OBJECTIVES/GOALS: To evaluate whether the default mode network experiences age-related changes in functional connectivity and to identify these patterns of progression across seven decades of life. The overall goal is to evaluate whether quantifying these functional changes can serve as potential neurobiomarkers of aging for further quantitative genetic analyses. METHODS/STUDY POPULATION: Scans were performed at the RII on a 3T Siemens Trio scanner with an 8-channel head coil. Whole-brain, rsfMR imaging was performed using a gradient-echo EPI sequence sensitive to the BOLD effect (TE/TR = 30/3000 ms; flip angle = 90°; isotropic 1.72 mm2). Subjects were instructed to lie in dimmed light with their eyes open and try not to fall asleep. Image analysis was performed with FMRIB’s Software Library tools (www.fmrib.ox.ac.uk/fsl). Preprocessing of resting state data includes motion correction, brain extraction, spatial smoothing, and high-pass temporal filtering. Time series data was extracted from 9 DMN ROIs using FSL’s Featquery tool with 6mm radius spherical ROI masks created in Mango. After extraction, DMN connectivity was assess using structural equation modeling implemented in Amos 22.0 (IBM, Inc.). RESULTS/ANTICIPATED RESULTS: The exploratory SEM (eSEM) default mode network (DMN) model used consists of 9 regions of interest and 13 functional connectivity paths. The eSEM DMN model exhibited exceptional model fit to a primary resting state data set of 1169 subjects from the Genetics of Brain Structure project (1R01MH078111-01, David Glahn PI) with an RMSEA of 0.037. This model also had excellent model fit in 7 cohorts that were grouped by decade age (10s – RMSEA: 0.058, 20s – 0.051, 30s – 0.045, 40s – 0.048, 50s – 0.043, 60s – 0.035, 70s – 0.037). Analysis of the decade group-wise path coefficients identified 7 of the 13 paths (pC -> LMTG, pC -> PCC, PCC -> MPFG, PCC -> vACC, MPFG -> vACC, LIPL -> RIPL, LMTG -> RMTG) significantly negatively correlated with age-related changes. As early as the 1st decade of life, the functional connectivity within the DMN decreases. DISCUSSION/SIGNIFICANCE OF IMPACT: The DMN experiences progressive age-related decreases in connectivity, beginning in the first decade of life. Our results suggest that DMN path coefficients can serve as biomarkers of cognitive aging, which can then be used as quantitative traits for genetic analyses to identify genes associated with normal aging and age-related cognitive diseases.

ABSTRACT IMPACT: This work will be used to improve the design of engineered dermal replacements that can be used to treat difficult-to-heal wounds such as burns or ulcers. OBJECTIVES/GOALS: Wounds of the skin are among the most common and costly medical problems experienced. Engineered dermal replacements have been developed to improve outcomes, but the optimal design features are unknown. Here we describe a hypothesis-driven study of scaffold parameters using a computational model of wound healing to simulate a variety of treatments. METHODS/STUDY POPULATION: The computational model, which was informed by animal data, was used to simulate cell, cytokine, and collagen density fields. There are reciprocal mechanobiological interactions between the cells and collagen that guide the wound healing process. We analyzed initial wound properties such as scaffold stiffness, microstructure, degradation, and wound geometry by running a one-at-a-time order-of-magnitude parameter change. We then conducted a derivative-based local sensitivity analysis for simulated experimental conditions and constructed a surrogate model of wound contraction using Gaussian process regression. RESULTS/ANTICIPATED RESULTS: We conducted finite element model simulations of scaffolds that varied in physical properties. A sensitivity analysis demonstrated that wound contraction was highly sensitive to collagen fiber stiffness and density. Wound contraction rate was also dependent on initial wound size and surface area. Collagen fiber orientation in the scaffolds affected contraction directionality and the orientation of the final wound area. A Gaussian process regression model was fit to the simulation results for use in rapid prototyping of scaffolds for design optimization. The Gaussian process model was able to reproduce the wound contracture for training and test cases. DISCUSSION/SIGNIFICANCE OF FINDINGS: This work further analyzes a computational model of wounds treated with collagen scaffold dermal replacements. The hypothesis driven analysis of the model suggested several key design features of scaffolds. The model surrogate will further be used for the purposes of prediction and optimization of tissue regeneration outcomes.

