Objectives/Goals: To screen community members for prediabetes and diabetes in the grocery stores located in urban areas, identify gaps in healthcare access, promote healthy food, teach participants about diabetes prevention and management, and learn from them via interactive community-based educational sessions. Methods/Study Population: 303 Tops Friendly Market customers in urban Buffalo, NY participated in this program. Customers without a diabetes diagnosis took a CDC Prediabetes Risk Test (score >5  =  prediabetes risk). Those with a previous diabetes diagnosis took a survey about their diabetes knowledge/management, healthcare access, and social determinants of health. Participants received a $5 voucher for fruit and vegetables. We conducted 5 educational sessions using an adult learning, participatory education approach. A $10 gift card was given for attendance. Participants shared questions/concerns and strategies to overcome barriers. We answered questions and collected information on barriers to diabetes care. Results/Anticipated Results: Seven-six participants (25%) had a diabetes diagnosis. Of these, 91% saw a doctor every 3 months, but 28% did not know the importance of HbA1c. 18% had trouble paying for medications, 15% had inadequate transportation. 227 took the Prediabetes Risk Test: 58% had a score >5, 47% had diabetes family history, 51% had hypertension, and 75% had a BMI that put them at risk for diabetes. 86% of those with a score5. 55 people (34 unique) participated in 5 sessions. We actively listened to diabetes perceptions, concerns, successes and barriers/facilitators to self-management, and discussed diabetes management strategies for heathier eating and lifestyle. Discussion/Significance of Impact: It is feasible to screen for health conditions in the supermarket setting, which can be an equalizer in enhancing access to healthcare. This study helped identify gaps in care and provided education. Importantly, people receiving this intervention lived in the poorest neighborhoods in Buffalo.

Objectives/Goals: To determine the role of carcinoembryonic antigen cell adhesion molecule 6 (CEACAM6) in signaling cascade and interaction with other cell surface proteins in human epithelial solid tumors such pancreatic adenocarcinoma and colon cancer Methods/Study Population: In this study, we employed three-dimensional (3D) tumor models to replicate the in vivo tumor microenvironment better, allowing for a more accurate assessment of cellular responses compared to traditional two-dimensional (2D) cultures. We used immunoprecipitate to pull down the CEACAM6 protein and investigate the integrins expression level. Results/Anticipated Results: The expression and functional activity of CEACAM6 are susceptible to modulation by various surface proteins, leading to notable alterations in cellular behavior. Integrins, particularly Integrin B4, are one such protein whose expression is influenced by CEACAM6-mediated intracellular signaling cascades, suggesting a complex interplay that enhances CEACAM6 activation.The 3D models facilitate cell–cell interactions, enabling tumor cells to proliferate and undergo metabolic changes that reflect actual tumor biology. Thereby enhancing the relevance of crosstalk between CEACAM6 and integrins. These findings underscore the potential of CEACAM6 as a promising therapeutic target. They reveal a molecular mechanism that could inform the development of innovative therapeutic strategies in cancer. Discussion/Significance of Impact: These findings underscore the potential of CEACAM6 as a promising therapeutic target, revealing a novel molecular mechanism that could inform the development of innovative therapeutic strategies for pancreatic and colon cancer and potentially other malignancies.

Objectives/Goals: Current popular scoring systems for evaluating facial nerve function are subjective and imprecise. This study aims to quantify speech and facial motor changes in patients suffering from facial palsy after cerebellopontine angle (CPA) tumor resection to lay the foundation for a scoring algorithm that is higher resolution and more objective. Methods/Study Population: We will obtain audio and video recordings from 20 adult patients prior to and after surgical resection of unilateral CPA tumors between October 2024 and February 2025. We will obtain preoperative recordings within two weeks prior to surgery and postoperative recordings following a preset schedule starting from the day after surgery up to one year. Audio recordings entail patient readings of standardized passages and phonations while video recordings entail patient performance of standardized facial expressions. We will analyze video data for key distance measurements, such as eye opening and wrinkle size, using DynaFace. We will process audio data using VoiceLab to extract metrics such as prominence and tonality. We will perform statistical tests such as t-tests and ANOVA to elucidate changes across time. Results/Anticipated Results: I expect to obtain 9 sets of audio and video recordings from each of the 20 participants. In terms of speech, I expect average speech duration to increase postoperatively. Similarly, I expect to find increases in time spent breathing, number of breaths taken, and mean breathing duration. In terms of facial movement, I expect nasolabial fold length to decrease postoperatively, as well as eye opening size and left-right symmetry at rest. For both audio and video, I expect these changes to revert towards their preoperative baseline as time passes. I also expect average House-Brackmann and Sunnybrook facial grading scores to increase postoperatively and then decrease with time, correlating strongly with the video and audio findings. I will use trajectory analysis and time point matching to handle any missing data. Discussion/Significance of Impact: This study will validate our analysis platform’s ability to automatically quantify measurable changes that occur to speech and facial movement which correlate strongly with existing scoring systems. Future work will synthesize these data streams to move towards establishing biomarkers for facial nerve function that aid clinical decision-making.

