Objectives/Goals: The need for accessible medical information has never been greater. Existing research and clinical documents are often too complex for the public to understand. This study aimed to evaluate the use of AI algorithms to convert research and clinical materials into language that is more easily understood while maintaining accuracy and informativeness. Methods/Study Population: We abstracted 21 half-page texts from informed consents, clinical documents, abstracts, and health-related websites. Each original text was then rewritten using 3 AI algorithms (resulting in 63 new, rewritten texts). Participants were given a set of 3 randomly selected surveys. Each survey contained the original text and an AI-rewritten text. Participants were then asked to answer 5 questions using a Likert scale 1-5 about the readability, clarity, and content of the two texts, their overall score of the new text, and which text they preferred. The study was IRB-approved. Participants were given a $10 gift card. Results/Anticipated Results: 68 participants (69.6% non-white, 65.2% female, mean age 58.3) completed the study task. 3 AI Algorithms were tested: * ConBART [Cripwell 2023]: context-aware method for text simplification * UL+Decoder [Flores 2023]: Flesh-Kincaid readability-driven method for text simplification * UBclear [House-made]: Iteratively improves readability with self-correction and retrieval-augmented generation. ConBART and UL+Decoder scored similarly across readability, clarity, and detail-fidelity metrics, but were preferred over original texts less than 50% of the time. UBclear scored higher in readability, clarity, detail, and overall score. Importantly, UBclear text was preferred over the original text 80% of the time, showing stronger alignment with human judgments of clarity, readability, and fidelity. Discussion/Significance of Impact: Our pilot study shows that AI can simplify existing research and medical care documents, potentially contributing to inclusivity and transparency in research and clinical care. “UBclear” was superior to the other 2 AI methodologies in readability, accessibility, and clarity while also being preferred over original texts and competing AI versions.

OBJECTIVES/GOALS: Exposure to arsenic, cadmium, manganese, and lead have been linked to adverse neurocognitive outcomes in adults/children, but effects in adolescents are not fully characterized. This study aims to examine the association between exposure to a mixture of metals (As, Cd, Mn, Pb, Se) and cognitive function in adolescents. METHODS/STUDY POPULATION: The Metals, Arsenic, & Nutrition in Adolescents Study (MANAS) is a cross-sectional study of 572 Bangladeshi adolescents. Blood levels of As, Cd, Mn, Pb, and Se were measured via ICP-MS. An abbreviated Cambridge Neuropsychological Test Automated Battery (CANTAB) was administered, with subtests assessing cognitive function and executive function tasks. Linear regression and Bayesian kernel machine regression (BKMR) were used to examine associations between individual metals, the overall mixture of metals, and cognitive function as measured by the CANTAB. RESULTS/ANTICIPATED RESULTS: Linear regression showed that As (B=−2.40) and Mn (B=−5.31) were negatively associated with Spatial Working Memory (p<0.05). Negative associations were also observed between Cd and Spatial Recognition Memory (SRM) (B=−2.77, p<0.05), and between Pb and Delayed Match to Sample (DMS), a measure of visual recognition and memory (B=−3.67, p<0.05). Se and Spatial Span Length (B=0.92, p<0.05) were seen to be positively associated. BKMR showed no overall effect of the mixture but indicated that Pb was negatively associated with DMS, and that Cd was negatively associated with SRM. Se was positively associated with Planning, Reaction Time, and Spatial Span. Posterior inclusion probability consistently rated Se as the most influential mixture component. DISCUSSION/SIGNIFICANCE: Se was positively associated with cognition, while Mn and As were linked to poorer working memory, and Cd and Pb were associated with poorer visual recognition and memory. We saw agreement between linear regression and BKMR in analyzing metal mixture exposures. Findings suggest interventions aimed at adolescents might influence lifelong cognition.

