OBJECTIVES/GOALS: Specific Aim 1 To examine sex distribution of psoas cross sectional area (CSA) on CT imaging in a cohort of trauma patients age 55 and older. We will use three methods of assessing psoas CSA: psoas CSA averaged between left and right, average psoas CSA adjusted for height, and average psoas CSA adjusted for body surface area (psoas index). Specific Aim 2 Use multivariable logistic regression prediction modeling to compare the 3 methods of CT psoas muscle measurement widely used in the literature in their ability to predict a composite of in-hospital morbidity and mortality in trauma patients ages 55 and older. METHODS/STUDY POPULATION: The Maine Medical Center Trauma Registry is maintained by the Trauma Surgery Service at Maine Medical Center in Portland, Maine, the only Level-1 trauma center in the state. After receiving approval from the Institutional Review Board of Maine Medical Center for this retrospective cohort study, we queried the Maine Medical Center Trauma Registry for all adults 55 years and older who underwent evaluation by the Trauma Service between January 1, 2015 and January 1, 2019. In the case of multiple admissions within the study time period, only a patient’s index admission was used. MaineHealth IMPACS imaging software was used to measure bilateral psoas CSA on each patient CT. The Maine Medical Center electronic medical record was queried for additional clinical information including the ICD codes associated with each patient encounter. Data analysis was performed using R statistical software (R project, Vienna, Austria). Data is reported as median + IQR for CSA measurements. The agreement between the three methods of quantifying psoas CSA was evaluated using Pearson correlation (R package “stats”). Inter-rater reliability of psoas muscle measurements was evaluated using intra-class correlation (R package “irr”). Prediction models for the composite outcome of in-hospital morbidity and mortality were constructed using multivariable logistic regression. Bootstrapping was used for internal validation and shrinkage to avoid overfitting. Models including psoas CSA were compared to a baseline model without psoas CSA to evaluated incremental added predictive ability. RESULTS/ANTICIPATED RESULTS: This cohort provides a basis for examining the population distribution of psoas CSA in adults 55 years and older. IN addition to a high level of agreement between the three methods of measuring psoas CSA (Spearman coefficient > 0.9), there was also high level of inter rater reliability in psoas muscle assessment (intraclass correlation 0.9). We anticipate that psoas CSA adjusted for body surface area will add the most incremental predictive ability to a model predicting in-hospital morbidity and mortality. DISCUSSION/SIGNIFICANCE OF IMPACT: Given the heterogeneity of health status amongst elderly trauma patients, a major challenge lies in the rapid objective identification of those elderly trauma patients who are frail. Due to the limitations in current frailty measures, there has been a surge of interest in surrogate markers of frailty, such as muscle mass, as predictive factors of poor outcomes after trauma.Several studies have found that sarcopenia is associated with post injury morbidity and mortality. Estimates of the prevalence of sarcopenia among trauma patients vary across studies due to differences in definition and sample characteristics. In order to appropriately categorize patients as sarcopenic, the population distribution of psoas CSA on CT must be established. The psoas measurement that best correlates with outcomes has yet to be determined, and it is unclear which measurement should be implemented in usual practice. Our main objective is to improve the outcomes of sarcopenic patients hospitalized with trauma by implementing in the future patient-centered interventions which will account for sarcopenia.

