OBJECTIVES/SPECIFIC AIMS: Our goal is to explore the value of learning algorithms to improve both the efficiency and accuracy of a clinician undertaking the cognitive task of selecting the best resuscitative intervention for a hemodynamically unstable patient in the ICU. Machine learning is an ideal discipline to solve this problem. The ICU is a data rich environment, however there is significant uncertainty regarding the interdependency of this data. Experts consistently struggle to develop deterministic models of the underlying forces driving hemodynamic perturbations and intervention responsiveness. Machine learning, especially deep learning, assumes no correlation between inputs. Deep architectures disentangle these high-level relationships through exposure to abundant, diverse data sets such as those used in this project, obviating the need to manually explore confounding interactions. METHODS/STUDY POPULATION: We are using the “Medical Information Mart for Intensive Care” (MIMIC-III) database for this project. MIMIC-III is a large, single-center database comprising information relating to patients admitted to critical care units at Beth Israel Deaconess Medical Center, a large tertiary care hospital, from 2001 to 2012. It contains data associated with 38,597 distinct adult patients and 53,423 distinct hospital admissions for those patients, with a mean of 4579 charted observations and 380 laboratory measurements available for each hospital admission. Classes of data in the MIMIC-III are varied and include billing, intervention, laboratory, medication, and physiologic data among others. In addition to training an RNN in the task of predicting hemodynamic states, we will also attempt to train 2 additional models on the same data—a multidimensional linear regression and a nonsequence-oriented deep neural network. For each of these models we will measure accuracy using root mean squared error (RMSE) and mean absolute error (MAE) to provide scale-dependent measurements of accuracy. RESULTS/ANTICIPATED RESULTS: Our results will be reported in 2 primary categories: numerical accuracy of the RNN model and applicability, utility, and accuracy in a live clinical setting. The use of RNNs in biomedical informatics, and in general, is a relatively new phenomenon. This means that the body of literature which could provide a basis for our expected results is limited. Because of this we have chosen staged goals in assessing our model. First, we hope to achieve a model that reliably predicts the direction of response. Being able to answer only the question of how a patient will respond—will they move toward or away from our therapeutic goal—is as good as existing prediction methods. It is well established in the literature that, by almost any metric, ~50% of hemodynamically unstable patients respond to a fluid challenge. If we are within 10% of this average (40%–60% respond), then we can be confident in the accuracy of our model in predicting direction. Upon achieving this, we will then measure accurate prediction of response magnitude. To this affect, we hope to achieve an RMSE <10% between our test data and corresponding predicted output before proceeding further. In addition to numeric accuracy, we acknowledge that a plan for practical, clinical validation is needed before utilizing this tool in a clinical environment. Such validation will require 3 separate components. First, numeric accuracy will need to be determined again as compared with prospective data on actual patients in the ICU. This step is critical to prove that no information leakage from target data back to input data occurred during training. Second, there must be a comparison to existing prediction methods, such as the passive leg raise in combination with measurement of cardiac output to predict volume responsiveness. Finally, we must measure the cost to the clinician of implementing our model in an ICU, specifically how it impacts their time to accomplish the task of selecting an intervention for the hemodynamically unstable patient. However, these tasks are beyond the scope of this project and will be left for later investigations. DISCUSSION/SIGNIFICANCE OF IMPACT: If we are successful, this study will provide the first step toward a data-driven model for predicting patient responsiveness to a given hemodynamic intervention or collection of interventions. As compared with current best practice maneuvers, this model will not require manipulation of the patient, have less rigid criteria for reliable interpretation, and not require as specific of a technical skillset to interpret. Furthermore, it will include many common categories of resuscitative therapies (eg, vasopressors, inotropes, fluids) and will allow effects of a combination of interventions to be predicted while making no assumptions of interdependence between said interventions. This study will also contribute a novel process of sequence prediction using RNNs by incorporating an element of context on top of the sequential data in every training step. An RNN learning the sequence of hemodynamic data comprising a patient’s hemodynamic state would, alone, fit into the realm of sequence prediction. Our innovation is the addition of treatment information with each temporal division of the hemodynamic data. The result is an RNN that combines the task of sequence prediction with sequence translation, the 2 major use cases for RNN learning algorithms.

