Strengthening the research workforce is essential for meeting the evolving needs and challenges in the health and biomedical fields. To do so effectively, it requires an understanding of how the experiences of a researcher shift over time and how one’s research career evolves, particularly as supports are put in place to foster research. This narrative review provides a summary of published individual-level assessment measures and survey tools from 2000–2024. All measures were abstracted, classified, and coded during analyses to describe the areas of focus, and they were organized into one of six research categories. The review identified a range of measures and methods across all categories. However, the measures were often narrow, focused on outputs, and not ideal for assessing the full range of experiences a researcher may have throughout their career. The most common metrics were related to research productivity and bibliometric measures. Our review of survey tools revealed a gap in comprehensive approaches available to assess an individual’s research experience, efforts, supports, and impact. As efforts expand to evaluate and study the research workforce, tools that focus on a broad range of individual-level measures, tied to specific underlying constructs and drawn from the literature, may prove useful.

Objectives/Goals: To evaluate the extent to which characterization of unstructured patient-generated health data (UPGD) (e.g., health journals) with human-guided machine learning (HGML) improves model explainability and integrates patient voices among renal cancer patients in a randomized control trial (RCT). Methods/Study Population: Data were collected in an RCT (NCT00505310) assessing the benefits of an emotional expression intervention on renal cancer patients’ quality-of-life outcomes. Over a 10-day period, patients completed four journal-type written responses to structured prompts about their health lifestyle behaviors or deepest thoughts and feelings linked to cancer. I will 1) evaluate the extent to which a standard ML model versus an HGML model aligns with principles of trustworthy health AI when characterizing UPGD, 2) evaluate the extent to which UPGD captures condition-specific data complementary to PROMs, and 3) extract journey maps from narratives about patient experiences navigating cancer care. Results/Anticipated Results: Results will illustrate a patient-centered value research approach that centers patient perspectives, contextualizes heterogeneous factors influencing patient outcomes, and mitigates biases in the health research machine learning pipeline. Discussion/Significance of Impact: This research contributes to the development of evidence-based and empirically validated strategies for health researchers to incorporate explainable HGML tools that facilitate the inclusion of patients’ experiences, perspectives, needs, and priorities throughout the research process.

Objectives/Goals: Our goal is to develop a CRM platform to streamline support for investigators, optimize resource use, and enhance service delivery within a CTSA institution. This platform will measure outcomes, improve transparency, and ensure compliance, creating an efficient, supportive research environment. Methods/Study Population: Beginning with the design concepts and collecting technical requirements, ensuring alignment with the needs of investigators, administrators, and service units. Apply project management methodologies to iteratively design, prototype, and test features. Focus on user-centric interfaces and seamless integration with institutional systems. Incorporate stringent data security protocols in compliance with regulatory standards. Conduct pilot studies to refine functionalities and gather constructive feedback. Facilitate extensive user training programs and offer continuous support. Regularly monitor performance metrics, iterating based on empirical data and user feedback to ensure continuous enhancement and adherence to institutional objectives. Results/Anticipated Results: YCCI successfully designed, developed, and implemented a CRM platform for managing the intake, navigation, consultation, service delivery, and outcomes tracking of the clinical and translational science activities that are supported by and beyond the CTSA-supported infrastructure. The CRM platform has been live in production since roughly July 1, 2024, and YCCI is excited to share data, results, and outcomes with the ACTS community. Discussion/Significance of Impact: YCCI’s CRM platform advances the CTS mission by streamlining PI support, enhancing resource utilization, and fostering inter-team collaboration within the research ops and administration teams. Measuring outcomes and service efficiency enables data-driven decisions, ensuring continuous improvement, and impactful translational science.