Objectives/Goals: The informed consent (IC) process is similar between clinical trials and expanded access (EA), which allows clinical use of investigational products outside studies. Physicians face unique barriers to IC in clinical environments. This project assesses IC documentation, identifies potential barriers, and evaluates efforts to improve compliance. Methods/Study Population: This is a continuous quality improvement project. To assess the compliance of IC processes for EA patients, informed consent documents signed by EA patients in 2023 were collected and reviewed against institutional standards. Five components of each form were evaluated, and the number and type of noncompliant documentation were tracked. Five physicians who provided EA treatments in 2023 were interviewed and the transcripts were analyzed to identify barriers to physician’s and teams’ IC processes. Efforts made to address these barriers and improve the compliance of informed consent documentation are being tracked and trends in compliance are being evaluated. Results/Anticipated Results: Sixty seven (67) signed informed consent documents for EA treatments were systematically reviewed and 34% were found to be compliant in all key aspects assessed. Analyses of interview notes, transcripts, and memos identified barriers to informed consent processes for expanded access treatments, including the infrequent or irregular occurrence of EA treatments making it difficult for care teams to develop and maintain their understanding of IC process and resources. Efforts made to improve compliance by pre-populating available information into informed consent documentation and removing unnecessary boxes in these forms may have driven improvement in compliance with further efforts underway. Discussion/Significance of Impact: This project evaluated the compliance of IC documentation for EA treatments and identified drivers affecting physicians’ IC processes for these patients. Different strategies to improve the compliance of IC documentation were evaluated and potential best practices for EA support were identified.

Objectives/Goals: We aim to enhance risk prediction in kidney transplantation outcomes by improving models of peptide antigen presentation of mismatched HLA molecules. HLA-derived peptides presented by HLA Class II to T-cells can activate an immune response, ultimately leading to graft failure. We aim to improve peptide prediction by modeling antigen processing. Methods/Study Population: T-cell epitope models for HLA mismatching struggle to predict which peptides are presented because antigen processing by proteases is not well modeled. We model antigen processing of HLA Class II proteins using 3D HLA structures (crystallography data) to create an HLA-specific antigen processing likelihood (APL) model. APL uses conformational stability measurements such as b-factor, COREX, solvent accessible surface area, and sequence entropy to predict cleavage sites from proteolysis. We will integrate APL into a T-cell epitope prediction tool for HLA-derived peptides based on donor and recipient HLA genotypes. Finally, we will associate the risk of graft failure with counts of these peptides derived from APL-integrated prediction models using a historical kidney transplant cohort from 2000 to 2023. Results/Anticipated Results: We expect that applying APL could reduce false-positive peptide binders influencing risk prediction scores. We anticipate improved peptide prediction accuracy compared to existing tools such as NetMHCIIPan, which assumes all possible peptides are equally likely to emerge from antigen processing. NetMHCIIPan is currently used by PIRCHE-II HLA mismatch risk algorithm. We expect that merging antigen processing (APL) and peptide-binding (NetMHCIIPan) models into a unified model would enhance risk stratification for graft failure. Current risk stratification still leads to poor outcomes post-transplant, especially for minority population groups. Our model can identify an alternative pool of well-matched donors and has the potential to improve equity for non-White minority candidates. Discussion/Significance of Impact: Improving the understanding of how HLA matching contributes to kidney transplant outcomes can better stratify risks for kidney transplant recipients, enable personalized treatment, and ultimately improve outcomes for those undergoing kidney transplantation to treat renal diseases.

