capture speech from patients with neurologic disease, most participants seen in neurology on our campus are invited to complete a self-administered speech examination. We exported participant data from Epic (semi-automated identification and invitation), Qualtrics (eligibility screening), the participant tracking database (consent), and the recording platform (completion) for March to July 2024. Data visualization was performed using a Sankey diagram. Socioeconomic status was assessed using the housing-based socioeconomic status (HOUSES) index and area deprivation index (ADI) national rank. Kruskal–Wallis and Wilcoxon rank-sum tests were used to compare the median age, socioeconomic indices, and time taken to reach different steps of the study. Results/Anticipated Results: Of the 5846 invited participants, 57% were from urban areas, 23% from rural areas, and 20% from urban clusters. Most did not read/respond (2739) or declined (1749) the initial invitation via Epic. Of the 1358 interested participants, 415 completed the study. Participants from urban areas completed enrollment steps faster than those from rural areas and urban clusters, though the variance was large (42.6 ± 41.4 days vs. 50.6 ± 42.2 days and 50 ± 43.9 days, respectively; p  =  0.030). Female participants took longer to complete enrollment than males (48.7 ± 44 days vs. 40.5 ± 38.8 days; p  =  0.026). Participants who successfully finished the study had significantly lower ADI national ranks compared to other common pathways (40.6 ± 19; p  =  0.0021). No associations were found with the HOUSES indices. Discussion/Significance of Impact: Our findings support differences in participant engagement, with urban participants and males more likely to complete enrollment steps. Those who finished the study were less disadvantaged suggesting potential bias in digital recruitment. These findings can inform strategies to improve digital recruitment in neurology research.

Objectives/Goals: Youth with IBD have preventive, psychosocial, and acute care needs beyond those of peers, yet receipt of services does not match those needs. Our objectives are to assess the feasibility of (1) an individualized care plan intervention to improve perceived and measured care quality and (2) a pragmatic trial design embedded in pediatric IBD practice. Methods/Study Population: This is a pilot rollout-design randomized trial (n = 60) at a regional academic medical center. Eligible patients are 13–19 years old with IBD for at least 3 months and scheduled for a follow-up visit during the trial. Research staff recruits from one cluster at a time until goal enrollment (14–16). Enrollees are randomized 1:1 to intervention (MyIBD now) or control (MyIBD after the trial). MyIBD combines a tabular summary of individualized acute, chronic, and preventive care needs with nurse facilitator support for patients to use the information. Surveys at baseline, 6 and 12 months measure care quality (Patient Assessment of Chronic Illness Care scale, vaccines, health services) and patient self-management skills (Partners in Health scale). Implementation outcomes are collected via chart review. Results/Anticipated Results: To date, 44 subjects have been randomized. Among subjects, the mean age is 16 years; 73% have Crohn’s disease, 77% have commercial insurance, 75% receive anti-TNF therapy, and 14% live in a rural area. Mean baseline perceived care quality (PACIC scale) is 76.9 (sd 16.3; out of 100); mean baseline perceived self-management skill (PIH scale) is 78.1 (sd 13.4; out of 96). On objective care quality measures, 59% have completed the HPV vaccine series, 32% have received an additional pneumonia vaccine; in the past year 68% have had a screening for mood disorders, 20% an emergency department visit for IBD, and 18% an IBD hospitalization. To date, the IBD clinical team has achieved 100% completion (intervention subjects receive MyIBD plus nurse facilitation) and 0% contamination (control subjects inappropriately receive MyIBD). Discussion/Significance of Impact: Study results to date support the feasibility of the pragmatic, embedded trial design and indicate opportunities for improvement in care quality as perceived by patients and as measured by common preventive and acute care quality indicators. An individualized care plan supported with nurse facilitation may improve pediatric IBD care quality.

