Objectives/Goals: The aging population faces unique health issues, many of which are exacerbated by aging-associated immune function decline. However, the driving mechanisms behind this decline are poorly understood. We use a mouse model to study the relationship between extracellular matrix (ECM) stiffness and cell mobility within the lymph node (LN) as one potential driving mechanism. Methods/Study Population: We will collect LN from young (6 weeks old) mice and acquire LN from aged (11 month old) mice from a collaborator. We will section LN for ex vivo analysis, including quantification and localization of collagen I using immunofluorescent staining, analysis of microrheological properties using multiparticle tracking (MPT) with PEGylated fluorescent nanoparticles, and migration assays to track the movement of B and T cells. Results/Anticipated Results: We hypothesize a positive correlation between collagen deposits and stiffness within murine LNs due to known mechanisms underlying age-related fibrosis. We also hypothesize that areas of increased stiffness (as revealed by MPT) will exhibit decreased cell migration due to physical hindrance to B and T cell mobilization. Furthermore, we hypothesize that aged murine LN will exhibit a significant increase in stiffness and resultant decreased cell mobility when compared to young murine LN, particularly in areas with increased collagen localization. Discussion/Significance of Impact: These studies will elucidate structure–function relationships driving age-associated LN fibrosis and stiffness, and the resultant impedance to cell migration, thus clarifying some of the potential driving mechanisms behind immune aging and providing data capable of informing the development of relevant models and interventions.

Objectives/Goals: Undergraduate Medical Education (UME) may apply Just-in-Time training (JITT) to provide medical students with learning experiences closely aligned with real-time clinical needs. The purpose of this scoping review is to offer an overview of the implementation of JITT training in UME. Methods/Study Population: Following the five-stage framework by Arksey and O’Malley to methodically collect and analyze studies on JITT in UME, five electronic databases were searched, and a supplemental search for grey literature was conducted. Studies exploring the integration of JITT principles into UME clinical training and their time to follow-up after training were included. Bloom’s Taxonomy was used to assess educational goals of JITT interventions. Results/Anticipated Results: The review yielded 21 studies across 4 countries. The majority were cohort studies (13) and randomized control trials (5). Assessment definitions and use of JITT varied widely. Most studies focused on short-term outcomes, defined by being measured immediately after JITT session (15) or at the end of JITT-based rotation or clerkship (3). Three studies evaluated outcomes at a period longer than 2 weeks after completion of session or clerkship. Attitudes (9), followed by skills (8) were the most common educational goals of intervention. The efficacy and utility of JITT in improving educational goal acquisition was demonstrated in 90% (17/19) of the studies with reported outcomes. Discussion/Significance of Impact: The introduction of JITT in UME has been shown to meet the immediate needs of healthcare environments; however, evidence is limited in the evaluation of longer-term outcomes. Further research to determine the impact of JITT on long-term learning retention and education goal acquisition in UME is merited.

Objectives/Goals: This proposal outlines the successful deployment of a research training initiative to support the formation of a Learning Healthcare System. Mayo Clinic Health System (MCHS) rural providers were offered the opportunity to the fundamentals of clinical research via Clinical and Translational Science Awards core curriculum, mentorship, and an online seminar series. Methods/Study Population: MCHS funded 4 key introductory research courses: 1) Manuscript Writing, 2) Grant Writing, 3) Basic Biostatistics, and 4) Essentials of Clinical and Translations Science Program. In addition to course offerings, a Research Interest Group was formed to guide novice rural researchers on topic selection and study design. This cultivated interest to create a 16-month clinical research webinar series offering CME credits. Subsequently, an internal MCHS RFA was launched seeking early-stage investigator pilot proposals focused on rural health. Results/Anticipated Results: In 2023, over 140 MCHS providers enrolled in 324 CCaTS research courses. This training led to the submission of 53 proposals to the inaugural MCHS 2023 RFA, of which 15 were awarded. Additionally, 14 MCHS extramural grants were submitted in 2023. Training efforts expanded in 2024 to include an online research seminar series covering various study topics and providing CME credit, with an approximate attendance up to 196 attendees per session. The second annual MCHS RFA resulted in 4 internal awards, with an additional 22 extramural grant submissions. These collective efforts have increased the number of MCHS first and last author publications and the number of MCHS providers with academic rank. Discussion/Significance of Impact: Leadership’s commitment of resources to educate, mentor, and engage clinicians was crucial to our success and demonstrated a strong return on investment. To maximize impact in community-based practice, continued commitment is needed in the form of protected research time, funding, and research administration support of projects of interest