OBJECTIVES/SPECIFIC AIMS: To study the role of OSA as an independent predictor of perioperative outcomes. METHODS/STUDY POPULATION: For this single-institution cohort study, we included data from patients who were enrolled into 1 of 3 prospective parent studies. All participants underwent in-patient surgeries, excluding neurosurgeries, which required general anesthesia and a postoperative stay of at least 1 day. Patients included in this study were assessed daily for postoperative delirium and pain severity as part of the parent studies. In the current study, determination of delirium diagnosis was based on the 3-minute Diagnostic Confusion Assessment Method (3D-CAM), and the Visual Analogue Pain Scale (VAS) was used for pain severity. Data on OSA diagnosis (determined by sleep study); OSA risk (determined by the STOP-Bang tool; snoring, tiredness, observed apnea, high blood pressure, body mass index>35 kg/m2, age>50, neck circumference, male gender); and compliance with treatment were obtained from the preoperative assessment record. Participants were grouped into 1 of 3 categories: high risk of OSA (HR-OSA; including patients with a previous positive sleep study or STOP-Bang score ≥5); intermediate risk of OSA (IR-OSA; including patients with a STOP-Bang score of 3 or 4); and low risk of OSA (LR-OSA; including patients with a previous negative sleep study or STOP-Bang score <3). Candidate risk factors for delirium and pain were also extracted from this record. RESULTS/ANTICIPATED RESULTS: Logistic regression will be used to test whether OSA independently predicts postoperative delirium and linear regression to assess OSAs relationship to acute pain severity. We hypothesize that patients in the HR-OSA category will experience a higher incidence of postoperative delirium and greater postoperative pain severity. We also predict a step-wise increase in risk of these adverse outcomes when analyzing patients stratified by OSA risk (HR-OSA vs. IR-OSA vs. LR-OSA). For our secondary analyses, we anticipate these outcomes are modified by compliance with CPAP treatment. We believe patients with OSA who do not use prescribed CPAP will experience a higher incidence of postoperative delirium as well as increased pain severity. DISCUSSION/SIGNIFICANCE OF IMPACT: OSA is a common and frequently undiagnosed perioperative problem associated with altered pain processing and a high incidence of postoperative delirium. While likely providing stronger evidence of OSA’s reported impact on postoperative delirium and pain, our findings might also help discern points of intervention for treatment and prevention. Since OSA’s presumed impact poses challenges to clinicians and patients, prospective, randomized trials testing preventative or mitigating interventions are necessary. We hope to use these results to design such trials and clinical plans, with the goal of reducing postoperative delirium and acute postsurgical pain severity for the large number of patients at risk due to OSA.

OBJECTIVES/GOALS: To teach the historical development of CTR, make a compelling scientific presentation, and use bibliographic databases and library resources. In addition, students learn how to write the research question, design the career development plan, know the protection of human subjects in research, and understand the mentor-mentee relationship. METHODS/STUDY POPULATION: The course includes a variety of educational strategies and activities that allow the student to increase their knowledge and initiate their interest in the field of CTR. Both academic semesters (August to December and January to May) are offered remotely in two-hour synchronous sessions on Fridays from 3:00 p.m. to 5:00 p.m. through videoconferences, in addition to asynchronous activities. Invited expert lecturers and faculty reinforce the course content in each of the topics they address. In addition, course coodinators assign guided tasks where the students perform the work. Then, they present or send their work to the course coordinators for evaluation. RESULTS/ANTICIPATED RESULTS: The course began in January 2020 and has six offerings, including one in the current academic semester (August to December 2023). Its first offering was in the semester from January to May, and due to the interest generated in students in August 2022, it is now avalilable in both semesters. From its beginning to the present, the course has included students from the University of Puerto Rico (UPR) Bayamón, Cayey, Humacao, Mayagüez, and Rio Piedras campuses, impacting all geographic areas of Puerto Rico. The course has also represented an opportunity for graduate faculty to teach CTR to undergraduate students. Until 2023, 56 students have enrolled. DISCUSSION/SIGNIFICANCE: Upon completing six-course offerings, the evaluation carried out by the students demonstrates satisfaction with the learning obtained. The knowledge and skills achieved have led them to participate in CTR with the mentoring of collaborating course professors and starting a new professional development opportunity for undergraduate students.