Objectives/Goals: The goal of this poster is to 1) describe the development of a graduate certificate program for community-engaged research for health (CEnRH) in a Clinical and Translational Science Awards-funded institution; 2) describe the initial impact of the program; and 3) discuss strengths, implications, and potential improvements for the future. Methods/Study Population: The CEnRH graduate certificate is a 12-credit, postbaccalaureate program offered at the University of Cincinnati co-created by faculty from the Community Engagement and Translational Workforce Cores of the CCTST with community partners. The goal is to support learning about community-engaged research (CEnR) and enhances capacity for academic-community partnered research. Student demographics are collected as part of university registration. Quantitative course evaluations are collected each semester. Program evaluations including qualitative data are collected from students enrolled in the program during and upon completion of the certificate. Results/Anticipated Results: The CEnRH curriculum includes 3 existing courses/electives in the College of Medicine and Psychology and three new courses in social justice and action research methodologies. Notably, the committee advocated for a scholarship to cover tuition for the certificate program to promote access for community partners. Since the fall of 2022, 17 students have enrolled in the CEnRH program, including 9 Faculty/Staff within CCTST institutions, 2 University of Cincinnati PhD Students, 5 Fellows, and 1 Community Member (who receives the scholarship). Notably, 24% of these students are from underrepresented minority backgrounds. Impact and evaluation data, as well as lessons learned, will be presented. Future directions for the CEnRH program will also be discussed. Discussion/Significance of Impact: The CEnRH is an impactful program for trainees, faculty, and staff who are planning to conduct CEnR, while also strengthening research capacity among community partners and advocates. This certificate program may be especially valuable to academic researchers as more funding agencies require community and stakeholder engagement in their proposals.

Objectives/Goals: This study aimed to identify preferences for nutrient-dense foods with critical nutrients associated with reduced neuroinflammation and perinatal depression risk. Aim two evaluated the acceptability of daily intake and preparation methods of select foods in Black American pregnant and postpartum people living in food apartheid in St. Louis. Methods/Study Population: The study included a mixed-methods sequential explanatory design with data collection at the YWCA of Metro St. Louis during Early Head Start programming with 21 participants living in geographies with low grocery-to-convenience store ratios. We conducted an open-ended online survey to determine participants’ preferences for specific foods with high nutrient density. Food preferences were subjected to nutrient analyses using FoodData Central, and foods with the highest concentrations of critical nutrients associated with reduced neuroinflammation and perinatal depression risk were identified. We presented results during a focus group with participants who completed the survey and evaluated the acceptability of daily intake and preparation methods. Results/Anticipated Results: Preferred food choices with the highest concentrations of critical nutrients associated with reduced neuroinflammation and perinatal depression risk included dark red kidney beans, black beans, pinto beans, black-eyed peas, peanuts, almonds, pistachios, walnuts, pecans, carrots, spinach, red bell pepper, sweet potatoes, and salmon. Participant justifications for low acceptance of daily intake included allergic reactions, “dry” or “slimy” texture, undesirable taste or appearance, absence of cravings, preferring alternatives, complicated preparation methods, and financial tradeoffs. Participant justifications for high acceptance included desirable taste and texture, diverse modification and preparation options, and nutrient composition critical for anemia treatment. Discussion/Significance of Impact: The study identified nutrient-dense food preferences within a sample vulnerable to nutrient-poor alternatives and health consequences. Participant acceptance of nutrient-dense intake was contingent upon recipes fulfilling cravings, acceptance among persons preparing meals, and diverse options to prevent boredom with preparation methods.