Objectives/Goals: Unhealthy lifestyle habits may increase medical students’ risk for metabolic dysfunction-associated fatty liver disease (MAFLD) and non-alcoholic fatty pancreatic disease (NAFPD). This study aims to investigate how these lifestyle factors affect liver and pancreas health in preclinical medical students using diagnostic ultrasound imaging. Methods/Study Population: Using diagnostic ultrasound imaging, we propose a research study to evaluate the anatomical changes of the liver and pancreas associated with lifestyle among medical students in UCC. Forty-two (42) medical students from the Central University of the Caribbean who are in their preclinical years will be recruited to perform an abdominal ultrasound. To measure the diameter of the right liver lobe, we will employ the craniocaudal measurement method established by Riestra. et al. (2018). The parameter established by Rumack et al. (2011) will be utilized to assess liver texture and categories by Lee JS et al. (2009) to pancreas fat infiltration grades. Results/Anticipated Results: This study expects to reveal a significant correlation between the lifestyles of preclinical medical students and the health of their liver and pancreas, particularly in size and texture. We anticipate identifying specific lifestyle factors – such as dietary habits and physical activity levels – that contribute to the prevalence of hepatic and pancreatic steatosis. Additionally, we expect to highlight the need for targeted interventions to promote healthier lifestyles among medical students to mitigate risks associated with MAFLD and NAFPD. Discussion/Significance of Impact: This study is significant for monitoring changes in liver and pancreas health, preventing complications, and improving health quality while reducing future costs. It may guide the creation of tailored wellness programs for medical students, enhancing their well-being and contributing to better healthcare practices and educational strategies.

Objectives/Goals: People experiencing homelessness (PEH) face excess cervical cancer burden and unique barriers to screening. As part of a broader study addressing cervical cancer disparities in homeless populations in Indiana, our goal was to engage unhoused women in a human-centered design process to inform a homeless shelter-based self-sampling intervention. Methods/Study Population: An established community-academic partnership enabled meaningful engagement of homeless communities in Indiana and informed the need to understand and address cervical cancer disparities in this population. Rapid assessment surveys (n = 202) and in-depth interviews (n = 30) were conducted with PEH at two major shelters in Indianapolis and Lafayette to understand cervical cancer screening coverage, knowledge, attitudes, and practices; barriers and facilitators; and acceptability of human papillomavirus (HPV) self-sampling for onsite shelter-based screening. A human-centered design session with (n = 12) unhoused women further explored motivators and concerns regarding self-sampling and informed key messages and informational materials to encourage uptake of screening. Results/Anticipated Results: At least 37% were overdue for screening (last screened >5 years ago; 50% were last screened >3 years ago), far greater than national (22%) or state (24%) averages. Despite common misconceptions regarding indifference toward preventive healthcare among homeless populations, most (87%) wanted to be screened and believed it is important for their health. Competing priorities for daily survival, transportation, cost, provider mistrust, stigma, and related trauma were common barriers to screening. Enthusiasm for HPV self-sampling centered on convenience, privacy, and comfort in taking one’s own sample at the shelter. Notable concerns included lack of confidence regarding ability to self-sample correctly, unhygienic conditions in shelter restrooms, preference to be seen by a doctor, and the need for education. Discussion/Significance of Impact: The unique challenges of PEH require human-centered strategies to improve cervical cancer screening access. Willingness to be screened and acceptability of HPV self-sampling is high. Identified concerns and preferences will guide implementation of HPV self-sampling delivered by trusted community health workers in homeless shelters in Indiana.

