Objectives/Goals: To identify and characterize future potentially high impact research generated by the Clinical and Translational Science Awards (CTSA) Program, we evaluated the Altmetric Attention Scores (AAS) of recent articles associated with the Program and conducted an initial assessment of the attributes associated with high AAS for Program articles. Methods/Study Population: We used the NIH Query, View, Report (QVR) tool to identify recently-published scientific papers that cited support from a CTSA Program grant. The unique publications identified by QVR were used to construct an Altmetric Explorer report. We examined the relationship between the AAS and other variables, including number of authors, number of grants supporting the publication, number of CTSA program institutions supporting the publication, and if the publication included group authorship. Results/Anticipated Results: Our analyses confirmed that the Program indeed supports potentially high impact research, as indicated by the highest scoring papers, across a wide range of diseases and conditions. Nearly all the highest scoring papers were focused on a specific disease or condition rather than broader methodological research, despite the disease-agnostic focus of the CTSA program. We also found that the Program significantly contributed to critical research on the once-in-a-century COVID-19 pandemic. We confirmed the entire CTSA consortium is contributing to potentially high impact research, with all institutions represented in the highest scoring publications. Discussion/Significance of Impact: Understanding the impact of the CTSA Program presents a unique challenge – the program supports biomedical research infrastructure and training programs whose outcomes and impact can be difficult to track or measure. These data offer early signals of impact and can assist evaluators with designing future evaluations.

Objectives/Goals: Osteoarthritis (OA) is a multifactorial disease where sustained gut inflammation is a continued source of inflammatory mediators driving degenerative processes in joints. The goal was to use spontaneous equine model to compare fecal and leukocyte microbiome and correlation to transcriptome in OA. Methods/Study Population: Seventy-six horses (31 OA, 45 controls) were enrolled by population-based sampling. Feces and peripheral blood mononuclear cells (PBMC) were collected. Horses were determined to have OA by clinical and radiographic evidence. Horses were excluded if they received medications or joint injections within two months. Fecal and circulating leukocyte bacterial microbial 16s-seq was performed. Bulk RNAseq of PBMC was performed by the Illumina platform. Gene expression data were mapped to the equine genome, and differential expression analysis was performed with DESeq2. Qiime2 was used for microbial analysis. Enrichment analysis was performed with a cluster profiler. Correlation analyses were performed between the datasets. Results/Anticipated Results: Beta and alpha microbial diversity differed in feces and PBMC of OA vs. healthy horses. Horses with OA had an increased Firmicutes to Bacteroidetes ratio compared with controls. The fecal microbiome of OA horses had significantly higher amounts of Firmicutes Oribacterium (q Discussion/Significance of Impact: These data suggest that altered microbiome and PBMC gene expression are associated with naturally occurring OA in the translational equine model. While Oribacterium has been detected in humans with rheumatoid arthritis, its role in OA warrants further proteomic and metabolomic profiling.

Objectives/Goals: Sexual minority populations report a disproportionately high prevalence of alcohol use, often attributed to coping with bi/homonegativity and systemic inequities across various social domains. This study aims to explore alcohol use patterns and associated neighborhood and individual factors among sexual minority populations (SMPs) using data from the NIH All of US dataset. Methods/Study Population: Alcohol use was assessed using the AUDIT-C (Alcohol Use Disorders Identification Test—Consumption) scale across a sample of 9,454 gay, 15,284 bisexual, 5,267 lesbian, and 349,748 straight participants. The AUDIT-C measured hazardous alcohol use, and logistic regression models were employed to examine its association with neighborhood-level factors (e.g., socioeconomic status, alcohol outlet density) and individual-level factors (e.g., age, race/ethnicity, income, and education) among SMPs. Interaction terms assessed how these relationships varied by sexual orientation. Sensitivity analyses were conducted to assess the robustness of the findings, including stratified analyses by gender identity and the exclusion of extreme outliers in alcohol use reporting. Results/Anticipated Results: Our analyses revealed that gay participants had the highest AUDIT-C scores (mean  =  3.60, SD  =  2.27), followed by bisexual (mean  =  3.35, SD  =  2.21), other SMPs (mean  =  3.18, SD  =  2.19), lesbian (mean  =  3.04, SD  =  2.08), and straight individuals (mean  =  3.05, SD  =  2.06). Alcohol use was positively associated with neighborhood disorder (β  =  0.12, 95% CI  =  0.07, 0.17), housing insecurity (β  =  0.14, 95% CI  =  0.03, 0.25), and male gender (β  =  0.98, 95% CI  =  0.96, 1.00). In contrast, neighborhood density (β  =  -0.11, 95% CI  =  -0.15, -0.07), food insecurity (β  =  -0.14, 95% CI  =  -0.20, -0.08), being Black, and identifying as bisexual were negatively associated with alcohol use. Sensitivity analyses determined no significant differences among specfic supgroups. Discussion/Significance of Impact: This study highlights important differences in alcohol use across SMPs and emphasizes the influence of neighborhood-level stressors (e.g., disorder and housing insecurity). These findings underscore the need for addressing social and environmental determinants of alcohol use in SMPs to mitigate the negative impacts of alcohol consumption.

