Objectives/Goals: As translational science (TS) emerges as a field, there is a need for research organizations to understand how to develop capacity for and support the advancement of TS. To support such institutional and infrastructural change, this poster outlines a Translational Science Promotion and Research Capacity (T-SPARC) framework. Methods/Study Population: The T-SPARC framework was developed by members of the Duke University Clinical and Translational Science Institute (CTSI) primarily from CTSI Pilots, Team Science, Evaluation, and Administration, all of whom had identified the need for building institutional capacity for TS at our institution. The group reviewed literature on TS to ensure grounding in current knowledge, drafted an initial TS logic model, and then determined the value of developing a framework addressing building TS institutional capacity. The group then identified other frameworks/models related to behavioral, organizational, and system change; examined scholarship addressing the building of research capacity in colleges and universities; and iterated on a TS-focused framework in multiple working sessions. Results/Anticipated Results: The resultant T-SPARC framework provides a foundation to 1) inform the development of interventions and programs advancing TS and 2) evaluate their effectiveness. It outlines: organizational levels for TS capacity building (large-scale systems, research institutions, teams, and individuals); intervention activities (policies and processes, funding, collaboration and partnership, and training); proximal outcomes (knowledge/attitudes, behaviors, resources/infrastructure, and connections); next-stage outcomes (e.g., interdisciplinary team processes, and research infrastructure); and ultimate goals (fewer translational impediments, improved public health, and health equity). It ingrates TS principles as foundational to, and outcomes of, capacity-building efforts. Discussion/Significance of Impact: T-SPARC, as a framework for building capacity in TS, provides added foundation for advancing the conceptualization and practice of TS. Ultimately, T-SPARC seeks to advance broader goals of reducing longstanding challenges in the translational research process and improving health outcomes.

This ethnographic study, conducted as part of the Pandemic Preparedness Project, explores the pandemic preparedness of communities in NG and its satellite settlements within Kailahun District, Eastern Province, Sierra Leone. The research site was particularly significant due to its history as one of the hardest-hit areas during the 2014–16 Ebola outbreak. NG is served by a Peripheral Health Unit (PHU) that provides health services to seven villages, as well as one distant village far from its designated facility. The study employed long-term observational research methods, where the researcher lived within the community, becoming an integrated observer familiar with local customs and daily life. This ethnographic approach aimed to understand the health-seeking behaviors of residents following the Ebola crisis. The onset of the Covid-19 pandemic during the study period shifted the focus to examine how the community understood and responded to a new pandemic threat. Additionally, the study reflects on the challenges faced by female social scientists in Sierra Leone, where few are trained in ethnographic methods. This article offers insights into the process of conducting ethnographic research in a challenging context, providing valuable guidance for other female researchers seeking to engage in similar bio-social studies.

Objectives/Goals: Kentucky (KY) is a high priority ending the HIV epidemic state, with high rates of new HIV diagnoses tied to injection drug use. The overall goal of this pilot is to launch sentinel surveillance of bloodborne infections and drug compounds among people who inject drugs (PWID) to monitor trends in near-real time and inform rapid community response. Methods/Study Population: In collaboration with the Clark County, KY, syringe service program (SSP), the pilot study involves two 1-month waves of data collection: enrolling eligible SSP participants and conducting anonymous behavioral surveys, collection of participants’ syringes, laboratory testing of syringes to detect HIV and hepatitis C (HCV), drug residue testing through National Institute of Standards and Technology, and statistical modeling approaches to produce outputs of bloodborne infection and drug detection. Syringes are tested from each enrolled individual for: 1) HIV antibody; 2) HCV antibody; 3) HIV and HCV PCR; 4) HIV antigen; and 5) drug residue. Collaboration with community and PWID stakeholders will identify optimal messaging for reporting results. Results/Anticipated Results: The first wave community-facing pilot was conducted in September–October 2024. 29 survey responses were obtained; median age of the sample is 42 years, 55.2% are gender female; 37.9% reported unstable housing in the past week. Primary drugs of injection reported via survey in the prior month were methamphetamine (62.1%), heroin (13.8%), fentanyl (13.8%), buprenorphine (10.3%), meth and fentanyl in combination (3.4%). PWID reported returning 900 used syringes and a median of 15 per participant visit. At most recent testing, 69.0% reported a positive HCV test; 0% reported a positive HIV test. Some level of drug checking with fentanyl test strips in past month was reported by 51.7%. Initially, 20 syringes were tested for drug compounds; results are pending. HIV and HCV detection testing will be completed by early 2025. Discussion/Significance of Impact: Early results document proof of concept for our sentinel surveillance study; all individuals screened were willing to participate in surveys and syringe collection. New methods to identify risk for disease outbreaks and emerging drugs can inform rapid allocation of prevention resources at a community level, especially where testing is infrequent.

