ABSTRACT IMPACT: This study characterizes interactions between human limbic circuitry and ventral temporal cortex using single pulse electrical stimulation, which may inform emerging stimulation therapies for epilepsy. OBJECTIVES/GOALS: The goal of electrical brain stimulation treatment is to modulate brain network function. However, stimulation inputs to different brain sites alter the network in a variety of ways. This study examines that variability by characterizing responses in a target region while stimulating multiple other brain sites. METHODS/STUDY POPULATION: We measured voltages in intracranial EEG in 6 patients who had electrodes implanted for epilepsy monitoring. We stimulated pairs of electrodes at multiple sites in the brain with a single pulse every 5 to 7 s and measured the resulting corticocortical evoked potential (CCEP) responses in the ventral temporal cortex (VTC). Using a novel clustering method, we uncovered sets of distinct canonical response shapes from the 20 to 500 ms post-stimulation period. This allowed us to group stimulation sites that evoked similar responses. We then related each group to high frequency, broadband, changes in spectral power as a reflection of local neuronal activity. RESULTS/ANTICIPATED RESULTS: We found that the VTC receives strong inputs specifically from the amygdala and hippocampus, both in terms of amplitude and broadband spectral power change. However, inputs from the hippocampus produced a different canonical shape than those from the amygdala. We also observed that VTC responses to inputs from the insula clustered in shape with those from the amygdala. These clustering patterns were consistent across subjects, although the actual shapes of the clusters showed variability. We further observed that some shapes were more associated with increases in overall neuronal activity than others, as reflected by broadband spectral power change. DISCUSSION/SIGNIFICANCE OF FINDINGS: Stimulation of connected sites may drive excitability at the target region in ways that are described by sets of full-time-course responses. By capturing their shapes, we can begin to decipher canonical input types at the circuit level. This approach might identify how stimulation inputs can be tailored to therapy while mitigating adverse effects.

OBJECTIVES/SPECIFIC AIMS: Facilitate relationships and partnership development to address the opioid crisis in Detroit and Wayne County Contribute to real-time conversations on opioid epidemic policy and practice to identify and build consensus on research questions Apply findings from each learning community session to policy briefs to better inform policymakers, providers and consumers; and advocate for institutional responsiveness METHODS/STUDY POPULATION: The study population utilizes a purposive sampling approach to intentionally organize relationships and partnership development. For example, participants registered for the December 2018 session, “Detroit/Wayne County Opioid Crisis Learning Community Series: Data Session,” include representation from school-based health clinics, community and faith-based organizations, health systems, city and county level public health, addiction/recovery organizations, law enforcement, academia and citizens. The team feels this approach ensures and builds diverse, team science perspectives and regional collaboration. The Detroit Area Mental Health Leadership Team formed in 2015 at a retreat held by the University of Michigan’s Clinical and Translational Science Initiative attended by nearly 100 community-academic partners. Mental health, stigma and suicide were identified as community priorities by participants who attended the summit. A mental health workgroup formed and later expanded its membership to strengthen diverse perspectives. The team immediately designed and administered a survey amongst its partners creating the following priorities and focus: substance abuse interventions, healthcare access, and consumer awareness of mental health issues/available resources. Since data, policy and service are common threads to design interventions, the partnership decided to facilitate dialogue and discussion from the community on special topics related to the crisis, and share the community’s recommendations on how to address them. The learning community series was designed as a bi-lingual format for sharing and expression. Deliberative democracy encourages inclusion of voices, interests and opinions often not heard or included in decision-making processes; driving the project’s purposive sampling approach. Institutional responsiveness and advocacy for adoption of the community’s recommendations will occur through strategic policy briefs summarizing each learning community session and the entire series. A dissemination plan will be utilized to encourage the policy briefs reach appropriate audiences for capacity building and institutional responsiveness. The learning community series will provide 5 sessions on data (impacting adolescents, emerging adults, and 20-mid 30 year-old adults), recovery/law enforcement, prescribing, and marijuana. The session topics arose from earlier assessment conducted by the Detroit Area Mental Health Leadership Team. RESULTS/ANTICIPATED RESULTS: A response to the opioid crisis should address community priorities identified through data, research and community input. Community providers should have access to real-time data and research to develop appropriate interventions and institutional responsiveness. Equally important is the need for legislators and others impacting resource allocation to hear from the community on priorities they feel should be addressed, and to better understand the need for new types of data and information to drive service delivery, policy and resources to address the crisis. The learning community series will focus on describing the epidemic and building infrastructure to collaborate, and share data and information to strengthen advocacy and responsiveness to address the crisis. We feel this will enable more efficient programming to strengthen service delivery that captures life experiences from those who directly interface with individuals impacted by the crisis. DISCUSSION/SIGNIFICANCE OF IMPACT: There is limited knowledge and consensus on types of data and information to effectively describe the opioid crisis. For example, data and information connecting gateway drugs such as marijuana with more hardcore drugs (i.e., opioids and heroin) is not available; community-based providers have limited access to what research says about the crisis; and local public and community providers are dependent upon the state for surveillance data. Individuals dealing with addiction and recovery often need immediate attention. A gap in access to services exists depending on types of insurance. For example, Medicaid and some HMOs require an assessment before clients can seek treatment, resulting in uncompensated care among providers to immediately address patients need. Access to healthcare is a longstanding issue in medically underserved communities. The impact of the crisis varies geographically in communities and regions due to cultural and ethnic differences, yet data and information on these differences is not readily available. Cultural competency and sensitivity is often an issue in medically underserved areas because stakeholders may feel professionals providing services do not relate to them effectively. Finally, the community does not understand the economic impact of the crisis. These issues make it difficult for community advocates and providers to work with elected officials, providers and others on the opioid crisis because they do not have the data and informed required to effectively flush out a hypothesis and form solutions. Information captured in the learning community series (i.e., presentations by experts, facilitated discussion and personal testimony) will be summarized in a policy brief after each session and the entire series. Recommendations and priorities from the community will be shared with providers, policymakers, the business community, consumers and others to provide community input on problem solving approaches, new interventions, types of data not currently available that should be captured, and other important strategies and information to address the crisis. This information will also encourage designing research questions to guide developing new community engaged and community based participatory research to address the crisis. Finally, utilizing a purposive approach in participant recruitment will encourage partnership development from a team science and capacity building perspective.