OBJECTIVES/GOALS: Our goal is to employ a structure-guided design approach to engineering a safer and more effective variant of the TIL1383I T cell receptor (TCR) currently under study in clinical trials for malignant melanoma METHODS/STUDY POPULATION: Using our unpublished structure of TIL1383I we are in process of designing a panel of TCR variants with the goal of identifying candidates that improve “focus” towards the tyrosinase antigen presented on the MHC class I molecule HLA-A2. RESULTS/ANTICIPATED RESULTS: Structural analysis of TIL1383I revealed key residues, particularly beta-chain residues E97, G101, L102, responsible for engaging the tyrosinase peptide bound to HLA-A2. The crystal structure of TIL1383I in complex with tyrosinase-HLA-A2 also highlighted its uncharacteristic binding geometry and we therefore hypothesize that this binding orientation is associated with the observed CD8 co-receptor independence of TIL1383I. Indeed, functional analysis with TIL1383I-transduced CD8-positive and CD8-negative T cells, transduced T cells expressing a truncated CD8 lacking the intracellular LCK signaling domain, and tyrosinase peptide variants presented by HLA-A2 mutants outline this co-receptor independence. Combined with our interrogation of tyrosinase peptide cross-reactivity via a peptide positional scanning library approach, structure-guided design resulted in the identification of TIL1383I variants with improved binding affinities to the tyrosinase peptide as well as an understanding of structural characteristics that may contribute to TIL1383I’s co-receptor independence.

Objectives/Goals: We investigated the risk of trauma in the form of fractures and traumatic brain injuries (TBIs) among Medicare beneficiaries with incident Parkinson’s disease (PD) age ≥67 compared to population-based controls. Secondarily, we examined the risk of death following a fracture in PD cases compared to controls. Methods/Study Population: We identified incident PD cases (N = 94,317) within a population-based sample of 2017 Medicare beneficiaries. Controls (N = 471,585) were matched 5:1 on month and year. We obtained claims data from 2017 to 2019 to follow cases and controls to identify new fractures treated in a hospital. Our primary outcome was any fracture. We also considered fracture type and TBI. We compared frailty level between cases and controls. We used logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between trauma and PD after adjusting for the following covariates: selected medical comorbidities, age, sex, race/ethnicity, smoking, and use of care. We used Cox regression to estimate hazard ratios (HRs) and 95% CI for trauma in cases compared to controls using the same covariates. Results/Anticipated Results: Compared to controls, PD patients who developed a fracture were more likely to have a history of falls (OR = 2.20, 95% CI 2.08–2.34) and difficulties in walking (OR = 2.66, 95% CI 2.50–2.82). Compared to controls with a fracture, PD patients with a fracture were more likely to be moderately frail (OR = 1.43, 95% CI 1.25–1.64). PD cases had a higher risk of all fracture types, including hip (OR = 1.93, 95% CI 1.85, 2.01), spine (OR = 1.90, 95% CI 1.79, 2.02), upper extremity (OR = 1.69, 95% CI 1.58–1.80), and other traumas such as a TBI (OR = 2.14, 95% CI 1.88–2.43). PD patients had greater mortality following a fracture (HR = 1.18, 95% CI 1.13–1.24) than controls. Discussion/Significance of Impact: The burden of trauma in the first two years immediately after PD diagnosis is high and warrants the initiation of early fall and fracture prevention strategies, in addition to aggressive treatment of PD symptoms by all providers caring for patients with PD.