Objectives/Goals: The Fanconi anemia (FA) pathway is responsible for faithful DNA damage repair. FA mutations are common in multiple types of cancer, including HPV-negative head and neck cancers. We sought to identify synthetic lethal genes within this pathway to target treatment of FA-mutant tumors through siRNA- and chemical-compound-based screens. Methods/Study Population: First, we completed siRNA-based and chemical compound-based screening assays to identify gene targets that reduce patient derived Fanconi pathway mutant cell (FA-D2) viability compared to Fanconi pathway proficient cells (FA-D2 + FANCD2). Five aurora kinase (AURK) inhibitors from the compound screen were chosen for further evaluation. Cell lines were treated with AURK inhibitors or siRNA-based AURK knockdown to assess viability, proliferation, DNA repair, and cell cycle progression differences. Patient mutational, mRNA expression, and outcome data were accessed through The Cancer Genome Atlas (TCGA) portal and the Caris CODEai portal. We stratified patients by tumor AURKA and AURKB mRNA levels and assessed differences in patient survival, tumor grade, and DNA repair proficiency. Results/Anticipated Results: In both screens, AURKA came up as a target to selectively reduce the growth of FA-D2 cells compared to FA-D2 + FANCD2 cells. All five AURK inhibitors identified showed selective growth inhibition (~50–75%) in FA-D2 cells at low nanomolar doses. We narrowed our selection to hesperadin, an AURKB-specific inhibitor, which showed the highest selectivity. siRNA knockdown of AURKA and AURKB decreased cell viability by 50% and 20%, respectively. Patients with FA-mutated tumors from the TCGA pan-cancer dataset had high AURKA (twofold) and AURKB (threefold) mRNA expression. AURKA and AURKB tumor mRNA expression was significantly associated with poor patient survival. Homologous recombination deficiency scores were increased ~5-fold (p Discussion/Significance of Impact: We hypothesize that in FA-deficient backgrounds, loss of AURKA or AURKB leads to heightened genomic instability due to cell cycle dysregulation and accumulated DNA damage. Our findings warrant investigation of the therapeutic potential for AURK inhibitors, specifically hesperadin, in FA-mutant head and neck cancers.

Objectives/Goals: Failure to achieve recruitment goals results in termination of ~20% of clinical trials and delays >85% of trial timelines. We aim to develop an electronic heath record (EHR)-based recruitment tool to ease identification of participants. We sought to determine whether criteria listed on clinicaltrials.gov could support selection of tool variables. Methods/Study Population: To inform the variables to include in the EHR-based recruitment tool, we data scraped clinicaltrials.gov to identify key inclusion and exclusion criteria common across a variety of diabetes clinical trials. We included actively recruiting or recently active phase 2 and 3 clinical trials of adults aged >18 years of age in the USA. We classified identified variables as clinically relevant or not and compared clinically relevant terms with inclusion and exclusion criteria (~20 variables) that were individually identified by three diabetes clinical trialists and two clinical research coordinators (CRCs). Results/Anticipated Results: We reviewed 203 clinical trials listed on clinicaltrials.gov. We identified 115 terms, 91 of which were clinically relevant. Three of 3 clinical trialists, 1 of 2 CRCs, and all trials listed age as a key variable. Consistent with data scraping, all trialists and CRCs identified glucose-lowering medications and kidney function as important criteria. Gender, ethnicity, and race were less commonly noted on clinicaltrials.gov and listed by 2 of 3 trialists and one CRC. Cardiovascular conditions (e.g., history of myocardial infarction), thyroid function tests, and contraceptive requirements were common criteria on clinicaltrials.gov, but only one trialist and one CRC identified these variables. Active infections (e.g., HIV) and c-peptide were not highlighted by trialists or CRCs but common on clinicaltrials.gov. Discussion/Significance of Impact: An EHR-based recruitment tool may facilitate identification of trial participants, but identifying key variables to include is essential. We found that data scraping for variables on clinicaltrials.gov mostly aligned with expert opinion, suggesting that automating variable selection via extraction from clinicaltrials.gov may be acceptable.

