OBJECTIVES/GOALS: In 2022, Chicago created the COVID-19 Response Corps, a cohort of community health workers (CHWs), trained to conduct contact tracing and vaccine outreach. Through an Earn and Learn program, corps members studied community-engaged participatory research, and co-led a rapid assessment with researchers to assess vaccine hesitancy in communities. METHODS/STUDY POPULATION: The Chicago COVID-19 Community Response corps worked to mitigate COVID-19 transmission in disadvantaged neighborhoods by activating CHWs, a diverse public health workforce from communities most affected by health and economic inequities. The Earn and Learn Program allotted 600 corps members up to 7.5 hrs/week of paid capacity building opportunities to learn new skills, pursue training programs, or college courses. Embodying a praxis of participatory action research and intergenerational organizing, corps members co-designed research questions and survey instruments, pilot tested the tools, trained other corps members on how to recruit and collect data, and contributed to the analysis and interpretation of the results. They generated evidenced-informed solutions to address future real-world problems. RESULTS/ANTICIPATED RESULTS: Corps members brought insight, cultural literacy, and lived experience that was invaluable in reaching the priority population of unvaccinated Chicagoans. They enhanced all aspects of the rapid assessment while conducting their work safely and comfortably in neighborhoods that outsiders consider challenging. Community member responses as to why they had not yet received a COVID-19 vaccine included being unable to risk putting what they saw as a rushed or improperly tested product into their bodies, to not being able to risk becoming ill even temporarily due to the potential for lost wages, as well as having other priorities in their lives which took precedence over concern about COVID-19, such as paying bills and feeding their families. DISCUSSION/SIGNIFICANCE: Research and evaluation benefits from the inclusion of CHWs. They are agile agents of change with the potential to replenish and repair trust in a fractured public health system. Engaging CHWs in evaluation work can strengthen community-academic partnerships and enhance the understanding of challenges and solutions to improving community health.

OBJECTIVES/GOALS: This project’s objective is to empower verbally-communicating autistic adults to express their mental health needs to mental health professionals, regardless of their training or experience in autism. By enhancing empowerment in this area, we aim to enhance their self-awareness and confidence in navigating and accessing mental health support. METHODS/STUDY POPULATION: Following the Toronto Translational Framework (TTF), our approach involves co-designing and testing an intervention directly with the autistic population through three phases. Phase I will review published literature on autism, mental health, and patient empowerment, validate our identified need through informal meetings with stakeholders, and assemble an autistic advisory committee (AAC) of 5-8 members who are able to provide informed conset without assistant, are fluent in English, and 18 years of age or older. Phase II will involve participatory design sessions with our AAC to develop a low-fidelity prototype to address the identified need. Phase III will evaluate our prototype’s effectiveness through a separate series of focus groups, which will consist of members from our target population. RESULTS/ANTICIPATED RESULTS: We are anticipating that by the end of our research, we have successfully co-designed an intervention that effectievly empowers autistic adults in their mental health journey through increasing their self-awareness and confidence in navigating and receiving mental health support. At a larger scale, results may include the empowerment of autistic adults to seek and receive mental health care from mental health professionals, regardless of professionals’ prior autism expertise. DISCUSSION/SIGNIFICANCE: By enhancing self-awareness of their mental healthcare needs and boosting self-reported confidence in communicating with mental health professionals, we aim to take the first step in creating timely, patient-centered solutions, and bridging gaps in the evolving neuro-affirmative healthcare system.

OBJECTIVES/GOALS: To describe the strategies our newly created Patient Partners Program has planned for engaging diverse patients in the co-creation of our planned Patient Partner Academy. We will elicit feedback from other CTSAs about their strategies for promoting individual patient partnerships in research. METHODS/STUDY POPULATION: Our program to promote authentic patient-researcher partnerships to advance clinical and translational research is grounded in participatory approaches to maximize meaningful engagement. The process of creating our Patient Partners Academy is co-led by a patient partner and national leader in re-envisioning the role of patients in research, and a University of Michigan faculty member who advocates for patient partnerships in research. Listening sessions and community engagement studios will involve the developers of patient partner training programs, patient partners who have received research capacity training (as well as researchers and patient partners interested in collaborative research. Insights from these sessions will inform the development of learning models and curriculum content. RESULTS/ANTICIPATED RESULTS: Through individual listening sessions and community engagement studios we will collect data on the barriers and facilitators to patient partner engagement in research and the experiences and preferred learning models in patient partner training programs. Both the listening sessions and community engagement studios will be recorded, transcribed, and analyzed for common themes. We aim to answer three questions: What do patient partners need to be meaningfully engaged as equal partners across the research continuum? How can we best engage people who experience serious illness or chronic conditions and may be underserved by healthcare systems? What do researchers, faculty, and clinicians need to create trusting, collaborative relationships with patient partners? DISCUSSION/SIGNIFICANCE: Integrating patient partners into study teams accelerates innovation and translational science, increases the relevance of research findings, improves health outcomes and patient empowerment, and elevates the value of the patient perspective allowing researchers to gain a new point of view from an individual with lived experience.