OBJECTIVES/SPECIFIC AIMS: The study aims to track and correlate ocular neuropathic symptoms, corneal sensitivity and dry-eye like pain, after scleral buckle and posterior vitrectomy surgeries. The goal is to identify a population of patients that receive these retinal surgeries that experience ocular neuropathic pain. METHODS/STUDY POPULATION: Methods - Prospective and Retrospective cohort studies were designed with the follow cohorts: scleral buckle, posterior vitrectomy, and control. Typical follow up for SB/PV surgeries are: 1 day, 1 week, 1, 3, 6, 12 months post surgery. CS and DELP metrics are measured at each visit. For study interventions, all subjects (from both arms) will undergo the same series of tests, in the same sequence at each visit. Phase 1 of the visit focuses on CS and phase 2 on DELP. These interventions are as follows: first, subjects will receive Drop A; Drop A will be administered in a randomized, double-blinded manner at each visit to either balanced salt solution (control) or Muro 128 5% hypertonic saline (experimental). Drop A will be administered to both eyes. After receiving the drops, subjects will complete a visual analog scale questionnaire to grade their corneal sensitivity. Next, subjects will undergo a five minute washout. After the washout, subjects will receive Drop B; Drop B will be whichever drop was not administered in the Drop A phase. After Drop B is given, subjects will complete the visual analog scale. To begin phase 2, subjects will be given the Ocular Surface Disease Index to record dry eye signs and symptoms. Finally, tear film parameters will be collected using Schirmer’s tear production test and tear film breakup time. Study Population. - Inclusion criteria: For retrospective cohort studies, subjects who have undergone unilateral SB or PV in the past year. For prospective cohort studies, subjects who will undergo unilateral SB or PV in the near future, and age-matched controls. Exclusion criteria: For both retrospective and prospective arms, the same exclusion criteria apply. They include: a previous diagnosis of dry eye; current use of neuropathic pharmacotherapies (including gabapentin, pregabalin, TCAs, SNRIs, carbamazepine, and opioids). RESULTS/ANTICIPATED RESULTS: As of 11/15/18, only the scleral buckle retrospective study arm had enough subjects for any meaningful preliminary report; the arm currently has 8 subjects. Of these 8 subjects, 5/8 subjects report increased surgical-eye corneal sensitivity and 6/8 show discordant dry eye symptoms and tearfilm parameters. Our power analysis showed that N=16 subjects in a group are required to detect a statistical significant difference in corneal sensitivity response. We expect to see a relapsing and remitting pattern of pain (as measured by corneal sensitivity and dry eye questionnaire), as is typical of neuropathic pain. Regarding dry eye symptoms, we anticipate subjects will have prominent dry eye symptoms (as measured by a validated questionnarie), but show no abnormalities in tearfilm parameters. DISCUSSION/SIGNIFICANCE OF IMPACT: To our knowledge, this is the first observational study of neuropathic pain symptoms of corneal sensitivity and dry-eye like pain, in post retinal surgery patients. We recognize the challenge of diagnosing neuropathic pain; currently the gold standard is clinical. However, symptoms of neuropathic pain are non-specific and subtle. Identification of a population suffering from post-retinal surgery ocular neuropathic pain will provide a foundation to test topical naltrexone as a diagnostic tool. If our hypothesis is correct, topical naltrexone could serve as a cheap, easy, and quick diagnostic test for ocular neuropathic pain. We envision this diagnostic test would allow many misdiagnosed and mistreated post-surgical patients to be treated with appropriate therapies aimed at neuropathic etiologies.