OBJECTIVES/GOALS: Selinexor is a novel XPO1 inhibitor that blocks nuclear export, thus impairing DNA repair and causing apoptosis. Our goal was to conduct preclinical and clinical studies to test our hypothesis that selinexor’s efficacy is boosted by priming with temozolomide and is associated with a tissue biomarker. METHODS/STUDY POPULATION: We leveraged a team science approach through the NCI Cancer Therapy Evaluation Program (CTEP) to design preclinical experiments, develop a novel RNAseq analysis pipeline, and use pre-existing clinical experience to open an early phase clinical trial for recurrent glioblastoma. Team members included a CTEP medical officer, cancer biologist, pharmacist, industry scientist, translational scientist, and early career clinician scientist mentored by an expert clinician scientist. Based on preclinical results, participants in the clinical trial experimental arm will receive sequential temozolomide 150mg/m2 on days 1-5 and a starting dose of selinexor 60mg on days 8 and 15 of a 28-day cycle. Participants in the control arm will receive monotherapy temozolomide. RESULTS/ANTICIPATED RESULTS: Sequential treatment of U87 cells and intracranial xenografts had superior DNA damage (É£H2A.X, cleaved PARP) and overall survival compared to combination or single-agent (HR 0.25 [95% CI, 0.07-0.84]; p=0.01, log-rank). We used the top-scoring gene pair method to identify an RNAseq signature associated with response to selinexor. We then designed a trial for first recurrent MGMT methylated glioblastoma. Primary objectives are safety and preliminary efficacy. Secondary objectives are overall response rate, efficacy, and validation of a molecular signature. Phase 1 dose finding (n=12) will be followed by a randomized phase 2 (n=72); using proportional hazards regression, RHR 0.5 with p DISCUSSION/SIGNIFICANCE: The NCI CTEP Project Team employs team science as a framework to successfully develop multidisciplinary collaborations, build investigator trial experience, and lead the way to future research opportunities. Our trial addresses a significant unmet need to offer novel therapies and molecular biomarkers in glioblastoma.

ABSTRACT IMPACT: Being explicit about the prevention of falls throughout an older adults’ episode of care may further help reinforce the role of physical therapy providers in falls prevention and improve dissemination of this knowledge. OBJECTIVES/GOALS: The purpose of this study was to determine older adults’ awareness of and perspectives about the role of physical therapy providers for falls prevention and determine potential barriers and facilitators to utilization of preventive rehabilitation services METHODS/STUDY POPULATION: We used a qualitative descriptive phenomenological approach to emphasize participants’ perceptions and lived experiences. Four focus groups were conducted with 27 community-dwelling older adults (average age = 78 years). Focus groups were recorded, transcribed, condensed, and coded using thematic analysis. RESULTS/ANTICIPATED RESULTS: Surveys indicated 37% of participants experienced a fall in the last year and 26% reported suffering an injury. Four main themes and six subthemes surrounding older adults’ perceptions of physical therapy providers’ roles for falls prevention emerged: (1) Awareness of Falls Prevention (subthemes: I Don’t Think About It, I Am More Careful); (2) Being Able to Get Up from the Floor; (3) Limited Knowledge about the Role of Physical Therapy Providers in Falls Prevention (subtheme: Physical Therapy Services are for After a Fall, Surgery, or for a Specific Problem); and 4). Barriers to Participating in Preventive Physical Therapy Services (subthemes: Perceived Need and Costs, Access Requires a Doctor’s Prescription). DISCUSSION/SIGNIFICANCE OF FINDINGS: Older adults lack awareness about the role of physical therapy services in falls prevention, perceiving services are only to treat a specific problem or after a fall. Physical therapists should be explicit about the role of physical therapy in falls prevention for all older adults undergoing rehabilitation, regardless of the reason.