OBJECTIVES/GOALS: To develop a two-staged convolutional neural network to identify the ovary and antral follicles within ovarian ultrasound images and determine its reliability and feasibility compared to conventional techniques in 2D and 3D ultrasonography image analysis. METHODS/STUDY POPULATION: De-identified and archived ultrasonographic images of women across the reproductive spectrum (N=500) will be used in the study. These ultrasound images will be labeled by experienced raters to train a two-staged convolutional neural network (CU-Net). CU-Net will first separate the entire ovary from the background and subsequently identify all antral follicles within the ovary. Following training, the CU-Net will evaluate a second set of independent images (N=100) to determine performance accuracy. Three specialized raters will establish the reliability and feasibility of CU-Net compared to conventional 2D and 3D ovarian ultrasound image analysis methods. RESULTS/ANTICIPATED RESULTS: The labeled training dataset of ovarian ultrasound images is expected to successfully train the CU-Net and allow for accurate identification of the ovary and the total number of antral follicles in the second testing set of ultrasound images. When compared to conventional 2D and 3D ultrasound image analysis methods, CU-Net is expected to have similar accuracy when compared to the gold-standard method (2D-Offline with Grid) and outperform other approaches, such as 2D-Real Time and 3D volume software (VOCAL and Sono-AVC). However, CU-Net is anticipated to be the fastest and most reliable method across users, supporting its clinical feasibility. DISCUSSION/SIGNIFICANCE: This study will immediately translate to providing a standardized platform that can improve the accuracy, reliability, and time demand required for the evaluation of ovarian ultrasounds across users and clinical and research settings.

The Stanford Population Health Sciences Data Ecosystem was created to facilitate the use of large datasets containing health records from hundreds of millions of individuals. This necessitated technical solutions optimized for an academic medical center to manage and share high-risk data at scale. Through collaboration with internal and external partners, we have built a Data Ecosystem to host, curate, and share data with hundreds of users in a secure and compliant manner. This platform has enabled us to host unique data assets and serve the needs of researchers across Stanford University, and the technology and approach were designed to be replicable and portable to other institutions. We have found, however, that though these technological advances are necessary, they are not sufficient. Challenges around making data Findable, Accessible, Interoperable, and Reusable remain. Our experience has demonstrated that there is a high demand for access to real-world data, and that if the appropriate tools and structures are in place, translational research can be advanced considerably. Together, technological solutions, management structures, and education to support researcher, data science, and community collaborations offer more impactful processes over the long-term for supporting translational research with real-world data.

