OBJECTIVES/GOALS: Guidelines suggest people with HIV (PWH) receive routine HIV viral load (VL) testing at least yearly and upon diagnosis with multidrug-resistant tuberculosis (MDR-TB). Many PWH and MDR-TB in South Africa seem to be missing VL results. This study’s goal was to find results which may be available from the National Health Laboratory Service (NHLS). METHODS/STUDY POPULATION: We abstracted HIV laboratory results, specifically baseline VL and CD4 count and VL at MDR-TB cure, from PWH enrolled in a cluster-randomized clinical trial of nurse case management for PWH and MDR-TB in South Africa who were cured of MDR-TB. For any participant missing one or more of these results, we thoroughly searched the electronic NHLS database using multiple separate searches varying terms including patient name, surname, date of birth, medical record number where available, and South African identification number. Returned results were compared to results abstracted from the parent study and any additional results were entered into the parent study data. RESULTS/ANTICIPATED RESULTS: Of 929 PWH cured of MDR-TB, 879 (94.6%) were missing at least one expected VL or CD4 result in the parent study database. Though our search strategy was successful in identifying participants and returning CD4 and VL results, we rarely found additional results that were not already in the parent study database. Following the search and entry of the few additional results retrieved, 116 (12.4%) participants were missing a baseline CD4, 309 (33.3%) missing baseline VL, and 385 (41.4%) missing VL at MDR-TB cure, representing 572 individuals or 61.6% of participants with at least one unavailable result. This high level of unavailability of key laboratory results used to guide MDR-TB and HIV treatment suggests that these tests were either not ordered, not collected, or not completed due to electronic gatekeeping at NHLS. DISCUSSION/SIGNIFICANCE: Unknown CD4 count or VL leaves PWH open to including MDR-TB treatment failure and death. Our search strategy found additional results but was time-consuming and cumbersome. Limitations included lack of information on why laboratory results were missing, which limits our ability to make recommendations for better collection and reporting.

OBJECTIVES/SPECIFIC AIMS: Microarray technology has produced large volumes of gene expression data profiling differences in gene expression in a vast array of conditions, much of which is publicly available. Methods to query these data for similarities in patterns of gene regulation are limited to comparisons between preannotated groups. In response, we developed openSESAME to find experiments where a set of genes is similarly coregulated without regard to experimental design. An important application of openSESAME is drug repositioning: if a pattern associated with disease is reversed by a given drug, the drug might target disease-related processes. METHODS/STUDY POPULATION: Experiments from the Gene Expression Omnibus (GEO) were normalized, signature-association (SA) scores computed for each sample, experiments assigned enrichment scores, and ANOVAs used to assign significance to experimental variables automatically extracted from GEO. SA scores were also generated for hundreds of publicly available signatures, and pairwise correlations used to create a relevance network. RESULTS/ANTICIPATED RESULTS: Using signatures of estrogen and p63, we recovered relevant experimental variables, and with the network approach, we recovered previously reported associations between disease states and/or drug treatments. DISCUSSION/SIGNIFICANCE OF IMPACT: openSESAME has the potential to illuminate “dark data” and discover novel relationships between drugs and diseases on the basis of common patterns of differential gene expression.

OBJECTIVES/SPECIFIC AIMS: To better understand host, viral and bacterial responses underlying disparate outcome. METHODS/STUDY POPULATION: We utilized metagenomic analysis of 559 genes, the NanoString nCounter Immunology Panel-Plus kit and FFPE mouse lungs from a published BSI time course. RESULTS/ANTICIPATED RESULTS: Results show an overall increased level of gene expression during BSIs associated with survival when compared to gene expression during peak viral titers. Early viral clearance and the presence of S. pyogenes in the lungs of TX98 infected lungs 24 hours after BSI was confirmed. Host responses tied to differences in early viral detection and clearance consisted of RIG-I, OAS, TLR3, TLR8 and TLR9. Key changes were noted in the expression of type I and II interferons, complement proteins, cytokines, chemokines, Fc receptors, scavenger receptors, the immunoproteasome and genes associated with T, B, Treg and NK cell activation. Interestingly, there was no significant increase in host antimicrobial peptides during BSIs associated with survival while CAMP and Nos2 were significantly increased 24hrs prior to death in lethal BSIs. DISCUSSION/SIGNIFICANCE OF IMPACT: To our knowledge this is the first side by side metagenomics study of influenza BSIs associated with death and survival. Results offer mechanistic insight into clinical outcomes.