Objectives/Goals: Caring for a loved one with heart failure (HF) is a chronic stressor that may elevate cardiovascular disease (CVD) risk. This study examined relationships between TNF-α, adiponectin, and clinical and demographic factors among HF family caregivers (FCGs). Methods/Study Population: This study is a secondary data analysis of baseline data from FCGs of individuals with HF enrolled in an intervention study (N=122, mean age 55 ± 11.7 years, range 25–80). The sample included 92% women and was racially diverse, with 59% identifying as African American, 39.3% as Caucasian, and 1.64% as other ethnicities. TNF-α and adiponectin levels were analyzed, and Spearman’s correlation was used to explore their associations with cardiovascular and metabolic indicators, including lipids and anthropometric measures. Results/Anticipated Results: TNF-α was inversely associated with total cholesterol (ρ = -0.241, p = 0.037) and adiponectin (ρ = -0.275, p = 0.017). Adiponectin was negatively associated with triglycerides (ρ = -0.208, p = 0.023), C-reactive protein (CRP; ρ = -0.283, p = 0.002), and metabolic syndrome (ρ = -0.181, p = 0.049). These findings suggest that TNF-α contributes to inflammation, while adiponectin may play a protective role in metabolic health. Discussion/Significance of Impact: Findings suggest that elevated TNF-α and reduced adiponectin may mark higher CVD risk in HF caregivers. Targeting inflammation and boosting adiponectin could reduce this risk. Longitudinal studies are needed to confirm these relationships and guide caregiver-focused interventions.

OBJECTIVES/GOALS: Hypertension is a major risk factor for coronavirus disease 2019 (COVID-19) severity. Our goal was to determine if hypertension worsens lung pathology induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in hamsters. METHODS/STUDY POPULATION: Male hamsters (7-8 weeks old) were infused with angiotensin II (AII; 200 ng/kg/min via osmotic minipump) for 4 weeks to induce hypertension. During the last week of the infusion, the hamsters were inoculated intranasally with vehicle (V) or SARS-CoV-2 (S; 1 x 105 plaque forming units/ml). Half of the hamsters were sacrificed 1 day post-inoculation (dpi-1) and the other half on dpi-6. Two scoring systems were applied to lung tissue sections stained with hematoxylin and eosin to determine the degree and severity of lung pathology: the first system assessed all pertinent alterations in the lungs, while the second system only assessed the pathology related to the pulmonary vasculature. Lung histopathology scores were calculated as the sum of the airway and lung alveolar scores in arbitrary units (AU). RESULTS/ANTICIPATED RESULTS: Studies revealed that the SARS-CoV-2-infected hamsters exhibited a 76-fold higher total airway score compared to vehicle controls [(AU): V, 0.25 ± 0.1; S, 19.00 ±1.35; p<0.05; n=4]. Total lung alveolar scores (27-fold) [(AU): V, 0.30 ± 0.11; S, 8.0 ± 4.1; p<0.05; n=4] and total vascular scores (17-fold) [(AU): V, 0.35 ± 0.2; S, 6.0 ±1.4; p<0.05; n=4] were also markedly higher compared to controls on dpi-1. AII increased blood pressure, which was sustained through the 4-week infusion period. Under these conditions, body weight slightly dropped by 4.5%. Ongoing studies are assessing the effect of hypertension on the % of airway, alveoli and vessels affected, airway and alveolar severity, and bronchiolar epithelial and type II pneumocyte hyperplasia. DISCUSSION/SIGNIFICANCE: Establishing the hypertensive hamster as a small animal model of COVID-19 will facilitate investigations into why preexisting hypertension is a risk factor for disease severity. These studies could lead to the development of novel therapeuticsfor treating COVID-19 patients with hypertension.