Objectives/Goals: Understanding the interconnections among over 20,000 human diseases spanning organ systems could inform more precise diagnosis and treatment of diseases. Here, we examine whether the ability of large language models (LLMs) to learn universal representations of concepts can be leveraged to discover complex relationships across human diseases. Methods/Study Population: To address the challenge of computationally representing thousands diseases spanning multiple organ systems, we used internal representations of concepts by LLMs to encode diseases based on their descriptions from standard disease ontologies (ICD10 and Phecodes). To do this, we leveraged application programming interfaces (APIs) of three LLMs-GPT3.5, Mistral and Voyage to encode disease relationships. We then performed unsupervised clustering of the diseases using their encodings (embeddings) from each LLM to determine whether the resulting clusters reflect disease relationships. To enable deeper exploration of disease relationships, we developed interactive plots that provide a system level view of the relationships between thousands of diseases and their association with specific organ systems. Results/Anticipated Results: We found that unsupervised analysis of disease relationships using the LLM encodings reveal high similarities among diseases based on organ systems they affect. All the LLMs clustered diseases into groups largely defined by the organ systems they affect without being trained to specifically classify diseases into their corresponding organ system classification. An exception to this was tumors in which we observed that most tumors cluster together as a group irrespective of the organs they affect. Interestingly, we found that tumors affecting anatomically related organs show higher similarity to each other than to those affecting distantly related organs. In addition to anatomical relationships between diseases, we found that the LLM embeddings capture genetic relationships between diseases. Discussion/Significance of Impact: Overall, we found that the LLM-derived encodings uphold biologically and clinically significant relationships across organ systems and disease types. These results suggest that LLM encodings could provide a universal framework for representing diseases as computable phenotypes and enable the discovery of complex disease relationships.

Objectives/Goals: 1) Determine the association between wildfire smoke-driven PM2.5 and risk of persistent respiratory symptoms and repeated asthma exacerbations after the acute wildfire period among adults with asthma. 2) Examine how measures to reduce personal exposure to wildfire smoke, including avoiding outdoor activities, modify this association. Methods/Study Population: This is a retrospective study of adults with asthma in WHAT-NOW, a cohort study of people living in Northern California during the 2018 Camp Fire. Daily smoke-driven PM2.5 was estimated for each participant based on their home address or evacuation location. We examined the association between mean PM2.5 exposure and the presence of respiratory symptoms at both the time of the survey (6–16 months post-wildfire) and at least one other post-wildfire time-period, as well as whether they had a medically attended respiratory illness (saw a doctor, visited the ER, or were hospitalized for a respiratory symptom). We examined the interaction of PM2.5 with spending time outdoors during the wildfires. Poisson regression models with robust standard errors were adjusted for age, sex, race, smoking, allergies, and education. Results/Anticipated Results: Among 337 adults with asthma in the WHAT-NOW cohort, one standard deviation higher smoke-driven PM2.5 was associated with higher risk of any persistent respiratory symptom (risk ratio (RR) 1.38, 95% CI 1.07 – 1.78) and having at least one medically attended respiratory illness (RR 1.33, 95% CI 1.07 – 1.65), but not significantly associated with repeated asthma exacerbations (RR 1.30, 95% CI 0.92 – 1.81). However, there was a significant interaction between PM2.5 and outdoor activities during the wildfire on the outcomes of any persistent respiratory symptoms (p = 0.041) and repeated asthma exacerbations (p = 0.028). The association between PM2.5 and repeated asthma exacerbations was greater among people who spent time outdoors (RR 3.36, 95% CI 1.47 – 10.23) than those who did not (RR 1.00, p = 0.99). Discussion/Significance of Impact: This study provides evidence that exposure to wildfire smoke increases respiratory morbidity among adults with asthma beyond the acute wildfire period. Additionally, it suggests that avoiding outdoor activities on smoky days can significantly decrease the risk of future repeated asthma exacerbations associated with smoke exposure.