Objectives/Goals: Our study’s objective is to evaluate RadOnc-GPT, a GPT-4o powered LLM, in generating responses to in-basket messages related to prostate cancer treatment in the Radiation Oncology department. By integrating it with electronic health record (EHR) systems, the goal is to assess its impact on clinician workload, response quality, and efficiency in healthcare communication. Methods/Study Population: RadOnc-GPT was integrated with patient EHRs from both hospital-wide and radiation-oncology-specific databases. The study examined 158 pre-recorded in-basket message interactions from 90 non-metastatic prostate cancer patients. Quantitative natural language processing analysis and two randomized single-blinded grading studies, involving four clinicians and four nurses, were conducted to evaluate RadOnc-GPT’s response quality in completeness, correctness, clarity, empathy, and estimated editing time. Response times were measured to estimate the time saved for clinicians and nurses. The study population included patient messages across all phases of care (pre-, during, and post-treatment) for those undergoing radiotherapy. Results/Anticipated Results: In the single-blinded grader study, clinician graders evaluated 316 responses (158 from human care teams and 158 from RadOnc-GPT). Results showed RadOnc-GPT outperformed human responses in empathy and clarity, while humans excelled in completeness and correctness. Sentiment analyses using TextBlob and VADER revealed RadOnc-GPT responses had a positive mean score of 0.25, whereas human responses clustered around neutral. VADER analysis indicated a high median score for RadOnc-GPT, nearing 1.0, reflecting predominantly positive sentiment, while human responses displayed a broader sentiment range, indicating sensitivity to context. Clinicians averaged 3.60 minutes (SD 1.44) to respond, compared to 6.39 minutes (SD 4.05) for nurses, highlighting RadOnc-GPT’s efficiency in generating timely responses. Discussion/Significance of Impact: RadOnc-GPT effectively generated responses to individualized patient in-basket messages, comparable to those from radiation oncologists and nurses. While human oversight is still necessary to avoid errors, RadOnc-GPT can speed up response times and reduce pressure on care teams, shifting their role from drafting to reviewing responses.

Objectives/Goals: This study will integrate scientific evidence to create messaging about the modifiable risk factors for Alzheimer’s disease (AD) and examine how culturally tailoring elements in message content, such as text and visualizations in infographic messaging, impacts cognitive processing of AD prevention messages among Black adults. Methods/Study Population: This study is guided by the two-dimensional theory of cultural sensitivity and the elaboration likelihood model (ELM). The two-dimensional theory distinguishes between surface structure (visualizations) and deep structure (text with embedded cultural features) in messaging. The ELM considers how message attributes influence cognitive processing. A 2 × 2 factorial experiment will test the impact of cultural features (surface vs. deep) and message type (text-based vs. infographic) on persuasive outcomes regarding modifying AD risk factors. Black adults will be recruited from local churches and randomly assigned to one of four conditions, after which they will complete post-test measures. Statistical analyses will determine the effects of cultural tailoring and message effects on outcome variables. Results/Anticipated Results: Guided by previous literature (Resnicow et al., 1999; Lazard & Atkinson, 2015; Lam et al., 2022), we hypothesize an interaction effect of cultural tailoring and message type, wherein surface structure infographic messages and deep structure text-based messages will outperform the other two message conditions, resulting in greater cognitive processing and more positive attitudes and behavioral intentions toward modifying AD risk factors. In addition, a research question asks whether there will be differences between surface structure infographic messages and deep structure text-based messages on outcome variables. The study will advance understanding of the effects of cultural sensitivity and visual vs. text-based messaging by integrating these literatures. Discussion/Significance of Impact: This research will contribute to the literature on culturally tailored health messages and persuasive effects of text vs. visual messages. The findings can inform the development of more effective, culturally relevant public health campaigns for AD prevention by reducing risk for AD through modifiable risk factors in diverse populations.

Objectives/Goals: This study aims to harmonize quality indicators (QIs) across University of Toronto-affiliated microbiology labs to establish universal benchmarks that enhance performance, patient safety, and health outcomes. Harmonized QIs will enable effective comparisons and enhance the consistency of care. Methods/Study Population: The study employed the Delphi method, a structured and iterative process to build consensus. An expert panel of clinical microbiology trainees, medical microbiologists, trainees, and site leads from five University of Toronto-affiliated microbiology labs was assembled. Initial insights were gathered through surveys and a comprehensive scoping review of the literature. The study involved two rounds of feedback, a SurveyMonkey-based survey, with a defined consensus of 75% agreement among participants. Followed by an implementation survey conducted through REDCap to assess how these QIs were adopted in practice and identify barriers to implementation. Results/Anticipated Results: The study achieved consensus on nine high-impact quality indicators, including blood culture volume and contamination rates, cerebrospinal fluid transport time, and turnaround times for Gram stain results. Blood culture contamination and positivity rates garnered the highest agreement, at 100% and 91%, respectively. While some indicators were widely accepted and implemented, others faced resistance due to feasibility concerns. The study also identified significant variability in the level of adoption across the participating laboratories, pointing to operational challenges and the need for further efforts to address these barriers. Discussion/Significance of Impact: This study highlights the importance of QI harmonization in improving lab services and patient safety. It reveals challenges in standardizing practices but promotes uniformity in QIs, laying the groundwork for better inter-lab collaboration, consistent outcomes, and improvements in microbiology.