OBJECTIVES/SPECIFIC AIMS: Pancreatic ductal adenocarcinoma (PDA) has a dismal 5-year survival rate of 9%, making this disease one of the deadliest human malignancies (https://seer.cancer.gov/). Primary barriers to the treatment of pancreatic cancer include extensive stromal interactions and sustained immune suppression. Aberrant Hedgehog (HH) pathway activity is a hallmark of pancreatic tumorigenesis. Tumor-derived HH ligands signal in a paracrine fashion to the surrounding stroma to influence tumor growth. Expression of HH ligands increases during PDA progression, and previous work has shown that genetic deletion of Sonic HH (Shh) from the epithelium of mice with pancreatic tumors results in increased Indian HH (Ihh) expression. This research aims to investigate the translational impact of changes in immune infiltration following deletion of IHH in a preclinical mouse model of pancreatic cancer. METHODS/STUDY POPULATION: Ihh was deleted in tumor cells lines (IhhKO) derived from a genetically engineered mouse model of pancreatic cancer (LSL-KrasG12D/+;LSL-TrpR270H;P48-Cre), using CRISPR/Cas-9 gene editing to assess the role of Ihh in the tumor microenvironment. The level of HH signaling was determined using tumor cell co-cultures with Gli1lacZ fibroblasts (derived from mice with a lacZ reporter allele knocked into the Gli1 locus), in which Beta Galactosidase activity serves as a readout for HH signaling. WT and IhhKO tumor cells were orthotopically transplanted into the pancreas of syngeneic C57BL/6 mice. Human pancreas samples were obtained from surgical resection of pancreatic adenocarcinoma, or fine needle biopsy procedure (FNB). Immune profiling of mouse and human pancreatic tumors was performed using Cytometry Time-of-Flight analysis (CyTOF), and tumor composition was analyzed by single-cell RNA sequencing (scRNA seq). In vitro cultures with pancreatic fibroblasts treated with either WT or IhhKO tumor cell conditioned media (CM) were cultured with bone-marrow derived macrophages to assess tumor crosstalk. RESULTS/ANTICIPATED RESULTS: Tumor cells lacking Ihh were generated through CRISPR/Cas-9 deletion, and this was confirmed by qRT-PCR. Co-culture of IhhKO tumor cells with Gli1lacZ fibroblasts results in decreased Gli1 expression both in vitro and in vivo. Immune profiling revealed that tumors lacking Ihh have significantly fewer tumor associated macrophages (CD11b+/F4/80+/CD206+), resulting in decreased presence of immunosuppressive factors such as arginase 1 and PDL1. Immune phenotyping of human pancreatic tissues revealed similar populations of immunosuppressive myeloid cells present in tumors. In vitro co-cultures demonstrated that, in the presence of bone-marrow derived macrophages, immunosuppressive IL-6 production was reduced in pancreatic fibroblasts cultured with IhhKO-CM, as compared to fibroblasts cultured with WT-CM, providing mechanistic insight into the in vivo phenotype observed. Further, scRNA seq analysis suggests that modulation of HH signaling in the tumor microenvironment alters chemokine and immunomodulatory signaling pathways driven by fibroblasts in the pancreatic tumor microenvironment. DISCUSSION/SIGNIFICANCE OF IMPACT: HH signaling in pancreatic fibroblasts contributes to the establishment of an immune suppressive environment in pancreatic cancer. Combining methods to target HH signaling and immune checkpoint therapy has translational potential in treating pancreatic cancer patients.