OBJECTIVES/SPECIFIC AIMS: The soluble adenylyl cyclase (sAC) is a noncanonical source of cAMP in mammalian cells. sAC is an ATP/bicarbonate ion sensor, whose activity responds to intracellular signals such as pH changes and metabolism. Unlike the more traditionally studied transmembrane adenylyl cyclase, sAC is not tethered to the cell membrane and instead is found in subcellular microdomains like the mitochondria and nucleus. In particular, sAC localization in the mitochondria has been implicated in oxidative phosphorylation and mitochondrial metabolism. Specific changes in sAC microdomain localization have diagnostic utility in a wide variety of cancers, namely melanoma. We have recently found that loss of sAC leads to tumorigenesis and a Warburg/cancer-like metabolic phenotype, consisting of an activated flux through glycolysis, increased lactate production, and dependence on glucose metabolism. In addition, computational analysis of the metabolomics profile of sAC null cells suggests an increased flux through serine synthetic pathways. We hypothesized that specific sAC microdomains are responsible for this cancer-like metabolic state. METHODS/STUDY POPULATION: We have established oncogenic SV40 large T antigen and HPV16-E6 expressing mouse embryonic fibroblasts lacking sAC expression (SV40 KO and E6 KO, respectively). Using these parental lines, we reintroduced sAC by targeting the protein to specific microdomains. sAC was either driven into the mitochondria (mito-sAC) or was driven into all possible microdomains (WT sAC). Single clones were generated and sAC expression was confirmed by Western analysis. Stable cell lines were evaluated for mitochondrial metabolism, glucose sensitivity, and serine sensitivity. RESULTS/ANTICIPATED RESULTS: We found that reintroduction of WT sAC into sAC null cells rescued sensitivity to glycolytic inhibition compared with control cells (p<0.01). The effect was not dependent on the method of immortalization as it was seen in both SV40 and E6 KO cell lines. sAC activity was not directly proportional to expression suggesting that additional regulatory pathways exist. Interestingly, targeted delivery of sAC to the mitochondria was not as effective in rescuing glucose sensitivity as untargeted delivery of sAC into all possible microdomains. Therefore, even though mitochondrial sAC is known to influence metabolism, our data suggests that the nonmitochondrial isoform is most important for cancer cell metabolism. Although metabolomics analysis suggested that serine synthetic pathways are activated in sAC null cells, there is no evidence to suggest that serine is required for sAC null cell growth. Neither inhibition of serine synthesis nor serine starvation differentially affected the growth of sAC null cells compared with WT sAC. DISCUSSION/SIGNIFICANCE OF IMPACT: These data suggest that the Warburg metabolic phenotype in sAC null cells is regulated by specific sAC microdomains. By targeting sAC to specific microdomains, we can further distinguish the role of sAC localization in cellular metabolism. Cancer cells have been shown to exhibit altered metabolic circuitry of pathways like glycolysis, which allow them to adapt to increased metabolic demands of cellular proliferation and waning environmental resources. Beyond helping us improve the use of sAC immunolocalization as a cancer diagnostic, a better understanding of sAC microdomains in transformed cells will help us understand how this signaling pathway is important in cancer. Pharmacologic manipulation of sAC signaling may represent a new cancer therapeutic strategy.

ABSTRACT IMPACT: MiaA has a human homolog known as TRIT1. Mutations in TRIT1 have been associated with rare diseases such as MELAS and MERRF syndromes. These diseases are associated with mitochondrial disfunction.Understanding the mechanisms of bacterial sRNAs, and the miRNAs associated with these diseases could potentially afford the insight into effective cures. OBJECTIVES/GOALS: The aim is to investigate the regulation and function of tRNA isopentyladenine transferase enzyme in Escherichia coli. We aimed to execute screens for the identification of small RNA regulators of MiaA. The study will also investigate if i6A tRNA modification is necessary for the expression of major heat shock and mitochondrial proteins. METHODS/STUDY POPULATION: We constructed a chromosomal miaA-lacZ translational fusion driven by the arabinose responsive PBAD promoter and used it to screen against an Escherichia coli small RNA library. Using CsrB, one of our candidate sRNA regulators from our genetic screen, we measured the steady state levels of MiaA by Northern Blot in a PBAD-miaA2(P2HS)-lacZ translational fusion strain whereby pBR-pLac-csrB, pBR-pLac-csrA and the pBR-pLac vector are over-expressed, and under the control of an IPTG inducible promoter. Additionally, and in the same PBAD-miaA2(P2HS)-lacZ translational fusion strain background, we measured the steady state levels of MiaA in the wild type, csrA:zeo mutant strain, and csrA:zeo pBR-pLac-csrA complementation strain to determine if a combination of the pair would restore the wild-type genotype. RESULTS/ANTICIPATED RESULTS: Upon measuring the effect of small RNAs on miaA expression using quantitative b-galactosidase assays, we saw a 5-fold decrease in the expression of MiaA in the miaA-lacZ translational fusion containing sRNA CsrB, suggesting that this sRNA may play a role in the regulation of post-transcriptional expression of MiaA.From our northern blotting analysis, we observed a 6-fold decrease in MiaA expression in the absence of csrA, suggesting that csrA is essential for MiaA expression. DISCUSSION/SIGNIFICANCE OF FINDINGS: Identifying, mapping and characterizing how MiaA is regulated post-transcriptionally will give us an increased understanding in the maintenance and regulation of the normal function of E.coli to conserve homeostasis and translation fidelity.