OBJECTIVES/GOALS: The purpose of this work is to assess antibiotic prescribing for inpatients with community-acquired bacterial pneumonia (CABP) due to methicillin-resistant Staphylococcus aureus (MRSA) in the All of Us database. The goal of this research is to determine if different subgroups are more or less likely to receive anti-MRSA antibiotics. METHODS/STUDY POPULATION: This is a retrospective cohort study of inpatients with CABP due to MRSA from 2/1/2011 to 7/1/2022 in the All of Us database. Cases will be excluded for other treatment settings, other pathogens, and other types of pneumonia. Patients will be stratified by age, sex, race, and ethnicity. The proportion of patients who received anti-MRSA antibiotic therapy will be compared within groups with the chi-square statistic. Significant associations between patient characteristics and anti-MRSA prescribing (p < 0.05) will be assessed using multivariate logistic regression, with subgroup as the independent variable, anti-MRSA prescribing as the dependent variable, and divergent baseline characteristics as potential confounders. Odds ratios (OR) and 95% confidence intervals (95% CI) will be calculated. RESULTS/ANTICIPATED RESULTS: Previous research by our group has demonstrated differences in guideline-concordant, empiric antibiotic prescribing, for inpatients with CABP in the All of Us database; however, guideline-concordant empiric antibiotics for CABP do not routinely cover for MRSA. Anti-MRSA antibiotics are recommended if the patient has known MRSA or risk factors for MRSA. Investigations of disparity in anti-MRSA prescribing have been limited, especially since the abandonment of the healthcare-associated pneumonia (HCAP) categorization. Since the All of Us database contains information on CABP pathogens, we can study sub-types of CABP; therefore, we now hypothesize that the proportion of inpatients who received anti-MRSA antibiotics for CABP, due to MRSA, in the All of Us database, will differ by age, race, sex, and ethnicity. DISCUSSION/SIGNIFICANCE: This is one of the first studies to evaluate antibiotic prescribing for CABP due to MRSA in the All of Usdatabase. Identifying and understanding differences in care, such as possible discrepancies in anti-MRSA prescribing by age, sex, race, or ethnicity, is essential to develop targeted interventions to address disparities in health outcomes.

OBJECTIVES/GOALS: We will describe the community-driven development and impact of the new Community Research Capacity-Building grants from the Alliance for Research in Chicagoland Communities, Northwestern University. Communities expressed that to enter equitably into partnerships with academics they need support to build their own community research capacity. METHODS/STUDY POPULATION: ARCC Seed Grants, since 2008, included Partnership Development and Research Pilots, which are both jointly submitted by a community-academic partnership. The new Community Grants are submitted only by community partners and don’t require an academic partner. These grants, $3,000 over 6 months, support the development or strengthening of organizational or community-level research capacity. This may include assessing community capacity to lead and/or collaborate on research; building research capacity of community organizations (staff, leadership, residents), developing community infrastructure (e.g. research principles; staff research responsibilities; process for assessing/ tracking researcher inquiries; template memorandum of understanding) or community research priorities, etc. RESULTS/ANTICIPATED RESULTS: Eight ARCC Community Research Capacity-Building Seed Grants have been awarded so far as a part of three cycles of applications over 2022-23 (2 in 2022, 6 in 2023). During this time period, data has been collected during the application process, in final reports, and in informal group and individual discussions. Information about the profile of grantees (community representation, health focus, etc.), the initial impact of grants, and feedback from grantees about the positive and challenging aspects of the grants will be shared. Grantees have informally shared that the awards have helped to address concerns that many low-income communities of color have their voices are not adequately included in research and other decision-making. The poster will be co-presented by a community grant recipient. DISCUSSION/SIGNIFICANCE: To ensure that research partnerships are community-driven & equitable, it is necessary to invest in community research capacity-building. More evaluation is needed to understand the grants impact, as well as other approaches to community research capacity and leadership development. Poster will be co-presented by a community grant recipient.