Objectives/Goals: Evaluate the effectiveness of ChatGPT as a complementary tool for addressing the mental health needs of Hispanic LGBTTQI+ young adult patients. We will also explore the experience of clinical healthcare providers with the integration of ChatGPT as a complementary tool in psychotherapy with Hispanic LGBTTQI+ young adults. Methods/Study Population: In this mixed-method study, we will create hypothetical clinical cases that reflect common mental health challenges experienced by LGBTTQI+ Hispanic population. These cases will be presented to three groups: 1) ChatGPT app, 2) clinical mental health care providers, and 3) clinical mental health care providers collaborating with ChatGPT. Each group will provide a diagnosis and a treatment plan based on the case information. A panel of experts will evaluate each plan using a standardized rubric to provide a score on clinical accuracy and on the ability to address specific needs of Hispanic LGBTTQI+ patients. Statistical analysis will be used to evaluate the differences in the scores of each domain and qualitative content analysis to evaluate the experience of clinical mental health care providers using ChatGPT. Results/Anticipated Results: The results will provide evidence of the effectiveness of ChatGPT as a supportive tool in mental health care. We anticipated that the combination of a clinical mental health care provider and ChatGPT to develop a diagnosis and treatment plan would produce better outcomes than either ChatGPT or the clinical mental health care provider working independently. We will also expect to find a positive attitude toward the integration of ChatGPT applications, viewing them as useful tools that complement traditional psychological interventions for Hispanic LGBTTQI+ young adults. The study will provide evidence of the effectiveness of ChatGPT to complementing clinical practice involving Hispanic LGBTTQI+ young adults. Those results in a preclinical phase are preconditions to a more applied intervention. Discussion/Significance of Impact: We aim to improve the quality of life for LGBTTQI+ Hispanics by developing innovative psychological treatments enhanced by AI apps. By developing innovative treatments, we are addressing and mitigating health disparities within the LGBTTQI+ Hispanic community in Puerto Rico and contributing to a broader effort of inclusivity and health equity.

OBJECTIVES/SPECIFIC AIMS: Pembrolizumab is an anti-PD-1 immune checkpoint antibody that has demonstrated promising anti-tumor activity in patients with solid tumor malignancies, including patients with brain metastases from malignant melanoma and non-small cell lung cancer. Leptomeningeal disease (LMD) is a rare form of malignant spread to the central nervous system (CNS), that occurs in 2%–10% of patients with solid tumors, most commonly in breast cancer and non-small cell lung cancer. We propose an open-label phase II study of pembrolizumab in patients with LMD from advanced solid tumors (NCT03091478). This study aims to determine if pembrolizumab therapy can lead to a radiologic, cytologic or clinical response in the CNS, in patients with LMD. METHODS/STUDY POPULATION: Patients with pathologically confirmed advanced solid tumors, and either radiologic or cytologic evidence of LMD, will be identified at a single institution. Radiologic LMD will be defined as a >4 mm area of measurable LMD on gadolinium-enhanced MRI brain/total-spine; and cytologic LMD will be defined as the presence of malignant cells on CSF cytology. Patients will be excluded if they have: active autoimmune conditions that require immunosuppression, received radiation therapy to the only area of measurable LMD within 3 months of study enrollment, have an ECOG performance status <1. Once enrolled, patients will receive pembrolizumab 200 mg intravenously every 3-weeks, until disease progression or unacceptable toxicity. Patients will have CSF sample sampling, blood draws, radiologic imaging of the body (CT), brain/total-spine (gadolinium-enhanced MRI) pre-treatment, after 2 and after 4 cycles of therapy, for response assessment and correlative studies. The primary endpoint of the study is CNS response assessed at 12 weeks/after 4 cycles of pembrolizumab, defined either as radiologic response (reduction in size of LMD on gadolinium-enhanced MRI) and/or cytologic response (conversion of positive to negative CSF cytology on 2 consecutive samples) and/or clinical response. Secondary endpoints will include progression-free survival, overall survival, and safety. To explore the mechanisms by which pembrolizumab may affect LMD, we will assess dynamic changes in genomic and immunologic markers in the CSF and serum pre and post pembrolizumab using next-generation sequencing and multi-color flow cytometry, respectively. RESULTS/ANTICIPATED RESULTS: We will aim to accrue a total of 20 patients, allowing for a 10% drop-out rate, the final sample size will include 18 patients who have received at least 1 dose of pembrolizumab. CNS-response at 12 weeks will be assessed radiologically +/− cytologically, and the proportion of patients with CNS response and associated 95% confidence interval with be reported. CNS-progression-free survival and overall survival will be assessed using the Kaplan-Meier method. Cause of death will be recorded. Safety will be assessed as detailed above, and monitored as per an institutional Data Safety and Monitoring Plan. Exploratory endpoints will include genomic testing of tumor cells and cell-free DNA in CSF and serum, and immunologic studies of immune cells in CSF and serum at pre-defined timepoints. These data will be presented descriptively. We conservatively estimate that we will accrue 1 patient per month at our institution. Study duration will be approximately 24 months, allowing 18 months for accrual and 6 months for follow-up and data analysis. DISCUSSION/SIGNIFICANCE OF IMPACT: There are no currently FDA-approved therapies for patients with LMD from solid tumors. Anti-PD-1 immunotherapy is a promising class of agents, with known efficacy in patients with CNS metastatic disease, across tumor types. This study seeks to identify whether pembrolizumab may lead to CNS responses in patients with LMD. Additionally, genomic and immunologic analyses in CSF and blood pre and post-pembrolizumab may identify mechanisms by which immunotherapy affects the CNS in patients with LMD.