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: Arterial stiffness is a determinant of vascular health. Older Black females exhibit greater arterial stiffness than White females. Exercise minimizes negative health effects of prolonged exposure to adverse social determinants of health (SDoH). Here, we will assess the role of exercise on race differences in arterial stiffness and SDoH in females. Methods/Study Population: We will recruit 96 postmenopausal females (48 Black, 48 White) from the Birmingham, AL area. Graded exercise tests will be used to define training status (“trained”: VO2max ≥60th percentile, “untrained”: ≤35th percentile). We will assess arterial stiffness via pulse wave velocity (SphygmoCor XCEL). SDoH will include income, education, neighborhood deprivation, racial discrimination, food insecurity, and healthcare access, all measured via corresponding surveys. We will then perform a two-way analysis of variance (race × training status) to assess the differences in arterial stiffness between groups. Through linear regression, we will evaluate the statistical relations between arterial stiffness and race, training status, and SDoH. Results/Anticipated Results: Our central hypothesis is that Black females will have greater arterial stiffness, by way of greater exposure to adverse SDoH, than White females, but that habitual aerobic exercise will attenuate this race difference. Ultimately, we aim to inform future clinical trials related to understanding female-specific cardiovascular disease progression. Discussion/Significance of Impact: Black females face significant exposure to adverse SDoH and have the highest rates of cardiovascular disease in the United States. However, females are still widely underrepresented in relevant research. This will be the first study to examine the roles of aerobic exercise, race, and SDoH in cardiovascular disease risk among females.

A common and unfortunate error in statistical analysis is the failure to account for dependencies in the data. In many studies, there is a set of individual participants or experimental objects where two observations are made on each individual or object. This leads to a natural pairing of data. This editorial discusses common situations where paired data arises and gives guidance on selecting the correct analysis plan to avoid statistical errors.

Objectives/Goals: In recent years, there has been growing interest in the development of air pollution prediction models, particularly in low- and middle-income countries that are disproportionately impacted by the effects of air pollution. Recent methodological advancements, particularly in machine learning, provide novel opportunities for modeling efforts. Methods/Study Population: We estimate daily ground-level fine particulate matter (PM2.5) concentrations in the Mexico City Metropolitan Area at 1-km2 grids from 2005 to 2023 using a multistage approach. Spatial and temporal predictor variables include data from the moderate resolution imaging spectroradiometer (MODIS), Copernicus Atmosphere Monitoring Service (CAMS), and additional meteorological and land use variables. We employed machine-learning-based approaches (random forest and gradient boosting algorithms) to downscale satellite measurements and incorporate local sources, then utilized a generalized additive model (GAM) to geographically weight predictions from the initial models. Model performance was evaluated using 10-fold cross-validation. Results/Anticipated Results: On average, the random forest, gradient boosting, and GAM models explained 75, 82, and 83% of variations measured in PM2.5 concentrations. PM2.5 levels were generally higher in densely populated urban centers and lower in suburban and rural areas. Important predictors of ground-level PM2.5 included wind (both u and v components), 2-meter mean air temperature, elevation, and the normalized difference vegetation index (NDVI). Discussion/Significance of Impact: Using novel machine learning-based approaches, we developed robust models with fine-scale spatial (1-km2) and temporal (daily) variations of PM2.5 in Mexico City from 2005 to 2023. The predicted PM2.5 concentrations can further advance public health research on air pollution in Mexico City and beyond.