OBJECTIVES/GOALS: Our goal is to determine whether microplastic fibers (MPFs) provide signals for dendritic cell-induced Th2 polarization via epithelial-cell-derived thymic stromal lymphopoietin (TSLP). We seek to highlight a potential mechanism for MPF-induced airway toxicity associated with asthma exacerbation. METHODS/STUDY POPULATION: Primary human bronchial epithelial cells (NHBEs) were grown and differentiated at an air-liquid interface. Dyed and undyed polyester MPFs (14x45 µm) generated using a cryomicrotome were delivered to NHBEs through a custom designed mesh-hopper system. After the exposure period (6, 12, 24 hrs), cell viability was assessed using alamarBlue, and RT-qPCR was performed to determine mRNA expression of asthma associated genes (i.e., TSLP, IL-13, IL-33, etc.,) in NHBEs. Bulk mRNA-sequencing followed by bioinformatics will be performed to observe other plausible pathways tweaked by lung cell exposure to MPFs. RESULTS/ANTICIPATED RESULTS: Through gravimetric analysis, it was determined that the mesh-hopper system can achieve delivery efficiencies of at least 85% for as low as 500 fibers. Following exposure, results show polyester MPFs (500 - 1,000 fibers) exposed to NHBEs at multiple time points (6, 12, 24 hrs) did not result in a statistically significant decrease in cell viability. Treatment with 500 undyed MPFs resulted in a slight increase in TSLP expression at 6 hrs that decreased over time, whereas all other treatment groups resulted in TSLP downregulation. Similarly, 500 undyed MPFs resulted in an increase in IL-13 expression at both 6 and 12 hrs with all other treatment groups leading to IL-13 downregulation. We anticipate the RNA-seq results will show pro-inflammatory pathways are highly targeted following NHBE exposure to MPFs. DISCUSSION/SIGNIFICANCE: This study is one of the first to mechanistically assess the impact of MPFs on lung cells while simultaneously addressing the need for a reliable system that delivers MPFs to ALI cultures to better mimic inhalation and avoid inadequate resuspension of particles in liquid medium.

OBJECTIVES/GOALS: Measuring the area of skin involvement in chronic graft-versus-host disease (cGVHD) relies on costly, time-consuming manual assessment, with high disagreement among experts (>20%). Our published AI method, trained on labeled 3D photos, showed promise for delineating affected areas. We aim to improve its performance using unlabeled 2D photos. METHODS/STUDY POPULATION: Our published AI model (baseline) was trained on 360 labeled photos of 36 cGVHD patients,from a 3D camera with calibrated distance and lighting.Our gold standard labels were contours around affected skin, marked by a trained expert. A second unlabeledcohort of 974 standard 2D photos of 8 cGVHD patients was used to improve the baseline model. First the baseline model predicted affected areas on the unlabeled photos. Photos with good predictions were added to the training set with their AI-predicted labels. The model was then re-trained with the expanded labeled set. Models were successively trained with more AI labels until performance stopped improving. AI performance was assessed on a test set of 20 photos from 20 patients unseen during training, labeled by 4 experts to improve accuracy. RESULTS/ANTICIPATED RESULTS: Model performance was calculated by comparing against the gold standard labels on the test set. To quantify the spatial overlap of labeled areas the Dice coefficient was used (0 is no overlap, 1 is complete agreement), where higher values are better. To estimate clinical error we used surface area error (Error), where lower values are better. On the test set, the baseline model had a median Dice of 0.57 [interquartile range: 0.39 – 0.82] and Error of 57.6% [20.2 – 103.3%]. Re-training with additional AI-predicted labels from 8 new patients, the model yielded a median Dice of 0.60 [0.35 – 0.80] and Error of 50% [12.5 – 103.8%]. This approach is being expanded to a further 300 unlabeled patients, where we anticipate significant improvements to AI performance and consistency. DISCUSSION/SIGNIFICANCE: Evaluating AI models in standard photos could provide a consistent method of assessing and tracking cutaneous cGVHD and relieve the burden of costly expert assessment. A reliable automated AI tool would provide a meaningful improvement to the current standard of manual assessment and could be easily applied to large patient cohorts.

OBJECTIVES/GOALS: This pilot study investigated psilocybin-induced changes in neural reactivity to alcohol and emotional cues in patients with alcohol use disorder (AUD). METHODS/STUDY POPULATION: Participants were recruited from a phase II, randomized, double-blind, placebo-controlled clinical trial investigating psilocybin-assisted therapy (PAT) for the treatment of AUD (NCT02061293). Eleven adult patients completed task-based blood oxygen dependent functional magnetic resonance imaging (fMRI) approximately 3 days before and 2 days after receiving 25 mg of psilocybin (n = 5) or 50 mg of diphenhydramine (n = 6). Visual alcohol and emotionally valanced (positive, negative, or neutral) stimuli were presented in block design. RESULTS/ANTICIPATED RESULTS: Across both alcohol and emotional cues, psilocybin increased activity in the medial and lateral prefrontal cortex (PFC) and left caudate, and decreased activity in the insular, motor, temporal, parietal, and occipital cortices, and cerebellum. Unique to negative cues, psilocybin increased supramarginal gyrus activity; unique to positive cues, psilocybin increased right hippocampus activity and decreased left hippocampus activity. DISCUSSION/SIGNIFICANCE: Greater PFC and caudate engagement and concomitant insula, motor, and cerebellar disengagement suggests enhanced goal-directed action, improved emotional regulation, and diminished craving. The robust changes in brain activity observed in this pilot study warrant larger neuroimaging studies to elucidate neural mechanisms of PAT.