Objectives/Goals: The goal of this project was to engineer 3D lung models by embedding human epithelial cells and fibroblasts within hybrid-hydrogels containing human decellularized extracellular matrix (dECM) from healthy and fibrotic lungs. This platform will enable us to study cell–matrix interactions involved lung fibrosis pathogenesis. Methods/Study Population: To incorporate dECM into hybrid-hydrogels it must be digested and functionalized. We determined the best conditions for pepsin digesting dECM from healthy and fibrotic human lung by collecting samples every 12 hours up to 96 hours and measuring total protein (BCA assay), total amine concentration (ninhydrin assay), and protein fragment size (SDS PAGE). Next, several molar excesses of Traut’s reagent were tested and functionalization was verified by comparing amine content (ninhydrin assay) to thiol content (Ellman’s assay). Hydrogel stiffness was measured initially and after stiffening using parallel-plate rheology. Results/Anticipated Results: The dECM was successfully pepsin-digested, with the 48-hour time point yielding the highest free amine levels. A 75-molar excess of Traut’s reagent was best for converting free amines to thiols. Dynamic stiffening allowed the creation of hybrid-hydrogels mimicking both healthy (1–5 kPa) and fibrotic (>10 kPa) lung microenvironments. We anticipate that this model will demonstrate differential fibroblast activation based on hybrid-hydrogel dECM source (healthy or fibrotic), microenvironmental stiffness, and cell source (healthy or fibrotic). Validation of this 3D co-culture system could accelerate drug discovery by providing a more accurate in vitro platform for high-throughput screening. Discussion/Significance of Impact: This work advances pulmonary fibrosis modeling by creating human dECM-based hydrogels that recapitulate the cellular and mechanical microenvironment of healthy and diseased lung, potentially enabling us to uncover novel therapeutic targets and improving drug efficacy testing in vitro.

Objectives/Goals: Using secure systems for sharing documents with external collaborators is essential for all researchers. These documents may include protected health information (PHI) or sensitive materials like protocols, study reports, DSMB reports, publications, presentations, abstracts, and statistical analysis plans (SAPs). Methods/Study Population: We surveyed the ACTS Biostatistics, Epidemiology, and Research Design Special Interest Group (BERD-SIG) to gather information about the systems they are currently using or have used in the past for document sharing with external collaborators. The survey focused on the security of these systems, particularly in relation to sharing documents containing PHI. In addition, the survey included questions about various system features of interest. These features included version control, simultaneous editing by multiple users, and access rights management, such as the ability to assign different permissions (e.g., read-only, write, and download) to different individuals. We also invited participants to provide feedback on any additional positive or negative aspects of the systems they use. Results/Anticipated Results: We received 28 completed survey responses. Respondents had an option for choosing more than one system. The top current systems reported were Microsoft Teams (OneDrive, SharePoint) (n = 16), Box (n = 11), Google Docs/Drive (n = 10), and Dropbox (n = 6). Among other systems listed individually were Filelocker, REDCap, Slack, Website, Significant Media Shuttle, and Zulip. Notably, 15 responses indicated the respondents were unsure if their system is secure for sharing documents containing PHI. Respondents also offered feedback on both the positive and negative aspects of these systems. For example, a key advantage of Box was its password-controlled access. However, its incompatibility with office tools and the challenges for external collaborators attempting to access the system were noted as drawbacks. Discussion/Significance of Impact: Utilizing secure institutional document-sharing systems and understanding their features significantly affects the effectiveness and security of collaborations among researchers, particularly with external partners. This knowledge is especially crucial when sharing documents containing sensitive patient and study data.