Objectives/Goals: Novel therapeutics to control Staphylococcus aureus (S. aureus) infections are needed for people with cystic fibrosis (CF, PwCF). In this study, our objective is to determine if the pharmacologic MEK1/2 inhibitor compound ATR-002 can restrict the growth of S. aureus clinical isolates and modulate infection in a murine model of S. aureus infection. Methods/Study Population: To evaluate the anti-inflammatory effects of ATR-002 on human macrophages, cells were stimulated with TLR2 agonists FSL1 or Pam3CSK4 with a dose range of ATR-002, and secretion of proinflammatory cytokines were measured by ELISA. To determine the direct antibacterial effect of ATR-002, minimum inhibitory concentration (MIC) assays were performed with the community-associated methicillin-resistant S. aureus strain USA300 and 40 S. aureus isolates from PwCF. To validate our results in vivo, mice were provided i.p. treatment with either vehicle, the MEK1/2 inhibitor compound PD0325901 (20 mg/kg), or ATR-002 (10 mg/kg) prior to intranasal infection with 1x10^7 CFU of USA300. Bacterial burdens at 4- and 24-hour post-infection (p.i.) and inflammatory cell recruitment at 24 hours p.i. were quantified. Results/Anticipated Results: Macrophages treated with ATR-002 exhibited a dose-dependent decrease in secretion of proinflammatory cytokines TNF and IL-8 following TLR stimulation. Our studies identified that ATR-002, but not PD0325901 or other MEK1/2 inhibitors, had direct antibacterial effects, and ATR-002 had an MIC range of 8 to above 64 ug/mL on CF S. aureus isolates. In the murine pulmonary infection model, delivery of ATR-002 and PD0325901 significantly prevented infection-induced loss of body mass and decreased neutrophil inflammation. However, when bacterial burdens were quantified 4-hours p.i., only ATR-002 treatment reduced lung bacterial burden compared to vehicle or PD0325901-treated groups. Discussion/Significance of Impact: These results are the first demonstration of the in vivo anti-inflammatory and antibacterial effects of ATR-002. Our results further demonstrate that ATR-002 exhibits direct antibacterial effects across a collection of clinical isolates of S. aureus. Future studies will continue to investigate the therapeutic potential of ATR-002.

OBJECTIVES/GOALS: The objective of our research is to define unique molecular and immune markers in benign breast tissue to better identify women at risk of node-positive breast cancer (BC). The goal of the work is to improve individualized risk assessment, to guide targeted prevention and screening recommendations, and to reduce disease incidence and mortality. METHODS/STUDY POPULATION: From the Mayo Clinic’s Benign Breast Disease (BBD) cohort, we matched women who developed node-positive breast cancer after a BBD biopsy (cases; n=42) with women who remained cancer-free (controls; n=37), considering patient age and biopsy date. We used NanoString gene expression profiling to identify differentially expressed genes (DEGs) between cases and controls. We optimized a multiplex immunofluorescence (mIF) approach to simultaneously detect multiple markers within single FFPE tissue slides to correlate cells expressing DEGs in relation to innate and adaptive immune effectors. We used tissue segmentation, cell phenotyping, and spatial relationships to define molecular and immune differences between cases and controls. RESULTS/ANTICIPATED RESULTS: We discovered higher gene expression levels of IRF8 (interferon regulatory factor 8, a factor involved in immune cell differentiation) in controls as compared to cases (p = 0.0024) and found that IRF8 expression is also associated with longer cancer onset times among cases (p = 0.0012). Our pilot mIF experiments revealed higher frequencies of CD4+, CD8+, CD68+, CD20+ and CD11c+ cells in controls compared to cases. We predict that higher IRF8 expression and increased frequencies of immune cells in BBD biopsies indicate a proactive immune environment that may act to prevent cancer development. Furthermore, we predict that our analyses of the spatial localization of these markers by mIF may offer further predictive insight. DISCUSSION/SIGNIFICANCE: Deciphering the relationship between immune alterations in BBD and risk of node positive BC has the potential to improve individualized risk prediction. These insights will foster improved surveillance and informed screening and prevention, ultimately reducing BC incidence and mortality.