Biospecimen repositories play a vital role in enabling investigation of biologic mechanisms, identification of disease-related biomarkers, advances in diagnostic assays, recognition of microbial evolution, and characterization of new therapeutic targets for intervention. They rely on the complex integration of scientific need, regulatory oversight, quality control in collection, processing and tracking, and linkage to robust phenotype information. The COVID-19 pandemic amplified many of these considerations and illuminated new challenges, all while academic health centers were trying to adapt to unprecedented clinical demands and heightened research constraints not witnessed in over 100 years. The outbreak demanded rapid understanding of SARS-CoV-2 to develop diagnostics and therapeutics, prompting the immediate need for access to high quality, well-characterized COVID-19-associated biospecimens. We surveyed 60 Clinical and Translational Science Award (CTSA) hubs to better understand the strategies and barriers encountered in biobanking before and in response to the COVID-19 pandemic. Feedback revealed a major shift in biorepository model, specimen-acquisition and consent process from a combination of investigator-initiated and institutional protocols to an enterprise-serving strategy. CTSA hubs were well equipped to leverage established capacities and expertise to quickly respond to the scientific needs of this crisis through support of institutional approaches in biorepository management.

ABSTRACT IMPACT: A single seismocardiography (SCG) parameter has been shown to accurately classify aortic valve disease (AVD) status in healthy controls and AVD patients. This could support development of SCG as a quick, inexpensive screening tool to better tailor MRI examination to patients’ needs. OBJECTIVES/GOALS: MRI is used commonly for monitoring of aortic valve disease (AVD), but it has high costs. We hypothesize that energy in seismocardiograms (SCG)’‘ signals from chest surface vibrations’‘ is different between healthy controls and AVD patients, and we evaluate potential efficacy of using SCG to recommend MRI only for patients with flow abnormalities. METHODS/STUDY POPULATION: With IRB approval, 45 healthy control subjects (47 ±18years, 18 female) and 9 patients (63 ±16years, 2 female) with aortic valve disease history and known flow abnormalities were recruited. SCG signals were acquired supine, immediately prior to MRI of thoracic aortic blood flow at 1.5T with a time-resolved phase contrast (4D Flow) sequence.

The SCG was processed to calculate late-systole high-frequency (120-240Hz) RMS energy. MR velocity images were analyzed to measure peak velocity and trace pathlines of flow.

Screening efficacy of the SCG energy metric was assessed, with hypothesis testing for differences in energy level distributions between controls and patients, and receiver-operator characteristic (ROC) analysis was used to calculate rates of correct/incorrect classification of disease. RESULTS/ANTICIPATED RESULTS: Healthy subjects had coherent flow pathlines through the aortic arch and mid-ascending aorta peak velocities of 106 ±21cm/s (cohort mean ±standard deviation). All valve disease subjects had flow abnormalities, such as jetting flow near the valve or swirling through the arch, as visualized by pathlines. Patients’ peak mid-ascending aorta velocities were 167 ±69cm/s. The SCG energy for healthy controls was significantly different than that of valve patients (-5.6 ±0.3dBmm/s/s vs. -4.0 ±1.2dBmm/s/s respectively; p<0.001). Thresholding SCG energy to distinguish patients from controls correctly classifies subjects with a high true-positive rate and low false-positive rate. The ROC for this classification has area-under-curve 0.956. DISCUSSION/SIGNIFICANCE OF FINDINGS: A high potential screening efficacy was observed using a single, linear SCG metric to identify AVD patients with flow abnormalities. If used to complement MRI surveillance protocols for AVD, this method has potential to serve as a quick, inexpensive tool for better tailoring MRI exams to patient needs.