Objectives/Goals: Translational researchers often struggle to navigate a complex constellation of institutional resources spanning the IRB to bioinformatics units. We had two aims 1) Systematically map all institution-wide research support units and 2) leverage this database within a generative AI virtual concierge tailored to local investigator queries and needs. Methods/Study Population: This study leveraged mixed methods approach. First, we conducted needs assessments of local study teams to identify barriers to translation, revealing that research resources are often unknown to study teams. Second, we identified all investigators, institutional units, and offices offering such resources that we call research support units (RSUs). RSUs were surveyed, collecting contact information (leadership, website, physical location), services provided, type of research supported, and performance metrics. Third, the resource database was integrated into a large language model (LLM, e.g., ChatGPT4o) using a retrieval augmented generation (RAG) system within an R Shiny application called virtual concierge. Queries and responses are recorded for quality improvement. Results/Anticipated Results: Needs assessment focus groups consisted of clinical and basic science investigators, study team members (e.g., clinical research assistants), core directors, and administrators (n = 26). Six sessions were conducted in Spring 2024. A major resultant theme was difficulty finding RSUs “by trial and error” and lacking a “clear defined pathway” for accessing RSUs. This prompted a survey-based environmental scan to identify institutional research resources. There were 122 diverse RSUs ranging from the IRB, to grant writing, to single cell sequencing. Each research unit offered a median of 6 service types, totaling 410 service types overall. The resultant Virtual Concierge meaningfully responds to investigator resource queries with appropriate contact and access information. Usability testing is underway. Discussion/Significance of Impact: Linking researchers with translational resources requires mutual understanding, timely communication, and coordination across teams. We systematically filled these information gaps between investigators and institutional resources. Our Virtual Concierge AI bot can help researchers navigate resources through the translational process.

Objectives/Goals: Decentralized clinical trials (DCTs) shift participation outside traditional sites. This poster explores innovative administrative strategies for incorporating decentralized elements, improving flexibility, access, and efficiency in clinical research. Methods/Study Population: Modern administrative approaches are crucial for unlocking DCT potential by streamlining logistics, enhancing participant experience, and ensuring regulatory compliance. Key innovations include expedited IRB Review: using innovative template language; innovative consent strategies – eConsent and remote/virtual and contactless enrollment; telehealth communications – Twilio (voice calls and text messages)/Zoom (virtual video visits); automated participant compensation and rideshare services – Greenphire ClinCard®; flexible data collection – automated recruitment/intake forms and research surveys – REDCap; mobile research unit/self-collection lab kits via mail. Implementing decentralization into your study unlocks the potential to rapidly recruit more diverse populations. Results/Anticipated Results: The integration of decentralized elements into clinical trials holds significant potential for reducing participant burden, thereby improving recruitment, retention, and overall trial efficiency. However, the success of decentralized clinical trials relies heavily on the implementation of modern administrative approaches that streamline operations and maintain regulatory compliance. Together, these administrative advancements not only enhance the operational flexibility of decentralized trials but also support the inclusion of diverse populations by reducing geographical and logistical barriers. Discussion/Significance of Impact: As decentralized clinical trials continue to evolve, the adoption and further innovation of modern administrative solutions will be essential in improving the overall efficiency and inclusivity of clinical research.

Objectives/Goals: Collaborations between Academic Medical Centers (AMCs) and Historically Black Colleges & Universities (HBCUs) are critical to addressing health disparities and building research capacity. Herein, we examine the Duke-NCCU Collaborative Translational Research pilot funding program [2018–2023] to identify opportunities, challenges, and lessons learned from querying key stakeholders. Methods/Study Population: The Duke-NCCU collaborative pilot funding program was launched to support new inter-institutional collaborations that aim to accelerate research discoveries into testing in clinical or population settings. Eight one-year, $50,000 collaborative grants were awarded. Each funded team was assigned a CTSI Project Leader (PL) for project management support. To evaluate the program, we developed surveys targeting principal investigators (PI) and PLs. Questions covered collaboration motivation, goals, outcomes, operational processes, project management support, institutional differences, and challenges. Qualitative analysis will be employed to evaluate the responses and identify common themes. Results/Anticipated Results: The PI survey examines aspects of inter-institutional collaborations, focusing on common themes, such as authorship, definition of success, and institutional culture. The PL survey prompts feedback on managing inter-institutional teams, expectations, and challenges. Select questions were shared between both surveys to capture both perspectives. Surveys were reviewed by members of the Duke CTSI evaluation and team science teams. The PI survey will be disseminated to 16 investigators, while the PL survey will reach 5 project leaders. Built on Qualtrics, each survey takes 20–30 minutes to complete. To encourage participation, incentives will be offered as two $100 gift card drawings. Respondents can choose to complete the survey on Qualtrics or through a recorded and transcribed Zoom session. Discussion/Significance of Impact: AMC-HBCU inter-institutional collaborations drive innovation, workforce development, and equitable dissemination of outcomes. This study exemplifies collaboration, offering insights into translational research collaborations critical to advance equitable healthcare and improving population health.