Objectives/Goals: We have shown that parathyroid hormone-related protein (PTHrP) is enriched at the LIFR promoter in breast cancer cells and inhibits the expression of dormancy-associated genes including LIFR. The objective of this study is to define where all PTHrP binds DNA and identify pathways that are regulated by PTHrP that promote breast cancer colonization of the bone. Methods/Study Population: In this study, we use human estrogen receptor-positive MCF7 breast cancer cells which we and others have reported lie dormant in the bone. MCF7 cells were engineered to express either PTHrP with an HA-tag (MCF7P), or a vector control (MCF7V). We use Cleavage Under Targets and Release Using Nuclease (CUT&RUN), a method of mapping protein-DNA interactions, to define where PTHrP binds DNA. Here, an HA-specific antibody identifies regions of DNA that are bound to PTHrP in MCF7P cells compared to MCFV cells. Next, we perform DNA sequencing and gene set enrichment analysis (GSEA) on genes identified by CUT&RUN to identify pathways that are regulated by PTHrP. These experiments will determine how PTHrP regulates dormancy and breast cancer colonization in the bone. Results/Anticipated Results: We completed IgG (-control), H3K4me3 (+ control), and HA (PTHrP) CUT&RUN on MCF7V and MCF7P cells, and submitted DNA for sequencing. This study will define where PTHrP binds the genome and identify pathways regulated by PTHrP. Previously, through ChIP-qPCR we showed that PTHrP binds the LIFR promoter to repress LIFR expression. Given this result, we expect that PTHrP binds to the promoters of dormancy-associated genes including LIFR in MCF7P cells compared to MCF7V cells. PTHrP may be involved in regulating other processes besides dormancy to induce expansion of breast cancer cells in the bone, so we will use GSEA to identify pathways that are altered in MCF7P cells when PTHrP is over-expressed compared to MCF7V cells. Together, this will define how PTHrP regulates gene expression of bone metastatic breast cancer cells. Discussion/Significance of Impact: This study will unveil mechanisms of metastatic breast cancer expansion in the bone by defining where PTHrP binds the genome to regulate gene expression. These findings will reveal therapeutic vulnerabilities that will be used to target bone-disseminated tumor cells to prevent lethal recurrence.

Objectives/Goals: Academic research centers struggle to recruit and retain a diverse, competent clinical and translational science (CTS) workforce. The clinical research professional career pathway is particularly underrecognized among undergraduates, despite offering multiple career opportunities. Methods/Study Population: To address these challenges, two undergraduate outreach programs were developed. First, an undergraduate certificate program in CTS (UC-CTS) was designed to equip students with the skills and knowledge needed to enter the workforce immediately after graduation. Second, a “CTS Roadshow” was launched to build awareness of CTS careers within a variety of undergraduate programs and majors. In this recruitment initiative, principal investigators (PIs) and CRPs visit classrooms to share information about CTS career pathways and offer insights into the roles, responsibilities, and professional opportunities available in the field. Results/Anticipated Results: The UC-CTS program launched in Fall 2024 as a 12-credit certificate that includes two paid internships: one in patient care and one in research. Currently, the program has 5 students enrolled with an anticipated increase in enrollment to 20 students by Spring 2025. Similarly, the CTS Roadshow has reached an increasing number of students each year. Since its inception in Spring 2023, the CTS Roadshow has introduced over 750 undergraduates across 21 courses to CTS careers. The CTS Roadshow has engaged students from a variety of majors, including biology, psychology, medical sciences, legal, finance, accounting, and pre-health programs, increasing awareness of and interest in CTS careers. Discussion/Significance of Impact: Both programs aim to expose students to CTS careers early in their education, better preparing them for full-time CTS roles after graduation. A rise in qualified applicants pursuing CTS careers locally and regionally is expected, improving job satisfaction and retention through enhanced preparation for the career field.