OBJECTIVES/GOALS: This project adopts a multifaceted approach to improving aquaculture management practices in Kenya’s Lake Victoria region by identifying fish pathogens, measuring algal toxin levels in commonly consumed fish, surveying fish farming practices, and educating the public. METHODS/STUDY POPULATION: Limited existing data on the state of floating cage culture in Kenya influenced our decision to begin this portion of the project with a brief literature review of potential Nile tilapia pathogens. Databases were screened for mention of disease in either wild or caged Nile tilapia, with emphasis given to those in Lake Victoria. Results were compiled into a spreadsheet and analyzed for frequently occurring pathogens. The next portion involved creating an interview style survey to assess current cage culture management practices in the region. Editing was done to ensure questions remained unbiased, non-leading, culturally sensitive, multilingual and relevant to the situation. Data went through a quality control screening and analysis was conducted through the R programming language. RESULTS/ANTICIPATED RESULTS: Beginning with mortality, of the 93 farms surveyed, data analysis revealed that there is a higher probability that farms will have a mortality of approximately 20%, over the course of a production cycle. For biosecurity and fish health practices, data shows that 97% of farms do not disinfect scooping nets or other fish handling materials when moving from one cage to another. During the 2022-2023 production cycle, 44% of farms experienced fish kills of over 50 fish. 73% of the 93 farms do not contact any organization when a fish kill occurs. In a qualitative answer, it also appears that many farm workers dispose of their dead fish within the lake, feed it to livestock or dogs, or eat it. Algae blooms have been experienced at 80% of the farms surveyed and 43% of farms say they have seen fish gasping at the surface for air. DISCUSSION/SIGNIFICANCE: While farms are implementing good management practices in the areas of cage design, stocking, and feeding practices, there is room for improvement in fish health, biosecurity, and managing algal blooms. The findings provide insight into the areas that should be considered when taking action to improve the welfare of the region.

OBJECTIVES/SPECIFIC AIMS: The knee injury osteoarthritis and outcomes survey (KOOS) is a commonly used instrument to measure patient-reported quality of life (QOL) post-ACLR. The purpose is to evaluate the psychometric properties of the QOL subscale of the KOOS. METHODS/STUDY POPULATION: Rasch analysis of KOOS QOL subscale from 39 individuals 1–2 years post ACLR was conducted. Measurement properties and model fit of the rating scale, items, and persons were evaluated. Relationship of item difficulties and person measures was evaluated using probability curves and item maps. Reliability indicators were also examined. RESULTS/ANTICIPATED RESULTS: All items demonstrated infit and outfit mean squares and standard z-scores. The majority of persons (n=38, 97.4%) demonstrated fit to the Rasch model. However, ceiling effects were noted (n=4, 10.26%), indicating some participants report higher QOL than is measurable. The mean person measure was 1.73 logits higher than the mean item measure: this sample is skewed toward higher QOL. Person reliability was adequate (0.67) and person separation was 1.42. Calculation of person strata revealed that the KOOS QOL separated participants into 2 strata. DISCUSSION/SIGNIFICANCE OF IMPACT: Although all items of the KOOS QOL fit the model, not all categories of the rating scale were used. Overall, this sample reported high QOL, which is to be expected given the time since ACLR. If participants with a broader range of time since ACLR were included, that the KOOS QOL could identify additional person strata.