OBJECTIVES/GOALS: Decoding the origins of cell-free DNA (cfDNA) released from dying cells in a liquid biopsy sample (e.g. blood) offers the potential to provide insight into the dynamic, organism-wide changes reflective of health and disease. Thus, making cfDNA an ideal target for serial, minimally invasive monitoring of disease-related changes. METHODS/STUDY POPULATION: We develop a probabilistic method that leverages the co-regulation of neighboring CpG sites on individual methylome-wide sequencing (WGBS) reads to more flexibly model cell-specific methylation compared to prior methods that focus on the methylation rate of a single CpG site. We then extend our cross-sectional model to account for sequential sampling within the same subject. The increased sampling frequency is critical to identifying the evolutionary dynamics of disease progression influencing treatment response and resistance, and disease recurrence. We utilize Bayesian inference techniques to model patient-specific longitudinal profiles of cell-type turnover in simulated serial samples. RESULTS/ANTICIPATED RESULTS: We found our model more effective at capturing a range of methylation patterns on cfDNA fragments with lower Root Mean Square Error across simulations compared to a single CpG model. We apply our model to detect significant (p < 0.05, Friedman’s test) increases in cellular contributions from lung and cardiac tissue in breast cancer patients (n=15) undergoing radiation therapy compared to baseline. We also identify signals of radiation induced toxicity to the liver in right-sided breast cancer patients (n=8) receiving radiation treatment compared to left-sided breast cancer patients (n=7). Finally, we show our extended model results in more efficient estimates of simulated cell-type turnover profiles compared to analyzing serial samples cross-sectionally, ignoring the longitudinal nature of the data. DISCUSSION/SIGNIFICANCE: Here we address an unmet need in developing novel statistical methodologies to decode the origins of methylated cfDNA obtained from liquid biopsy samples. We demonstrate the far-ranging clinical utility of serial liquid biopsy sampling to complement and advance the standards of clinical care in oncology and other pathologies.

OBJECTIVES/SPECIFIC AIMS: To share the experience gained and lessons learned from a cross CTSA collaborative effort to improve the review process for Pilot Studies awards by exchanging external reviewers. METHODS/STUDY POPULATION: The CEREC process is managed by a web-based tracking system that enables all participating members to view at any time the status of reviewer invitations. This online tracking system is supplemented by monthly conference calls during which new calls for proposals are announced and best practices are identified. Each CTSA hub customized the CEREC model based on their individual pilot program needs and review process. Some hubs have supplemented their internal reviews by only posting proposals on CEREC that lack reviewers with significant expertise within their institutions. Other hubs have requested 1–3 external reviewers for each of their proposals or a selection of most promising proposals. In anticipation of potential scoring discrepancies, several hubs added a self-assessment of reviewer expertise and confidence at the end of each review. If a proposal is on the cusp of fundability, then the reviewers’ self-assessment may be taken into account. In addition to the tracking data collected by the online system, a survey of CEREC reviewers was conducted using Qualtrics. RESULTS/ANTICIPATED RESULTS: Across the 144 proposals submitted for reviews, CEREC members issued a total of 396 email invitations to potential reviewers. The number of invitations required to yield a reviewer ranged from 1 to 17. A total of 224 invitations were accepted, for a response rate of 56%. An external reviewer was unable to be located for 5 proposals (3%). Ultimately, 196 completed reviews were submitted, for a completion rate of 87%. The most common reasons for non-completion after acceptance of an invitation included reviewer illness and discovery of a conflict of interest. CEREC members found the process extremely useful for locating qualified reviewers who were not in conflict with the proposal being reviewed and for identifying reviewers for proposals related to highly specialized topics. The survey of CEREC reviewers found that they generally found the process easy to navigate and intellectually rewarding. Most would be willing to review additional CEREC proposals in the future. External reviewer comments and scores were generally in agreement with internal reviewer comments and scores. Thus, hubs could factor in external reviewer scores equally to internal reviewer scores, without feeling compelled to calibrate external reviewer scores. Overall, through CEREC external reviewers, mainly due to the stronger matching of scientific expertise and reduction of potential bias, the quality of reviews appear to be higher and more pertinent. DISCUSSION/SIGNIFICANCE OF IMPACT: Some aspects of the process emerged that will be addressed in the future to make the system more efficient. One issue that arose was the burden on the system during multiple simultaneous calls for proposals. Future plans call for harmonizing review cycles to avoid these overlaps. Efficiency also will be improved by optimizing the timing of reviewer invitations to minimize the probability of obtaining more reviews than requested. In addition to the original objective of CEREC, the collaboration has led to additional exchange of information regarding methods and processes related to running the Pilot Funding programs. For example, one site developed a method using REDCap to manage their reviewer database; an innovation that is being shared with the other CEREC partners. Another site has a well-developed process for integrating community reviewers into their review process and is sharing their training materials with the remaining CEREC partners.