Objectives/Goals: This Weill Cornell Clinical and Translational Science Collaborative (CTSC) project evaluates whether large language models (LLMs) can generate accurate summaries of translational science benefits using the Translational Science Benefits Model (TSBM) framework, aiming to identify optimal LLMs and prompting strategies via expert review. Methods/Study Population: We are using prompt engineering to train multiple LLMs to generate one-page impact profiles based on the TSBM framework. LLMs will be selected via benchmarks, focusing on models excelling in information extraction. Leading LLMs (e.g., Llama 3.2, ChatGPT 4.0, Gemini 1.5 Pro, and Claude) and other high-performing models will be considered. Initial work has utilized Gemini 1.5 Pro. Models use data from CTSC-supported projects in WebCAMP, our local instantiation of a translational research activity tracking system used by >20 CTSA hubs, and manuscripts from the Overton database cited in policy documents. Human experts will evaluate the quality and accuracy of LLM-generated profiles. Results/Anticipated Results: Preliminary results using Gemini 1.5 Pro indicate that LLMs can generate coherent and informative impact profiles encompassing diverse areas within the TSBM. Face validity appears satisfactory, suggesting the outputs align with expectations. We anticipate that further exploration with other LLMs and expert validation will reveal strengths and weaknesses of the LLM approach, including the potential for naccuracies (“hallucinations”), informing further refinement of models and prompting strategies. Analysis of manuscripts cited in policy will provide valuable insights into communicating policy-relevant benefits effectively, and benchmark comparisons will identify optimal LLMs for this use case. Discussion/Significance of Impact: This project demonstrates LLMs’ potential for streamlining and enhancing impact reporting in translational science, enabling broader dissemination of research outcomes and promoting better understanding among stakeholders. Future work will integrate LLM-based reporting into research infrastructure.

Objectives/Goals: This study evaluates the role of visual machine learning algorithms (VMLA) in automating a predictive model of central sarcopenia in geriatric trauma patients based on the psoas:lumbar vertebral index (PLVI) and trauma-specific frailty index (TSFI). Methods/Study Population: 150 trauma patients seen at Jon Michael Moore Trauma Center within J.W Ruby Memorial Hospital in rural West Virginia were included in this investigation across the life spectrum. The VMLA was trained on their standard of care trauma panoramic CT scans. Five expert reviewers segmented bilateral psoas muscles and the L4 vertebrae of each CT image at one slice inferior to the posterior elements of the L4 vertebrae. The data were read into a U-net convoluted neural network as ground truth. Labels were preprocessed to focus on the regions of interest and standardized into four classes: right psoas, left psoas, L4 vertebrae, and background. Performance was evaluated using accuracy, Dice coefficient, and F1 score. Results/Anticipated Results: Between our expert reviewer segmentations, we had significant inter-reader reliability with a Kappa greater than 0.8 and a mean standard deviation of the PLVI of 0.10mm^2. Preliminary VMLA testing on a subset of 70 patients yielded a validation accuracy of 88.5%, a Dice coefficient of 0.86, and an F1 score of 0.87 after 20 epochs. There was a moderate interclass correlation between PLVI and TSFI even though the TSFI lacks sensitivity. In fact, the PLVI is a more accurate predictor of frailty in trauma patients based on various outcome measures such as corrected length of stay. Our ongoing efforts are centered around improving the VMLA. Discussion/Significance of Impact: Our VMLA outperforms the current clinical standard, TSFI. Integration of our VMLA into the clinical workflow has the potential to revolutionize geriatric trauma care by providing rapid, accurate, identification of high-risk frail patients.