OBJECTIVES/GOALS: The goal of U-LINK is to bring together diverse scholars from multiple disciplines to address complex and challenging problems in healthcare, climate change, social equity, and community, through innovative team science, and aligned with the University of Miami’s strategic plans. METHODS/STUDY POPULATION: The U-LINK program has supported developmental and implementation projects through a competitive selection process. Developmental funding was intended for teams to develop and refine ideas and to become established as an effective team. Additional funding was provided to teams to advance their projects by conducting data collection and feasibility testing. In addition, U-LINK has supported fellowship for pre-doctoral and affiliated doctoral trainees. Team science training was provided to all teams through didactic lectures and hands-on training. Teams were tracked longitudinally by using surveys and bibliometrics to measure success and impact including scholarly output and follow on funding. Network analysis was performed to analyze research collaboration networks before and after ULINK funding. RESULTS/ANTICIPATED RESULTS: U-LINK has funded pilot programs and initial phases for 57 projects and 13 fellowships in the last three years. Over 400 individuals on teams from 16 schools/academic units collaborated on these projects on topics such as resilience, climate change, social equity and societal challenges, health, and impact of recent legislation on LGBTQ+ community. While data collection and analysis are ongoing, initial results show successful outcomes from U-LINK projects including publications and $29.5m in follow-on external funding. We anticipate network analysis to demonstrate increased and continued multi-disciplinary collaborations among U-LINK teams through co-authorship networks and increase in collaborative grants being submitted and/or funded. DISCUSSION/SIGNIFICANCE: The University of Miami’s U-LINK program has demonstrated success in forming interdisciplinary teams that have produced real-world solutions to complex problems by harnessing the inherent diversity and strength across UM’s programs.

OBJECTIVES/GOALS: * Patients with skin of color (SOC) are disproportionately affected by systemic lupus erythematosus (SLE) and cutaneous lupus erythematosus (CLE). In this study, we aim to address this disparity and characterize the real-world efficacy and tolerability of anifrolumab in CLE patients using validated disease activity instruments. METHODS/STUDY POPULATION: This single-center, prospective observational cohort study includes SLE patients with severe or refractory CLE who have received ≥ 1 dose of anifrolumab. Cutaneous disease activity is assessed periodically at 2, 6, 9, 12, and 18 months using the Cutaneous Lupus Disease Area and Severity Index (CLASI). Adverse events and concurrent treatments are also routinely evaluated. To date, 22 patients have been enrolled, with 6-month follow-up data available for 15. At the time of anifrolumab initiation, 95% of participants had discoid LE (DLE), 60% had mucosal DLE, and 13% had subacute CLE. Nine patients identified as SOC, two as White, and four did not report race/ethnicity. RESULTS/ANTICIPATED RESULTS: A Friedman test showed statistically significant changes over time in CLASI activity score (CLASI-A) (χ2(2) =20, p<0.0001) (Figure 1) and CLASI damage score (CLASI-D) (χ2(2) =9.5789, p=0.0083) (Figure. To estimate effect sizes, we employed linear mixed models, which demonstrated statistically significant reductions in the CLASI-A score from baseline by an average of 14 points at 2 months (p<0.001) and 18 points at 6 months (p<0.001); notably, a reduction in CLASI-A of 4 is considered clinically meaningful. At 2 months, 20% of patients experienced a 50% or more reduction in CLASI, which increased to 60% of patients at 6 months. Patients on systemic corticosteroids could taper off. Adverse events were minimal and did not lead to treatment discontinuation. Fig. 1:[blob:https://acts.slayte.com/045319b4-7272-4351-a771-78ba9ee57f5c] Fig. 2:[blob:https://acts.slayte.com/67df7653-0cd8-4e8e-a3e1-d5c565b19dce] DISCUSSION/SIGNIFICANCE: As SOC patients with CLE have significant potential for permanent pigmentary alternations, early treatment is imperative. Effective treatments for refractory CLE are elusive. Our study represents the largest single-center cohort of CLE patients treated with anifrolumab and suggests that it is a promising therapeutic option for patients with SOC.