Objectives/Goals: Engaging interest holders in research is increasingly common, and guidelines include creating engagement plans. A detailed plan may be especially helpful when researchers perceive engagement as difficult or less relevant. We tested whether a study’s translational stage or an investigator’s years of research experience affect their perceptions. Methods/Study Population: Since 2019, the Tufts Clinical and Translational Science Institute Pilot Studies Program required applicants to submit plans to engage interest holders. Applicants in three cohorts responded to a survey about this requirement, including perceived difficulty developing an engagement plan, perceived relevance of engagement, and self-reported years of research experience (≤5, 6–10, and ≥10 years). Two raters assigned translational stage(s) of proposed studies: T0 (basic science), T.5 (pre-clinical to initial human studies), and T1 through T4. Separate analyses were conducted when multistage studies were coded as the earliest vs. latest stage and for individual stage vs. groups of stages (T0/T.5/T1 vs. T2/T3/T4). The Fisher’s exact statistical test was used to assess associations between variables. Results/Anticipated Results: Analyses included 67 participants. Developing an engagement plan was perceived as more difficult for studies at earlier translational stages when those studies were coded as the earliest applicable stage. This significant association held both when stages were grouped as T0/T.5/T1 and T2/T3/T4 (P  =  .03) and when analyzed as a single stage (P  =  .01); however, when studies were coded as the latest applicable stage, there were no significant associations. Similarly, when multistage studies were coded as the earliest applicable stage, engagement was perceived as less relevant for early-stage studies when grouped (P  =  .04), but not for individual stages or when studies were coded as the latest applicable stage. No significant association between years of research experience and perceived difficulty was identified. Discussion/Significance of Impact: Results show that investigators conducting early-stage research perceive more difficulty engaging interest holders, aligning with prior qualitative studies. These investigators may need more evidence of the value added to early-stage studies, targeted and practical training, and funder requirements to establish a culture of engagement.

Objectives/Goals: To create, train, and evaluate the FAST-PACE (Promoting Academic and Community Engagement) Toolkit that catalyzes academic-community translation science teams during a public health emergency. The toolkit is a road map based on the Research Readiness and Partnership Protocol (R2P2), which was developed from the Flint Water Crisis. Methods/Study Population: A literature review was conducted by the Michigan Institute for Clinical & Health Research Community Engagement (MICHR CE) program and the Community-Based Organization Partners (CBOP), to identify important and common elements in disaster response protocols with a set of key interviews (n = 31) to glean perspectives from community leaders. Key findings were extracted and reviewed to generate guidelines and recommendations for the R2P2 protocol. The co-developed FAST-PACE Toolkit launched its expansion statewide to address emergencies and health disparities of communities in crisis. The iterative process consisted of community report-outs, gathering input from stakeholders, via discussion, and evaluation surveys. The feedback was used to develop, enhance, and tailor the toolkit and training content. Results/Anticipated Results: Data from training (n = 8) of the critical elements of the FAST-PACE Toolkit, which provides guidance for academic and community team members that includes 1) assessing community assets and needs; 2) engaging in clear and bidirectional communication; 3) facilitating transparency and equitable partnering; 4) identifying health equity and justice issues; and 5) conducting the evaluation of research. The training will be disseminated in-person and virtually across the state of Michigan resulting in participants sharing community-identified health issues and social determinants of health to assist MICHR CE to suggest resources to address health impacts. Discussion/Significance of Impact: The FAST-PACE Toolkit borne from the flint water crisis and confounded by other crises used CEnR principles to create a translation science roadmap. It equips communities and collaborating academic institutions across the state to respond to public health crises and fosters equitable translation science partnerships built on respect and trust.