Objectives/Goals: MyCTSC harmonizes data from many sources into one database for evaluation, marketing, and CTSC member management to address current disparate collection and siloed use of data. It simplifies report creation with real-time dashboards so administrators and leadership can view progress quickly and plan for improvements based on real-time data. Methods/Study Population: MyCTSC is built using open-source software like Python, Django, MariaDB, Bootstrap, and Chart.js, and integrates data from sources such as systems for consult requests, pilot/voucher applications, and REDCap surveys. Each data source is imported into the warehouse either automatically via API, if available, or via manual file upload. De-duplication and other data cleaning are performed as well. Customized, real-time dashboards are developed based on the needs of administrators and leadership. While MyCTSC does not have a study population, it does have the stakeholders mentioned above as well as leadership. The development timeline spans three years: initial development and data warehouse population in Year 1, data cleaning and dashboard creation in Year 2, and full rollout to all CTSC members in Year 3. Results/Anticipated Results: MyCTSC aims to create a seamless data and member management system to resolve issues stemming from multiple data sources. Demographic challenges are addressed by implementing data cleaning and consolidating duplicate identities into a single profile. The initiative will enhance stakeholder buy-in by presenting evaluation use cases that show the impacts of CTSC resources. For example, workforce development needs will be met through surveys and integration of a course catalog. MyCTSC will also facilitate targeted resource and event advertising, and support investigator outreach and collaboration by utilizing dashboards and reports. Furthermore, it will serve as the consolidated data source for all CTSC modules, promoting greater interaction and collaboration across administration and modules. Discussion/Significance of Impact: MyCTSC integrates multiple sources, consolidates identities, and simplifies reporting for outreach and collaboration. It enhances interaction with researchers and community members, advancing translational science by linking projects and publications. MyCTSC, built with open-source software, can be made available to other CTSA hubs.

OBJECTIVES/GOALS: We are investigating the role of IL-6 in regulating renal function by measuring mean arterial pressure (MAP), renal plasma flow (RPF) and glomerular filtration rate (GFR) in wild type (WT) and IL-6-knockout (KO) mice in established mouse models of angiotensin II (AII)-dependent- hypertension and -salt-sensitive hypertension. METHODS/STUDY POPULATION: Twelve-week-old male WT and KO mice on the C57BL6 background strain were infused with vehicle (V; saline) or angiotensin II (AII; 200 ng/kg/min) for 12-14 days. Half of the AII-treatment groups were maintained on a high salt (HS; 6% NaCl) diet for the duration of the experiment, while the other half of the AII treatment groups and both vehicle groups were fed normal rat chow. MAP was continuously measured by a fluid filled catheter in conscious mice for the duration of the experiment. RPF and GFR were measured on days 12-14 in anesthetized mice by the para-aminohippurate, and fluorescein isothiocynate-Inulin techniques, respectively. All data were analyzed by 2-way ANOVA; *p<0.05 vs. WT, same treatment; #p<0.05 vs.V, same genotype; ^p<0.05, AII vs. AII+HS, same genotype. RESULTS/ANTICIPATED RESULTS: MAP was 31% lower in KO vs WT mice. AII increased MAP (1.2-fold) in WT but not KO mice. HS diet magnified AII-induced increases in MAP in WT and moderately increased MAP in AII-KO mice: [MAP (mmHg): WT+V, 130±7.0; KO+V, 91.0+4.0*; WT+AII, 153±5.0#; KO+AII, 83.0±4.0*; WT+AII+HS, 150±11#; KO+AII+HS, 93.0±4.0#]. AII infusion reduced RPF in the KO but not WT mice. Addition of HS reduced RPF in WT and exacerbated AII-induced reductions in RPF in KO mice [RPF (ml/min/g): WT+V, 1.82±0.23; KO+V, 1.91+0.40; WT+AII, 3.16±0.75#; KO+AII, 1.65±0.42*; WT+AII+HS, 1.10±0.31#^; KO+AII+HS, 1.13±0.XX#^]. The HS diet reduced GFR in AII-infused KO but not WT mice [GFR (µl/min/g): WT+V, 756±XX; KO+V, 788±XX; WT+AII, 1010±63*#; KO+AII, 756±23*; WT+AII+HS, 1100±150#; KO+AII+HS: 540±210*#^]. DISCUSSION/SIGNIFICANCE: The absence of IL-6 in male mice attenuated AII- and/or AII+HS-induced increases in MAP; however, it exacerbated HS-induced reductions in RPF and GFR. These findings suggest inhibiting IL-6 has therapeutic potential as an antihypertensive but not as a renal protective agent in hypertension and salt-sensitive hypertension disease states.