OBJECTIVES/GOALS: This study aimed to investigate the mechanistic effects of the omega-6-derived eicosanoid 12-HETrE on platelets of cardiovascular patients at risk for a recurrent cardiovascular event triggered by thrombosis. 12-HETrE negatively regulates platelet reactivity through binding to the prostacyclin receptor in platelets. METHODS/STUDY POPULATION: Healthy donors were recruited from the Ann Arbor community and the University of Michigan Medicine Center. Cardiovascular patients with elevated cardiovascular risk were recruited from the Cardiac Catheterization Laboratory at Michigan Medicine Hospital. All subjects were recruited under study protocols approved by the University of Michigan IRB. Healthy donors were matched with the cardiovascular patients regarding age, sex, race, and BMI. Whole blood was collected via venipuncture into vacutainers containing sodium citrate. Platelets were isolated via serial centrifugation and treated ex vivo with vehicle control, 12-HETrE, or Iloprost. RESULTS/ANTICIPATED RESULTS: Based on our previous studies, we chose to treat platelets ex vivo with 25uM of 12-HETrE for 10 minutes. Using platelets of healthy donors, we have shown that treatment with 25uM of 12-HETrE for 10 minutes inhibited platelet aggregation and activation, and activated protein kinase A, suggesting activation of the prostacyclin receptor. We conducted a preliminary study to demonstrate that ex vivo treatment of 12-HETrE regulated signaling pathways in platelets such as cell-to-cell interaction, platelet activation and cytoskeleton rearrangements. In this study, we have demonstrated that treatment with 12-HETrE regulated receptors and intraplatelet proteins in platelets of cardiovascular patients. Furthermore, these proteins are involved in critical pathways in the platelet. DISCUSSION/SIGNIFICANCE: Dual antiplatelet therapy has significantly decreased mortality due to thrombotic events. However, cardiovascular events triggered by thrombosis persist as the leading cause of death in the US. This study may uncover key regulators to be targeted for the long-term goal of providing additional protection to reduce future incidence of thrombosis.

OBJECTIVES/SPECIFIC AIMS: Helping researchers assess and effectively translate innovations into healthcare improvements is a complex process (Terry et. al., 2013). The Clinical Translational Science Awards (CTSA)—supported by the National Institute of Health (NIH) under the auspices of the National Center for Advancing Translational Sciences (NCATS)— provide the resources and support needed to strengthen our nation’s clinical and translational research (CTR) enterprise. In 2008, Stanford University was awarded a CTSA from the NIH, establishing Spectrum (the Stanford Center for Clinical and Translational Research and Education). Under the Spectrum umbrella, the Byers Center for Biodesign manages the MedTech Pilot Program with the goal of translating discoveries into novel health technologies that address important unmet health needs. The MedTech Pilot Program is an innovative funding mechanism that seeks to (1) stimulate clinical translational research, (2) help promising projects bridge the gap between the bench and the patients’ bedside, and (3) encourage collaborative, transdisciplinary work. Specifically, the Pilot Program offers up to $50,000 to support projects involving medical devices and mobile technologies used for (1) therapeutic applications and (2) device-based patient-specific (or POC) diagnostic applications. This analysis of the MedTech Pilot Program will: 1) describe the Program’s structure and process; 2) highlight the intensive, hands-on mentorship and practical guidance awardees receive that enables them to more efficiently and effectively advance their projects toward patient care; and 3) characterize the progress of the 36 funded projects. METHODS/STUDY POPULATION: Key elements of the Pilot Program’s infrastructure and mentoring processes as they relate to project outcomes were identified. Additionally, outcomes data were collected from two sources: (1) annual survey of Pilot Awardees and (2) publicly available information relevant to the pilot projects. RESULTS/ANTICIPATED RESULTS: The Pilot Program’s framework and infrastructure has supported a diverse group of transdisciplinary projects. These projects were evaluated using both traditional and non-traditional metrics (e.g., patents, startups, publications). The initial investment of $1.5 million to fund 36 projects has led to over $88 million dollars in additional funding. Additionally, taking full advantage of the expertise in Silicon Valley, strong mentorship has helped advance projects along the clinical and translational path. DISCUSSION/SIGNIFICANCE OF IMPACT: The Pilot Program has benefited Stanford innovators and researchers by providing seed funding to help promising projects bridge the gap between the bench and the bedside. The intensive, hands-on mentorship, early pilot funding, and practical guidance pilot awardees receive effectively help translate their technologies into patient care.