Objectives/Goals: Failure to achieve recruitment goals results in termination of ~20% of clinical trials and delays >85% of trial timelines. We aim to develop an electronic heath record (EHR)-based recruitment tool to ease identification of participants. We sought to determine whether criteria listed on clinicaltrials.gov could support selection of tool variables. Methods/Study Population: To inform the variables to include in the EHR-based recruitment tool, we data scraped clinicaltrials.gov to identify key inclusion and exclusion criteria common across a variety of diabetes clinical trials. We included actively recruiting or recently active phase 2 and 3 clinical trials of adults aged >18 years of age in the USA. We classified identified variables as clinically relevant or not and compared clinically relevant terms with inclusion and exclusion criteria (~20 variables) that were individually identified by three diabetes clinical trialists and two clinical research coordinators (CRCs). Results/Anticipated Results: We reviewed 203 clinical trials listed on clinicaltrials.gov. We identified 115 terms, 91 of which were clinically relevant. Three of 3 clinical trialists, 1 of 2 CRCs, and all trials listed age as a key variable. Consistent with data scraping, all trialists and CRCs identified glucose-lowering medications and kidney function as important criteria. Gender, ethnicity, and race were less commonly noted on clinicaltrials.gov and listed by 2 of 3 trialists and one CRC. Cardiovascular conditions (e.g., history of myocardial infarction), thyroid function tests, and contraceptive requirements were common criteria on clinicaltrials.gov, but only one trialist and one CRC identified these variables. Active infections (e.g., HIV) and c-peptide were not highlighted by trialists or CRCs but common on clinicaltrials.gov. Discussion/Significance of Impact: An EHR-based recruitment tool may facilitate identification of trial participants, but identifying key variables to include is essential. We found that data scraping for variables on clinicaltrials.gov mostly aligned with expert opinion, suggesting that automating variable selection via extraction from clinicaltrials.gov may be acceptable.

OBJECTIVES/GOALS: Lack of blood vessels remains a major obstacle in tissue regeneration. Angiopoietin 1 and 2 modulate angiogenesis through the Tie2 receptor tyrosine kinase. Ang1 activates pAKT to promote endothelial cell survival while Ang2 antagonizes these effects. We aim to dissect the Ang/Tie2 pathway to uncover the molecular basis for these opposing effects. METHODS/STUDY POPULATION: Ang1 and Ang2 bind Tie2 via nearly identical F-domains (Fd). To investigate the molecular basis regulating the Tie2 pathway, we generated a series of computationally designed self-assembling protein scaffolds presenting F-domains in a wide range of valencies and geometries using Rosette Molecular Modeling Suite. We examined the protein kinase activation, cell migration, and blood vessel formation produced by the designed proteins in human umbilical vein endothelial cells. RESULTS/ANTICIPATED RESULTS: Two phenotypic classes were demonstrated by the number of presented F domains: scaffolds presenting 3 or 4 Fd have Ang2 like activity, upregulating pFAK and pERK but not pAKT and failing to induce cell migration and tube formation; scaffolds presenting more than 6 Fd have Ang1 like activity, upregulating the three signaling branches and enhancing cell migration and tube formation. Scaffolds with 8 or more Fd show superagonist activity, producing significantly stronger phenotypes than Ang1. These results suggest that Fd valency largely determines Ang1 vs Ang2 signaling outcomes, and our designed superagonists can outperform Ang1 in vascularization and wound healing. In in vivo experiments, nanoparticles displaying 60 copies of Fd produce significant revascularization in hemorrhagic brains. DISCUSSION/SIGNIFICANCE OF IMPACT: Targeting the Tie2 pathway is a new paradigm in regenerative medicine. Our designed constructs will enable us to generate high-affinity Tie2 agonists and antagonists as drugs to control angiogenesis, enabling tissue regeneration that recapitulates the biological architecture of the native tissue physiology, improving organ transplant outcome.

OBJECTIVES/SPECIFIC AIMS: The long-term goal of this project is to develop a cost effective 3D printed multipurpose intravaginal ring (IVR) to prevent against unintended pregnancies and infectious diseases.Our goal is to develop a female-controlled method for prevention using innovative IVRs. METHODS/STUDY POPULATION: In vitro and in vivo characterization. RESULTS/ANTICIPATED RESULTS: Controlled and fine-tuned release kinetics 100% drug release from 3D printed IVRs compared with 10%–15% with traditional injection molded IVRs cost-effective engineering of multipurpose IVR with CLIP 3D printing technology. DISCUSSION/SIGNIFICANCE OF IMPACT: If successful, this project will revolutionize the engineering of IVRs and will have a global impact on human health. Not only we will help save millions of women around the world but also millions of children that are infected by their HIV-positive mothers through gestation or breast feeding.