Objectives/Goals: To explore how generative AI and chatbot technologies can transform clinical research administration by improving operational efficiency, reducing administrative burden, and thereby enhancing overall productivity and accuracy in clinical research environments. Methods/Study Population: This explores AI’s application in enhancing clinical research administration. We specifically address AI’s role in QCT/MCA activities, charge master data cleaning, and generating IRB consent forms from award documents. AI algorithms optimize charge master data for accuracy and compliance. Generative AI models are employed to produce IRB consent forms efficiently, incorporating key grant documents. AI also conducts thematic analyses of historical CTSA aims to identify trends and recurring themes. Furthermore, AI-assisted tools enhance study design through innovative approaches to hypothesis generation, sample size calculation, and protocol development. Integrating these AI methods aims to significantly improve efficiency, accuracy, and overall quality in clinical research administration. Results/Anticipated Results: Incorporating AI into clinical research administration will yield improvements in efficiency and accuracy. AI-driven QCT/MCA steps are expected to reduce human error and enhance data integrity. Chargemaster data cleaning via AI prompts will likely result in optimized, error-free data, ensuring compliance with regulations. The use of genAI for creating IRB consent forms from grant documents should significantly streamline the IRB approval process, reducing preparation time and administrative burdens. Thematic analysis of CTSA aims by AI will provide deep insights into historical trends and recurring themes, aiding in strategic planning. AI-assisted study design tools are anticipated to optimize sample estimation, protocol development, and advance the quality of clinical research administration. Discussion/Significance of Impact: The significance lies in enhancing efficiency, accuracy, and quality in clinical research administration. By streamlining processes, reducing errors, and providing strategic insights, AI supports the CTSA mission to accelerate translational research, thus improving public health outcomes and scientific innovation.

OBJECTIVES/GOALS: Involving community partners in translational research improves impact. Yet, community-engaged research is challenging, and teams vary in their success. This study builds the evidence of key barriers and facilitators to effective community-engaged team science by drawing on the perspectives of seasoned researchers and community partners. METHODS/STUDY POPULATION: We conducted 3 focus groups with academic researchers (n=9) and 2 focus groups with community research partners (n=8). All participants were adults from the Southern California area, and had experience working on research teams that included academics and community partners. The focus group guide included questions about the participant’s experience with community-engaged research, including the value of these partnerships, examples of success and challenges, and opportunities for improvement. Transcriptions of the focus group recordings were analyzed to identify key themes and insights, and to explore similarities and differences between academic and community participant perspectives. RESULTS/ANTICIPATED RESULTS: Both researchers and community partners saw the potential value of participating in community-engaged research. However, they identified challenges to address, including: 1) Community partners should be invited to participate in early stages of the research process as equal partners to help frame the objectives. 2) Community partner’s knowledge should be valued through the use of their ideas and input, and providing monetary compensation for their time. 3) Academic researchers should aim to build long-term meaningful relationships with the community and build cultural competency (language, culture, and trust). 4) Community partners should be closely involved with the interpretation of results to confirm accuracy and identify valuable insights, and these contributions should be acknowledged. DISCUSSION/SIGNIFICANCE: Community partners being undervalued is a central challenge of community-engaged research teams. Greater adoption of best practices in team science could empower community partners and increase the value of this research. Structural barriers related to research funding and academic promotion should align to support these efforts.