OBJECTIVES/SPECIFIC AIMS: A small molecule therapy is within reach to treat a molecular mechanism known to result in thousands of fatal diseases. For 10% of patients with a genetic disease, a nonsense/STOP mutation/premature termination codon (PTC) is the underlying cause of their malady. PTCs prematurely stop protein synthesis and yield truncated proteins. Truncated proteins typically provide little to no proper function or activity and are rapidly degraded; thus, disease is imminent. Recent work has demonstrated that small molecules including aminoglycosides can cause the ribosome to readthrough these PTCs. Thus, PTC readthrough with small molecules is a very attractive approach for treating diseases caused by PTCs. Small molecules that promote readthrough act on the ribosome and induce a ribosomal conformational change. In this conformation, the PTC is not recognized by the translational machinery and an amino acid is incorporated into the growing peptide chain, thus protein synthesis continues and does not stop. The use of a single small molecule to readthrough various PTC mutations has been repeatedly effective for in vitro studies and some of these have progressed to clinical trials. Although there has been success in defining these small molecules, the field has discovered that every PTC is unique and likely requires a different small molecule. Thus, developing a cell culture model to test read-through of Lafora PTCs and the functionality of the protein product is the first step to developing a readthrough therapy for a LD. METHODS/STUDY POPULATION: Method for in vitro quantification of readthrough: 24 hours before transfection, HEK293 cells were split in 6-well plates. On the following day, approximately 60% confluence, the cells were transiently transfected with the WT or PTC mutated constructs using Polyethylenimine HCl MAX. Cells were transfected with a total amount of 0.35 μg DNA/well and 2 μl Polyethylenimine HCl MAX/well. Four hours later, the transfection medium was removed and replaced with fresh medium, without streptomycin and penicillin. The fresh media contained gentamicin diluted to the indicated concentration per well. Fresh gentamicin-containing medium was replaced after 24 hours. After 48 hours, lysates were collected in 100 μL mRIPA supplemented with protease inhibitors for each construct. The lysates were run on a western blot and the N-terminal was probed with anti-FLAG. A malachite green phosphatase assay to measure inorganic phosphate release from phospho-glucans, that is glycogen or LBs. Glycogen is used in this laforin bioassay as the biologically relevant substrate in order to determine the specific activity of the readthrough products. All reactions are incubated for 40 minute the absorbance is measured at 620 nm and the pmoles of phosphate released/min/nmol protein was calculated using a standard curve. RESULTS/ANTICIPATED RESULTS: HEK293 cells were transfected with MeCP2 R241X, laforin R241X, or laforin WT NT-FLAG construct, treated with different concentrations of gentamicin for 48 hours, and laforin levels were assessed by Western analysis with anti-FLAG. HEK293 cells were transfected with WT laforin or a laforin PTC CT-FLAG construct, treated with different concentrations of gentamicin for 48 hours, and laforin levels were assessed by Western analysis with anti-FLAG. B. Quantification of read-through for PTC experiments. *p-value≤0.001. #p-value≤0.001. Schematic of laforin bioassay. The assay has been performed with human and mouse tissue as well as cultured cells. B. Laforin bioassay results using laforin from PTC experiment. **p-value≤0.001. *p-value≤0.01. DISCUSSION/SIGNIFICANCE OF IMPACT: Our results suggest that gentamicin is not only responsible for inducing readthrough of the PTC mutations, but also for promoting translation of fully functional laforin. Therefore, our in vitro system for the analysis of PTC readthrough of laforin will be useful for determining which PTC mutations are suppressible with gentamicin or other small molecules, in what quantities laforin is recovered from PTC mutations, and if the protein products possess the appropriate enzymatic function.

OBJECTIVES/GOALS: Can we detect Parkinson’s-disease-related motor impairments using computer vision and machine learning? METHODS/STUDY POPULATION: A sample of 29 people with Parkinson’s disease (PD) and 29 non-Parkinson’s disease (non-PD) controls were recruited from the University of Iowa Movement Disorders Clinic. Videos of 3 motor assessment tasks performed using the hands were recorded and hand location information was abstracted using the computer vision program MediaPipe. Measures from the raw data series and FFT were used as features to train a model using boosted trees to classify each video as PD or non-PD. Model performance was evaluated using leave-one-out cross-validation. Additionally, we used recursive feature elimination to reduce model complexity. RESULTS/ANTICIPATED RESULTS: A model using two features identified by recursive feature elimination yielded a model with an overall accuracy of 81% in cross-validation. In our sample, the model had 86.2% sensitivity, 75.9% specificity, and an AUC of 0.839. Additional improvement may be possible with more data processing, especially in the time-domain. DISCUSSION/SIGNIFICANCE: We built a classifier that was able to reliably and accurately discriminate between videos of motor assessments in people with Parkinson’s and people without. This may provide a low cost screening tool in rural areas or primary care clinics with limited access to neurologist expertise.

OBJECTIVES/GOALS: Determine if exposure to violence at different life stages (childhood versus recent exposure) in postpartum women is associated to increased risk of weight retention more than 1 year and no more than 2 years after delivery, thus increasing health risk in short and long term. METHODS/STUDY POPULATION: Participants will be recruited from a cohort of post-partum women who received services from the Puerto Rico Women and Children Program (PR WIC) during pregnancy and postpartum period as per PR WIC established criteria. Families that have completed their participation in a Lifestyle intervention trial will be paired 2:1 with eligible nonparticipants that fulfill trial enrollment criteria. Language, culture validated instruments will be used to document maternal violence exposure in childhood and recent exposure, defined as within the last 12 months. To asses weight retention, pre-pregnancy weight will be compared to actual weight at the moment of evaluation, anthropometric measurements (weight, length, body composition, and fat mass) will be used to determine the health risk category for each participant. RESULTS/ANTICIPATED RESULTS: Expected results will be that there is an association between violence exposure and weight retention among post-partum women, thus influencing their weight status. The use of the questionnaires as screening tool for history of violence and whether recent or childhood exposure should be considered a health risk during pregnancy and post-partum predisposing women to adipose tissue related disorders. DISCUSSION/SIGNIFICANCE: Findings will reinforce the importance of integrated screening and proactive management of social determinants of health within clinical and social services that target this population. Also, contribute to the development of strategies tailored to break violence cycle as a public health measure.