Objectives/Goals: Cerebral amyloid angiopathy-related inflammation (CAA-ri) is a spontaneous inflammatory cerebral vasculopathy that mimics complications of Alzheimer’s disease immunotherapies. Our objective is to evaluate imaging and cerebrospinal fluid (CSF) markers of blood–brain barrier (BBB) impairment and inflammation in CAA-ri. Methods/Study Population: We plan to enroll 20 patients total: 1) 10 patients with CAA-ri as defined by Auriel et al (JAMA Neurology 2016) (exposure group). 2) 10 patients with non-inflammatory CAA defined using Boston criteria 2.0 that do not also meet criteria for CAA-ri (control group). The primary outcome will be Ktrans, a parameter of BBB impairment calculated from dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) of the brain. Secondary outcomes will include DCE-MRI parameter VL, CSF albumin index, CSF fibrinogen, CSF sPDGFR-β, CSF MMP-2, CSF MMP-9, CSF C3, CSF IL1β, CSF IL6, IL8, and TNFα. Statistical comparisons between the exposure and control groups will be made using Wilcoxon rank sum test. Results/Anticipated Results: We anticipate significantly higher levels of BBB impairment and inflammatory biomarkers from DCE-MRI and CSF in subjects with CAA-ri relative to control subjects with non-inflammatory CAA. Discussion/Significance of Impact: Biomarkers are essential to characterize risk factors, pathophysiology, and possible treatment targets in CAA-ri. We plan to use the results of the current study to inform longitudinal studies that will test whether these markers are useful in identifying not only the presence of CAA-ri but also severity, progression, and response to treatment.

Objectives/Goals: Neuromodulation strategies like transcranial magnetic stimulation (TMS) can target specific neural circuits underlying particular psychiatric symptoms, potentially 1) enhancing understanding of mechanisms of illness and recovery and 2) acting as novel therapeutics. These feasibility studies lay foundation for a study of major depression. Methods/Study Population: Four healthy volunteers completed structural and functional MRI (fMRI). fMRI included a trait-adjective task, a negative self-referential processing task known to activate VMPFC, which is known to be abnormal in major depression. During the task, participants respond on a task pad whether they feel that each of a series of displayed adjectives (positive, negative, or neutral) applies to them. Three participants then participated in a simulated image-guided TMS session using their MRI data to target their VMPFC. Three-dimensional tracking of the participant’s head and the TMS coil was used to position the coil for peak stimulation of the targeted brain region. Results/Anticipated Results: Our team collected quality neural and behavioral data on the fMRI task; participants reported a tolerable experience. Simulated neuronavigated TMS showed feasibility and tolerability of positioning the device to stimulate VMPFC. The fMRI task activated the VMPFC as predicted. The MRI and TMS protocols were replicable and tolerable. These procedures can now be used experimentally by our team with confidence to test our hypothesis that targeting the VMPFC within the brain’s default-mode network may normalize aberrant VMPFC activity seen in major depression, thereby improving excessive negative self-referential processing. Discussion/Significance of Impact: This project lays essential groundwork for my K12 project, “Targeting Negative-Self Referential Processing in Depression with TMS,” a longitudinal neuroimaging and behavioral study using these methods in the study population of people with major depression.

Objectives/Goals: Osteosarcoma (OS) is the most common primary bone malignancy in humans and dogs. >40% of children and >90% of dogs succumb to metastatic disease. We hypothesize MYC overexpression in metastatic canine and human OS contributes to an immunosuppressive tumor environment by driving tumor-associated macrophage influx and T lymphocyte exclusion. Methods/Study Population: To characterize the role of oncogenic MYC signaling in the canine metastatic tumor immune microenvironment (TIME), 42 archived FFPE lung metastatic canine OS samples were evaluated for MYC copy number variation (CNV), mRNA, and protein expression via ddPCR, nanostring analysis, and immunohistochemistry (IHC). Seven samples also underwent GeoMX spatial profiling to more specifically evaluate T cell and macrophage transcriptional profiles based on MYC status. To determine the role of MYC target modulation as a potential therapeutic option, canine and human OS cell lines were treated with a novel MYC inhibitor (MYCi975) and assessed for effects on survival, proliferation, and cytokine profiles. Results/Anticipated Results: We demonstrate that copy number gains are not a key driver of MYC hyperactivity in canine metastatic OS. However, stratification based on MYC protein expression demonstrates that “MYC-high” tumors are associated with downregulation of cytotoxic effector T-cell associated transcripts and upregulation of tumor-associated macrophage (TAM) and extracellular matrix remodeling transcripts. We also report that MYCi975 treatment of canine and human OS cell lines results in significant inhibition of OS cell survival and proliferation at concentrations that are pharmacologically achievable in mice. Furthermore, we demonstrate MYC inhibition by MYCi975 is associated with reduced pro-inflammatory cytokine secretion in OS cell culture models. Discussion/Significance of Impact: While MYC overactivity in metastatic canine OS may not be genomically driven, other mechanisms that lead to increased MYC protein expression are associated with transcriptomic profiles supportive of local immunosuppression. Pharmacologic targeting of MYC may serve as a strategy to bolster immunotherapeutic options in metastatic OS treatment.