OBJECTIVES/GOALS: The 'field effect' is a concept in pathology that pre-malignant tissue changes forecast health. Spatial transcriptomics could detect these changes earlier than histopathology, suggesting new early cancer screening methods. Knowing how normal tissue damage relates to cancer’s origin and progression may improve long-term outcomes. METHODS/STUDY POPULATION: We trained DEGAS, our machine learning framework, with prostate cancer data, combining both general cancer patterns and in-depth genetic information from individual tumors. The Tumor Cancer Genome Atlas (TCGA) shows how gene patterns in tumors relate to patient outcomes, emphasizing the differences between tumors from different patients (intertumor). On the other hand, spatial transcriptomics (ST) shows the genetic variety within a single tumor (intratumor) but has limited samples, making it hard to know which genetic differences are important for treatment. DEGAS bridges these areas by finding tissue sections that resemble those in TCGA profiles and are key indicators of patient survival. DEGAS serves as a valuable tool for generating clinically-important hypotheses. RESULTS/ANTICIPATED RESULTS: DEGAS identified benign-appearing glands in a normal prostate as being highly associated with poor progression-free survival. These glands have transcriptional signatures similar to high-grade prostate cancer. We confirmed this finding in a separate prostate cancer ST dataset. By integrating single cell (SC) data we demonstrated that cells annotated as cancerous in the SC data map to regions of benign glands in the ST dataset. We pinpoint several genes, chiefly Microseminoprotein-β (MSMB, PSP94), where reduced expression is highly correlated with poor progression-free survival. Cell type specific differential expression analysis further revealed that loss of MSMB expression associated with poor outcomes occurs specifically in luminal epithelia, the putative progenitor of prostate cancer. DISCUSSION/SIGNIFICANCE: DEGAS reveals that normal-appearing tissue can be highly-associated with tumor progression and underscores the importance of the 'field effect' in cancer research. Traditional analysis may miss such nuance, hiding key transitional cell states. Validating gene markers could boost early cancer detection and understanding of metastasis.

OBJECTIVES/GOALS: Many providers share patients resulting in networks where clinical information is exchanged, and which can impact the quality and efficiency of care. Here we analyzed the network properties of a primary care service area (PCSA) in Harris County TX, motivating our ongoing analysis of how they are associated with disparities in cancer screening. METHODS/STUDY POPULATION: Data.All providers (n=731, Medicare 2018) from the PCSA with the most providers in Harris County TX, with gender, specialty, and the number of shared patients. Method. Modeled the data as a network consisting of provider nodes, connected in pairs by edges if they shared >11 patients (an empirically-determined threshold). Analyzed the network structure using (1) modularity maximization and its significance to identify densely-connected communities; (2) degree centralization to measure whether a few providers shared many patients, and betweenness centralization to measure whether a few providers connected densely-connected communities; and (3) chi-squared to measure if pairs of connected providers tended to be of the same gender compared to disconnected provider pairs. RESULTS/ANTICIPATED RESULTS: The results (Fig. 1, http://www.skbhavnani.com/DIVA/Images/Fig-1-SNA-Network.jpg [http://www.skbhavnani.com/DIVA/Images/Fig-1-SNA-Network.jpg]) revealed a fragmented network with 120 small components (connected subnetworks, not part of any larger connected subnetwork), and 1 large component. The large component (n=244) had strong and significant modularity (Q=0.73, z=53.13, P<.001) with communities of providers that shared more patients than expected by chance; low degree centralization (dc=0.11) suggesting that no provider dominated patient sharing, in addition to high and significant betweenness centralization (bc=0.5, P<.01) suggesting that a few providers were responsible for connecting the densely-connected communities; and a significant gender bias (X2=10.05, df=1, P< .01) among those that shared patients, versus those that did not. DISCUSSION/SIGNIFICANCE: The analysis revealed a specific type of vulnerability (betweenness) for network fragmentation, and a gender bias in how patients were shared. These results motivated our ongoing analysis on how the network properties are associated with disparity in cancer screening within PCSAs across Texas.