Objectives/Goals: People with insulin-treated diabetes face hypoglycemia risk due to imperfect insulin replacement and impaired counterregulation. We identified the dopamine antagonist, metoclopramide, as a potential treatment. Hypothesis: Treatment with metoclopramide will prevent the development of impaired counterregulatory response to hypoglycemia. Methods/Study Population: In a pre-clinical model, diabetes was induced in 10-week-old Sprague-Dawley rats with streptozotocin (STZ, 65 mg/kg IP). Rats were divided into three groups: 1) diabetic controls (STZ+RS, n = 6), 2) recurrent hypoglycemia (STZ+RH, n = 7), and 3) recurrent hypoglycemia + metoclopramide (STZ+RH+MET, 3 mg/kg IP, n = 7). After 3 days, all rats underwent a hyperinsulinemic (50 mU/kg/min) and hypoglycemic (~45 mg/dl) clamp. In the clinical trial, adults with Type 1 diabetes (age 20–60, ≥5 years duration) were enrolled in a phase II, double-blinded, placebo-controlled trial. Awareness status was assessed via Gold score, and subjects maintained drug regimens and underwent two hyperinsulinemic-hypoglycemic clamps (where blood glucose was lowered to 100, 65, 55, and 45 mg/dl) to assess counterregulation. Results/Anticipated Results: In the pre-clinical model, glucose infusion rates (GIR) to maintain hypoglycemia were higher in STZ+RH (27±0.9 mg/kg/min) than STZ+RS (19±0.8 mg/kg/min, p Discussion/Significance of Impact: Metoclopramide improves glucoregulatory, sympathoadrenal, and counterregulatory responses to hypoglycemia in pre-clinical models, suggesting dopaminergic regulation. While clinical data are still blinded, increased epinephrine and growth hormone responses suggest treatment may preserve or restore counterregulation.

OBJECTIVES/SPECIFIC AIMS: Patients with undiagnosed obstructive sleep apnea (OSA) will often present to an otolaryngologist with symptoms of chronic rhinosinusitis (CRS). Differentiating CRS from OSA may help obviate unnecessary and costly work-up for CRS. This study analyzes symptom profiles of such patients to help identify which require polysomnography. METHODS/STUDY POPULATION: This is a three-year retrospective analysis of adult patients seen in an academic practice with a rhinologic chief complaint. The 22-Item Sinonasal Outcomes Test (SNOT-22) survey, which is a validated patient-reported outcome measure widely adopted for CRS featuring a symptom scale of 1 (least severe) to 5 (most severe), was completed by patients with untreated OSA confirmed on polysomnography without CRS (OSA group) and a control group of CRS patients (CRS group). Results were compared using Chi-square test (categorical) and Wilcoxon rank-sum test (continuous) with Bonferroni correction, and multiple logistic regression. RESULTS/ANTICIPATED RESULTS: 43 patients were included in the OSA group [mean apnea-hypopnea index: 27.9 (SD: 21.2)] and 124 patients were included in the CRS group. The CRS group demonstrated significantly higher scores in nasal (p < 0.001), extra-nasal (p < 0.001) and ear/facial symptom domains (p = 0.001) while the OSA group reported higher psychological (p = 0.028) and sleep symptom domain scores (p = 0.052). As for the cardinal symptoms of CRS, nasal discharge and loss of smell were significantly higher in the CRS group (both p < 0.001), whereas facial pain (p = 0.117) and nasal obstruction (p = 0.198) were not significantly different between the two groups. After adjustment, for every 1-point increase in a patient’s score for ear pain, thick nasal discharge and loss of smell or taste, their odds of having CRS increased by a factor of 3.18 [(95% CI 1.61-6.29), p = 0.001], 1.60 [(95% CI 1.22-2.10], p = 0.001] and 1.36 [(95% CI 1.04-1.78), p = 0.025], respectively, compared to having OSA. OSA patients were more likely to choose a sleep-related symptom as a “most important complaint” (MIC) (p < 0.001). Facial pain and nasal obstruction were the most common MIC in the rhinologic domain for OSA patients, whereas thick nasal discharge and post-nasal discharge were the most common MIC for CRS patients. DISCUSSION/SIGNIFICANCE OF IMPACT: For patients presenting with rhinologic symptoms, the SNOT-22 can help identify those with undiagnosed OSA. OSA should be suspected in patients with sleep and psychological dysfunction as their primary complaints without the significant nasal drainage and anosmia that characterizes CRS.