Objectives/Goals: Discriminatory experiences within healthcare settings significantly hinder equitable health access for sexual minority groups (SMPs) in the USA. These discriminatory experiences can manifest in various forms (e.g., refusal of care). We aimed to explore different types of discrimination encountered by SMPs in the healthcare settings. Methods/Study Population: This study utilized secondary data from the NIH All of Us Research Program. For this analysis, we selected cohorts self-identifying as gay (n  =  9,454), bisexual (n  =  15,284), lesbian (n  =  5,267), and straight (n  =  349,748), enabling robust comparisons across SMPs and straight individuals. We employed analysis of variance and Chi-square analyses to assess group differences in healthcare discrimination, using key indicators from the Discrimination in Medical Settings Scale. These indicators captured experiences such as being treated with less respect or courtesy and feeling ignored by healthcare providers, providing a comprehensive view of discriminatory encounters in healthcare settings for SMPs. Results/Anticipated Results: Our analyses revealed that bisexual individuals reported the highest levels of healthcare discrimination (mean  =  3.64, SD  =  2.45), followed by lesbians (mean  =  3.37, SD  =  2.47), other SMPs (mean  =  3.36, SD  =  2.53), gay (mean  =  2.69, SD  =  2.47), and straight participants (mean  =  2.60, SD  =  2.42). Among the seven discrimination indicators, the most reported experience was feeling like a doctor or nurse was not listening, with 76.8% of bisexual participants, 72.3% of lesbians, 68.8% of other SMPs, and 56.9% of gay participants reporting this experience. This was followed by reports of being treated with less respect and being treated with less courtesy in healthcare settings. These findings highlight the pervasive nature of healthcare discrimination among SMPs, particularly bisexual individuals. Discussion/Significance of Impact: SMPs experience higher levels of discrimination in healthcare settings compared to their straight counterparts. Our results underscore the urgent need to foster respectful, inclusive healthcare environments and ensure that healthcare providers are adequately trained to address the unique health needs and experiences of SMPs.

Objectives/Goals: The second highest fear of the aging population is cognitive decline. Diet is associated with brain aging; therefore, the objective is to determine the effects of a Western diet (WD) on cognitive decline and the efficacy of a Mediterranean diet (MeDi) fecal microbiota transplant (FMT) in WD-induced cognitive deficit progression in aged rats. Methods/Study Population: For Study 1, 12-month-old Fischer344 rats (NIA Aging Colony) will be randomly assigned to a WD, MeDi, or control (positive control) for 6 or 12 months. Microbiota composition, blood pressure, and body composition (DXA Scan) will be longitudinally assessed. Groups will undergo a battery of neurobehavioral assessments to measure cognitive performance. At the end of the study, mitochondria bioenergetic assays in isolated cerebral microvessels will be used to determine changes in cerebrovascular function. For Study 2, 18-month-old Fischer344 rats (NIA Aging Colony) will be randomly assigned to a WD, MeDi, or control for 6 months. At month 4, the WD+ MeDi-FMT group will receive once weekly MeDi-FMT for two months. Assessments will be performed as described in Study 1. Results/Anticipated Results: It is anticipated that the WD-related gut dysbiosis will increase blood pressure, fat-free mass, neurovascular dysfunction, and induce cognitive impairment relative to a MeDi. When using a MeDi-FMT as an intervention, it is anticipated that there will be measurable improvements in cognitive function relative to a WD through the regulation of gut dysbiosis, blood pressure, fat-free mass, and neurovascular dysfunction. Discussion/Significance of Impact: These results are expected to have an important positive impact because they will provide insights into the WD-induced gut dysbiosis-associated cognitive impairments, and evaluate the roles and mechanisms of MeDi-FMT in the therapeutic intervention of aged rats.

Objectives/Goals: The Translational Science Benefits Model (TSBM) offers a key framework for demonstrating the real-world health outcomes of research. This study uses a mixed-methods approach combined with the TSBM to show how researchers from Case Western Reserve University’s Clinical and Translational Science Collaborative (CTSC) have advanced health equity or improved public health in the USA and globally. Methods/Study Population: Using the TSBM indicators, we surveyed 72 former CTSC KL2 Program trainees and 469 CTSC Pilot Program awardees for documented evidence that their research led to demonstrated health benefits. We used purposive sampling of the survey responses to obtain examples highlighting research that led to advances in health equity as well as international public health improvements. We conducted in-depth interviews with six investigators to assess the populations impacted and the scope of their contributions. For each investigator, we examined how their publications informed both national and international policy. Through this approach, we will present specific case studies highlighting research that led to advances in health equity as well as international examples of public health improvements. Results/Anticipated Results: Among KL2 Scholars, we achieved a 40% response rate (29/72), with 90% (26/29) reporting 86 significant benefits across the four TSBM areas. For Pilot Program awardees, 18.5% responded (87/469), with 40% documenting 136 benefits. Several different types of translational science benefits resulted in improved health and health equity for several diverse national and international beneficiaries, including racial and ethnic minorities (e.g., Blacks, Hispanics), potentially vulnerable populations (e.g., pregnant women, victims of intimate partner violence, individuals on Medicaid, infants), international populations (e.g., people from low-resource countries with genetic disorders or parasitic infections), as well as people from rural areas and professions at high risk of developing cancer. Discussion/Significance of Impact: Leveraging KL2 and Pilot Grant successes, the TSBM shows how research improves public health and health equity for underserved populations. It streamlines outcome reporting, enabling researchers to demonstrate their societal impact while providing funders and policymakers with clear, data-driven evidence of the value of translational science.