OBJECTIVES/GOALS: Non-alcoholic fatty liver disease increases with aging and may be associated with MCI. Thus, adults >65 years with NAFLD have a greater risk of MCI. Our objective is to associate NAFLD with MCI and, therefore, optimize the management of MCI through prevention strategies and early interventions. METHODS/STUDY POPULATION: We will recruit 100 patients >65 of all sexes from the GI and Geriatrics clinics of the University of Puerto Rico (UPR). NAFLD prevalence in aging adults will be estimated via ICD-10 codes and definition will be liver fat accumulation or steatosis (AASLD) without secondary causes. We will exclude patients RESULTS/ANTICIPATED RESULTS: We expect to find a higher NAFLD prevalence in aging adults >65 years old compared to younger ones. Furthermore, we aim to elucidate an association of NAFLD with MCI in aging adults. Besides, as the literature has shown, we anticipate that the main cognitive domains affected by NAFLD will be the visuospatial and executive functions. As the population ages, this study will help identify future targets for early interventions in people diagnosed with NAFLD that could have a greater risk for cognitive impairment. DISCUSSION/SIGNIFICANCE: To our knowledge, no study has determined the association of NAFLD with MCI in Hispanics >65 in PR. Raising awareness of NAFLD as a possible treatable or preventable risk factor for MCI by screening NAFLD patients for MCI may improve not only their global health but their quality of life as well.

ABSTRACT IMPACT: My work is on the development of a novel tumor immunotherapy to treat various types of cancer OBJECTIVES/GOALS: As iNKT cells can have direct and indirect killing effects on tumor cells, we propose a novel strategy for activating iNKT cells, via a PLGA nanoparticle delivery platform, to promote anti-tumor immune responses. METHODS/STUDY POPULATION: Poly-lactic-co-glycolic acid (PLGA) nanoparticles can be reproducibly loaded with an iNKT cell glycolipid agonist, alpha-galactosylceramide (αGalCer), and a tumor associated antigen, ovalbumin (OVA). We then test our nanoP prophylactically and therapeutically against a murine model of melanoma, B16F10-OVA. RESULTS/ANTICIPATED RESULTS: These dual-loaded PLGA nanoparticles rapidly activate iNKT cells in vivo to produce IFNgamma. Furthermore, in an in vivo model of melanoma, using B16F10-OVA cells, both prophylactic and therapeutic administration of nanoparticles containing αGalCer and OVA led to decreased tumor cell growth and increased survival. We also show our nanoparticle therapy has synergistic potential with clinically used immune checkpoint blockade (ICB) therapies, anti-PD-1 and anti-CTLA-4, indicated by the significance increase in survival and lower tumor growth rate of ICB +nanoP treated mice compared to either ICB or nanoP alone. DISCUSSION/SIGNIFICANCE OF FINDINGS: This novel delivery system provides a platform with tremendous potential to harness iNKT cells for cancer immunotherapy purposes against many cancer types.

OBJECTIVES/SPECIFIC AIMS: To examine and compare the claims in Bzdok, Altman, and Brzywinski under a broader set of conditions by using unbiased methods of comparison. To explore how to accurately use various machine learning and traditional statistical methods in large-scale translational research by estimating their accuracy statistics. Then we will identify the methods with the best performance characteristics. METHODS/STUDY POPULATION: We conducted a simulation study with a microarray of gene expression data. We maintained the original structure proposed by Bzdok, Altman, and Brzywinski. The structure for gene expression data includes a total of 40 genes from 20 people, in which 10 people are phenotype positive and 10 are phenotype negative. In order to find a statistical difference 25% of the genes were set to be dysregulated across phenotype. This dysregulation forced the positive and negative phenotypes to have different mean population expressions. Additional variance was included to simulate genetic variation across the population. We also allowed for within person correlation across genes, which was not done in the original simulations. The following methods were used to determine the number of dysregulated genes in simulated data set: unadjusted p-values, Benjamini-Hochberg adjusted p-values, Bonferroni adjusted p-values, random forest importance levels, neural net prediction weights, and second-generation p-values. RESULTS/ANTICIPATED RESULTS: Results vary depending on whether a pre-specified significance level is used or the top 10 ranked values are taken. When all methods are given the same prior information of 10 dysregulated genes, the Benjamini-Hochberg adjusted p-values and the second-generation p-values generally outperform all other methods. We were not able to reproduce or validate the finding that random forest importance levels via a machine learning algorithm outperform classical methods. Almost uniformly, the machine learning methods did not yield improved accuracy statistics and they depend heavily on the a priori chosen number of dysregulated genes. DISCUSSION/SIGNIFICANCE OF IMPACT: In this context, machine learning methods do not outperform standard methods. Because of this and their additional complexity, machine learning approaches would not be preferable. Of all the approaches the second-generation p-value appears to offer significant benefit for the cost of a priori defining a region of trivially null effect sizes. The choice of an analysis method for large-scale translational data is critical to the success of any statistical investigation, and our simulations clearly highlight the various tradeoffs among the available methods.