Objectives/Goals: The goal of this study is to investigate the peri-metastatic rims of peritoneal lesions to determine features that predict malignancy using both imaging processing techniques and machine learning. This information will subsequently be added to our existing knowledge of peritoneal lesions to improve classification accuracy as benign or malignant. Methods/Study Population: The study population consists of 521 imaged lesions from 163 subjects with cancers of GI-origin with biopsy results as well as the clinical subject information and follow up. All images were obtained during staging laparoscopy by the senior author (TS). On the images, the central lesion as well as the surrounding peri-metastatic rim will be segmented as regions of interest (ROIs). Image processing will be used to calculate a variety of metrics for these two regions. A general estimating equation approach will be used to determine significance of these metrics compared to the dependent outcome of malignancy determined on the pathology report as the ground truth. These ROIs and significant metrics will then be used to improve the accuracy of a machine learning model to classify these lesions as benign or malignant. Results/Anticipated Results: Our previous research showed that experts performed this task at only a 52% accuracy rate (classifying lesions as malignant or benign based on imaging). A previous machine-learning model on a much smaller dataset was able to achieve by contrast an area under the curve of 0.78. We anticipate that by including a larger dataset in addition to including the peri-metastatic rim, we will be able to improve the accuracy of the the model in this task while uncovering significant biomarkers as well that can be used in future studies. Discussion/Significance of Impact: Classifying peritoneal lesions determines the correct treatment for cancer patients whether chemo-radiation, definitive surgery or palliative surgery. This project aims to develop an improved model that can perform this task using nonlabeled laparoscopic imaging with a particular focus on the diagnostic value of the peri-metastatic rim.

OBJECTIVES/GOALS: Aim 1: We will determine whether temporal changes in the fecal microbiome signature correlate with a clinical multiple system atrophy (MSA) phenotype. Aim 2: We will evaluate whether secretomes cultured from fecal samples from MSA patients enhance intracellular and extracellular α-synuclein (αSyn) aggregation using in vitro functional assays. METHODS/STUDY POPULATION: Aim 1: Gut microbiome profiling will be performed by 16S rRNA gene sequencing, tandem mass spectrometry for expression proteomics, and targeted metabolomics in fecal samples from 30 MSA cases matched to 30 healthy controls, a Parkinson’s disease comparison group, and household controls. Aim 2: Microbial species will be isolated using dilution-to-extinction on MSA fecal samples and then will be cultured to obtain secretomes. To assess the effect of MSA fecal secretomes on αSyn aggregation, culture media from microbial isolates will be used in fluorescence resonance energy transfer (FRET) assays and luciferase reporter assays, both modified to measure αSyn aggregation. Positive tests will undergo expanded metagenomic characterization of the microbes and secretome to identify potential causative agent(s). RESULTS/ANTICIPATED RESULTS: Based on cross-sectional metagenomic studies on MSA, MSA cases are expected to have genus reductions in Blautia and Dorea (acetate production); Paraprevotella (succinic and acetic acid production); and Ruminococcus, Coprococcus, and Faecalibacterium (butyrate production). Increases in genus Bacteroides (clinical pathogen) and Akkermansia (mucin degradation) and pro-inflammatory families Clostridiaceae and Rikenellaceae are also expected. MSA is predicted to be associated with reduced levels of short chain fatty acids and increased lipopolysaccharide. These microbial proteins and metabolites are anticipated to modulate intracellular and extracellular αSyn aggregation in vitro. Microbe isolation and secretome culturing methods are expected to identify additional drivers of αSyn aggregation. DISCUSSION/SIGNIFICANCE: This study’s novel use of longitudinal sampling, household controls, and secretome culturing aim to develop a more comprehensive understanding of the complex interactions between the gut microbiome and MSA. The success of this work offers the potential for new insights into the impact of the gut microbiome and secretome on MSA and αSyn aggregation.