OBJECTIVES/GOALS: Molar hypomineralization (MH) is a highly prevalent dental disease that leads to rapid enamel decay even with preventative measures. While the harm is apparent, the etiology of the condition is not. Further, MH is difficult to study due to limited intact extracted teeth. Therefore, we need a method to study MH non-destructively and intraorally. METHODS/STUDY POPULATION: Recent work has shown excess proteins not commonly found in enamel are present in teeth with MH. This is theorized to be due to disruption and infiltration in the cells that form enamel leading to leftover protein and under mineralized enamel. We hypothesizethese proteins have specific spectroscopic signatures that can be detected using light. We further hypothesize that modern fiber optic probes can provide a method for non-destructive, pain-free, and rapid intraoral examination of MH. Initially, Micro Raman spectroscopy was used to detect specific vibrational bands associated with organics in teeth with MH followed by the collection of spectra of teeth with MH and heathy enamel using a spectrophotometer. These spectra were examined for any obvious differences. RESULTS/ANTICIPATED RESULTS: Currently 12 teeth were collected, and micro-computed tomography reconstructions confirmed location in 3D of MH lesions. Micro Raman of a MH-affected tooth revealed clear organic associated Amide I and III vibrational bands when compared to a synthetic hydroxyapatite (mineral in enamel) powder standard. We determined the wavelength of light that can be used to detect spectral differences between healthy enamel and teeth with MH. The next steps include optimization of the protocol of the intraoral spectrometer with the determined wavelength for implementation in clinic to allow for collection of spectra without the need for tooth extraction. DISCUSSION/SIGNIFICANCE: We hope that this work will lead to advancements in our understanding of the mechanism of MH as well as act as a proof of concept for a MH diagnostic tool. In the long term, the goal is to ideally lead to improvements in dental health care, decrease dental costs, and improve overall quality of life for the children with this condition.

OBJECTIVES/GOALS: The goal of this study is to reveal strong candidate genes for inherited retinal diseases (IRDs) in humans to better understand the mechanisms behind IRD development and reveal potential therapeutic targets. We hope these findings will help improve our understanding of IRDs and, subsequently, diagnostic accuracy and prognosis for IRD patients. METHODS/STUDY POPULATION: The goal of the International Mouse Phenotyping Consortium is to identify the function of all protein-coding genes in the mouse genome via generation and phenotypic characterization of single gene knockout (KO) mice. Using this database, we identified all KO strains associated with abnormal retinal phenotypes, removed all RNA coding genes and pseudogenes, converted to human orthologues, and conducted a literature search for existing research regarding candidate IRD genes and retinal function/abnormalities. A similar process was used for RetNet genes. Subsequently, we performed bioinformatics analysis, including functional annotation (e.g. panther-db), pathway analysis (e.g. KEGG), and string-db to visualize known and predicted protein-protein interactions between the two data sets. RESULTS/ANTICIPATED RESULTS: Analysis of the IMPC database revealed, out of 8481 phenotyped genes, 572 unique protein coding genes were associated with 14 categories of retinal abnormalities such as abnormal retinal vasculature and abnormal retinal thickness, 377 of which have never been associated with retinal pathology in humans or mice. Pathway analysis of the IMPC database highlighted a general metabolism pathway as well as PI3K-Akt and MAPK pathways, not found in RetNet pathway results. Unique clusters from functional annotation clustering of the IMPC include DNA methylation and protein ubiquination. Visualization of protein-protein interactions in string-db between the IMPC (mouse) and RetNet (human) revealed 4 clusters of interest with gold standard RetNet IRD proteins interacting with candidate IMPC IRD proteins. DISCUSSION/SIGNIFICANCE: IMPC analysis revealed 572 candidate IRD genes, 377 of which are novel with no existing independent research related to the retina outside of the IMPC. Bioinformatic analysis reveals 4 strong clusters of interest through string-db where a gold standard RetNet gene interacts with candidate IRD genes as well as many functional pathways of interest.