OBJECTIVES/SPECIFIC AIMS: Polyglutamine (polyQ) neurodegenerative diseases, associated with the unstable expansion of polyQ tracts, are devastating diseases for which no treatments exist. Moreover, most drug discovery attempts have been hindered by the lack of understanding on the relevant pathogenic mechanisms. Here, using previously reported 3D protein predicted structures of ataxin-2 and ataxin-3, we analyze the effect of polyQ enlargement on hydrogen bonding and water accessibility patterns as a possible mechanism for pathogenesis thought enhanced protein aggregation. METHODS/STUDY POPULATION: Using the I-TASSER predicted structures of ataxin-2 and ataxin-3 with different numbers of glutamine repeats representing polyQ lengths characteristic of both normal and pathological tracts (Journal of Biomolecular Structure and Dynamics, 2016: 1–16), we identified hydrogen bonds (HBs, UCSF Chimera FindHBond module) and calculated solvent-accessible surface areas (SASA, DSSP program) for the polyQ tracts available in the 3D structures. RESULTS/ANTICIPATED RESULTS: The identified HBs were analyzed as the function of the number of glutamines in the polyQ tracts and characterized as those intra-polyQ and exter-polyQ, respectively. The SASA of the polyQ region was also studied as the function of the polyQ tract length. DISCUSSION/SIGNIFICANCE OF IMPACT: The results obtained here indicate that polyQ regions increasingly prefer self-interactions, which consistently can lead to more compact polyQ structures. The results strongly support the notion that the expansion of the polyQ region can be an intrinsic force leading to self-aggregation of polyglutamine proteins and suggest that the modulation of solvent-polyQ interactions could be a possible therapeutic strategy for polyQ diseases.

OBJECTIVES/GOALS: The goal of this presentation is to highlight the role of and challenges to the Biostatistics, Epidemiology and Research Design (BERD) Core as it transitions into (i) the resources and services module (ii) and also possibly a regional center of translational science. METHODS/STUDY POPULATION: BERD cores play key roles in translational research missions, often in the form of long-term collaborative relationships focusing on project conception and design, interim monitoring and review, analysis and dissemination. The resources and services module encourages consolidation of all resources and services under the single modular umbrella, which can pose challenges to BERD autonomy and function. CTSAs transitioning from local to regional centers can also threaten to overwhelm BERD workloads and resources. Our CTSA planned an outsource-insource model to make the BERD a central feature of the new module and transplant its functionality to partner institutions. RESULTS/ANTICIPATED RESULTS: The team has planned a centralized, web-based entry-point for both self-guided inquiry and electronic requests of all resources and services, which aides project database creation and provides notification for review. The review process adds two new approval types: guided assistance to help navigate connections to relevant resources, and triaged referrals to training modules for remediation and skills development. Our BERD has added a Consulting Laboratory for projects of sufficient but non-priority merit that would otherwise be waitlisted, and established connections with regional partner institutions to whom they can refer investigators. DISCUSSION/SIGNIFICANCE: We have consolidated all resources and services into a single, accessible location, emphasizing tailored guidance to maximize limited resources. We also planned a transportable regional model that accounts for local resources and capacity to keep from overstretching the BERD and other hubs.

OBJECTIVES/GOALS: This study models a framework for integrating epidemiological and experimental approaches to investigate the effect of prenatal polycyclic aromatic hydrocarbon (PAH) exposure on mitochondrial function (mtDNAcn, superoxide production and membrane potential) as a potential mechanism of toxicity. METHODS/STUDY POPULATION: The epidemiological aim of this study characterizes mitochondrial outcomes in samples of umbilical cord tissue and blood from two Manhattan based birth cohorts. Prenatal PAH exposure is quantified using silicone wristbands worn for 48 hours during the third trimester of pregnancy. Experimentally, we are applying a PAH mixture designed to emulate the exposure profile of the human cohorts to mouse preimplantation embryos on various dosing schedules and quantifying the same mitochondrial outcomes. mtDNAcn is quantified using rtPCR while superoxide production and membrane potential are measured using fluorescence microscopy. The goal of this study design is to leverage the strengths of each approach to draw more robust conclusions than could be derived from either alone. RESULTS/ANTICIPATED RESULTS: Preliminary results of this study have found associations between higher levels of PAH exposure and increased mitochondrial superoxide production and hyperpolarization of the mitochondrial membrane potential in mouse preimplantation embryos. We anticipate these findings to persist across dosing schedules. We furthermore expect a decrease in mtDNAcn in association with higher PAH exposure in umbilical cord tissue samples and decreased mtDNAcn with exposure to the PAH mixture in mouse embryos. DISCUSSION/SIGNIFICANCE: Characterizing the effect of prenatal PAH exposure on the mitochondria is a critical step in understanding the mechanisms that underlie the toxicity of this exposure. By employing a similar exposure mixture and mitochondrial outcomes across epidemiological and experimental approaches, we offer a model of true interdisciplinary research design.