OBJECTIVES/GOALS: MiaA is a highly conserved prenyl transferase that catalyzes synthesis of the i6A37 tRNA modification in E. coli. While transcriptional regulation of MiaA is well characterized, there is no information on the MiaA post-transcriptional regulation. The aim of this study is to characterize the post-transcriptional regulation of the MiaA gene in E. coli. METHODS/STUDY POPULATION: To characterize the post-transcriptional regulation of miaA, we executed a targeted genetic screen of an E. coli small RNA library on a miaA-lacZ translational reporter fusion strain to identify small RNAs (sRNAs) that modulate MiaA translation or transcription termination. We also measured MiaA mRNA levels and miaA-lacZ activity in the absence or over-expression of candidate sRNA regulators of MiaA. We also measured MiaA mRNA levels in the absence of RNaseE and PNPase, two enzymes involved in mRNA turnover. Finally, we measured the ability of purified recombinant CsrA to bind to the MiaA mRNA transcript in vitro. RESULTS/ANTICIPATED RESULTS: We identified the carbon sensing sRNA CsrB and its cognate protein interaction partner CsrA, as potential post-transcriptional regulators of MiaA. Over-expression of CsrB fully repressed miaA-lacZ activity and MiaA mRNA levels. The absence of CsrA resulted in a defective miaA-lacZ activity and a 10-fold decrease in MiaA mRNA levels. We also identified an increase in the MiaA mRNA half-life particularly in the absence of RNaseE. Our results demonstrate an additional layer of regulation for the miaA operon by the CsrA/CsrB protein-sRNA system. DISCUSSION/SIGNIFICANCE: MiaA is a highly conserved bacterial protein. Our data may represent phenomena in an array of bacteria that could be targeted by novel antibiotics. The human MiaA homologue, TRIT1, plays a role in mitochondrial disorders. We anticipate that information garnered from MiaA studies will elucidate TRIT1 function and its role in mitochondrial disorders.

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

OBJECTIVES/GOALS: Aim 1: Define the genetic events that cooperate with Trp53 mutations to mediate the transformation of MDS to sAML at the stem cell level. Aim 2: Use Bayesian networks to model the signaling pathway activation states identify aberrant regulators of self-renewal in LSCs. METHODS/STUDY POPULATION: To model the transformation of MDS, I will utilize a mouse model of MDS and sAML. The Trp53 mutated mouse mimics the genetics of human MDS and develops MDS. To discover how additional mutations contribute to disease progression, I use the Sleeping Beauty transposon system which induces random mutations. I propose to use this mouse model to define the molecular mechanisms of transformation of MDS to sAML. I will also measure levels of activated signaling intermediates in sAML using CyTOF. CyTOF is a method of flow cytometry that measures up to 40 proteins simultaneously at single-cell resolution. I will also use Bayesian network to model the signaling architecture of the MDS/sAML stem cells. RESULTS/ANTICIPATED RESULTS: I will identify putative mediators of self-renewal in gene expression data and the corresponding Bayesian networks model. I will prioritize genes and signaling intermediates that act in pathways that rank highly in both methods and those that have previously published roles in self-renewal. Based on prior work, I will focus on EZH2, NFï «B, and mTOR pathways in addition to candidate pathways revealed by these studies. Small molecule inhibitors that target candidate signaling intermediates will be used for experimental validation. I will test the impact of these small molecule inhibitors on LSC self-renewal using serial colony forming assays as well as in vivo mouse reconstitution assays. DISCUSSION/SIGNIFICANCE: We focus on the role of stem cells in the transformation of MDS to sAML. Understanding the mutations and signaling relationships that mediate self-renewal in Trp53 mutant stem cells will allow for precise therapeutic target of this disease and improve outcomes for these patients.

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

OBJECTIVES/GOALS: Current surgical flap and replantation monitoring techniques have limitations in detecting the pathologic state, calibration and cost-to-patient issues. Our hypothesis is that novel implantable oxygen sensors can provide a more efficient, accurate, and reliable monitoring of tissue oxygenation. METHODS/STUDY POPULATION: Experimental sensors were used with an exogenous remote used as a reader once implanted (Fig. 1) A rat tissue perfusion model with three regions of an SIEA flap as well as into adjacent control sites was made (Tip, Middle, and Base) Blood flow was greatest at the base, diminishing towards the Tip, thus creating a perfusion gradient. Changes in tissue oxygen tension PO2 were estimated by the steady-state fluorescence of the optical sensors using an IVIS imaging system. The sensors were used to collect data from days 0, 3, and 7 as a reading of Tissue Oxygen Tension (TOT) with ANOVA used to assess for statistical significance in blood oxygen data with respect to relative perfusion status. RESULTS/ANTICIPATED RESULTS: Inspired FiO2 was decreased from 100% to 12% with a corresponding change in the TOT readings from all sensors. (Fig. 2) The tip portion of the flap demonstrated the most profound detection of tissue necrosis, with the middle demonstrating the second most necrosis and the base demonstrating the least with correlating TOT sensor readings. (Fig. 3) Acute vascular compromise of the feeding blood vessels in the pedicle was immediately detected within 70 seconds (*p<0.05). (Fig. 4) DISCUSSION/SIGNIFICANCE OF IMPACT: This study introduces and validates a recent technique to monitor acute vascular occlusion, flap viability, and necrosis in the immediate postoperative period in a validated rodent model. Future directions of this novel technology will aim to reproduce these findings in clinical feasibility studies.