OBJECTIVES/GOALS: There are178 million bone fractures globally each year, and 46% of fractures that have accompanying vascular damage (ischemia) will not heal without surgical intervention. Using single cell RNAseq we identified Cdk8 as a gene upregulated under ischemic fracture. Our work seeks to inhibit Cdk8 to assess its potential as a therapeutic target. METHODS/STUDY POPULATION: Most bone injuries heal through a cartilage intermediate that requires mesenchymal progenitor cells (hMSCs) to become cartilage forming chondrocytes. hMSCs underwent pelleted 3D chondrogenic differentiation in the presence of Cdk8 inhibitor, Senexin B. Chondrogenic gene expression was assessed via gene analysis of Aggrecan, Collagen II, and Collagen X. Content of sulfated glycosaminoglycans (sGAGs) was quantified through DMMB analysis. With IACUC approval, C57Bl/6 WT mice underwent femoral artery isolation and resection to create an ischemic environment prior to a transverse tibia fracture. Mice underwent intraperitoneal injections of Senexin B from day -1 to 8 and were harvested at 10 days post fracture. Control mice received vehicle injection. Calluses were analyzed through µCT and histomorphometry. RESULTS/ANTICIPATED RESULTS: At 14 days, Senexin B increased chondrogenic gene expression and improved sGAG content in hMSCs. This persisted to day 21, suggesting that Cdk8 inhibition via Senexin B promotes chondrogenesis and matrix deposition. Histomorphometric analysis reveals thatin vivotreatment with Senexin B increases cartilage content and reduces mineralization of the fracture callus compared to the Control. µCT analysis corroborates this, with distinctly less peri-cortical mineral present in Senexin B-treated calluses, and a decrease in total bone volume. These results suggest an altered progression of cartilage formation and endochondral ossification with Cdk8 inhibition. DISCUSSION/SIGNIFICANCE: Our findings reveal that increased Cdk8 is associated with poor healing in ischemic fractures. Inhibition of Cdk8 appears to increase chondrogenesis of hMSCsin vitroand in the murine fracture callusin vivo. Targeting Cdk8 offers potential to improve callus formation in impaired healing scenarios.

OBJECTIVES/GOALS: To investigate digital behavior patterns before cerebrovascular disease (CeVD), we compared accelerometer-measured physical activity (PA) phenotypes of future CeVD patients versus controls in UK Biobank. METHODS/STUDY POPULATION: Accelerometer data from 76,525 eligible participants monitored for 7-days (Jan. 2013-Dec. 2015) was classified into four categories: sedentary, light PA (LPA), moderate-to-vigorous PA (MVPA), and sleep. Covariables and diagnoses were defined using baseline data and patient records. Daily PA patterns associated with incident CeVD were compared to controls using negative binomial regression models. RESULTS/ANTICIPATED RESULTS: Adult participants with future CeVD (n = 2,163) spent 4.4% less time in MVPA (Incident Rate-Ratio (IRR) 0.956; 95% CI = 0.923-0.992; p = 0.016) compared to controls. During 0:00-5:59h (midnight to 5:59AM), future CeVD patients were less likely to sleep (IRR = 0.985; 95% CI = 0.977-0.992; p <0.001) but more likely to be sedentary (IRR = 1.189; 95% CI = 1.098-1.290; p <0.001) or in LPA (IRR = 1.108; 95% CI = 1.015-1.211; p <0.001). In subgroup analyses, decreased MVPA was observed in current/former smokers (IRR = 0.887; 95% CI = 0.819-0.963), males (IRR = 0.931; 95% CI = 0.870-0.997), and the unemployed/retired (IRR = 0.923; 95% CI = 0.856-0.998), an effect more pronounced in depressed patients (p for interaction = 0.044) and prolonged (> 2 hr/day) screen users (p for interaction = 0.018). DISCUSSION/SIGNIFICANCE: The digital phenotype of PA prior to CeVD is characterized by less sleep during 0:00-5:59h and less daily MVPA, demonstrating the utility of accelerometer data in identifying candidates for preventative intervention.

OBJECTIVES/GOALS: Our goal was to distinguish SARS-CoV-2 CD8+ T cell epitopes of spike, membrane, and nucleocapsid products in 27 of the most frequent HLA-Aand -B alleles.We hypothesize that differences mediated by variation in SARS-CoV-2 and host HLA genetics affect the differential clinical severity and presentation of acute infection and PASC. METHODS/STUDY POPULATION: Genomic sequences of SARS-CoV-2 variants were blasted against the original Wuhan strain using Ensembl’s SARS-CoV-2 browser. We examined 16 COVID variants: 2 Alpha (B.1 and B.1.1.7), 5 Delta (AY.100, AY.25, AY.3, AY.3.1, and AY.44), and 9 Omicron (BA.1, BA.1.1, BA.2, BA.4, BA.5, BQ.1, BQ.1.1, XBB.1, and XBB.1.5), sequenced from the Louisiana patient population. cDNA sequences were translated using the Expasy tool. To predict MHC-I epitope binding, we used the Immune Epitope Database and Analysis Resource, via TepiTool utilizing the IEDB recommended default prediction and the 27 most frequent HLA-A and -B alleles. In silico peptide docking was conducted on FoldX, utilizing HLA-B*15:01 structures (n= 7) from the Protein Data Bank. RESULTS/ANTICIPATED RESULTS: CD8+ epitope conservation was estimated at 87.6-96.5% in S, 92.5-99.6% in M, and 94.6-99% for N. As the virus mutated, an increasing proportion of S epitopes experienced reduced predicted binding affinity: 70% of Omicron BQ.1- XBB.1.5 S epitopes experienced decreased predicted binding, as compared to ~ 3% and ~15% in Delta AY.100-AY.44 and Omicron BA.1-BA.5 respectively. Additionally, we identified several novel candidate haplotypes that may be susceptible to severe disease, notably HLA-A*32:01, -A*26:01, -B*58:01, and -B*53:01, and relatively protected from disease, such as -A*01:01, -A*02:01,-A*31:01, -B*15:01, -B*40:01, -B*44:03, and -B*57:01. In silico analysis of COVID peptides and HLA-B*15:01, a common allotype in the United States, largely matched predicted binding patterns. DISCUSSION/SIGNIFICANCE: To elicit long term COVID-19 immunity and prevent PASC, it is important to understand the relationship between T-cells, viral variants, and HLA genetics. This project is one of the first to explore the interaction between CD8+ epitope diversity and viral genetics for the majority of the United States population.