OBJECTIVES/GOALS: Predictive models for health outcomes often have poor calibration potentially due to interactions that are ignored by standard methods. Using AHRQ models for Inpatient Quality Indicator (IQI) 11 Abdominal Aortic Aneurysm Repair and IQI 09 Pancreatic Resection mortality, we hypothesize that identifying interactions may improve model calibration. METHODS/STUDY POPULATION: We used adult discharge data from 16 states obtained from AHRQ Healthcare Cost and Utilization Project (State Inpatient Database), California Department of Health Care Access and Information, and New York State Department of Health. We used AHRQ’s v2021-1 Clinical Classifications Software Refined (CCSR) with present on admission flags to create features for risk-adjustment. We compared the performance of Least absolute shrinkage and selection operator (LASSO) model and first-order interaction models estimated using Hierarchical Group Lasso Regression (HGLR), after splitting the data into training and test sets. C-statistics, area under the precision-recall curve and Hosmer-Lemeshow calibration plots are reported. Finally, logistic regression models with selected CCSRs were evaluated on the test set. RESULTS/ANTICIPATED RESULTS: IQI 11 has four strata: open and endovascular repair of ruptured aneurysms (39% and 21% mortality, respectively); open and endovascular repair of unruptured aneurysms (6% and 0.8% mortality, respectively). IQI 09 has two strata: with and without pancreatic cancer (2% and 2.5% mortality, respectively). Comparing the HGLR model (with interaction effects) with Lasso models (without interactions), we noticed meaningful improvements in discrimination and calibration. However, for IQI 09, the extremely low mortality rate did not result in good HGLR or LASSO models. Interactions involving CCSRs could be identified using the novel HGLR method, which improved model performance given a heterogeneous population in IQI 11 with a mix of high and low event rates, unlike the more homogeneous patient population in IQI 09. DISCUSSION/SIGNIFICANCE: Standard implementations of regression models fail to address critical issues that arise in healthcare data – (a) quadratic explosion of potential interactions that cannot be manually identified, and (b) categorical variables with multiple levels or values (e.g., age categories). We propose innovative use of HGLR to robustly address these issues.