OBJECTIVES/GOALS: Roughly 8% of children in the United States have a diagnosed food allergy (FA). The ubiquity of most food allergens increases the potential for accidental exposures. Clinical trials (CT) are used to test novel treatments for FA. This project will evaluate the influence of biopsychosocial factors on interest in CT participation for pediatric FA. METHODS/STUDY POPULATION: This project is subsumed under the FORWARD study (5R01AI130348-04), a multisite study currently underway at four pediatric FA clinics across the United States. Eligible participants include patients and families who meet the following criteria: 1) New clinic visit presenting for a possible FA complaint and/or has a physician diagnosis in a follow-up clinic visit; 2) child is between the age of 6-months and 12 years at intake visit; 3) are English speaking, and 4) no history of developmental disorders. Parents are asked to complete an intake survey, followed by a series of quarterly surveys administered via REDCap. A single variable from the intake survey queries interest in CT participation; quarterly surveys assess FA knowledge, attitudes, health beliefs, and management practices. RESULTS/ANTICIPATED RESULTS: To date, 890 families have completed the intake survey. Working hypotheses include: 1) parents of older children and children with a higher condition severity rating will report greater levels of interest in CT participation; 2) parents with greater FA knowledge, more health management beliefs that support action, and less FA-related anxiety, will report greater levels of interest in CT participation; 3) relative to White families, African American families will be less interested in participating; 4) families with >1 child with FA will report greater levels of interest in CT participation; 5) families who are uninsured, low-SES, and are unemployed will report lower levels of interest in CT participation; and 6) families with higher educational attainment will report lower levels of interest in CT participation. DISCUSSION/SIGNIFICANCE: This study will advance decision science, address existing disparities, and have far-reaching clinical implications. This novel approach will enhance our ability to predict who is at the greatest risk of anaphylaxis and help healthcare providers identify families who could benefit from experimental treatment options for pediatric FA.

OBJECTIVES/GOALS: Regionalized sepsis care could improve sepsis outcomes. There are no measures of sepsis capability to guide the identification of hospitals that can best serve sepsis patients. We derived Capability-Based (CB) scores from specific hospital characteristics and evaluated their performance as system predictors of mortality among adults with sepsis. METHODS/STUDY POPULATION: We used the 2018 State Inpatient Databases to identify 90051 adult sepsis encounters at 157 non-federal NY hospitals (derivation cohort), and 130,249 sepsis encounters at 220 hospitals in FL and MA (validation cohort). We used Principal Component Analysis to analyze to reduce 14 hospital-level resource use characteristics to 3 interpretable, linear data combinations (principal components (PC). We calculated CB scores for each hospital as a sum of standardized values for each component multiplied by the respective PC loading. We evaluated the correlation of sepsis volume and each CB score with hospital mortality and with outward sepsis transfer proportions. We fitted linear, nested, predictive models to compare the system predictive abilities of CB scores and sepsis volume in relation to hospital mortality. RESULTS/ANTICIPATED RESULTS: In the derivation cohort, 83963 (93.2%) patients were non-transferred, of which 20230 (24.1%) died. The mean (range) score was 0 (-3 - +5) with higher scores denoting more capable hospitals. Higher scores were weakly and inversely correlated (spearman’s [r]: - 0.28) with outward sepsis transfer proportions. Higher scores had weak but better positive correlation with hospital mortality (r: 0.33), than sepsis volume (r: 0.24). CB scores explained more variation in sepsis mortality (R2 = 0.24, P DISCUSSION/SIGNIFICANCE: Capability-based hospital scores account for three times more variation in sepsis mortality than sepsis volume and outperform sepsis volume as a system predictor of mortality. With further refinement and validation, these scores may find utility for improving system-based approaches to sepsis care.