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: 1. Demonstrate the need to apply principles of community-engaged research to various stages of the research process. 2. Outline the process of using CE Studio(s) to redesign an interview guide for service providers of youth involved in the justice system. Methods/Study Population: Service-providers provide a critical lens with which to view the sexual health needs of justice-involved youth. Minimal research describes the unique perspectives of those who work directly with this vulnerable population to address their sexual health needs. The goal of this project is to outline the process of using CE Studio(s) to redesign an interview guide for service providers. The guide is aimed at gathering insight into the knowledge, access, and use of sexual health services for justice-involved youth. Preparation involves the preplanning phase, including the drafting of the interview guide; engagement consists of recruitment and implementation of the CE Studio; and restructuring will outline the application of feedback and finalization of the interview guide. Results/Anticipated Results: During the preparation phase, the researcher was tasked with (1) developing a visual guide to highlight key points of the research study and (2) providing a draft of the tentative interview guide for review prior to the CE Studio session. For the engagement stage, participants were recruited from listservs, community organizations, and word-of-mouth to participate in a session facilitated by a member of the CE Studio team. Lastly, we anticipate that the restructuring phase will not only allow us to use feedback from the CE Studio session to alter the interview guide but provide insight into potential recruitment strategies for the overarching research project. Discussion/Significance of Impact: Leveraging CE Studios to elicit feedback from service providers will provide unique insight into addressing the sexual health needs of justice-involved youth. We expect that the overall CE Studio process and feedback will be integral in eliciting strong qualitative feedback and shaping the implementation of the overall research project.

Objectives/Goals: Research participation by adolescents and young adults (AYAs) is critical for advancing therapeutic interventions applicable across the life course. Identifying effective strategies to recruit and retain AYAs is challenging. This poster elucidates the process and outcomes of working with an AYA Health Research Board and surveying AYAs. Methods/Study Population: The AYA Health Research Board established in 2022 as part of an AYA Program within the UC Davis (UCD) Clinical and Translational Science Center (CTSC). The Board is composed of youth advisers, ages 13–39, from across CA. In 2023, the Program supplemented insights from the board with a national online survey of AYAs using the Amazon Mechanical Turk (MTurk) platform. Two separate instruments were administered, one on recruitment and another on retention, each with over 400 responses. The UCD AYA Board was then engaged to provide crucial insights contextualizing the survey findings, ensuring their relevance and applicability to the AYA population. Results/Anticipated Results: Overall, survey results indicate that AYAs are aware of health studies and clinical trials. Responses affirm that incentives are the biggest driver of AYA participation, while side effects were identified as the biggest reason to drop out of a study. Overall, youth appear more interested in participating in online studies versus those that require in-person appearances. Text messages, regular updates, and sharing of study results were identified as strategies to maintain participant engagement. Additional results will be available through a one-page factsheet for researchers to use as they think about retention and recruitment of AYAs. Discussion/Significance of Impact: Survey results will be made available to health researchers to help move the needle on recruitment and retention efforts of AYAs. This mixed-methods case study serves as an example of the impact AYAs can have on shaping research and validating survey findings.

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: We hypothesized that the bulk transcriptomic profiling of blood collected from within the ischemic vasculature during an acute ischemic stroke with large vessel occlusion (LVO) will contain unique biomarkers that are different from the peripheral circulation and may provide much-needed insight into the underlying pathogenesis of LVO in humans. Methods/Study Population: The transcriptomic biomarkers of Inflammation in Large Vessel Ischemic Stroke pilot study prospectively enrolled patients ≥ 18 years of age with an anterior circulation LVO, treated with endovascular thrombectomy (EVT). Two periprocedural arterial blood samples were obtained (DNA/RNA Shield™ tubes, Zymo Research); 1) proximal to the thrombus, from the internal carotid artery and 2) immediately downstream from the thrombus, by puncturing through the thrombus with the microcatheter. Bulk RNA sequencing was performed and differential gene expression was identified using the Wilcoxon signed rank test for paired data, adjusting for age, sex, use of thrombolytics, last known well to EVT, and thrombolysis in cerebral infarction score. Bioinformatic pathway analyses were computed using MCODE and reactome. Results/Anticipated Results: From May to October 2022, 20 patients were screened and 13 were enrolled (median age 68 [SD 10.1], 47% male, 100% white). A total of 608 differentially expressed genes were found to be significant (p-value) Discussion/Significance of Impact: These results provide evidence of significant gene expression changes occurring within the ischemic vasculature of the brain during LVO, which may correlate with larger ischemic infarct volumes and worse functional outcomes at 90 days. Future studies with larger sample sizes are supported by this work.