ABSTRACT IMPACT: A one-stage Bayesian multilevel model for meta-analysis integrating different survival data is introduced to complete the information synthesis without assuming proportional hazard. OBJECTIVES/GOALS: To develop a general modeling approach to perform efficient and robust meta-analyses using aggregated data (AD) for survival type endpoint and apply to a meta-analysis to examine the association between measurable residual disease (MRD) and disease-free survival (DFS) and overall survival (OS) in patients with acute myeloid leukemia (AML). METHODS/STUDY POPULATION: A Bayesian semi-parametric hierarchical model with a time-varying HR effect was presented. Three common types of survival information, including reconstructed survival data, the hazard ratio (HR) estimates with corresponding CIs and survival rates at specific time points, are synthesized such that all literature from the systematic review can contribute properly to the estimation and uncertainty quantification of the model parameters. The time-varying effects was modeled by assuming piecewise hazard risk and piecewise constant hazard ratio. The heterogeneity across studies was expressed by an additive random study effect and a random treatment-by-study interaction. The method was applied to a systematic review of 81 publications reporting on 11,151 AML patients. RESULTS/ANTICIPATED RESULTS: In simulation studies that the proportional hazard assumption is either valid or violated, the proposed method was efficient to achieve comparable performance to IPD meta-analysis, a gold standard approach, in estimating the survival rates, the restricted mean survival time at specific time points and median survival time with the point estimates close to the true values. When HR is not proportional over time, the proposed method was robust in estimating HR and significantly outperformed the classical random-effects meta-analysis. In the application to AML study, the average HR for achieving MRD negativity was 0.36 (95% CrI, 0.33-0.39) for OS and 0.37 (95% CrI, 0.34-0.40) for DFS. The association of MRD negativity with OS and DFS was significant and consistent across all subgroups. DISCUSSION/SIGNIFICANCE OF FINDINGS: The proposed novel method provided a flexible framework for meta-analysis of survival data, to accommodate various types of survival data in one model without assuming proportional hazards assumption. The findings of AML meta-analysis suggest that achievement of MRD negativity is associated with superior DFS and OS in patients with AML.

OBJECTIVES/SPECIFIC AIMS: We aim to leverage our analysis of the scientific collaboration network at a research university to design an innovative pilot program and foster scientific productivity. We test the impact of creating a new collaboration in a research community, which decreases the average network distance and accelerates the diffusion of information and expertise among the community’s investigators. METHODS/STUDY POPULATION: We mapped the whole network of co-authorship on publications and co-participation on extramurally awarded grants at the University of Florida (UF) between 2013 and 2015. We used network science methods to identify research communities of investigators who have consistently worked together and/or have other collaborators in common with at least one researcher based in the UF Health Science Center. We selected pairs of communities with (i) similar productivity levels, research interests, and network structures and (ii) no research projects in common. Communities in each pair were randomly assigned to a treatment or control group. In each treatment community, we selected 1 pair of investigators who had not collaborated in the past 3 years and whose connection would maximally reduce average network distance in the community. The pair was provided with an economic incentive to collaborate for the submission of a CTSA pilot proposal. RESULTS/ANTICIPATED RESULTS: We successfully identified 15 pairs of treatment/control communities. In each of 8 treatment communities, a pair of potential collaborators agreed to participate in the intervention. DISCUSSION/SIGNIFICANCE OF IMPACT: Network-informed Clinical Translational Science Awards (CTSA) pilot programs can identify research communities and create innovative collaborations. Statistical experiments can establish the programs’ causal effects on scientific productivity.

OBJECTIVES/GOALS: CTSIs around the country rely on Community Engagement Advisory Boards (CEABs) to bridge research and communities. The history of this 22-year-old board offers insight on 1) how it was created and has been sustained over time 2) its evolution, and 3) members’views of their contributions to translational research at UIC. METHODS/STUDY POPULATION: As founding members began to step down from this long-standing board, we started to document its history and members’ narratives and perspectives of the work conducted at UIC since its inception. Using an Oral History methodology, we conducted three virtual focus groups with 13 short and long-term members (n=6, n=4, n=3) to learn about changes within CEAB and in members’ roles, and individual semi-structured interviews with three long-standing members to expand on the origin and evolution of CEAB. Focus group data was coded and analyzed. We also extracted data on key events from archived files including grant proposals and CEAB meeting notes. A steering committee of three CEAB members helped guide this process. RESULTS/ANTICIPATED RESULTS: The CEAB was founded at the UIC College of Nursing in 2001 under the Center for Research on Cardiovascular Respiratory Health, with a grant from the National Institutes of Nursing Research (NINR). It was established as college-wide advisory board of community experts to help engage underserved communities and to contribute to research beyond recruitment and retention. In 2009, upon receipt of a Clinical Translational Science award that established the Center for Clinical Translational Science (CCTS), the CEAB became a campus-wide board. Over 30 community organizations and many non-affiliated community members have contributed to translational research at UIC throughout the board’s history. DISCUSSION/SIGNIFICANCE: Over twenty years later, the CEAB continues to help bridge researchers and communities, and to raise awareness about community needs, the importance of cultural relevance, and the inclusion of underserved communities in research. Long-term members have played a key role in providing continuity over the years.