OBJECTIVES/SPECIFIC AIMS: Long interspersed element-1s (L1s) are autonomous, mobile elements that are able to copy and insert themselves throughout the genome with their own reverse transcriptase and endonuclease. These elements make up 17% of the human genome with over 500,000 copies, though the vast majority of L1s are defective with only a few dozen potentially responsible for L1 activity. Full-length L1s have the potential to contribute to mutagenesis through random insertion and increased genetic instability. Here we set out to study L1 expression at the specific loci level in bone marrow-derived stem cells (bmSCs) and adipose-derived stem cells (ASCs) and compare the levels of expression from ASCs from donor patients who are young and lean, obese, and old. Our hypothesis is that L1-related damage may contribute to mutation and inflammation that alters the function of these stem cells throughout the life of an individual. METHODS/STUDY POPULATION: ASCs and bmSCs were isolated from patient donors. The following samples were collected: ASCs from 3 young (under the age of 59) and lean (BMI<30) patients, ASCs from 3 older patients (over the age of 59), ASCs from 3 patients with BMI>30, and bmSCs from 4 young and lean patients. Cytoplasmic RNA from the cell populations was isolated and sequenced by RNA-Seq from the cell populations. Using our recently developed bioinformatics pipeline, we set out to quantify L1 expression and identify the few culprit L1s at specific loci that are actively transcribing to RNA in the ASC and bmSC samples. RESULTS/ANTICIPATED RESULTS: Here we provide proof of concept with the application of this novel method in characterizing full-length expressed L1s at the specific loci level in ASCs and bmSCs. We identified L1 loci that are commonly expressed in these cell types and observed an increase in L1 expression in the obese and old ASC cells compared with the young, lean ASCs and bmSCs. DISCUSSION/SIGNIFICANCE OF IMPACT: ASCs hold the promise of broad application in the biomedical field including regenerative treatment. There are reports that ASCs cultivated from older and obese donors are less effective in regenerative treatments. By demonstrating an increased expression of the mutagenic L1 element in ASCs from obese and old donors, this study provides further evidence suggesting the preferable use of ASCs from young and lean donors for regenerative therapies. These studies will also help us to understand the potential contribution of L1 expression to loss of stem cell function during the aging process.

ABSTRACT IMPACT: This work will lead to improved efficacy of immunotherapy directly impacting the survival of patients with hard to treat cancers. OBJECTIVES/GOALS: Immune checkpoint inhibitors (ICI) are most effective against ‘hot’ tumors highly infiltrated with cytotoxic T lymphocytes (CTLs) but have not worked well in poorly infiltrated ‘cold’ tumors. Thus, we are working to achieve a pretreatment regimen that will create a favorable immune profile allowing more effective ?PD-1 therapy. METHODS/STUDY POPULATION: BALB/c or C57BL/6 mice were inoculated with CRC murine cells CT26 or MC38, respectively. Mice were inoculated by two injection types: subcutaneous (SC), for systemic therapy, or intraperitoneal (IP), for local therapy. Tumor-bearing mice were given a two dose course of CKM consisting of IFN-? and rintatolimod via IP injection. Following CKM administration, mice were treated with three doses of ?PD-1 via IP injection. Mice were monitored for the kinetics of tumor growth and survival following treatment. The tumor microenvironment of treated mice was analyzed for production of chemokines, inflammatory cytokines and immune cell infiltration. RESULTS/ANTICIPATED RESULTS: CKM consisting of combination IFN-? and rintatolimod, but neither monotherapy alone, sensitized murine CRC tumors to subsequent ?PD-1 treatment. In both CT26 and MC38 tumor-bearing mice, tumor growth was hindered by CKM plus ?PD-1 treatment, independently on the route of treatment (local or systemic). Mice which experienced complete tumor regression were protected from re-challenge with a dose of tumor cells double that of the initial inoculation. Sensitizing tumors to ?PD-1 did not require intratumoral CKM administration and was observed with systemic application at distant sites. In accordance with these observations we expect that systemic CKM will induce strong increases of total and tumor-specific CTL counts in the tumor tissues as measured by both PCR and flow cytometry. DISCUSSION/SIGNIFICANCE OF FINDINGS: CKM sensitizing cold tumors to ?PD-1 indicates that intratumoral CTLs are an important factor dictating therapeutic effectiveness, independent of other factors such as tumor mutational load. The benefit of the sequential short-term CKM followed by routine ?PD-1 make this strategy feasible for rapid inclusion of into routine immunotherapy plans.