Objectives/Goals: This study aimed to enhance clinical trial data management through large language model information retrieval and generation techniques within the clinical trial reporting workflow. We focused on improving compliance with reporting, reducing human labor, and promoting standardized reporting structure and data quality oversight. Methods/Study Population: We used approved study protocols from UC Davis IRB-approved investigator-initiated studies compared to the same studies reported to ClinicalTrials.gov. Our baseline data extraction system employs commercial large language models (LLMs) and retrieval augmented generation (RAG) to isolate data sources within the secure extraction environment. We stratified protocol documents into easy, complex, and random categories based on study focus, document complexity, the extent of amendments or modifications, and completion metrics from ClinicalTrials.gov. We developed a pilot web-based architecture to capture variations in categorization, labeling, and reporting style and compared generated extraction data. We primarily focused on qualitative evaluation through a review of expert staff. Results/Anticipated Results: Our results revealed significant variations in reporting quality, with dependencies stemming from multiple authors and stages throughout the clinical trial protocol lifecycle. Based on these variations, we used prompt engineering to improve the pilot application’s output compliance with the protocol registration and results system (PRS) structured data format for various study types. We piloted the assisted workflow with prospective studies by partnering with study investigators and the clinical trial office staff to assist in review and clinical trial reporting creation. Initial studies reported by our system were approved and released to the public by PRS staff. We are refining content generation and workflows to different components of studies and evaluating their use in quality and training areas. Discussion/Significance of Impact: Our system fosters collaboration, efficient review, and compliance with clinical trial reporting standards. It supports the promise of AI-driven assistance in clinical trial management, design, and reporting. We focus on the multiple stakeholders, expertise, and data flows in the organizational management of clinical and translational science.

Objectives/Goals: We assessed the feasibility of using a large language model (LLM) to create lay language descriptions of study protocols for recruitment, which has the potential to improve accessibility and transparency of clinical studies and enable participants to make informed decisions. Methods/Study Population: All studies from a clinical research recruitment platform were included, which features human-written lay descriptions and titles for study recruitment. Corresponding protocol summaries in the IRB system were extracted and translated into lay language using a LLM (gpt-35-turbo-0613). A subset was used to develop prompt variations through an iterative process. Prompt strategies evaluated include chain-of-thought and few-shot prompting techniques. LLM-generated and human-written descriptions were compared for readability using Flesch–Kincaid and Simple Measure of Gobbledygook (SMOG) reading grade levels and information completeness using Word Movers’ Distance (WMD). Results/Anticipated Results: A total of 55 study descriptions were included – 10 were used to develop prompts and 45 were used for evaluation. The final LLM instructions included multistep prompts. The LLM was first instructed to produce a two- to three-sentence long description without using scientific jargon and included two pairs of examples. The LLM was then asked to shorten the description and finally to provide an engaging title. LLM-generated and human-written summaries were similar in length (median (IQR) 328 (278.5–360.5) vs. 342 (203–532.5) characters, respectively). LLM-generated summaries had lower Flesch-Kincaid grade level (5.15 vs. 8.28, p Discussion/Significance of Impact: An LLM can be used to generate lay language summaries that are readable at a lower grade level while maintaining semantic similarity. This approach can be used to improve the drafting of summaries for recruitment, thereby improving accessibility to potential participants. Future work includes human evaluation and implementation into practice.