Objectives/Goals: Early identification of heart failure with reduced ejection fraction (rEF) by emergency medical service (EMS) providers is challenging, particularly in rural settings. We developed a rEF decision aid that addresses barriers to adoption using demographics, measurements, and computerized findings from ubiquitous EMS 12-lead defibrillators. Methods/Study Population: We identified all patients at Tufts Medical Center between Jan 1, 2012 and Apr 16, 2024 who had a 12-lead ECG taken within 30 days of an echocardiogram. Using the echocardiogram left ventricular ejection fraction (LVEF), each ECG-echo pair was classified as reduced EF (rEF – LVEF < 40) or non-rEF (LVEF >= 40%). The rEF is the outcome in a step-wise logistic regression model (LRM) to predict rEF. Variables of interest in the model were selected based on literature review in clinical assessment for heart failure with reduced ejection fraction (HFrEF) and what can be provided by a 12-lead ECG. We also included left ventricular damage score (e.g., Selvester Score) due to previous myocardial infarction (MI). Prior MI is a known risk factor in HFrEF. We used R 4.5 to perform the analysis and logistic regression modeling. Results/Anticipated Results: 2,289 patients were identified with a 12-lead ECG taken within 30-days of an echocardiogram. Our final regression model included demographic and ECG features: age, sex, myocardial scarring score, computerized interpretation of conduction defects (bundle branch block, early repolarization, and intraventricular conduction defect), and acute myocardial infarction findings. The rEF prediction model had an area under the curve of 0.684 and good calibration along the identity line up to predicted probability of 0.3. Discussion/Significance of Impact: A LRM to predict rEF using an ECG is computationally efficient and address important barriers of adoption in the EMS setting. It does not require additional EMS training or equipment. LRM transparency facilitates communication between paramedics and medical control clinicians to make shared decisions regarding treatment and transport decisions.

ABSTRACT IMPACT: The proposed study has the potential to inform new paradigms of type 1 diabetes prevention and therapy with the overall goal of improving β cell health during autoimmunity. OBJECTIVES/GOALS: Type 1 diabetes (T1D) results from immune-mediated destruction of pancreatic βcells. Recent data suggest that activation of senescence and acquisition of a senescence associated secretory phenotype (SASP) by βcells may contribute to T1D pathogenesis. However, the molecular mechanisms responsible for this phenotype are not well understood. METHODS/STUDY POPULATION: We hypothesize that loss of endoplasmic reticulum (ER) Ca2+ induces βcell senescence, SASP as well as mitochondrial dysfunction which drive T1D development. The current study utilizes SERCA2 KO INS-1 βcells (S2KO) exhibiting loss of ER Ca2+ and a SERCA2 haploinsufficient mice on a non-obese diabetic background (NOD-S2+/-) to test the role of ER Ca2+ loss during T1D development. Senescence associated βgalactosidase staining (SA-βgal), expression of senescence markers (RT-qPCR), mitochondrial function (Seahorse, TMRM) and mitochondrial copy number (qPCR) were all measured in S2KO versus WT βcells and are currently being measured in the NOD-S2+/- mouse model at 6, 8, 12, 14, and 16wks of age. RESULTS/ANTICIPATED RESULTS: RT-qPCR assays detecting senescence markers cdkn1a and cdkn2a and mitochondrial specific genes cox1 and nd1 were developed and validated in both INS-1 βcells and mouse islets. Mitochondrial function assay (Seahorse) was optimized for use in INS-1 βcells and is currently under development for use in intact mouse islets. S2KO βcells displayed increased SA- βgal staining as well as increased mitochondrial coupling efficiency (p=0.0146) and baseline mitochondrial copy number (p=0.0053) compared to WT βcells, suggesting a senescence phenotype and altered mitochondrial function. NOD-S2+/- mice exhibited increased expression of the senescence marker cdkn2a in the islet at 12wks (p=0.0117) compared to control mice, whereas cdkn1a remained unchanged across all timepoints tested. DISCUSSION/SIGNIFICANCE OF FINDINGS: Our results suggest that loss of SERCA2 and reduced ER Ca2+ alter βcell mitochondrial function and are associated with features of senescence. Future studies will test whether SERCA2 activation and/or senolytic/senomorphic drugs are able to prevent or delay diabetes onset in NOD-S2+/- mice.