OBJECTIVES/GOALS: The main objectives are to obtain a preliminary profile of the adult Puerto Rican patient with hearing impairment and to identify the factors, variables and barriers that thess patients face accessing intervention and adscribing to it. METHODS/STUDY POPULATION: Adults between the ages of 21 and 64 years old were surveyed using a questionnaire with items guided to obtain information regarding their socio-demographic and health characteristics and the variables associated to treatment access and adherence to the intervention plan. A descriptive approach will be used to create the sample profile and an age stratified analysis will be used to interpret the empirical data. The identified variables associated to treatment access and adherence will be identified and analyzed to study if there is a possible geographic zone and socio-economical association. RESULTS/ANTICIPATED RESULTS: Preliminary results suggest that regardless of the subject’s age and degree of hearing loss their socio-economical strata is a decisive factor in treatment adherence as well as the lack of medical insurance coverage for therapy, hearing prosthesis and assistive technology for the hearing-impaired. Access to service was found to be a barrier associated to the subjecs geographical place of origin. DISCUSSION/SIGNIFICANCE: Research findings suggest that there is an association between the socio-economical status of the Puerto Rican hearing impaired patient, the lack of medical coverage and the level of treatment adherence. Patients from a lower socio-economical status and remote towns exhibited less adherence which points to a health disparity for this population.

OBJECTIVES/SPECIFIC AIMS: Translational science supports the continuum of activities from early-stage bench research to implementation of discoveries for better and faster treatments to more patients. Past studies have attempted to clarify our understanding of the spectrum of translational research by categorizing the activities into stages ranging from T0 to T4 using explanatory definitions. Unfortunately, this approach is often vague and relies on a process of manual classification and binning of research publications into predetermined categories. This study aims to provide a big-picture analysis of clinical and translational science (CTS) based on an in-depth analysis of the entire corpus of publications resulting from research funded by Clinical and Translational Science Awards (CTSA) U54 awards (through 2016). METHODS/STUDY POPULATION: We harvested bibliographic metadata from all papers that cited any of the U54 award numbers since the inception of the CTSA program to the most recent award announcement. Natural language processing techniques were used to create term co-occurrence networks based on English-language textual data. Relevant and nonrelevant terms were distinguished algorithmically and processed accordingly to provide the clustered visualization. RESULTS/ANTICIPATED RESULTS: With this approach, we uncovered 6 natural clustered areas of emphasis of published CTS research, the evolution of specific concepts through time, and gained a better understanding of their relative impact as demonstrated by citations. We performed additional analyses including discipline-specific impact assessment; identification of categories of excellence relating to both productivity and citations; characteristics of collaborative networks such as organizational, industry, and international collaborations and network dynamics; and resulting global impact of the CTSA program. DISCUSSION/SIGNIFICANCE OF IMPACT: Ultimately we gained a clearer understanding of the CTSA program, its evolution through scholarly publications, and key areas of impact of the program using computational, data-driven evaluation methods.

OBJECTIVES/GOALS: Neoantigen vaccine immunotherapies have shown promise in clinical trials, but identifying which peptides to include in a vaccine remains a challenge. We aim to establish that molecular structural features can help predict which neoantigens to target to achieve tumor regression. METHODS/STUDY POPULATION: Proteins were prepared by recombinant expression in E. coli followed by in vitro refolding. Correctly folded proteins were purified by chromatography. Affinities of protein-protein interactions were measured by surface plasmon resonance (SPR) and thermal stabilities of proteins were determined by differential scanning fluorimetry. All experiments were performed at least in triplicate. Protein crystals were obtained by hanging drop vapor diffusion. The protein crystal structures were solved by molecular replacement and underwent several rounds of automated refinement. Molecular dynamics simulations were performed using the AMBER molecular dynamics package. RESULTS/ANTICIPATED RESULTS: A T cell receptor (TCR) expressed by tumor-infiltrating T cells exhibited a 20-fold stronger binding affinity to the neoantigen peptide compared to the self-peptide. X-ray crystal structures of the peptides with the major histocompatibility complex (MHC) protein demonstrated that a non-mutated residue in the peptide samples different positions with the mutation. The difference in conformations of the non-mutated residue was supported by molecular dynamics simulations. Crystal structures of the TCR engaging both peptide/MHCs suggested that the conformation favored by the mutant peptide was crucial for TCR binding. The TCR bound the neoantigen/MHC with faster binding kinetics. DISCUSSION/SIGNIFICANCE OF IMPACT: Our results suggest that the mutation impacts the conformation of another residue in the peptide, and this alteration allows for more favorable T cell receptor binding to the neoantigen. This highlights the potential of non-mutated residues in contributing to neoantigen recognition.