OBJECTIVES/GOALS: To facilitate data exploration at an academic medical center, we piloted self-service data science tools to provide easy access to research data and provide analytical workspace. The objectives are: i) data delivery with data governance and cohort discovery under a managed self-service model and ii) data science and analytics tool for advanced users. METHODS/STUDY POPULATION: Using existing commercial frameworks, we implemented a few pilot self-service tools. The key characteristics of the tools were i) high degrees of functionality and flexibility for data access and data governance, ii) lower cost to build and maintain, and iii) long-term organizational strategic alignment with the academic medical center. We conducted a two-phase evaluation with the pilot self-service tool: functionality-based assessment, prioritizing tools for data science users, and usability-based assessment, evaluating selected tools through customized maturity models and surveys. The evaluation study targeted a focus group study with five diverse faculties and researchers in an academic medical center seeking improved access to research resources. RESULTS/ANTICIPATED RESULTS: In evaluation phase 1, we explored seven self-service tool frameworks suitable for our research data warehouse (RDW). In phase 2, we implemented the top two tools selected from phase 1, QlikView and Palantir Foundry. Although the tool built on Palantir has higher mean and individual scores for user feedback than Qlik's, there is no statistically significant difference. Both tools had steep initial learning curve. Palantir has better feedback from qualitative responses. Our study findings highlight prioritized functionalities (efficiency, flexibility, sustainability, security, and cost reduction) for data science tool users; however features and the tool itself requires long term organizational planning and investment. DISCUSSION/SIGNIFICANCE: Academic and research medical centers strongly focus on efficient pilot data access for researchers to aid hypothesis generation. Establishing a clinical research-focused self-service data tool addresses the well-established demand for research resources and offers a model for similar organizations.

OBJECTIVES/GOALS: Women are twice as susceptible to ailments like anxiety, PTSD, and Alzheimer’s disease compared to men. The locus coeruleus (LC), the primary source of noradrenaline for the brain is implicated in these disorders, however physiological sex differences have never been assessed in the LC. METHODS/STUDY POPULATION: To address this gap, In vivo electrophysiology under anesthesia was used to measure single unit activity of noradrenergic LC firing patterns in 4-month-old wild-type Fischer male and female rats. Recordings measured neuronal activity under basal conditions and in response to a footshock stimulation which elicits burst firing in LC neurons. Single unit activity is sorted via automatic valley seeking scan PCA, additional manual sorting is done via line and template method. Analysis is done extracting interspike interval (ISI) and firing rate of single units, additional analysis is done to quantify properties of bursting patterns (burst duration, spikes per burst, interburst interval, etc…). RESULTS/ANTICIPATED RESULTS: This data shows that during LC burst firing, females have longer interspike intervals compared to males, supporting the inhibitory effect of E2 on LC firing. Additionally, females have significantly different waveform patterns than males, indicating possible differences in intrinsic properties, but further supporting sexually distinct physiology of the LC . Because female rats have been estrous cycle tracked via vaginal lavage, stratification into estrus groups and further analysis may uncover differences within females. These data suggest that estrogen acts as a potent neuromodulator of noradrenergic LC neurons, providing valuable insights into the physiology of this brain region. DISCUSSION/SIGNIFICANCE: This study is the first exploration of LC physiological sex differences. This work offers insights into a critical brain region implicated in many diseases, and may pave the way for future therapeutic approaches, particularly for women, who are at a higher risk of neurological disease developing.