Objectives/Goals: Bacterial dysbiosis has emerged as an accomplice in the progression of many cancers. The pancreas microbiome changes in pancreatic cancer patients. The mechanisms via which components of the microbiome regulate tumor growth is unclear. We seek to determine if bacterial dysbiosis influences cancer cell behavior thereby promoting tumor progression. Methods/Study Population: We performed immunohistochemistry for lipopolysaccharide and observed bacteria preferentially located in close proximity to cancer cells. We utilized an in vitro cell culture system and in vivo mouse models, in the presence and absence of gut bacteria, to assess the effect of bacteria and bacterial metabolites on pro-tumorigenic signaling and transcriptional changes in the cancer cell. We analyzed cancer cells and epithelial cells using RNA sequencing, flow cytometry, and enzyme-linked immunosorbent assay. We also used targeted metabolomics to identify bacterial and cancer cell produced metabolites. Results/Anticipated Results: We found microbial dysbiosis can induce proliferation, an inflammatory response and an increase in tryptophan metabolism via the kynurenine pathway in the pancreatic cancer cell. Along with upregulated expression of IDO1 in vivo, we observe an increase in nicotinic adenine mononucleotide. Also, we observe an increase in nicotinic acid in vitro and nicotinic adenine dinucleotide within the cancer cell compartment in the presence of bacteria and bacteria conditioned media. Due to the critical role in many vital pathways of cell survival, NAD+ production is thought to play a significant role in cancer progression. Nicotinic acid can stimulate NAD production to protect cells from cell death. Discussion/Significance of Impact: Pancreatic cancer is associated with a distinct tumor microbiome and ablation slows disease progression. Our data delineate mechanisms via which microbes modulate the pancreatic cancer cell and provide insight into therapeutic strategies for gut microbial modulation in treating pancreatic cancer.

Objectives/Goals: Delving into the intricate web of translational research collaborations, this study analyzed the evolving landscape of the Hispanic Alliance of Clinical and Translational Research from 2020 to 2024 using cutting-edge social network analysis (SNA). SNA is a powerful tool for visualizing, understanding, and harnessing the power of networks. Methods/Study Population: We conducted a systematic document review of all the Alliance IDeA-CTR Network Calls for Pilot Projects from 2020 to 2024 including key attributes of the investigators and collaborators (e.g., academic institution, highest degree, collaborator type). Scientific collaboration was defined as two or more researchers working together in a grant proposal for a pilot project application. Study data was recorded and tracked using an Excel spreadsheet. R-Statistical software was used to analyze and map the networks resulting from collaboration interactions comparing the 2020 Call and 2024 Call. Network statistics were performed including nodes, isolates, edges, components, density, diameter, average degree, and the size of the main component. Results/Anticipated Results: Within a vibrant network comprising over 150 investigators from local and national academic institutions, clinicians (49.3%), and basic researchers (25.4%) are predominant. Initial findings showcase a remarkable surge in interdisciplinary collaborations and affiliations over time. Preliminary findings demonstrated that the number of nodes/actors increased from 16 to 75 comparing 2020 to 2024 and the edges/relationships from 12 to 66. Notably, the number of translational research clusters surged from 4 to 18, with mentorship emerging as a critical conduit bridging diverse research clusters; 16 to 78 nodes in comparison from 2020 to 2024. More extensive collaborative clusters occurred across time with over 20 researchers collaborating. A mentor was the main actor connecting these research clusters. Discussion/Significance of Impact: This study unveils the intricacies and power of translational research dynamics, showing a palpable surge in collaboration diversity and depth. By harnessing data-driven insights, our approach catalyzes informed decision-making to amplify collaboration, diversity, and network efficacy, offering invaluable guidance for policy and practice.

Objectives/Goals: The operation of a clinical trials unit involves multifaceted tasks and stakeholders. A competent information system is critical to daily operations while ensuring smooth conduct of clinical research. We share 15 years of experience in the design and implementation of such a system at Mayo Clinic to inform other institutions with similar interests. Methods/Study Population: The Informatics team collaborated closely with nurse leaders and elicited input from additional stakeholders including nurse unit coordinators, lab managers, schedulers, investigators, study coordinators, and regulatory specialists throughout the phases of system design, development and continuous enhancements, and expansion. The stakeholders offered insights on the corresponding requirements throughout the study life cycle, from engaging with the study sponsor, operational review for protocol execution, development of study budgets, human subject protection and risk mitigation, data management and integration, to outcome monitoring, and regulatory reporting. The activities were then translated into functional components and implemented as a seamless and effective solution. Results/Anticipated Results: Patient safety, scientific rigor, operation automation, efficiency, and regulatory requirements were all considered in developing an integrated system, or the clinical research trials unit (CRTU) Tools. Our institution has leveraged the system for essential tasks from the study start-up, visit scheduling and execution, specimen collection and tracking, to individual protocol metrics and billing. We adopted a measure-as-we-go methodology so that data such as visit census, resource usage, and protocol deviation are tracked and collected during routine use of the system. Specifically, an issues/concerns/exceptions (ICE) tool is used for quality control and patient safety. Moreover, data quality greatly benefits from a task dictionary, standardizing the study activities that can be ordered and executed. Discussion/Significance of Impact: The implementation of a well-rounded clinical trials unit information system not only improves the operation efficiency and team productivity but also ensures scientific rigor and contributes to patient safety. We believe the experience can be informative to other institutions. More details will be shared in the poster.