OBJECTIVES/GOALS: Six CTSA sites formed a collaboration to DEVELOP, DEMONSTRATE, AND DISSEMINATE new infrastructure to streamline collection and analysis of research participant feedback, using the Research Participant Perception Survey (RPPS), common standards, and customized REDCap-based tools, to improve the clinical research enterprise. METHODS/STUDY POPULATION: DEVELOP charter, consensus approach, core survey, deployment standards, data-use agreements; define meta-data, system requirements for the infrastructure, use-cases. Engage stakeholders for broad institutional and community input. Build RPPS/REDCap project, visual analytics Dashboard External Module, and Program Dashboard module for evaluation. Configure to use with Multilingual Module. DEMONSTRATE by implementing site-based use cases that reflect local priorities and span diverse populations, testing different methods of survey deployment (REDCap, patient portal, SMS) to showcase utility and flexibility. Generate data for local and inter-institutional benchmarking. Refine, then DISSEMINATE new infrastructure across the Consortium and REDCap community for broader testing and uptake. RESULTS/ANTICIPATED RESULTS: The project team refined the RPPS survey for inclusivity and mode of informed consent; defined standards for survey timing, sampling, and study metadata; configured the data dictionary in English and Spanishfor use with the multi-lingual module ; developed tools for project evaluation. Stakeholder engagement identified themes of anticipated value and fears about feedback. We designed an At-a-Glance Dashboard to display survey results with detailed analytics and filters. A REDCap application programming interface will send de-identified site data to the EPV Consortium Database to support benchmarking. Full implementation began November 2021 and will scale in 2022. Dissemination to Consortium and REDCap users is ongoing through presentations and a project website (www.Rockefeller.edu/research/epv). DISCUSSION/SIGNIFICANCE: Direct feedback from representative populations about their experiences in research is essential to understand and resolve barriers to broad participation in research. Streamlined RPPS/REDCap infrastructure provides a platform for local and national benchmarking, and collection of actionable data to improve clinical research.

OBJECTIVES/GOALS: Dysfunction of the autonomic nervous system (ANS) may be important in both depression and coronary artery disease (CAD). A novel heart rate variability (HRV) metric, Dyx, may be a be a potentially useful tool to study ANS dysfunction in these diseases. We propose that ANS dysfunction, measured by decreased Dyx, will associate with both depression and obstructive CAD. METHODS/STUDY POPULATION: We included participants undergoing coronary angiography for suspected CAD. Depressive symptoms were assessed with the Patient Health Questionnaire-9 (PHQ-9). HRV data were collected continuously on participants before catheterization using a new ECG patch (VivaLNK). We assessed HRV by Dyx (primary) and high and low frequency power, multiscale entropy, and deceleration capacity. Two-sample t-tests and logistic regressions (with adjustment for age and sex) were used to study the difference in HRV (before cardiac catheterization) between those with high versus low depressive burden (PHQ-9 ≥ 10), and in those with versus without obstructive CAD (>70% stenosis). RESULTS/ANTICIPATED RESULTS: We assessed 30 individuals with mean (SD) age 62.4 (13.2); 7.1% were female and 15.4% were black. Mean Dyx in high depressive symptoms (N = 21, 70%) was 1.8 (0.2) and in none-low depressive symptoms (N = 7, 23%) was 2.2 (0.2). Differences were also observed for high frequency (HF) (4.4 (1.1) vs. 6.0 (1.4)) and deceleration capacity (−4.2 (2.1) vs. −10.7 (8.5)). Mean Dyx in obstructive CAD (N = 17, 57%) and non-obstructive CAD (N = 10, 33%) was 1.7 (0.6) and 2.6 (1.2) respectively. Differences were seen with sample entropy (1.2 (0.2) vs. 1.5 (0.2)). Every 1 unit of log(HF) had an odds ratio = 0.14 (95% CI 0.06 – 0.36) for depression. DISCUSSION/SIGNIFICANCE OF IMPACT: ANS dysfunction, measured by HRV, associates with both depression and obstructive CAD. Autonomic ECG markers may play an important role in assessing brain-heart pathology, and may be useful to study the interaction between depression and CAD.