Objectives/Goals: Opioid use disorder (OUD) in pregnancy and its implications on the maternal-fetal interface has been relatively understudied. Here, we aimed to uncover the impact of maternal OUD on placental structure, function, and inflammatory responses and further stratified our findings by maternal hepatitis C (HCV) infection. Methods/Study Population: To address this knowledge gap, we collected placental tissue from healthy pregnancies (control) and those with opioid use disorder with and without maternal HCV infection. First, placental development was assessed by gross and histological examination of the placenta. Immune cells were then isolated from decidua (maternal) and chorionic villous (fetal) placental tissues, and the frequency and phenotype of immune subsets were determined by flow cytometry. Markers of inflammation, placental perfusion, growth factors, tissue remodeling, and vascularization were measured in placental tissue homogenate by multiplex Luminex assay. Finally, gene expression alterations in placental architecture were assessed by Visium spatial transcriptomics, integrating transcriptomic data with spatial information. Results/Anticipated Results: Our results indicate that maternal OUD impairs placental perfusion/development and is accompanied by increased markers of inflammation in the decidua (IL-1Ra, IL-2, IL-18, IP-10, MIP-1β, and TNFα) and villous (IL-6 and IL-8). Furthermore, markers of angiogenesis and placental development are altered in the decidua, including increased EGF and IL-6Ra, but decreased FLT-1, FLT-4, and bFGF. The abundance of placental immune cells is varied with OUD/HCV, including decreased frequencies of decidual macrophages and NK cells, critical for blood supply to the fetus, and increased abundance of infiltrating maternal macrophages in fetal chorionic villous. Finally, spatial transcriptomics revealed aberrant infiltration of activated immune cells and modified processes associated with inflammation and angiogenesis. Discussion/Significance of Impact: Altogether, these findings suggest a profound impact of maternal OUD with and without maternal HCV infection on the structure, function, and immune landscape of the maternal–fetal interface that can alter fetal development and maturation.

OBJECTIVES/GOALS: Sirtuin 3 (Sirt3), a mitochondrial NAD+-dependent deacetylase, is decreased in diverse models of kidney disease, and Sirt3 activation prevents disease progression in many of those models. We are investigating if pharmacological activation of Sirt3 ameliorates kidney disease in a mouse model of Alport syndrome. METHODS/STUDY POPULATION: Alport syndrome is a hereditary orphan disease arising from a defect in the collagen IV α3α4α5 heterotrimer, a component of the glomerular basement membrane. Male and female Col4a3tm1Dec knockout mice and wild type controls on the 129X1/SvJ background were harvested at 9–10 weeks of age. Serum and urine were collected prior to euthanasia; renal pathology was assessed by histology; and renal cortical mRNA and protein levels were assessed by qRT-PCR and western blot, respectively. Studies are ongoing using dietary administration of a Sirt3 activator, nicotinamide riboside (500 mg/kg/day), in Col4a3 transgenic mice on both the 129X1/SvJ and C57BL/6J backgrounds. RESULTS/ANTICIPATED RESULTS: Col4a3−/− mice have elevated BUN (P < 0.0001, both sexes), serum creatinine (P < 0.001, male; P < 0.0001, female), and urinary albumin-to-creatinine ratio (P < 0.0001, both sexes) compared to Col4a3+/+ controls. On histology, Col4a3−/− mice have extensive renal fibrosis compared to Col4a3+/+ controls. Sirt3 expression is decreased in the renal cortices of Col4a3−/− mice at the mRNA (P < 0.0001, male; trend, P = 0.07, female) and protein levels (P < 0.05, male; P < 0.001, female) compared to Col4a3+/+ controls. All experiments had 5–9 mice per group. Results of the prevention study with nicotinamide riboside, a Sirt3 activator, are unknown at the time of abstract submission. DISCUSSION/SIGNIFICANCE OF IMPACT: Col4a3−/− mice have severe renal impairment and decreased renal cortical expression of Sirt3 at the mRNA and protein levels compared to Col4a3+/+ controls. However, it is unknown at this time if pharmacologically activating Sirt3 prevents this renal decline.