Objectives/Goals: Rare disease patients often face lengthy delays in receiving accurate diagnoses or experience misdiagnoses due to a lack of available information. The NCATS Rare Disease Alert System (RDAS) is a public, comprehensive rare disease resource to collect and share accurate, up-to-date, and standardized data on rare diseases. Methods/Study Population: RDAS is composed of a frontend UI, Application Programming Interfaces, and backend Neo4j graph database. Each component of data collection, data annotation, data standardization, and data representation as steps were implemented during the process of each graph database creation. The UI allows users to search, browse, and subscribe to RDAS to receive the latest information and findings about their rare disease(s) of interest. The back-end data include four knowledge graphs built by integrating information from the NCATS Genetic and Rare Disease program, PubMed articles, clinical trials, and NIH grant funding. Ultimately, the integrative information pertinent to rare diseases from RDAS would advance rare diseases research. Results/Anticipated Results: Of 5001 rare diseases belonging to 32 distinct disease categories, we identified 1294 diseases that are mapped to 45,647 distinct, NIH-funded projects obtained from the NIH ExPORTER by implementing semantic annotation of project titles. To capture semantic relationships presenting among mapped research funding data, we defined a data model comprised of seven primary classes and corresponding object and data properties. A Neo4j knowledge graph based on this predefined data model has been developed, and we performed multiple case studies over this knowledge graph to demonstrate its use in directing and promoting rare disease research. Discussion/Significance of Impact: We developed an integrative knowledge graph with rare disease data and demonstrated its use as a source to identify and generate scientific evidence to support rare disease research. With the success of this study, we plan to implement advanced computation to analyze more funding related data and link to other types of data to perform further research.

Objectives/Goals: This work aims to identify functional brain networks that differentiate opioid use disorder (OUD) subjects from healthy controls (HC) using machine learning (ML) analysis of resting-state fMRI (rs-fMRI). We investigate the default mode network (DMN), salience network (SN), and executive control network (ECN), as well as demographic features. Methods/Study Population: This work uses high-resolution rs-fMRI data from a National Institute on Drug Abuse study (IRB #HM20023630) with 31 OUD and 45 HC subjects. We extract rs-fMRI blood oxygenation level-dependent (BOLD) features from the DMN, SN, and ECN. The Boruta ML algorithm identifies statistically significant features and brain activity mapping visualizes regions of heightened neural activity for OUD. We conduct fivefold cross-validation classification experiments (OUD vs. HC) to assess the discriminative power of functional network features with and without incorporating demographic features. Demographic features are ranked based on ML classification importance. Follow-up Boruta analysis is performed to study the medial prefrontal cortex (mPFC), posterior cingulate cortex, and temporoparietal junctions in the DMN. Results/Anticipated Results: Boruta ML analysis identifies the DMN as the most salient functional network for differentiating OUD from HC, with 33% of DMN features found significant (p < 0.05), compared to 10% and 0% for the SN and ECN, respectively. The Boruta ML algorithm identifies age and education as the most significant demographic features. Brain activity mapping shows heightened neural activity in the DMN for OUD. The DMN exhibits the greatest discriminative power, with a mean AUC of 69.74%, compared to 47.14% and 54.15% for the SN and ECN, respectively. Fusing DMN BOLD features with the most important demographic features improves the mean AUC to 80.91% and the F1 score to 73.97%. Follow-up Boruta analysis highlights the mPFC as the most important functional hub within the DMN, with 65% significant features. Discussion/Significance of Impact: Our study enhances the understanding of OUD neurobiology, identifying the DMN as the most significant network using ML rs-fMRI BOLD feature analysis. Ethnicity, education, and age rank are the most important demographic features and the mPFC emerges as a key functional hub for OUD. Future research can build on these findings to inform treatment of OUD.