Objectives/Goals: The relationship between factors that strain a healthcare system and delays in antimicrobial dosing for patients with sepsis is unclear – including redosing after first administration. The objective of this study is to define elements of capacity strain that impact timely second antimicrobial administration using electronic health record data. Methods/Study Population: In our planned retrospective cohort study, patients are eligible for inclusion if they present to one of 19 Atrium Health hospitals’ emergency department (ED) between 2022 and 2024, meet 2 or more Systemic Inflammatory Response Syndrome criteria within 6 hours, and are subsequently admitted to an intensive care unit (ICU). Capacity strain is defined using multiple measures including ED and ICU census, ED acuity, patient turnover, and ED wait times. The primary outcome is time between first and second doses of antimicrobials. Secondary outcomes are hospital length of stay (LOS), ICU LOS, days free of mechanical ventilation, and 90-day hospital re-admission. Association between variables will be assessed using univariate and multivariable regression models. Fit statistics will compare model performance. Results/Anticipated Results: Based on prior literature, we anticipate finding high rates of antimicrobial dosing delays (>10% incidence). We hypothesize that higher census, higher ED acuity, higher turnover, and wait times will each be associated with increased risk for delay in antimicrobial administration. This association will hold true when exposures are assessed in the ED, as well as in the ICU. We also expect that a model containing a combination of our proposed exposures will outperform each individual measure. Discussion/Significance of Impact: Gaps remain in understanding how system pressures interact with sepsis care delivery and outcomes. Health system strain may contribute to poor adherence to evidence-based practices. Identifying key strain measures can help direct the design and implementation of targeted interventions to improve care delivery and resource allocation.

Rutgers Health, Clinical Research Management (CRM) program with support from New Jersey Alliance for Clinical and Translational Science (NJ ACTS) provide scholarships to establish a “Clinical Research Experience” (CRE). The CRE focuses on building an entry-level Clinical Research Coordinator (CRC) workforce. The six-month precepted CRE is embedded in an accelerated master’s degree and demonstrates a skill-based approach to developing CRC resources. The CRE structure affiliated site collaboration; competency based curriculum objectives; standardized competency aligned on-boarding; and preceptor-evaluated performance. The experiential education is designed for academic medical centers (AMCs) to foster the development of qualified research coordinators. The CRE model supports “teach one, see one, do one” coupled with preceptor-evaluated feedback to cultivate clinical research competency.

We used a Zoom Un-meeting as an educational approach to provide experienced clinical research professional (CRP) adult learners a collaborative learning space to learn more about current issues for academic medical center (AMC) clinical research workforce development and collaborate on solution finding. CRPs operationalize the conduct of clinical trials and represent a significant brain trust for the Clinical and Translational Science (CTSA) consortium hubs with their vast knowledge base, extensive experience, understanding of relevant institutional policy, organizational culture, and clinical research operations. Un-meetings are an intentionally organized and coordinated group activity that encourages participants to focus on a topic and incorporate an open flow of ideas through brainstorming and an open discussion format, setting the stage for future collaborative action. We divided topics into a series of six consecutive monthly Un-meeting Zoom workshops. Ultimately, one resulting output from the meeting was the Center for Leading Innovation and Collaborations (CLIC) synergy paper award to support continued collaborative work. Currently, work teams have emerged to analyze qualitative data from brainstorming and breakout session recordings and to identify small-group activities. We describe this adult learning tool as valuable for exploring issues of AMC CRP professional development. This approach encouraged creative/critical thinking and opportunities for leadership, team science, and problem-solving among participants.