Objectives/Goals: Research participants are not representative of our communities. To determine research perceptions, we are recruiting individuals who have and have not participated in studies. We aim to identify trends, capturing motivating factors, access barriers, and participants’ concerns to inform best practices to engage participants. Methods/Study Population: We developed a 25-item survey with a goal of engaging 500 individuals. Survey questions were developed based on published literature of research motivations and barriers, as well as focus groups conducted in our central Pennsylvania community. Survey questions consist of Likert-scale, multiple choice, and free text, with administration through REDCap. Potential survey participants will be recruited from the Penn State Volunteer Repository and through partnering clinical networks, including federally qualified health centers. We will also recruit individuals who have never participated in research to engage underrepresented groups via the Penn State Clinical and Translational Science Institute’s community partner network. Analyses will include Chi-squared tests and binomial logistic regression. Results/Anticipated Results: The primary dependent variable will be past participation in research, while the primary independent variables will be binary responses to questions relating to motivators and barriers to participation in research. Secondary analysis will stratify these comparisons by race or rurality with a subgroup analysis using the same methods as the primary analysis. Based on these analyses, we anticipate that those who have never participated in research will face greater and different barriers than those who have participated in research. We also anticipate that motivators will be similar between to the two groups. We anticipate finding differences in motivators and barriers among different races as well as differences when examining rurality versus non-rurality. Survey results will be available in January. Discussion/Significance of Impact: This will be one of the few studies in the literature focused on uncovering motivators and barriers to research participation. Understanding what motivates and prevents individuals from participating in research is one of the first steps to enhancing the research process so that people want, and are able, to participate in studies.

Objectives/Goals: This study aimed to investigate the role of artificial intelligence (AI) in translational science, including personalization of interventions and drug development. Methods/Study Population: A comprehensive literature search was conducted via PubMed, the Cumulative Index for Nursing and Allied Health Literature (CINAHL), Cochrane Library, Medline, and Web of Science. The risk of bias in the eligible studies was assessed using the risk of bias in nonrandomized studies. Data were systematically extracted and analyzed. Results/Anticipated Results: The literature search yielded 2129 records, from which 20 studies that met the eligibility criteria were included. Meta-analysis demonstrated the high specificity of AI-based diagnostics, reassuring the reliability of AI. Furthermore, AI applications significantly improved biomarker identification through machine learning algorithms, enhancing prognostic accuracy and treatment personalization. Moreover, AI showed enhanced diagnostic precision with high sensitivity and specificity in cancer detection, further validating its role in healthcare. AI-driven risk stratification was used in chemotherapy decisions. Discussion/Significance of Impact: This study highlights the transformative power of AI in translational oncology research with applications in drug development and personalized patient care in cancer treatment and research.