Objectives/Goals: Opioid use disorder (OUD) at delivery increased between 1999 and 2014. Clinical guidelines include medication for OUD (MOUD) for pregnant women with OUD and is associated with better fetal outcomes. Few large studies have compared prenatal MOUD outcomes to no MOUD. We evaluated the association of documented MOUD prescription during pregnancy with maternal outcomes. Methods/Study Population: We utilized aggregated electronic health records using the TriNetX platform to conduct a retrospective cohort study of females, aged 1249 years with a childbirth CPT code and documented opioid use via ICD-10 codes in the nine months before delivery between 2014 and 2020, comparing patients with MOUD prescription of buprenorphine or methadone during the nine months before delivery to demographically matched patients without any documented MOUD, using hazard ratios and 95% CIs for outcomes occurring one week to one or three years after childbirth. Results/Anticipated Results: MOUD cohort (n = 6,945, 85.33% White; 82.77% Non-Hispanic or Latino) was associated with significantly higher subsequent documented MOUD prescription (HR, 9.26 [95% CI, 7.98–10.76]; 6.21 [95% CI, 5.60–6.88]) and new remission codes (HR, 2.79 [95% CI, 2.15–3.62]; 2.85 [95% CI, 2.38–3.40]) at one and three years, lower ED visits at one year (HR, 0.88 [95% CI, 0.81–0.96]), no significant association of ED visits at three years (0.95 [95% CI, 0.89–1.02]), higher outpatient visits (HR, 1.26 [95% CI, 1.20–1.32]; HR, 1.27 [95% CI, 1.21–1.33], and no significant association of inpatient visits at one and three years (HR, 0.93 [95% CI, 0.813–1.06]; 1.06 [95% CI, 0.96–1.18]) than the never-MOUD cohort (n = 4,708, 76.11% White; 75.68% non-Hispanic or Latino). Discussion/Significance of Impact: A documented prescription for MOUD during pregnancy is associated with newly documented remission of OUD, increased outpatient visits, decreased ED visits, and additional documented MOUD prescriptions suggestive of increased access to continuity care. Efforts to increase MOUD use in pregnancy may improve maternal outcomes.

Objectives/Goals: Primary care physicians (PCPs) have limited awareness of assistive technology (AT) devices that can improve the daily functioning of older adults. This study aimed to assess the quality of the My Assistive Technology Guide (MATG), an informative web app, among PCPs and to describe their experiences using it. Methods/Study Population: In this pilot project, our team – comprising an established researcher, an undergraduate faculty member, and a graduate student – enrolled ten PCPs. In Phase I, the PCPs received training on how to use the MATG and were encouraged to utilize it for 30 days. At the end of this usage period, we implemented a concurrent parallel mixed-method design to collect both quantitative and qualitative data. Quantitative data were gathered using the User Mobile Application Scale (uMARS), while qualitative data was obtained through interviews. Data analysis involved descriptive statistics and thematic content analysis. Results/Anticipated Results: The mean score for the subjective quality of the MATG was high, 4.1 ± 1.1. The information domain received the highest rating, with a mean score of 4.6 ± 0.51, while the engagement domain received the lowest rating, at 3.3 ± 1.5. Overall, subjective quality was rated moderately high (mean 3.9, interquartile range 1.2), with perceived impact rated the highest at 4.8 ± 0.4. PCPs reported increased awareness, knowledge, attitude, intention, and behaviors to learn about AT and to inform and recommend AT devices to older adults. In addition, PCPs provided suggestions to improve the MGAT and its integration into their medical practice. Discussion/Significance of Impact: The results demonstrated the high quality and utility of the MATG, indicating that it could serve as a valuable resource for PCPs in addressing functional disabilities among older adults. Future research should evaluate the effectiveness of the MATG in enhancing older adults’ function in daily living activities.