Objectives/Goals: Although several studies have identified significant associations between specific social determinants of health (SDoH) and adverse outcomes, little is known about how SDoH co-occur to form subtypes and their outcome-based risks. Here we analyze how SDoH co-occur across all participants with a cancer diagnosis in the All of Us program. Methods/Study Population: Data: All participants (n = 3361) with cancer and their responses to 110 survey questions related to SDoH. Independent variables: 18 SDoH factors aggregated from the questions to address uneven granularity. Dependent variables: depression, delayed medical care, and ER visits in the last year. Analytical Method. (1) Bipartite network analysis with modularity maximization to identify participant-SDoH biclusters, measure the degree of their biclusteredness (Q), and estimate the significance of Q. (2) Visualization of the results using the ExplodeLayout force-directed algorithm. (3) Multivariable logistic regression (adjusted for demographics and corrected through FDR) to measure the odds ratio (OR) of each bicluster compared pairwise with the other biclusters to estimate their risk for the 3 outcomes. Results/Anticipated Results: As shown in Fig. 1A (http://www.skbhavnani.com/DIVA/Images/Cancer-SDoH.jpg), the analysis (n = 3361, d = 18) identified 4 biclusters with significant biclusteredness (Q = 0.13, random-Q = 0.11, z = 9.94, P Discussion/Significance of Impact: Currently, many health equity policies allocate resources based on sociodemographic factors like race and income to address disparities. The 4 distinct subtypes and their outcome-based risks suggest that such policies could be more precise if they were based directly on combinations of need using SDoH subtypes and their risk stratification.

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: The ITHS KL2 Seminar Fellows program creates a larger cohort by inviting additional early career faculty to join the tailored career development curriculum. The implementation of this program seeks to increase collaboration and innovation by amplifying diverse perspectives and increased networking. Methods/Study Population: In addition to the funded KL2 Scholars awarded each year, 13–15 Seminar Fellows are invited to be full participants in the KL2 curriculum, which includes monthly career development seminars and opportunities for feedback on their research. Invited Fellows are early career investigators who were promising KL2 applicants, faculty with alternative career development funding, and/or new underrepresented faculty in Washington, Wyoming, Alaska, Montana, and Idaho. Fellows commit to one year of participation, which can be renewed on a case-by-case basis. Fellows have been integrated into the ITHS implementation of Flight Tracker (Vanderbilt) to follow the career pathways alongside funded KL2 award recipients. Results/Anticipated Results: The key measures of success will be the rate of seminar fellows transitioning into K-level or similar career development awards and securing other subsequent funding. Preliminary data demonstrates significant collaborations between KL2 Scholars with different areas of scientific inquiry and promotion of at least half of our past KL2 Scholars into leadership positions at prestigious medical schools in the USA and Canada. We suspect that the trends evidenced by the career progression of early KL2 recipients will be expanded into newer and different translational research projects with the addition of the KL2 Fellows program. Discussion/Significance of Impact: The Seminar Fellows program presents a cost-effective way to increase the impact of an existing career development program by amplifying cross-boundary interactions to form a strong, diverse translational research workforce.

Objectives/Goals: The study’s goal is to investigate the role of PPAR-α on regulating blood pressure, glomerular filtration rate (GFR), renal inflammation, and renal sodium reabsorption in mice on a 4% high-salt diet. Methods/Study Population: GFR, systolic blood pressure (SBP), inflammatory biomarkers (KIM-1, TIMP2, NGAL, MCP-1, TNF-α, IL-6, IL-10, and IL-17), and renal sodium transporter expression (NKA, NHE3, NKCC2, NCC, ENaC, Aqp-2, and NHERF1) were measured in PPAR-α KO mice and wild-type controls treated with a 4% high-salt (HS) diet. Male C57BL6, B129S1, and PPAR-α KO mice (12 weeks old) will be treated with 4% HS diet for 28 days. Systolic blood pressure is measured by tail cuff. GFR is measured by transdermal FITC-Inulin radioactive fluorescence. Inflammatory biomarkers will be measured by cytokine array and western blot. Sodium transporter expression will be measured by western blot. Results/Anticipated Results: Baseline SBP was 146 ± 31 mmHg (C57), 140 ± 24 mmHg (B129), and 153 ± 23 mmHg (KO). After 21 days of normal (control diet) or treatment (HS diet), control systolic pressures were 139 ± 18 mmHg (C57), 107 ± 23 mmHg (B129) and 147 ± 34 mmHg (KO), while HS systolic pressures were 166 ± 23 mmHg (C57) and 119 ± 34 mmHg (B129). We are collecting blood pressure for the KO HS group. Baseline GFR was 1194 ± 140 µL/min/g (C57), 1167 ± 279 µL/min/g (B129), and 1191 ± 157 µL/min/g (KO). Discussion/Significance of Impact: We hypothesize significantly higher SBP, inflammatory marker expression, and renal sodium transporter expression in KO and B129 mice on a HS diet. We predict that PPAR-α expression in the kidney will be higher in C57 compared to B129. We predict that PPAR-α activity plays a vital role in reducing high-salt-induced hypertension and inflammatory markers.