Objectives/Goals: Injury to the medial knee ligaments (sMCL, dMCL, POL) and anterior cruciate ligament (ACL) can cause anteromedial rotatory instability (AMRI). AMRI can cause knee instability and ACL graft failure, but it is unclear how the sMCL, dMCL, POL, and ACL resist AMRI. We aimed to characterize the in-situ forces of the sMCL, dMCL, POL, and ACL under loading conditions involved with AMRI. Methods/Study Population: We characterized the in situ forces of the sMCL, dMCL, POL, and ACL under 1) isolated external tibial rotation torque (ER), 2) isolated anterior tibial force (Ant), and 3) combined ER+Ant loading. Twenty-eight human cadaveric knees (18 male; mean age, 48±13; 21–65 years) were tested on a robotic manipulator with force sensing. Tibiofemoral kinematics were recorded under isolated ER (4Nm, 0–90°), isolated Ant (134N at 0–90°), and combined ER+Ant (4Nm+100N at 15, 30, 90°). The sMCL, dMCL, POL, and ACL were dissected in random order. The in situ force (N) in the sMCL, dMCL, POL, and ACL at the peak applied load for each loading condition was calculated using superposition and compared with Kruskal–Wallis tests with post hoc pairwise testing using a Bonferroni–Holm correction for multiple comparisons (α = 0.05). Results/Anticipated Results: Under isolated ER, the force in the sMCL (32–52N) from 0°-90° exceeded that of the ACL, dMCL, and POL at each flexion angle (p0.05). Force in the ACL was the second highest (26–6N from 0°-90°). Force in the dMCL and POL was low (≤12N). Under isolated Ant, the ACL carried the highest force at all flexion angles (≥113N) (p0.05), but at 90° the sMCL carried the highest force of all ligaments (p0.05). At 90°, force in the dMCL diminished (Discussion/Significance of Impact: We show that the sMCL is the major stabilizer to external rotation torques and combined anterior and external loading conditions related to anteromedial rotatory instability across the arc of knee flexion, while the dMCL, POL, and ACL play a less prominent role, with the exception of the ACL and dMCL near full extension.

Objectives/Goals: The impact of the program on alumni students was measured in a 2023 survey, which assessed key factors and student perspectives on motivation to apply/remain in the program, their engagement activities, how they used the skills acquired in RAP upon graduating, and if they were currently serving in a health profession and/or clinical research. Methods/Study Population: Survey questions were based upon specific components of CTSI-RAP that make it unique. Covered topics related to motivation for participation, meaningful experiences, program effectiveness, future use of RAP knowledge/training, and current career roles in the health professions and/or clinical research. The survey was built and analyzed in REDCap and deployed May–July 2023. The study received exempt certification from the IRB. The survey was sent to 123 alumni from the 2013 to 2021 cohorts. Bounced e-mails were followed up on and two reminder e-mails were sent to initial non-responders. Identifiable demographic information was separated from program evaluation questions for analysis. A subanalysis was performed to determine program impact on students who identified as underserved or disadvantaged. Results/Anticipated Results: Respondents included 82/123 (66.7%) alumni. The survey took approximately 15 minutes. Most of the students 64/82 (78.0%) had 1 year or less research experience. The top three motivating factors for joining the RAP program were gaining clinical research experience, exposure to healthcare settings, and interest in pursuing a healthcare related career. Most alumni rated the overall effectiveness of the RAP program as very or somewhat valuable and the majority felt that the program ranked high or very high among their undergraduate experiences. The program was very influential or influential in defining their long-term plans and goals. Just under half felt that their career aspirations were changed or influenced by the program, which was especially true for those who identified as underserved/disadvantaged. Discussion/Significance of Impact: CTSI-RAP alumni highly value their experience in the program. They have benefitted professionally and are motivated to keep their connection to the program alive. With a decade of clinical research excellence and programming, CTSI-RAP’s impact is well established as a proven model benefiting both students and the clinical research infrastructure.

Objectives/Goals: The expanding emphasis on translational science necessitates a rethinking of traditional academic formats. To align with the central themes of CTS, we have redesigned our PhD journal club and WIP sessions, introducing novel and innovative approaches that enhance the relevance of these activities to real-world scientific and clinical challenges. Methods/Study Population: The newly adapted journal club format for CTS Predoctoral students at Mayo Clinic maintains the traditional focus on literature review but now incorporates a structured analysis of the clinical implications and potential applications of the research. This innovation aims to foster a deeper understanding of how basic research findings can be translated into improved patient outcomes and healthcare practices. Similarly, the WIP sessions have been restructured to offer an engaging and dynamic learning environment designed to empower clinical and translational science predoctoral students to effectively present their research while emphasizing the challenges they have overcome, demonstrating the translational potential of their findings, and enhancing their communication skills. Results/Anticipated Results: Feedback from participants demonstrates strong support for the new format. Students report a greater engagement with the material and a clearer understanding of how their research can contribute to improving patient outcomes. Discussion/Significance of Impact: These changes accommodate the diverse projects in CTS and embody a commitment to pushing the boundaries of knowledge in CTS. This dual transition marks a significant advancement in preparing PhD students for careers in translational science, ensuring that their research is not only rigorous but also impactful in the real world.