OBJECTIVES/GOALS: Thiswork is an evidential study that demonstrates the positive impactof integrating Community Health Workers (CHWs) and SocialDeterminants of Health on an important health outcome, notably in decreasing the 30-day unplanned hospital ED readmissions at Sinai Health Systems. METHODS/STUDY POPULATION: Using datafrom the Sinai Urban Health Institute (SUHI), we compare predictingthe readmissions of patients with and without data pertainingto Social Determinants of Health (SDoH). We thoroughly describe the data cleaning and data pre-processing, done in collaboration with experts in community health. We use a fundamental and ubiquitous classifier in Random Forest for its feature characterization capability in order to translate models results into insights and recommendations for the CHW program. RESULTS/ANTICIPATED RESULTS: We show that when patients are simply engaged byCHWs, regardless of the content of those conversations, we canincrease the predictive accuracy of our classifier by 5%. We usethis result to make recommendations for improving patient careand discuss limitations and future work. Importantly our workpoints directly to the human connection between patients andCHWs as an important feature in the readmission rate. DISCUSSION/SIGNIFICANCE: Our work shows that the predictive capabilities of the classifier increases with CHW logs and SDoH survey data, highlighting the benefit of collecting this information. This is the first step in early identification of such patients so that CHWs are focusing on and providing resources to patients who will most benefit from the program.

OBJECTIVES/GOALS: The Clinical Implementation stage in the translational pipeline is hampered by the tension between formal evidence and clinician perceptions. For instance, when guidelines are translated into electronic clinical decision support alerts, they are often ignored. Using advances in LLMs we present a framework to quantify these discrepancies. METHODS/STUDY POPULATION: We hypothesize that ignoring guideline-based alerts may be driven by discordances between clinical guidelines’ deterministic realities and clinician’ perception of clinical reality. Until now this has been very difficult to measure using quantitative methods. We argue that advances in Large Language Models (LLM) provide an avenue for exploring this quantitatively. Here we present the method and preliminary results comparing the responses of BioBERTT from a carefully designed set of questions when the LLM is fine-tuned using either formal guidelines or transcripts of clinicians discussing guidelines and clinical care in the parallel domain. The formal “distance” between the LLM responses is evaluated using quantitative metrics like the Hamming Distance. RESULTS/ANTICIPATED RESULTS: We present a description of the architecture used to prove or disprove our hypothesis. We will present results obtained when training the architecture with data that could be used to test the limits of our hypothesis, by fine-tuning BioBERT with diverse synthetic clinical views, either in agreement or disagreement with the formal guidelines. Results comparing sepsis guideline text with transcripts of interviews with Emergency Department clinicians discussing care practices for sepsis in the ED transcripts will also be considered. Our current emphasis is on securing a wider range of transcripts of clinicians interviewed from different clinical specialties and different clinical settings. While here we focus on clinical guidelines, the framework supports any intervention in the Clinical Implementation stage. DISCUSSION/SIGNIFICANCE: Leveraging recent advances in LLMs, we develop a framework that can quantitatively measure the differences between guidelines and clinician perception of best practices. We demonstrated the functionality of this approach using synthetic data and initiated the collection of clinician transcripts to test the framework in real clinical situations.

OBJECTIVES/GOALS: Fluid boluses are administered to hypotensive, critically ill children but may not reverse hypotension, leading to delay of vasoactive infusion, end-organ damage, and mortality. We hypothesize that a machine learning-based model will predict which children will have sustained response to fluid bolus. METHODS/STUDY POPULATION: We will conduct a single-center retrospective observational cohort study of hypotensive critically ill children who received intravenous isotonic fluid of at least 10 ml/kg within 72 hours of pediatric intensive care unit admission between 2013 and 2023. We will extract physiologic variables from stored bedside monitors data and clinical variables from the EHR. Fluid responsive (FR) will be defined as a MAP increase by 310%. We will construct elastic net, random forest, and a long short-term memory models to predict FR. We will compare complicated course (multiple organ dysfunction on day 7 or death by day 28) between: 1) FRs and non-FRs, 2) predicted FRs and non-FRs, 3), FRs and non-FRs stratified by race/ethnicity, and 4) FRs and non-FRs stratified by sex as a biologic variable. RESULTS/ANTICIPATED RESULTS: We anticipate approximately 800 critically ill children will receive 2,000 intravenous isotonic fluid boluses, with a 60% rate of FR. We anticipate being able to complete all three models. We hypothesize that the model with the best performance will be the long short-term memory model and the easiest to interpret will be the tree-based random forest model. We hypothesize non-FRs will have a higher complicated course than FRs and that predicted non-FRs will have a higher rate of complicated course than FRs. Based on previous adult studies, we hypothesize that there will be a higher rate of complicated course in patients of black race and/or Hispanic ethnicity when compared to non-Hispanic white patients. We also hypothesize that there will be no difference in complicated course when comparing sex as a biologic variable. DISCUSSION/SIGNIFICANCE: We have a critical need for easily-deployed, real-time prediction of fluid response to personalize and improve resuscitation for children in shock. We anticipate the clinical application of such a model will decrease time with hypotension for critically ill children, leading to decreased morbidity and mortality.