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.

Objectives/Goals: Sexual minority populations (SMPs), including lesbian, gay, and bisexual groups, disproportionately encounter discriminatory experiences due to bi/homonegativity and systemic inequities across various social domains. We aim to understand how the neighborhood-level stressors and resilience sources differed across specific groups in SMPs. Methods/Study Population: Utilizing the NIH All of Us’ cloud-based platform, we selected cohorts self-identifying as gay (n  =  9,454), bisexual (n  =  15,284), lesbian (n = 5267), or straight (n  =  349,748). We explored multiple key measures of neighborhood-level stressors (e.g., neighborhood disorder, neighborhood cohesion, and environment index) and resilience sources (e.g., neighbor cohesion, social support), and other factors (e.g., food insecurity, housing insecurity, and housing instability) by their sexual orientations using analysis of variance or Chi-square analyses. Results/Anticipated Results: Our sample comprised 60.8% females and 37.5% males identifying as non-binary or transgender, with an average age of 55.6 years (SD  =  17.1). The racial composition was 56.0% White, 19.4% Black, 18.7% Hispanic, and 5.9% others (e.g., Asian, multiracial). Compared to straight individuals, SMPs reported high neighborhood stressors (e.g., disorder, worse environment) but lower neighborhood-level resilience sources (e.g., social support, cohesion). In addition, bisexual groups reported highest prevalence of housing insecurity (6.7% vs. 2.3%), housing instability (36.0% vs. 19.6%), and food insecurity (26.57% vs. 12.21%). Discussion/Significance of Impact: SMPs, particularly bisexual individuals, face greater neighborhood stressors and fewer resilience sources than their straight counterparts. These findings call for targeted interventions to address these disparities and promote health equity, using large-scale datasets to inform community-based solutions.

Objectives/Goals: Transgender women who have sex with men (TGWSM) have higher HIV risk. The rectal mucosal (RM) immune environment of TGWSM who choose feminizing hormone therapy (FHT) has been shown to be distinct from the RM of cisgender men who have sex with men (MSM). We studied the impact of FHT on the adaptive immune cellular composition of the RM. Methods/Study Population: We sampled cross-sectional and longitudinal cohorts of TGWSM and cisgender MSM from The Silom Clinic in Bangkok, Thailand from December 2020 to December 2023. We included participants aged >18 years, all cisgender MSM and TGWSM with FHT levels in the therapeutic range for cisgender women. We performed RM biopsies and analyzed the adaptive immune cell characteristics via flow cytometry. We will perform binary linear regression to assess the association between systemic FHT levels and the percentage of CD4+ T cells expressing key biomarkers. Primary outcomes include the percentage of CD4+ T cells that express CCR5, with a secondary outcome of the percentage of CD4+ T cells that express Ki67. Results/Anticipated Results: The cross-sectional cohort included 100 TGWSM on FHT and 50 cisgender MSM. The longitudinal cohort included 25 TGWSM who were initiating FHT. Similar primary and secondary outcomes are to be elucidated in both cohorts. We anticipate the RM environment of TGWSM using FHT in both cohorts compared to the RM environment of cisgender MSM in the cross-sectional cohort will be associated with greater percentages of activation/co-receptor expression of CD4+ T cells that express biomarkers of interest. In the longitudinal cohort, we similarly anticipate increased percentages and activation/co-receptor expression of CD4+ T cells expressing biomarkers of interest in TGWSM after in comparison to before initiating FHT. Discussion/Significance of Impact: This is the largest study of its kind to compare HIV target cells in RM of TGSWM, which challenges prevailing perspectives suggesting to group cisgender MSM with TGWSM. Anticipated results will inform HIV prevention strategies and future vaccine studies in this high-risk population.