OBJECTIVES/GOALS: The goal of this proposal is to develop a technology that combines calcium imaging via confocal microscopy, and force measurement via monolayer stress microscopy to perform simultaneous quantitative measurements of agonist-induced Ca2+ and mechanical signals in HASMCs. METHODS/STUDY POPULATION: The methods by which second messenger signals and changes in mechanical forces determine specific physiological responses are complex. Recent studies point to the importance of temporal and spatial encoding in determining signal specificity. Hence, approaches that probe both chemical and mechanical signals are needed. We combine hyperspectral imaging for second messenger signal measurements, monolayer stress microscopy for mechanical force measurements, and S8 analysis software for quantifying localized signals. Imaging was performed using an excitation-scanning hyperspectral microscope. Hyperspectral images were unmixed to identify signals from fluorescent labels and microparticles. Images were analyzed to quantify localized force dynamics through monolayer stress microscopy. RESULTS/ANTICIPATED RESULTS: Results indicate that localized and transient cellular signals can be quantified and mapped within cell populations. Importantly, these results establish a method for simultaneous interrogation of cellular signals and mechanical forces that may play synergistic roles in regulating downstream cellular physiology in confluent monolayers. DISCUSSION/SIGNIFICANCE: We will measure the distribution of chemical and mechanical signals within cells, providing insight into the dynamics of cell signaling. Studies will have implication in the understanding of infections, drug delivery in which non-uniform distributions of drugs are a certainty, and in understanding coordinated responses in cellular systems.

OBJECTIVES/GOALS: The purpose of this retrospective cohort study was to evaluate the impact of mental illness on first-time transcatheter aortic valve replacement (TAVR) and repeat TAVR (viv-AVR) outcomes including postoperative atrial fibrillation (POAF/AFL), as well as trends over time. METHODS/STUDY POPULATION: Using de-identified data reports from the New York Statewide Planning and Research Cooperative System (SPARCS) database from 2005-2018, multivariate logistics models were used to predict endpoints including POAF, the Society of Cardiothoracic surgeon (STS) endpoint (MM), and 30-day readmission (READMIT) in patients with and without mental illness. The TAVR procedure was approved for high-risk patients after 2012, and intermediate-risk patients after 2016, indicting a need to analyze the two populations separately. Multivariate analysis was only conducted on the first-time TAVR patients because of the small n in the viv-TAVR population. RESULTS/ANTICIPATED RESULTS: After 2012, 13.05% (1,810/13,870) of patients undergoing TAVR and 20.83% (15/72) undergoing viv-TAVR were diagnosed with a mental illness before the procedure. After 2016, 15.59% (1,485/9,524) TAVR patients and 20.00% (11/55) viv-TAVR patients had a preoperative diagnosis of mental illness. Multivariate analysis showed that mentally ill patients did not have significant differences in rates of POAF, 30-day readmission, and 30-day composite outcomes when compared to patients without mental illnesses following TAVR procedures after 2012 and 2016. Patients with POAF after both 2012 and 2016 were significantly less likely to be mentally ill, Black, and Hispanic. DISCUSSION/SIGNIFICANCE: Of the mentally ill patients who underwent TAVR, there was no significant difference in short-term outcomes after 2012 vs. 2016, compared to patients without mental illnesses. The small number of mentally ill patients undergoing TAVR may point to provider bias as a contributor to this high selectivity, and further evaluation would be of clinical use.

OBJECTIVES/GOALS: NASH increases the risk of cirrhosis and liver cancer. High-fat diets increase CCK levels and CCK receptors have been identified on fibroblasts and immune cells. We hypothesized that CCK receptor blockade could prevent NASH by altering the hepatic microenvironment and macrophage activation. METHODS/STUDY POPULATION: Female mice were fed a Choline Deficient Ethionine supplemented (CDE) saturated fat diet or control high-fat diet for 18 weeks. Mice in each group were treated with a CCK receptor antagonist, proglumide (0.1 mg/ml) in the drinking water or regular water. Resected livers were stained for H&E for features of NASH and F4/80 for macrophages analysis. Liver RNA was evaluated for the expression of cytokines and chemokines using an 84-gene Profiler array (Qiagen). Oxidative stress was analyzed by qRT-PCR for heat shock proteins (HSPs) 27, 60, 70 and 90 and for glutathione by a fluorometric assay. Differences in CDE fed and CDE/proglumide-treated mouse livers were evaluated. RESULTS/ANTICIPATED RESULTS: Livers from mice on the CDE diet displayed histologic features of NASH that were prevented by proglumide. Cytokines and chemokines expression, especially CCL20 and CCL2, were increased in the CDE fed mice and these levels were reduced greater than 20-fold with proglumide. Infiltration of F4/80+ macrophages was markedly increased in the CDE livers and these were reduced by > 50% (p < 0.0001) with proglumide. RNA expression of HSP70 (p = 0.006) and HSP27 (p = 0.011) were reduced with proglumide. Hepatic glutathione concentration more than doubled in the CDE/proglumide treated mice compared to CDE mice. CCK-B receptor expression increased in the CDE-fed mouse livers compared to controls. DISCUSSION/SIGNIFICANCE OF IMPACT: CCK receptor blockade decreases NASH by reducing hepatic macrophages, oxidative stress, and blocking inflammatory cytokines and chemokines. This data supports our novel hypothesis that CCK receptors play a role in NASH and proglumide may provide an innovative treatment for this condition.