Objectives/Goals: Micro-credentials (MCs) or digital badges are short programs designed to allow learners to gain knowledge and skills at their own pace to tailor their professional development. This study aims to examine the characteristics of learners completing MCs and explore their motivation for pursuing MCs through the University at Buffalo Clinical and Translational Science Institute (CTSI) program. Methods/Study Population: Currently, the CTSI offers five MCs in Effective Teaching, Good Clinical Practice, Responsible Research, Scientific Communication, and Translational Teamwork. Individuals who completed an MC (2019–2024) were identified by the UB Office of Micro-credentials. An invitation email and two reminders were sent to all individuals who received MCs asking them to complete a short online survey in July-August 2024. The survey included three questions about the type(s) of MCs completed, learners’ motivation for pursuing MCs, and perceived or actual benefits of completing an MC. The questions included multiple choice, select all that apply, and open-ended format, respectively. The survey was sent using Google Forms; data were analyzed using descriptive statistics. We received 25 completed surveys (29% response rate). Results/Anticipated Results: Since 2019, 85 individuals completed MCs at Buffalo CTSI including 21 faculty, 18 trainees, 26 students, and 20 staff. The most popular MC, Responsible Research (65% of completers), is based on the Responsible Conduct of Research series, which consists of modules on authorship ethics, ethical use of animals (IACUC) and human subjects (IRB), conflicts of interest/commitment, and responsible data acquisition and management. We found that 33% of responders were motivated to obtain the MC to advance their career and for professional development, 30% for lifelong learning, and 23% intended to use the badges to showcase their proficiency to potential employers. The greatest benefits reported were to obtain knowledge/skills for their professional career (46%) and improve their ability to receive research funding (14%). Discussion/Significance of Impact: Micro-credentials are valuable learning tools to stay current on changing research requirements, with ability to engage asynchronously. Badges also provide unique professional development opportunities for students and research workforce (staff and community stakeholders) who have limited resources (time and money).

Objectives/Goals: As life expectancy increases in people with HIV, neurocognitive impairment is becoming more common, and women with HIV (WWH) are disproportionately impacted. This work investigated mitochondrial function and oxidative stress in WWH in order to understand the relationship between mitochondrial function and cognition in future studies. Methods/Study Population: Peripheral blood mononuclear cells were isolated from virally suppressed WWH (n = 64) and underwent the Seahorse Cell Mito Stress test to assess different realms of mitochondrial function. Cells were then lysed for direct DNA extraction, and quantitative PCR was performed to understand mitochondrial DNA expression (mtDNA) levels as a measure of oxidative stress. A series of simple linear regressions was then conducted to understand the relationships between mitochondrial function and mtDNA content. Future work will expand this analysis to investigate associations between demographic dynamics, such as trauma history, and mitochondrial function, as well as to understand the relationships between mitochondrial function and cognitive outcomes in WWH. Results/Anticipated Results: In our cross-sectional analysis of mitochondrial dynamics in WWH, we found a significant association between maximum mitochondrial respiration ability and mtDNA content, with greater mtDNA expression associated with increased levels of maximum respiration following stimulation. There was no association between basal respiration and levels of oxidative stress. There was also a significant variation in mitochondrial function in our participants, indicating that future analyses to investigate the source of that variation are warranted. The work presented here sheds light on mitochondrial dynamics in WWH and will be the basis for future studies that will investigate how demographic dynamics may be associated with mitochondrial function, as well as how mitochondrial dynamics may predict cognitive outcomes. Discussion/Significance of Impact: There is significant variation in mitochondrial function in WWH. More analysis is needed to understand what may be associated with these variations, including an investigation of both clinical factors as well as cognitive outcomes. This analysis will inform directions for future mechanistic work aimed at mitigating adverse cognitive outcomes in WWH.

Objectives/Goals: Physical activity (PA) is a well-documented protective factor against many cardiovascular diseases. PA guidelines to reduce these risks and the impact of variability are unclear, and most studies only examine a 7-day activity window. This study aimed to examine factors related to variability in step counts in a 3-year study of adults aged ≥18 years. Methods/Study Population: Included were 6,525 participants from the Michigan Predictive Ability and Clinical Trajectories study, a prospective cohort of community-dwelling adults enrolled between 8/14/2018 and 12/19/2019 who received care at Michigan Medicine and were followed for 3 years. Data were collected from Apple Watches provided to participants via the HealthKit. This secondary analysis included those with ≥4 valid weeks of data (≥4 days with at least 8 hours of wear time). Season was defined as Spring (March 20–June 20), Summer (June 21–September 21), Fall (September 22–December 20), and Winter (December 21–March 19). GEE models against the outcome of variability, defined as weekly standard deviation of step counts, and the predictor of season were adjusted for age, sex, race/ethnicity, weekly average step count, diabetes, and body mass index. Results/Anticipated Results: The average (standard deviation (SD) step counts by season were 7101 (3434) in Spring, 7263 (3354) in Summer, 6863 (3236) in Fall, and 6555 (3211) in Winter. Compared to winter, there was statistically significantly higher variability in all other seasons (p Discussion/Significance of Impact: In this cohort of community-dwelling adults, we found significant differences in variability of physical activity by season, age, and BMI. Future work will examine how this variability impacts the risk of development of cardiovascular disease, incorporating the impact and recovery trajectories of COVID-19 and other acute respiratory infections.