External advisory committees (EACs) are critical peer-review meetings that drive improvement at Clinical and Translational Science Award Program Hubs. Despite their ubiquity, evaluations of EAC optimization and effective implementation remain scarce. We present a two-tiered approach to optimizing EAC meetings through (1) in-depth, topically focused “pre-review” meetings comprised of external topic experts and at least one standing “full-board” EAC member, followed by (2) a traditional “full-board” EAC meeting. This approach allowed pre-review discussion of program-focused topics and specific recommendations, later delivered to the full-board for review and direction. To evaluate this approach, we interviewed 18 people who planned, administered, or attended pre-review and/or full-board meetings, including internal Hub staff, external topic experts, and standing EAC members. Thematic analysis was used to explore planning, implementation, and value of our two-tiered approach versus the traditional single full-board approach. Interviewees preferred the two-tiered approach, noting benefits including additional time to reflect, shared identification of strengths and challenges, and discussion of solutions to share later with the full-board. Those who attended pre-review meetings described building “transformational,” rather than “transactional,” relationships with invitees through more discussion and inter-hub sharing. That increased sharing invited more exploration, discussion, and planning of next steps toward innovation.

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

OBJECTIVES/GOALS: Contingency management (CM) procedures yield measurable reductions in cocaine use. This poster describes a trial aimed at using CM as a vehicle to show the biopsychosocial health benefits of reduced use, rather than total abstinence, the currently accepted metric for treatment efficacy. METHODS/STUDY POPULATION: In this 12-week, randomized controlled trial, CM was used to reduce cocaine use and evaluate associated improvements in cardiovascular, immune, and psychosocial well-being. Adults aged 18 and older who sought treatment for cocaine use (N=127) were randomized into three groups in a 1:1:1 ratio: High Value ($55) or Low Value ($13) CM incentives for cocaine-negative urine samples or a non-contingent control group. They completed outpatient sessions three days per week across the 12-week intervention period, totaling 36 clinic visits and four post-treatment follow-up visits. During each visit, participants provided observed urine samples and completed several assays of biopsychosocial health. RESULTS/ANTICIPATED RESULTS: Preliminary findings from generalized linear mixed effect modeling demonstrate the feasibility of the CM platform. Abstinence rates from cocaine use were significantly greater in the High Value group (47% negative; OR = 2.80; p = 0.01) relative to the Low Value (23% negative) and Control groups (24% negative;). In the planned primary analysis, the level of cocaine use reduction based on cocaine-negative urine samples will serve as the primary predictor of cardiovascular (e.g., endothelin-1 levels), immune (e.g., IL-10 levels) and psychosocial (e.g., Addiction Severity Index) outcomes using results from the fitted models. DISCUSSION/SIGNIFICANCE: This research will advance the field by prospectively and comprehensively demonstrating the beneficial effects of reduced cocaine use. These outcomes can, in turn, support the adoption of reduced cocaine use as a viable alternative endpoint in cocaine treatment trials.

Objectives/Goals: Conduct an evaluation of the Clinical Research Support Center (CRSC) model using a structured methodology, leverage insights to drive continuous improvement and evolution, and broadly disseminate outcomes to promote knowledge sharing and best practices for similar translational science initiatives. Methods/Study Population: We will utilize a structured case study approach, including adapting a translational science case study evaluation approach to assess impact as well as support practices, barriers, and facilitators that influence research translation. We will collect data from diverse sources. Primary data will come from structured interviews with stakeholders and a survey of a random sample of faculty and research staff. Secondary data includes grant applications, reports, and publications; public stories/media related to research supported by CRSC; scientific publications; and organizational documents. Results/Anticipated Results: The case study will identify the CRSC model’s impact on the research enterprise. Findings will articulate the specific strategies and practices the CRSC implemented to support clinical research; key factors, people, and resources that helped develop, improve, and promote CRSC services; significant milestones in evolution of the CRSC; and specific ways in which support services impact clinical research infrastructure and outcomes. The findings will highlight both strengths and areas for improvement. Early results show historical challenges with operational silos and resource limitations. Findings suggest CRSC facilitators include a team science approach with institutional support. Discussion/Significance of Impact: This case study will provide insights related to benefits, challenges, and facilitators of a translational science support model. Insights will guide the CRSC’s evolution and be broadly disseminated to promote knowledge sharing and best practices for future translational science applications.