OBJECTIVES/GOALS: Research on mild cognitive impairment (MCI) risk factors in type 2 diabetes mellitus (T2DM) is scarce; however, MCI is a concern in T2DM as it can adversely impact self-care behaviors. This study aims to estimate the proportion of MCI and describe its sociodemographic, clinical, psychosocial, and lifestyle characteristics in older adults with T2DM. METHODS/STUDY POPULATION: Cross-sectional pilot study of 60 adults (aged ≥50yrs) with a diagnosis of T2DM will be recruited at a diabetes center located in San Juan, Puerto Rico. Data on sociodemographic, clinical, psychosocial (depressive symptoms and social support), and lifestyle characteristics related to diabetes self-management (diabetes self-care activities and activities of daily living) will be collected through face-to-face interviews using validated questionnaires. Our primary outcome will be MCI assessed via the Spanish-language version of the Montreal Cognitive Assessment (MoCA-S). The proportion of adults with MCI (MoCA-S score<26) will be estimated, and the sociodemographic, lifestyle, psychosocial, and clinical characteristics of older adults will be compared across MCI status using bivariate analysis. RESULTS/ANTICIPATED RESULTS: Expected results include an estimate of the proportion of MCI among older adults with T2DM, which we hypothesize will be higher in our study than in Puerto Rico’s older adult population (previously reported as 17%). Additionally, we will describe the sociodemographic, clinical, psychosocial, and lifestyle characteristics that significantly differ by MCI status in older adults with T2DM. We expect that those with MCI will be more likely to be females, have lower education and annual income, longer time with a diabetes diagnosis, worse psychosocial profiles (higher levels of depressive symptoms and lower levels of social support), and worse lifestyle profiles (poorer glycemic control and lower activities of daily living score) than those without MCI. DISCUSSION/SIGNIFICANCE: This pilot study is a first step to understanding MCI among older adults with T2DM in Puerto Rico, a Hispanic population with a higher prevalence of T2DM than their US non-Hispanic White counterparts. Its findings can guide the design and implementation of a larger epidemiological study aimed at understanding MCI risk factors among adults with T2DM.

ABSTRACT IMPACT: This study advances our understanding of potentially key drivers in the early formation of pancreatic cancer, a disease with few treatment options and poor patient outcomes. OBJECTIVES/GOALS: Patients diagnosed with pancreatic ductal adenocarcinoma (PDAC) have a 5-year survival rate of ˜9%. A key driver of poor patient outcomes is late-stage diagnosis. A better understanding of PDAC onset is needed. This study was developed to understand how extracellular vesicles may be involved in the early formation of PDAC. METHODS/STUDY POPULATION: Extracellular vesicles (EVs) were isolated from several human PDAC and normal pancreatic cell lines, using ultracentrifugation with filtration or size exclusion chromatography. We next treated normal pancreatic cell lines with cancer cell EVs (cEVs). Next generation sequencing was used to measure global gene expression changes after treatment. Validations were performed using qPCR and luciferase activity assays. Multi-omics characterization of EVs was accomplished using mass spectrometry based proteomics, metabolomics and lipidomics analysis. RESULTS/ANTICIPATED RESULTS: We found that normal cells upregulated a variety of stress response pathways in response to cEVs. Lipid synthesis was also severely downregulated in these cells. We further validated activation of the unfolded protein response (UPR) in normal cells treated with cEVs. Multi-omics characterization of cEVs identified several enriched proteins, lipids and metabolites which may play a role in the activation of the UPR. DISCUSSION/SIGNIFICANCE OF FINDINGS: Our results indicate that cEVs induce stress, and in particular the UPR, in normal pancreatic cells. Long-term UPR can impact a variety of cancer hallmarks. The UPR can mediate progression of pancreatic intraepithelial neoplasia (PanIN) to PDAC. Our results highlight a potential role for cEVs to alter the function of normal cells, aiding disease onset.

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.