Objectives/Goals: Accurately stratifying patients with clinically isolated syndrome by risk of developing multiple sclerosis is of great clinical importance. Though numerous prediction models attempt to achieve this goal, no systematic review exists to independently evaluate these models. We aim to systematically identify and assess the risk of bias in all such models. Methods/Study Population: Studies developing or validating prediction models to assess risk of developing MS in patients with CIS who are not receiving an MS-indicated disease-modifying therapeutic will be identified via a systematic literature search. Studies will be evaluated for overall risk of bias using PROBAST (Prediction model Risk Of Bias Assessment Tool). Briefly, data sources, predictor, and outcome definition and assessment, applicability, and analysis will be assessed for each model in each identified study, and an overall risk of biased judgment will be assigned. Identified studies, predictors incorporated, results, and risk of bias assessment with accompanying rationale will be summarized in the final report. Results/Anticipated Results: Based on an initial exploratory search, we anticipate that most, if not all, identified prediction models will have high risk of bias. We anticipate that many studies will have limited applicability due to the use of outdated diagnostic criteria for definition of outcomes, or high risk of bias concerns originating from their analysis due to insufficient volume of included participants or poor model validation practices. We further anticipate that most, if not all, of the identified prediction models will have limited potential to be translated to use in a clinical setting. Discussion/Significance of Impact: Understanding how to identify patients with high-risk CIS may inform and improve clinician treatment decisions, patient outcomes, and future research study design. This work may also reveal flaws in current prediction models for CIS, opening new avenues of research and prompting development of improved prognostic models for patients with CIS.

Objectives/Goals: Identifying and indexing rare disease studies is labor intensive, especially in research centers with a large number of trials. To address this gap, we applied natural language processing (NLP) and visualization techniques to develop an efficient pipeline and user-friendly web interface. Our goal is to offer the rare disease study identification (RDSI) tool for adoption by other sites. Methods/Study Population: The RDSI retrieves study information (short and long titles, study abstract) from the IRB system. These descriptive fields are then processed by the MetaMap Lite NLP program for identifying disease terms and standardizing them to UMLS concepts. By terminology identifier mapping, the diseases intersecting with concepts in rare disease databases (Genetic and Rare Disease program and Orphanet) are further scored to pinpoint studies that focus on a rare disease. The web interface displays a scatter bubble chart as an overview of all the rare diseases, with each bubble size proportional to the number of studies for that disease. In addition to the visual navigation, users can search studies by disease name, PI, or IRB number. Search results contain detailed study information as well as the evidence used by algorithms of the pipeline. Results/Anticipated Results: The RDSI identification results and functions were verified manually and spot-checked by several study investigators. The web interface is a self-contained solution available to our staff for various use cases like reporting or environment scan. We have built in a versioning mechanism that logs the date of each major result in the process. Therefore, even as the rare disease data sources evolve over time, we will be able to preserve any historical context or perform updates as needed. The RDSI outputs are replicated to Mayo Clinic’s enterprise data warehouse daily, allowing tech-savvy users to leverage any useful intermediate results at the backend. We anticipate the performance of the rare disease identification to be further enhanced by employing the advancements in AI technology. Discussion/Significance of Impact: The RDSI represents an informatics solution that offers efficiency in identifying and navigating rare disease clinical studies. It features the use of public databases and open-source tools, manifesting return on investment from the broad translational science ecosystem. These considerations are informative and adoptable by other institutions.