OBJECTIVES/GOALS: We aim to develop an understanding of how polysubstance use (PSU) relates to the general psychopathology factor (p-factor), as well as to individual components of the Hierarchical Taxonomy of Psychopathology (HiTOP) model (e.g., fear, distress). This insight can help identify treatment targets related to substance use and psychopathology. METHODS/STUDY POPULATION: Psychopathology and substance use data, collected at a Baltimore treatment center over several years, will be analyzed. The center aids about 6000 underserved clients per year, and the population is primarily African American clients of all genders. Structural equation modeling (using Mplus software) will be used to develop the latent models and identify relationships between psychopathology and PSU (i.e., direct and indirect pathways). The current latent HiTOP model was developed from symptom checklists completed upon entry at the treatment center. The PSU latent factor will be developed from a biopsychosocial assessment where clients list their drug of choice. Due to the varying organizations of the datasets, smaller-scale preliminary models will be developed to ensure an accurate large-scale final model. RESULTS/ANTICIPATED RESULTS: Current models being tested are derived from January to September 2023 data (i.e., completed months' data), with an N of 1,564. From symptom checklist data collected at the treatment center, a preliminary HiTOP model was derived with reasonable fit (χ2 = 4532.35 (df = 321, p<.001), CFI = .77, SRMR = .07, RMSEA = .09 (.089, .094)). Data analysis is being conducted to derive the PSU factor before relating PSU to the HiTOP model. Given previous work at a local treatment center (Pavuluri etal., 2022) and with the National Comorbidity Survey-Replication data, we expect all positive direct relationships, negative indirect relationships between internalizing factors (fear and distress) and PSU when accounting for p-factor, and a positive indirect relationship between antagonism and PSU when accounting for p-factor. DISCUSSION/SIGNIFICANCE: Given our previous work to develop such models, we want to establish proof of concept in alarger treatment center population. This confirmation will help provide a path towards conducting therapeutic trials to target psychopathology when treating substance use given the shared relations, some of which are less understood (e.g., fear and PSU).

OBJECTIVES/GOALS: Reactive gliosis is a hallmark of neurodegenerative disease and is characterized by the release of pro-inflammatory cytokines and physiologic changes to glial cells. Our work identifies a novel inflammatory glial-glial cell interaction and role for mGluR5 that has the potential to provide novel insight into the mechanisms of neurodegeneration. METHODS/STUDY POPULATION: Cell Culture: Mouse primary astrocytes and microglia were isolated from P0-P3 C57BL/6 or Cx3cr1GFP/+ mice.1Treatment: Glia were treated with oligomeric α-synuclein 1μg/mL or mGluR5 agonist CHPG 100 μM.2,3ELISA: Glia culture media was collected and analyzed according to the manufacturer. qRT-PCR: TaqMan™ probes were used according to manufacturer on extracted glia mRNA. ICC: Microglia were labeled with 1:750 Rb x Iba1 (Wako) and 1:500 Alexa Fluor 488 Gt x Rb. Phagocytosis Assay: Primary glia were treated with α-synuclein or astrocyte-conditioned culture media for 24-48hrs. For treatment of microglia with conditioned media, astrocytes were washed with PBS and fresh media was added to prevent carry over of α-synuclein to microglia. The number of fluorescent microbeads per microglia was quantified. RESULTS/ANTICIPATED RESULTS: Mouse primary cortical astrocytes simulated with α-synuclein aggregates adopt a reactive A1 phenotype independent of microglial stimulation. This A1 phenotype is characterized by release of pro-inflammatory cytokines including Complement Component 3 and the monocyte chemoattractant CCL2. Reactive astrocyte media induces a phagocytic phenotype in primary mouse microglia. Along with this, α-synuclein-directed microglial phagocytosis was attenuated with the addition of the mGluR5 agonist CHPG. DISCUSSION/SIGNIFICANCE OF IMPACT: Our findings suggest that oligomeric α-synuclein is capable of inducing a reactive phenotype in astrocytes independent of microglia and implicate crosstalk between glia as an important mediator of inflammation and microglial phagocytosis in synucleinopathies.