OBJECTIVES/GOALS: Changes associated with placental vasculature contribute to the progression of gestational hypertensive disease preeclampsia. Caudal-type homeobox-2 (CDX2) regulates trophoblast stem cell differentiation. In this study, we investigate the role of placental CDX2 cells in healthy pregnancy and in conditions of preeclampsia. METHODS/STUDY POPULATION: To understand the role of CDX2 cells, here we collected human placenta samples from the prospectively enrolled cohort and also the de-identified cohort (n=84). We studied CDX2 distribution, and function using a lentivirus-based approach. We studied the CDX2 expression and functional differences using transcriptomics and examined the function in invasion and vasculogenesis in the presence and absence of the new target genes we have discovered in our study. RESULTS/ANTICIPATED RESULTS: Analysis of healthy human placenta samples showed that CDX2-expressing cells were present in fetal chorionic regions and are associated with HLA-G and cytokeratin-7 confirming their trophoblast identity. CDX2 cells demonstrated the potential to form a capillary network akin to endothelial cells. Placental samples from healthy (n=6) and preeclampsia (n=8) patients revealed higher levels of CDX2 expression in preeclampsia. Within preeclampsia CDX2 cells, Natriuretic peptide receptor 1 (NPR1), RET oncogene, and Homeobox D10 (HOXD10) were significantly differentially regulated, including a unique long-non-coding anti-sense RNA (KANSL1-AS1) that affected the function of CDX2 and trophoblast cells in invasion and normal vasculogenesis. DISCUSSION/SIGNIFICANCE: In sum, based on these observations, the present study postulates that CDX2 cells present in a healthy human placenta may serve as a prospective cellular reservoir for angiogenesis. Conversely, altered gene programs within CDX2 cells cause aberrant vascular function that could contribute to the progression of preeclampsia.

The Clinical and Translational Science Award (CTSA) Consortium and the National Center for Advancing Translational Science (NCATS) undertook a Common Metrics Initiative to improve research processes across the national CTSA Consortium. This was implemented by Tufts Clinical and Translational Science Institute at the 64 CTSA academic medical centers. Three metrics were collaboratively developed by NCATS staff, CTSA Consortium teams, and outside consultants for Institutional Review Board Review Duration, Careers in Clinical and Translational Research, and Pilot Award Publications and Subsequent Funding. The implementation program included training on the metric operational guidelines, data collection, data reporting system, and performance improvement framework. The implementation team provided small-group coaching and technical assistance. Collaborative learning sessions, driver diagrams, and change packages were used to disseminate best and promising practices. After 14 weeks, 84% of hubs had produced a value for one metric and about half had produced an initial improvement plan. Overall, hubs reported that the implementation activities facilitated their Common Metrics performance improvement process. Experiences implementing the first three metrics can inform future directions of the Common Metrics Initiative and other research groups implementing standardized metrics and performance improvement processes, potentially including other National Institutes of Health institutes and centers.

The Harvard Catalyst KL2/CMeRIT program is a 2-year mentored institutional career award that includes KL2 grants funded by National Institutes of Health (NIH) and CMeRIT grants funded by Harvard Catalyst nonfederal funds. The purpose of this study was to compare outcomes for early-stage investigators funded by the KL2/CMeRIT program to a group of applicants who were not chosen for support to assess the potential impact of the program on early career outcomes. Career data, including academic promotions, subsequent grant funding, and publication rates, from both successful and unsuccessful 2008–2018 KL2/CMeRIT applicants were compiled throughout the year 2020. Data were obtained directly through outreach to both groups and through assessment of online resources. The cohort comprised 487 individuals, 109 awardees, and 378 nonawardees. Awardees were more likely to be subsequently involved in clinical and translational research than nonawardees (92% vs 75%, p < 0.001). A higher proportion of awardees also had achieved academic promotion (81% vs 69%, p = 0.016) and subsequent NIH funding (72% vs 58%, p = 0.047), while there was no difference in publication rates (p = 0.555). Participants in the Harvard Catalyst KL2/CMeRIT program demonstrate greater early career success than nonparticipants though the nonparticipants also fared relatively well.