OBJECTIVES/GOALS: Women with diabetes (DM) have higher rates of unplanned pregnancy and pregnancy complications, indicating a need for DM-specific counseling. Our aim is to use the Health Belief Model (HBM), widely applied to DM interventions, to create a conceptual model of contraceptive decision-making for women with DM. METHODS/STUDY POPULATION: Our convergent mixed methods study integrates quantitative survey data and qualitative interview data from women aged 18-50 with DM. We will interview until theoretical saturation is achieved. Descriptive statistics will be calculated to summarize demographics, health history, and contraceptive use and knowledge. Using a grounded theory approach, qualitative analysis will be conducted by JW and EJ with special focus on exploring HBM constructs. A joint display will be used to integrate key quantitative variables by qualitative themes. Finally, we will aim to implement these HBM constructs within the context of contraceptive decision-making for women with DM. RESULTS/ANTICIPATED RESULTS: To date, we have interviewed 16 women with average age of 35 and an equal mix of type 1 vs. type 2 DM and those who identify their health as poor/fair vs. good/very good. The following HBM domains have emerged as relevant to contraceptive decision-making: perceived threats, perceived barriers, cues to action and self-efficacy. An analysis of the cues to action domain suggests that patients’ responses to provider counseling are substantially dependent on provider tone and awareness of patient context. Effective cues were delivered supportively with focus on health promotion, while ineffective cues focused on adverse outcomes or were delivered to women not at risk of pregnancy. DISCUSSION/SIGNIFICANCE OF IMPACT: The application of the HBM to contraceptive decision making among women with DM will provide insight into critical factors that inform both patient and provider attitudes and behaviors and can be targeted for future interventions to reduce unplanned pregnancy in this vulnerable population.

ABSTRACT IMPACT: Medication non-adherence is a widespread problem in glaucoma care, and this abstract shows that a free and easy to implement tool can be used to accurately screen and identify patients who are not adherent to their glaucoma medication. OBJECTIVES/GOALS: To compare the accuracy of pharmacy refill data and five measures of self-reported adherence in identifying patients with poor electronically monitored glaucoma medication adherence. METHODS/STUDY POPULATION: Glaucoma patients (age ≥40, poor self-reported adherence, and ≥1 medication) recruited at the University of Michigan completed five surveys of adherence and 3-months of electronically monitored medication adherence; pharmacy refill data were obtained. Electronically monitored adherence was summarized monthly as percent of doses taken on time. Median monthly adherence ≤80% was considered non-adherent. Pharmacy refill data were reported as the proportion of days covered. The accuracy of the measures in predicting ≤80% adherence was assessed with receiver operating characteristic curves such as estimation of area under the curve (AUC), sensitivity, specificity, and accuracy. RESULTS/ANTICIPATED RESULTS: 95 patients completed electronic monitoring with a median monthly adherence of 74% (±21%); 53 patients (56%) were non-adherent. Pharmacy refill adherence was not significantly correlated with electronically monitored medication adherence (r=0.12, p=0.2). A single-item adherence question (‘Over the past month, what percentage of your drops do you think you took correctly?’) had the largest correlation with electronically monitored adherence (r=0.47, p<0.0001), the largest AUC for predicting non-adherence (AUC= 0.76, [95% Confidence Interval = 0.66, 0.87]), best accuracy (71%, [61, 82]), and good sensitivity (84%, [73, 96]). DISCUSSION/SIGNIFICANCE OF FINDINGS: A free, single-item screening question ('Over the past month, what percentage of your drops do you think you took correctly?') offers an easy-to-implement tool for identifying glaucoma patients with poor medication adherence in clinical practice.