OBJECTIVES/SPECIFIC AIMS: To mobilize and engage CHWs/promotores as stakeholders, we aim to promote the capacity for CHWs participate in patient centered research (PCOR) by locally implementing a structured research training curriculum for CHWs. Main Questions: How the process of mobilization and engagement would be implemented at local/state level? What would be project challenges, risks and barriers at each and across sites? What modifications would be made to the initial PCOR for CHWs training curriculum and toolkit based on local feedback from collaborators, in both English and Spanish? What would be lessons learned on mobilization, engagement of, and sustainability for CHW training organizations as partners in PCOR? METHODS/STUDY POPULATION: Measures: Monthly calls and quarterly reports from local organizations on activities, deliverables status, modifications, project implementation challenges/barriers and solutions (experienced and potential) to achieve goals of training 10 PCOR CHW Champions and a total of 360 CHWs/promotores trained in PCOR. Input from Note taker reports, Feedback and Evaluation Forms from training attendees at each session. Co-authorship of team members on dissemination activities (submissions for presentations, posters, blogs entries, webinars). Activities/Procedures: Via a highly participatory, consensus-driven decision-making approach, each of the organizations in the target states provide input into refining the toolkit for local use, select the training champions and develop CHW/promotor outreach and recruitment plans, and deliver the PCOR training to CHWs. In addition, the organizations will also set up a local stakeholder CHW/promotores advisory group. Environmental scan and literature review continues on training content areas to complement field experience in implementing the trainings at local sites. Project information tools developed (info sheet for local organizations, informational slide set to be used at calls and statewide seminars, a templates for flyer for training recruitment, agenda, certificates). FL and TN pilot of the translation of the curriculum, addressing problematic concepts and terms, collecting feedback forms eliciting input on terminology variations across Spanish speaking populations and literacy levels. Project Collaborators: Día de la Mujer Latina, a patient advocacy group in Texas with CHW trainings in several states and Puerto Rico Chula Vista Community Collaborative, a community health empowerment organization in Southern California Progresso Community Center, a Latino-focused health coalition based in Tennessee Florida Community Health Worker Coalition, a statewide partnership dedicated to the support and promotion of the CHW profession in Florida. RESULTS/ANTICIPATED RESULTS: Results: Trainings per State - Y1 Jan- October 2018 Totals: 11 PCOR Champions and 252 PCOR-Trained CHWs in CA-TX-TN Y2 Plans (October 2018-September 2019): Will continue to collect CHW trainee demographic data, CHW certification and patient/patient advocate status. Will conduct qualitative and quantitative analysis of all quarterly reports, Note taker, and trainee Feedback and Evaluation forms. Will reach goal of 360 PCOR-trained CHWs in FL, CA, TX and TN. Will continue to submit abstracts on our story on building patient and stakeholder capacity to participate as partners in patient-centered outcomes research, engagement and mobilization, from topic generation through the dissemination of research results. From evaluation analysis of content and process measures, we will discuss sustainability strategies as shared learning collaborative. DISCUSSION/SIGNIFICANCE OF IMPACT: Challenges/Decision Points Y1: On Mobilization and Engagement: Across partners, different levels of readiness/capacities/structures, and access to local resources Process application for request for content and guest instructor approvals to the Texas Department of State Health Services (DSHS) for CHW and CHW Instructor credit Co-branding of informational products (recruitment flyers, agendas, certificates), slides of Welcome section On Content and Curriculum Development: Address different levels of literacy Format (1-day vs spread, in person/online, prescriptive vs open) Clear distinction between service provision and research; paradigm shift of transfer of skills Inserting examples of unethical health research past activities with both African American and Hispanic/Latino populations Reinstating phases of clinical studies basic information Creating a study research design activity in Chapter 1 CHW role as member of research team Adding PCORI-funded project summary fact sheet per state On translations: Diversity of nuances of meaning in vocabulary for concepts On sustainability: Different degrees of organizational and personal involvement Next for newly PCOR-trained CHWs Meaningfully engaging patients and other stakeholders is increasingly recognized as requisite to generate research findings that are trusted, meaningful, and useful to clinicians, patients, and their families. One key engagement strategy used for engaging specific patients/caregivers and patient advocates in underserved communities is leveraging our partnerships with Community Health Workers (CHWs). Moreover, there is a documented need for higher level of training skills to undertake activities such as community health assessments, program evaluations and clinical studies. University of Miami (UM) along FL partners has successfully developed a 7-hr specialized toolkit on patient-centered research for CHWs and trained 148 CHWs/promotores (original plans were for 100) across the six major statewide regions. Evaluation data resulted in 100% of attendees responses’ as excellent and 99% would recommend it to others. Qualitative comments included “even though the training was tailored for research, I feel that it applies to many other aspects of the CHW role” and “I feel more empowered in my role after hearing explicitly the opportunities…for a CHW to be more involved in the research process”. UM has partnered with stakeholders in FL, Texas, southern California and Tennessee to develop a Spanish version of the PCOR for CHWs Training Toolkit (including a slide deck, Facilitator’s Guide and Student Workbook) that can be culturally and linguistically appropriate, to train local CHWs/promotores as PCOR CHW Champions. Attendees will receive lunch and a certificate of participation upon completion of the module. In turn, they agree to train local CHWs in their region. These 7 credit hrs could be used as credits towards state certification requirements, in states with CHW certification programs. This partnership for the mobilization and engagement of CHWs/promotores aims to strengthen their capacity to be involved in PCOR at the local and national level and increase the organizational capacity of CHW representative organizations in their promotion of PCOR. This type of research aims to help patients and those who care for them make better-informed decisions about the healthcare choices they face every day, guided by those who will use that information. In doing so, CHWs/promotores are contributing to PCOR in addressing health disparities and achieving health equity as a more culturally and linguistically diverse healthcare workforce and PCOR research team members.