Cardiovascular disease (CVD) is largely preventable, and the leading cause of death for men and women. Though women have increased life expectancy compared to men, there are marked sex disparities in prevalence and risk of CVD-associated mortality and dementia. Yet, the basis for these and female-male differences is not completely understood. It is increasingly recognized that heart and brain health represent a lifetime of exposures to shared risk factors (including obesity, hyperlipidemia, diabetes, and hypertension) that compromise cerebrovascular health. We describe the process and resources for establishing a new research Center for Women’s Cardiovascular and Brain Health at the University of California, Davis as a model for: (1) use of the cy pres principle for funding science to improve health; (2) transdisciplinary collaboration to leapfrog progress in a convergence science approach that acknowledges and addresses social determinants of health; and (3) training the next generation of diverse researchers. This may serve as a blueprint for future Centers in academic health institutions, as the cy pres mechanism for funding research is a unique mechanism to leverage residual legal settlement funds to catalyze the pace of scientific discovery, maximize innovation, and promote health equity in addressing society’s most vexing health problems.

OBJECTIVES/GOALS: Since 2013, managers of community engagement (CE) programs across the Clinical and Translational Science Award (CTSA) consortium funded by the National Center for Advancing Translational Sciences (NCATS) have convened monthly to build connections, share knowledge, and enable collaboration. METHODS/STUDY POPULATION: Notable for focus on staff leadership, the CE Brokers group has been central to the ongoing success of CTSA community engagement partnerships and approaches to research. In early 2022, a survey of the 139-member group asked about their roles and responsibilities, the ways the CE Brokers network has contributed to their hubs adoption and development of best practices and innovations, resources and lessons learned, and the creation of opportunities for members to collaboratively conduct and disseminate original research, and research on the science of community engagement. The survey also asked CE Brokers if they or their community partners are part of an underrepresented community. RESULTS/ANTICIPATED RESULTS: These demographic data will be shared, along with analyses of data on growth of the group over time, evolving themes, and a SWOT analysis completed in 2021. DISCUSSION/SIGNIFICANCE: This will provide a platform to explore new avenues for the CE Brokers and their impact within the NCATS CTSA consortium, in line with the evolving direction of the clinical and translational research enterprise.

OBJECTIVES/GOALS: The prevalence of patients with end-stage kidney disease (ESKD) in PR has increased in the last decade along with an aging population, while waitlisted patients have decreased. Our objective is to compare clinical and sociodemographic characteristics of patients with ESKD on dialysis who are waitlisted from those who are not waitlisted. METHODS/STUDY POPULATION: Retrospective study of all patients with ESKD who received dialysis in PR from 2013-2019, based on the United States Renal Data System data. Variables: (1)waitlisting status (yes or no; waitlisting date); (2)sociodemographics (age at dialysis initiation, sex, zip-code area, health insurance type, and employment status); and (3)clinical characteristics (dialysis initiation date, primary diagnosis of renal disease, comorbidities including obesity, diabetes, peripherovascular/cardiovascular disease, cancer, etc.). Statistics: (1)descriptive statistics (continuous - central tendency [mean, median] and dispersion [standard deviation, interquartile range]; and categorical [frequencies and percentages]); (2)Chi-square test, Students t-test, and Mann Whitney U test to evaluate differences. RESULTS/ANTICIPATED RESULTS: We expect patients on dialysis not waitlisted will be older and have more comorbidities than those who are on dialysis and waitlisted. DISCUSSION/SIGNIFICANCE: Kidney transplant is the choice of therapy for ESKD and its benefits are better quality of life, improved survival, and best long term-cost effectiveness. If our hypothesis is true, findings will highlight the importance of characterizing which patients with ESKD on dialysis are kidney transplant candidates when considering barriers to waitlisting.