Objectives/Goals: To assess the impact of the MATCH Program on mentees and mentors over the years, we have surveyed both groups on the effectiveness of the mentorship process, how the MATCH program influenced mentees’ future career plans, and their ongoing interest in clinical research. Methods/Study Population: To evaluate impact on mentees and mentors in the most recent cycle, we fielded two program evaluation surveys, for mentors and mentees. The surveys were distributed and collected using Qualtrics in May 2024. The mentee survey collected data on relationship with mentors, quality of mentorship, future career/education plans, and self-assessment of the program impact. The mentor survey collected data on relationship with mentees, mentees’ engagement, and a self-assessment of the program impact. Qualitative analysis was conducted to determine key themes expressed by participants. The responses were compared to assess the effectiveness of the mentoring relationship from both parties. Results/Anticipated Results: Respondents included 15/20 (75%) mentees and 15/20 (75%) mentors. All mentees (100%) and mentors (100%) stated they would like to continue their relationship outside of the program. The majority of mentees 13/15 (87%) and mentors 13/25 (87%) also viewed their mentee/mentor relationship to be excellent or good. Most mentors 10/15 (67%) stated it was their first time serving as a mentor for the program. Mentees also found their experience in the program very beneficial with 6/15 (40%) stating that MATCH changed their career plans. In addition, most mentees 14/15 (93%) indicated that they are community college or four-year college/university bound. Most mentees 11/15 (73%) indicated an interest in pursuing a health or medical career. Also, 10/15 (67%) mentees stated an interest in pursuing a career in research. Discussion/Significance of Impact: Both mentees and mentors have benefited from the program’s daisy chain mentoring and the program has helped facilitate a potential lifelong mentorship between mentees and mentors. The program also demonstrates promise of developing a pre-health pathway for historically underrepresented students in STEM.

Objectives/Goals: Originally presented at TS24, we would like to discuss follow-up outcomes and preliminary findings“Building Empowerment Through Fitness” – objectives were designed to address the “whole women” in underserved segments of the population in impoverished and/or underprivileged communities with fewer opportunities and promote economic mobility. Methods/Study Population: A qualitative study design to understand unique cultural context and challenges faced by women residing in the Birmingham Housing Authority, regarding physical activity engagement, including sedentarism. The needs assessment approach examined barriers, support systems, and social networks. Semi-structured, pre, mid, and post program focus groups explored challenges and opportunities for health, such as diet and exercise, and are being analyzed by hand with a thematic analysis. The project framework used movement, home repair tools with a life-building/life repair curriculum to influence self-efficacy and program engagement. The study enrollment included 51 women over two cohorts in a 12-week project. Results/Anticipated Results: Preliminary are results showed the women did face heightened health risks due to sedentary lifestyles, educational gaps, and socioenvironmental barriers. We incorporated tool skills, healthy lifestyles, and social/emotional focus group to explore social/emotional perceptions, concerns, and needs. Although our results were on target, there were some unexpected outcomes related to family dynamics, literacy, housing stability, and peer support. Discussion/Significance of Impact: Women are more likely to be sedentary and have poor health. BeFit served as a solution to addressing problems related to economic mobility barriers, poor health, sedentariness, and low self-esteem/self-efficacy. Additionally, exercise/movement programs can be a powerful tool to address disparities and help prioritize health.

Objectives/Goals: The Research Education and Community Health (REACH) coalition proposes to develop the infrastructure for continuous and comprehensive collection of community health data to drive programs, education, and funding priorities across municipal agencies, institutions, and nonprofit organizations in Galveston County. Methods/Study Population: The workgroup through REACH will organize and adopt a comprehensive community health needs assessment that 1) accumulates existing, readily available data for shared use (e.g., Center for Health Care Data at the UT School of Public Health, the Texas Department of State Health Services Center for Health Statistics, and Epic Cosmos, a data aggregation tool, used by UTMB and other health systems to improve patient care); 2) utilizes data collected throughout the community (i.e. non-profits, municipal agencies, and law enforcement); and 3) applies qualitative data from focus groups and/or key informant interviews, so we can hear directly from community members about what their needs are. By doing so, we hope all can benefit from having access to current and relevant data to drive our programs, education, and funding. Results/Anticipated Results: This Community Health Needs Assessment is being coordinated by a diverse workgroup including community organizations, researchers, and policy makers who will benefit from access to current and relevant data. The Galveston Youth Risk Student Survey, completed every three years and most recently in 2024, revealed lingering health and mental health effects of the COVID-19 pandemic on County youth. This highlighted the need for community access to current, accurate, and ongoing data to drive programming, interventions, and education. The REACH Coalition, made up of 23 UTMB Centers and Institutes and 39 community organizations, is spearheading this effort as a part of its mission to facilitate collaborative research, service, and educational efforts. Discussion/Significance of Impact: Collected data will be used to establish and support ongoing, coordinated interventions in response to identified needs. Shared ownership of data and project implementation optimizes resources and reduces gaps and/or redundancy in community programming.