OBJECTIVES/SPECIFIC AIMS: 1. To assess feasibility (efficacy, safety, acceptability) of the menstrual cup for managing urinary incontinence among women with obstetric fistula 2. To examine pre-implementation facilitators and barriers (including appropriateness) among additional stakeholders METHODS/STUDY POPULATION: Sequential explanatory mixed methods study whereby repeated measures clinical trial results are explained by subsequent interviews with additional women with OF on coping and stigma and other stakeholders on perceptions of fistula self-management. RESULTS/ANTICIPATED RESULTS: Of the 32 patients screened, 11 were eligible (100% consent rate). At baseline, mean (±SD) leakage in ml was 63.2 (±49.2) (95% CI: 30.2-96.3) over two hours, while the mean leakage over two hours of use of the cup was 16.8 (±16.5) (95% CI: 5.7-27.9). The mean difference of 46.4 (±52.1) ml with use of the cup (95% CI: 11.4-81.4) was statistically significant (p = 0.02). With the cup, women experienced an average 61.0% (±37.4) (95% CI: 35.9-86.2) leakage reduction, a difference 10/11 users (91.0%) perceived in reduced leakage. One participant, reporting four previous surgical attempts, experienced a 78.7% leakage reduction. Acceptability was high–women could easily insert (8/11), remove (8/11), and comfortably wear (11/11) the cup and most (10/11) would recommend it. No adverse effects attributable to the intervention were observed on exam, although some women perceived difficulties with insertion and removal. Data collection tools were appropriate with slight modification advised. Interviews highlighted that women were already using various active coping and resistance strategies but lacked access to tools to support coping. Additional stakeholders reported the innovation was a simple, low-cost device that is an appropriate fit with ongoing fistula programming. Pre-implementation facilitators include the clear relative advantage to existing self-management strategies, the potential to build upon existing partnerships to implement, and a tension for change to address surgical gaps. Barriers included additional stakeholder’s perceptions of low user acceptability and appropriateness in some cases and the need for additional study data to inform decision making for practice and policy. DISCUSSION/SIGNIFICANCE OF IMPACT: The innovation is efficacious, acceptable, adds to current coping strategies, and fits within existing fistula programs. Stakeholders’ pre-implementation perceptions highlight the importance of partnerships and the need for an evidence base related to effectiveness, acceptability, and cost. Challenges to address include access to resources within these contexts (water, soap, and safe space to empty cup) and development of a culturally appropriate counseling message. Future research warranted.

Failure to accrue participants into clinical trials incurs economic costs, wastes resources, jeopardizes answering research questions meaningfully, and delays translating research discoveries into improved health. This paper reports the results of a pilot test of the Median Accrual Ratio (MAR) metric developed as a part of the Common Metrics Initiative of the NIH’s National Center for Advancing Translational Science (NCATS) Clinical and Translational Science Award (CTSA) Consortium. Using the metric is intended to enhance the ability of the CTSA Consortium and its “hubs” to increase subject accrual into trials within expected timeframes. The pilot test was undertaken at Tufts Clinical and Translational Science Institute (CTSI) with eight CTSA Consortium hubs. We describe the pilot test methods, and results regarding feasibility of collecting metric data and the quality of data that was collected. Participating hubs welcomed the opportunity to assess accrual efforts, but experienced challenges in collecting accrual metric data due to insufficient infrastructure and inconsistent implementation of electronic data systems and lack of uniform data definitions. Also, the metric could not be constructed for all trial designs, particularly those using competitive enrollment strategies. We offer recommendations to address the identified challenges to facilitate progress to broad accrual metric data collection and use.