ABSTRACT IMPACT: Through conducting this systematic review and meta-analysis, we will elucidate which factors influence thoracic aortic aneurysm growth, which will further help clinicians to properly stratify and manage their patients with TAAs. OBJECTIVES/GOALS: Thoracic aortic aneurysms (TAA) are an indolent but fatal disease, and the patient characteristics that predict both overall growth and growth rate are still not well characterized. Our goal is to conduct a systematic review and meta-analysis in other to better describe different patient characteristics that predict TAA growth. METHODS/STUDY POPULATION: M.M. conducted a search of Ovid MEDLINE, Embase, and Scopus to identify articles. Inclusion criteria were any longitudinal study reporting asymptomatic TAA growth, growth rates, or clinical proxies for growth such as dissection, rupture, emergency surgery, and death. M.H and P.B. independently applied the criteria to the results of the search. Conflicts were resolved by N.B. Data was extracted and risk of bias assessed independently by M.H. and P.B. Summary estimates of the outcome variables are combined across studies using standard meta-analysis methods. Heterogeneity is assessed via forest plots, chi2 test (Q test), and I2 statistic. Sensitivity analysis is conducted to assess robustness of the findings. RESULTS/ANTICIPATED RESULTS: The literature search resulted in 3,419 abstracts, of which 176 were included and thus require a full text review. Cohen’s Kappa coefficient was 0.64, indicating substantial agreement and high inter-rater reliability. We describe four categories of patient characteristics influencing the growth of asymptomatic TAAs: demographics, genetic or inheritable conditions, hemodynamic or biomechanical factors, and serum biomarkers. We describe the measure of effect for all variables. We anticipate there is a significant level of heterogeneity between studies, and potentially moderate risk of bias for many of the included studies as they are retrospective and observational in nature. Furthermore, we anticipate publication bias and evaluate it with funnel plots. DISCUSSION/SIGNIFICANCE OF FINDINGS: Understanding the factors that influence the growth of asymptomatic thoracic aortic aneurysms (TAA) is paramount, as the size and growth rate of TAAs dictates the clinical course. Little is understood about the degree to which different characteristics influence growth. This meta-analysis will help elucidate factors that promote TAA growth.