OBJECTIVES/GOALS: We investigated the association between gut microbiota features in newly admitted nursing facility (NF) patients and the acquisition of vancomycin-resistant Enterococcus (VRE) and/or resistant Gram-negative bacteria (rGNB) within 14 days. METHODS/STUDY POPULATION: Patients were recruited at 6 Michigan NFs from 09/16-08/18. VRE or rGNB colonization status was determined by culture swabs collected from multiple body sites at enrolment, day 7, and day 14. Our analysis focused on patients with no colonization at baseline, a perirectal swab collected at baseline, and at least one follow-up visit. The V4 hypervariable region of the 16S rRNA gene from bacterial DNA in each sample was PCR-amplified and sequenced on the MiSeq platform. Sequencing results were then processed with the mothur bioinformatics pipeline to classify bacterial taxa present in each sample. Taxa typically associated with the skin microbiota were removed. The primary outcome was acquisition of VRE and/or rGNB within 14 days. Exposures of interest included patient and microbiota characteristics. RESULTS/ANTICIPATED RESULTS: Among 61 patients, 18 (30%) acquired AROs within 14 days of enrolment (3 VRE, 13 rGNB, 2 both) (Table 1). The baseline microbiota features differed significantly in those who acquired a new ARO. Of the major 8 phyla found across samples, patients who acquired an ARO were depleted in the number of phyla present (5.74 ± 1.20 vs 5.06 ± 1.43; p = 0.037) (Fig. 1). The log10-transformed relative abundance of Enterococcus was enriched in patients who acquired an ARO (−0.32 ± 1.47) compared to those who did not (−1.68 ± 1.76; p = 0.021) (Fig. 2). Patients who did not acquire an ARO tended to harbour more butyrate-producing bacterial taxa and strict anaerobes, although the differences were not statistically significant (relative abundance of butyrate producer: 29.49 ± 22.09 vs 22.05 ± 17.76; anaerobes: 64.78 ± 23.54 vs 53.68 ± 27.61). DISCUSSION/SIGNIFICANCE OF IMPACT: Microbiota metrics calculated from perirectal samples are predictive of ARO acquisition. The clinical utility of perirectal samples thus warrants further assessment.

Objectives/Goals: Blood pressure (BP) control remains suboptimal among US patients with hypertension. Single-pill combination (SPC) therapies are commonly used to improve adherence; however, their effectiveness for achieving early and sustained intensive BP control is unclear. Methods/Study Population: We performed a post hoc analysis of SPRINT including 2,736 participants propensity matched in 1:2 ratio to compare effects of SPCs with equivalent multi-pill therapy. The estimated marginal odds of achieving optimal BP control were derived using generalized linear mixed models with repeated measures (LMMRM). The association between time-updated SPC use and BP change in short- (≤6 months) and long-term (>6 months) follow-up was assessed with LMMRM and SPC*time interaction term. Multivariable Cox models evaluated association of SPC use with CV events and serious adverse events (SAEs). Results/Anticipated Results: Among SPRINT participants (N=8623), 9.3% (N=803) were prescribed SPC at baseline with greater use in the intensive vs. usual care group (5.79 vs. 3.90 per 100 person-months; p-diff<0.001). Among matched pairs (SPC[n=912); multi-pill therapy[n=1824]), SPC use was associated with 22% increased likelihood of achieving target BP by 6 months [OR(95% CI): 1.22(1.05, 1.42)]. Participants receiving SPCs (vs multi-pills) experienced more rapid BP reduction in the first 6 months (-2.0 vs. -1.2 mmHg monthly change; p-diff<0.001). Over long-term follow-up, participants using SPCs achieved significantly lower SBP at each timepoint. The risk of the primary CV composite endpoint and SAEs was not significantly different between groups. Discussion/Significance of Impact: SPC therapy resulted in more rapid and sustained BP reduction and a greater likelihood of achieving BP control compared with multi-pill therapy without increase in SAEs. Future research is needed to identify optimal strategies for implementing SPC-based approaches at the population-level and optimize public health benefits of intensive BP control.

OBJECTIVES/SPECIFIC AIMS: This poster presents preliminary results of using in silico approaches to predict a priori, based on sequence alone, the pathogenesis of novel influenza A virus. METHODS/STUDY POPULATION: Here we analyzed the structure of the NS1 protein of 11 strains of well characterized influenza A virus with known pathogenesis, reported in the literature as LD50 values, and published sequences. We performed homology comparison of these sequences using the ExPASy SIM alignment tool for protein sequences and then predicted their 3D structures using the I-TASSER method for protein structure prediction. We retained the best 20 I-TASSER models for the NS1 sequences considered here and compared their structures with that of the X-ray crystallographic structure of the NS1 protein in the A/blue-winged teal/MN/993/1980 (H6N6). The average RMS between this experimental structure and the best 20 I-TASSER models was used as a measure of structural similarity between the 3D structures among the proteins. RESULTS/ANTICIPATED RESULTS: The sequence homology shows modest correlation between sequence and pathogenicity. Linear correlations with R values as large as 0.6 where observed for the full sequence homology and the homology of the RBD domains of the proteins. The correlations with the other protein domains were significant lower. We did not found overall correlation between the 3D structures and pathogenesis of all the variants considered here, but the initial results suggest that correlations do exists for different subgroups of viruses. In future work we will use advanced data mining methods to better understand clustering and correlation between structure and pathogenesis. DISCUSSION/SIGNIFICANCE OF IMPACT: The results presented in this poster demonstrate, as proof of concept, the use of in silico approaches to determine pathogenesis of viruses with substantial impact on human health. The ability of computationally predicting pathogenesis of rapidly mutating viruses can be an effective way to accelerate the development prevention strategies because computational methods are relatively inexpensive and much more scalable than in vivo approaches.