While mentors can learn general strategies for effective mentoring, existing mentorship curricula do not comprehensively address how to support marginalized mentees, including LGBTQIA+ mentees. After identifying best mentoring practices and existing evidence-based curricula, we adapted these to create the Harvard Sexual and Gender Minority Health Mentoring Program. The primary goal was to address the needs of underrepresented health professionals in two overlapping groups: (1) LGBTQIA+ mentees and (2) any mentees focused on LGBTQIA+ health. An inaugural cohort (N = 12) of early-, mid-, and late-career faculty piloted this curriculum in spring 2022 during six 90-minute sessions. We evaluated the program using confidential surveys after each session and at the program’s conclusion as well as with focus groups. Faculty were highly satisfied with the program and reported skill gains and behavioral changes. Our findings suggest this novel curriculum can effectively prepare mentors to support mentees with identities different from their own; the whole curriculum, or parts, could be integrated into other trainings to enhance inclusive mentoring. Our adaptations are also a model for how mentorship curricula can be tailored to a particular focus (i.e., LGBTQIA+ health). Ideally, such mentor trainings can help create more inclusive environments throughout academic medicine.

The COVID-19 pandemic led to an increased need to conduct research and community engagement using digital methods. Unfortunately, the shift away from in-person research activities can make it difficult to engage and recruit participants from under-resourced communities that lack adequate digital infrastructure. At the beginning of the pandemic, our team recognized that imminent lockdowns would significantly disrupt ongoing engagement with low-income housing resident community partners and that we would ultimately bear responsibility if that occurred. This manuscript outlines the development of methods designed to create capacity for virtual engagement with a community advisory board that were subsequently applied to a longitudinal mixed-methods study. We describe how our experience engaging low-income housing residents during the height of the pandemic influenced the approach and offer guidelines useful for engaging under-resourced communities regardless of setting. Of these, a strong commitment to providing technology, unlimited data connectivity, and basic digital literacy training/technical support is most important. While each of these is essential and failure in any one area will reduce overall effectiveness of the effort, providing adequate technical support while maintaining ongoing relationships with community members is the most important and resource-intensive.

OBJECTIVES/SPECIFIC AIMS: In patients with recurrent glioblastoma (GBM) who undergo a second surgery following standard chemoradiotherapy, histopathologic examination of the resected tissue often reveals a combination of viable tumor and treatment-related inflammatory changes. However, it remains unclear whether the degree of viable tumor Versus “treatment effect” in these specimens impacts prognosis. We sought to determine whether the percentage of viable tumor Versus “treatment effect” in recurrent GBM surgical samples, as assessed by a trained neuropathologist and quantified on a continuous scale, is associated with overall survival. METHODS/STUDY POPULATION: We reviewed the records of 47 patients with histopathologically confirmed GBM who underwent surgical resection as the first therapeutic modality for suspected radiographic progression following standard radiation therapy and temozolomide. The percentage of viable tumor Versus “treatment effect” in each specimen was estimated by one neuropathologist who was blinded to patient outcomes. RESULTS/ANTICIPATED RESULTS: After adjusting for other known prognostic factors in a multivariate Cox proportional hazards model, there was no association between the degree of viable tumor and overall survival (HR 0.83; 95% CI, 0.20–3.4; p=0.20). DISCUSSION/SIGNIFICANCE OF IMPACT: These results suggest that, in patients who undergo resection for recurrent GBM following standard first-line chemoradiotherapy, histopathologic quantification of the degree of viable tumor Versus “treatment effect” present in the surgical specimen has limited prognostic influence and clinical utility.

OBJECTIVES/SPECIFIC AIMS: A mimic of congenital infections and a rare genetic cause of interferon overproduction, Aicardi Goutières Syndrome (AGS) results in significant neurologic disability. AGS is caused by pathogenic changes in the intracellular nucleic acid sensing machinery (TREX1, RNASEH2A, RNASEH2B, RNASEH2C, SAMHD1, ADAR1, and IFIH1). All affected individuals exhibit neurologic impairment: from mild spastic paraparesis to severe tetraparesis and global developmental delay. We hypothesize that genotype influences the heterogeneous developmental trajectory found in AGS. METHODS/STUDY POPULATION: To characterize this spectrum, age and symptoms at presentation and longitudinal developmental skill acquisition was collected from an international cohort of children (n=88) with genetically confirmed AGS. RESULTS/ANTICIPATED RESULTS: We found that individuals present at variable ages, with the largest range in SAMHD1, ADAR, and IFIH1. There are 3 clusters of symptoms at presentation: altered mental status (irritability or lethargy), systemic inflammatory symptoms, and acute neurologic symptoms, with variability across all genotypes. By creating Kaplan-Meier curves for developmental milestones, we were able to create genotype-based developmental trajectories for the children affected by the 5 most common genotypes: TREX1, IFIH1, SAMHD1, ADAR, and RNASEH2B. Individuals with AGS secondary to TREX1 were the most severely affected, significantly less likely to reach milestones compared to the other genotypes, including head control, sitting, and nonspecific mama/dada (p-value <0.005). Individuals affected by SAMHD1, IFIH1, and ADAR collectively attained the most advanced milestones, with 44% of the population achieving a minimum of a single word and 31% able to walk independently. Three retrospective scales were also applied: Gross Motor Function Classification System, Manual Ability Classification Scale, and Communication Function Classification System. Within each genotypic cohort, there was pronounced heterogeneity. DISCUSSION/SIGNIFICANCE OF IMPACT: Our results demonstrate the influence of genotype on early development, but also suggest the importance of other unidentified variables. These results underscore the need for deep phenotyping to better characterize subcohorts within the AGS population.