Objectives/Goals: Sleep is a useful intervention target to improve mental and physical health. Yet, the contextual factors that impact sleep in real-life settings are poorly understood. We assessed how psychological and socioenvironmental factors influence self-reported sleep in a large, US sample (Study 1) and sleep physiology in a prospective cohort (Study 2). Methods/Study Population: Study 1: 13,483 participants (63% males, mean age 46, 24% non-White) completed on-demand blood pressure (BP), self-reported stress, physical health, and sleep duration assessments for 3 weeks. Study 2: 42 Black adults (23% males, mean age 42) completed up to six ambulatory sleep recordings at home for 2 weeks. Stage durations for rapid eye movement (REM) and non-REM Stages 1, 2, and 3 were determined. Daily self-reports of stress and physical health were also gathered. For both studies, residence zip codes were linked to a national database to quantify neighborhood factors (i.e., built environment, poverty, social cohesion, etc.). Multiple linear regressions and mixed-effect models assessed whether neighborhood factors, demographics, health indices, and stress could predict sleep durations. Results/Anticipated Results: In Study 1, neighborhood disadvantage, perceived stress, and systolic BP were associated with shorter sleep durations. Better self-reported health predicted longer sleep durations. Black, Native, Latino/as, and Pacific Islander participants had shorter sleep durations, whereas White participants had longer sleep durations. An interaction between perceived stress intensity and health indicated that better health (+1SD) protected sleep from increasing stress. Preliminary analyses in 26 participants from Study 2 revealed that neighborhood disadvantage and self-reported poor health are associated with shorter Stage 2 sleep durations. However, daily stress did not predict stage durations, and no interactions emerged. Discussion/Significance of Impact: Neighborhood disadvantage led to short sleep in two studies, with novel findings indicating that Stage 2 durations may be most sensitive to structural disadvantage. Interventions that invest in material resources to reduce neighborhood inequities may be an innovative approach to protect sleep and mitigate related illness.

Objectives/Goals: This research develops a Ruthenium (III)–Fruquintinib complex for lung cancer treatment. Goals include structural characterization using MALDI-TOF and UV–Vis spectroscopy, synthesis optimization, and antitumor activity assessment comparing efficacy against Fruquintinib alone through cell studies. Methods/Study Population: The Ruthenium(III)–Fruquintinib complex is synthesized through an optimized coordination chemistry protocol ensuring reproducibility. Small-scale reactions defined baseline conditions, monitored by UV–Vis spectroscopy for ligand–metal charge transfer. After successful crystallization, the method was scaled up consistently. Structural characterization using MALDI-TOF mass spectrometry will be performed in collaboration with the MSRC, University of Puerto Rico, with infrared spectroscopy as a complementary validation. Biological evaluation will use NSCLC cell lines to compare cytotoxic efficacy against Fruquintinib alone, employing MTT assays to determine IC50 and potential synergistic effects. Results/Anticipated Results: Lung cancer remains the leading cause of cancer-related mortality, with 125,070 projected deaths in 2024. Current treatments for metastatic disease include surgery, chemotherapy, radiation, and targeted therapy. Fruquintinib (FQ), a VEGFR inhibitor, showed promise in early NSCLC trials but limited efficacy in advanced stages. Ruthenium (III) complexes, based on the hard–soft acid–base principle, offer potential anticancer properties. Combining FQ with Ruthenium (III) may enhance therapeutic outcomes. Preliminary synthesis yielded reproducible crystals confirmed by UV–Vis signals. Future MALDI-TOF characterization and biological assays will assess structural validity and antitumor potential. Discussion/Significance of Impact: The Ruthenium (III)–Fruquintinib complex could enhance Fruquintinib efficacy in advanced NSCLC. This approach demonstrates the potential of metal-based drug design to improve cancer therapies, offering insights into combinatorial strategies and advancing coordination chemistry in medicinal research.