Objectives/Goals: Professional coaching greatly enhances faculty personal and professional development through fostered empowerment and a culture of continuous growth within the academic environment. The UMN Clinical and Translational Science Institute (CTSI)’s coaching program provides a variety of coaching formats (1:1, group, special programs). Methods/Study Population: CTSI provides professional coaching to faculty in the KAP, K12, KL2, and K-R01 and NLITeS programs. Typically, coaching begins with a HoganLead™ assessment and debrief. Scholars may pursue further coaching through individual sessions (up to 6 sessions during or 1-year post CTSI award) or a monthly peer coaching group facilitated by certified coaches. New URM faculty hires in the Early Career Research Awards (ECRA) program receive monthly coaching support to problem solve and attend to wellbeing. The NLITeS leadership development program for senior and mid-career faculty includes the HoganLead debriefing and 1–2 individual coaching sessions. All sessions are confidential. Results/Anticipated Results: Since 2016/2017, 80 scholars have taken the HoganLead assessment (72 debriefs), and 23 scholars have made use of 217 individual coaching sessions (most use between 6 and 12). Since 2021, 10 Scholars have participated in the Peer Coaching Group with 7 continuing over multiple years. Since 2021, 12 ECRA scholars have been supported in monthly coaching. Frequent coaching topics include self-awareness, work-life balance, overwhelm, negotiation, and leaving academic medicine. Scholar comments include: “I initially approached this professional coaching with some curiosity but fairly minimal expectations that it would change much. It has reshaped the way I approach my academic career and its associated challenges for the better, giving me confidence that I can handle the unique challenges that this career presents…” Discussion/Significance of Impact: The UMN CTSI coaching programs are extensively used and highly valued by participating faculty. Professional coaching with Hogan assessments provides faculty scholars with support that complements the mentoring they receive by going beyond a teach and learn model.

Objectives/Goals: The overall goal of this project is to determine bacterial transcriptional signatures from clinical sputum and assess their potential to monitor treatment response and predict the outcome of drug therapy in patients with tuberculosis (TB). Methods/Study Population: We are developing a novel transcript capture sequencing (TC-Seq) approach to sequence the mRNA of Mycobacterium tuberculosis (Mtb) and analyze transcriptomes from clinical samples containing minimal amounts of bacterial RNA. This protocol generates single-stranded biotinylated probes from Mtb DNA. Probes are hybridized to and allow enrichment of Mtb-specific mRNA within next-generation RNA sequencing libraries. We will apply TC-Seq to sputum samples collected throughout an 18-month Phase II clinical trial investigating response to TB treatment to compare the transcriptome of Mtb between patients whose treatment results in cure or relapse. Results/Anticipated Results: We have refined a technique to generate biotinylated probes starting from DNA of lab grown Mtb. This protocol achieves robust and unbiased sampling of the Mtb transcriptome from mixed samples containing both human and Mtb RNA. Preliminary sequencing of clinical sputum collected pretreatment has generated 1–4 million Mtb-specific reads, a sequencing depth that allows examination of the entire bacterial transcriptome. We will measure differential gene expression before and during treatment as well as between cure and relapse cases. These results will allow us to characterize bacterial response to treatment and identify bacterial markers that correlate with relapse. Discussion/Significance of Impact: Understanding Mtb activity during treatment will offer new ways to assess the efficacy of different treatment regimens. Crucially, identifying clear bacterial markers that demarcate a cure or relapse outcome will have a significant impact on determining patient eligibility for shorter drug therapy.