ABSTRACT IMPACT: This work will discuss informatics methods enabling the use of exposure health data in translational research. OBJECTIVES/GOALS: 1. Characterize gaps and formal informatics methods and approaches for enabling use of exposure health in translational research. 2. Education of informatics methods enabling use of exposure health data in translational research. METHODS/STUDY POPULATION: We performed a scoping review of selected literature from PubMed and Scopus. In addition we reviewed literature and documentation of projects using exposure health data in translation research. RESULTS/ANTICIPATED RESULTS: Primary challenges to use of exposure health data in translational research include: (1) Generation of comprehensive spatio-temporal records of exposures, (2) Integration of exposure data with other types of biomedical data, and (3) Uncertainties associated with using data as exact quantifications of exposure which are dependent on both - the proximity of measurement to subject under consideration and the capabilities of measuring devices. We identified 9 major informatics methods that enable incorporation and use of exposure health data in translational research. While there are existing and ongoing efforts in developing informatics methods for ease of incorporating exposure health in translational research, there is a need to further develop formal informatics methods and approaches. DISCUSSION/SIGNIFICANCE OF FINDINGS: Depending on the source about 50 - 75% of our health can be quantified to be a contribution of our environment and lifestyles. In this presentation, we summarize the studies and literature we identified and discuss our key findings and gaps in informatics methods and conclude by discussing how we are covering these topics in an informatics courses.

OBJECTIVES/GOALS: While CTSA hubs have contributed to the successes in COVID-19 clinical research, understanding the role of the CTSA consortium in translating vaccine efficacy and availability to awareness and implementation. The goal of this study is to quantitatively assess the use of social media in the dissemination of COVID 19 vaccine content across 60+ CTSA Hubs. METHODS/STUDY POPULATION: Structured search terms in the CTSA Search Solutions database were used to identify CTSA Hub website pages highlighting “COVID-19 Vaccination Information.” Each link identified was manually reviewed for vaccination content. The links and content identified by CTSA Search Solutions were then validated by advanced Google search operator “vaccine site” and manual review of CTSA Hub websites. Official CTSA Hub social media platforms were searched for vaccine proliferation content from January 1, 2020 to November 11, 2021. Data points collected included Community Targeted Vaccine Content, Vaccine Awareness, Vaccine Distribution, Vaccine Clinical Trial, Vaccine Related Media, Social Media Presence, and Social Media Vaccine Proliferation. RESULTS/ANTICIPATED RESULTS: In examining content, of the 64 listed CTSA Hubs, 52 of (67.2%) hosted one or more categories of COVID-19 vaccine information, and 16 (25%) hosted three or more categories. The most common category was “Community Targeted Information” with 27 (42.2%) hubs; the least common category was “Vaccine Distribution” with 5 (7.8%) hubs. Examining social media for vaccine proliferation, 41 (64.1%) hubs had connected social media and 23 (35.9%) hubs had vaccine proliferation posts. The most common platform was Twitter with 37 hubs; the least common platform was Instagram with 5 hubs. DISCUSSION/SIGNIFICANCE: Our investigation demonstrated varying Phase 4 translational efforts via social media among the CTSA Hubs for COVID-19 vaccine implementation. These novel findings identify promising opportunities for enhancement while emphasizing proven strategies from CTSA hubs nationwide. Further research will elucidate granular trends among CTSA hubs.