Objectives/Goals: Community health workers (CHWs) are links between the community and healthcare. As primary care (PC) expands to address social drivers of health, CHWs are becoming part of PC teams, yet how the two integrate is not well understood. Using an input-mechanism-outcome (IMO) model, this research seeks to develop a model to expand CHW-PC integration efforts. Methods/Study Population: Participants were recruited from Roots Community Health Center (Roots), a CHC serving historically marginalized communities, that has successfully integrated a CHW role, Roots Health Navigators (RHNs), into PC services. The preliminary conceptual framework for this study was guided by an overarching IMO model and informed by social identity theory, team science, and the interprofessional care literature. A mixed methods study was conducted in three phases: 1) cross-sectional survey, 2) semi-structured interviews, and 3) model development. The survey identified team dynamics such as communication, trust, and shared understanding, and interviews explored how these collaborative teaming mechanisms take shape. Findings were merged into a final model of CHW-PC integration that was reviewed by Roots leaders. Results/Anticipated Results: Survey results (n  =  25) highlighted highly rated team dynamics including shared understanding and acting and feeling like a team. Qualitative findings (n  =  10) described how integration occurred through complex interactions that were community-responsive and collectively reduced burnout among the team. Joint findings noted the importance of RHNs to continuity of care, building trust, and enhancing PC team effectiveness. Findings informed the development of a model of CHW-PC integration. This expanded on the preliminary conceptual framework by highlighting the dynamic relationship between mechanisms, processes, and team emergent states, as well as providing evidence to support feedback loops between inputs, mechanisms, and outcomes with overarching influence from the contextual setting. Discussion/Significance of Impact: With a deeper understanding of the mechanisms of CHW-PC integration, findings informed the development of a model that can support other communities to replicate this approach to care and address critical patient needs. Teaming factors that sustain CHW-PC integration may be transferrable to other care teams integrating nontraditional roles.

Objectives/Goals: Diamond Blackfan anemia (DBA) is caused by loss of ribosomal proteins leading to death of red blood cell progenitors. We identified a novel heterozygous variant (c.167+769C>T) in RPL30 in a patient with DBA. We hypothesized that this variant, in a gene not previously studied in DBA, would demonstrate DBA phenotype and reveal early drivers of disease. Methods/Study Population: To study the role of our novel variant, we developed an induced pluripotent stem cell (iPSC) model, including wild type (WT) and CRISPR-edited RPL30 mutant clones. We differentiated the iPSC into hematopoietic stem cells, identified cell populations with flow cytometry, and applied single-cell RNA sequencing. We identified erythroid clusters for differential gene expression analysis, using R Studio DESeq followed by Gene Ontology (GO) enrichment analysis. We are differentiating cells into red blood cells for further comparison with flow cytometry, bulk RNA sequencing, protein analysis, and hemoglobin staining. Our approach has relied on multidisciplinary expertise in clinical hematology and genetics, basic science study of ribosomes, computational biology, stem cell, and hematopoietic biology. Results/Anticipated Results: Compared to WT hematopoietic stem cells, RPL30mutant cells had significantly decreased expression of RPL30. Analysis of top differentially expressed genes revealed downregulation of HSPA1A which encodes heat shock protein 70 (HSP70), chaperone of a critical red blood cell transcription factor. Loss of HSP70 protein has been implicated in RPL-mutated red blood cells previously as a potential modulator of severe DBA phenotype. Upon GO enrichment analysis of downregulated genes, biologic process terms GO:0042254 ribosome biogenesis, GO:1903708 positive regulation of hemopoiesis, and GO:0045646 regulation of erythrocyte differentiation were all highlighted as driver terms. We expect further differentiation to reveal early death of RPL30mutant cells with associated downregulated HSP70. Discussion/Significance of Impact: Our results support our hypothesis that the RPL30 variant downregulates erythropoiesis, with a potential early role of HSP70 protein. Upon completion of our study, we will demonstrate the role of RPL30in DBA pathogenesis as well as provide understanding of its drivers, which is critical for improved management of this disease.

Objectives/Goals: To use patient-level Center for Medicare and Medicaid Services (CMS) mandated quality metrics for inpatient rehabilitation facilities (IRFs) to develop and validate predictive models of functional recovery and interactions of baseline characteristics with therapy time. Methods/Study Population: Retrospective cohort study of a national US sample of ~40,000 adults with a primary diagnosis of stroke admitted to IRFs in 2023. Records will be randomly allocated to equal training and validation samples. We will use a random forest approach to generate predictive models for self-care and mobility functional outcomes using patient baseline and demographic data from a CMS-mandated assessment for IRFs (Section GG). We will also examine how predictive variables modulate the effects of occupational, physical, and speech-language therapy minutes. The random forest is a machine-learning approach that trains multiple models and combines their predictions to improve their overall performance. Results/Anticipated Results: Predictive models developed from the training sample will be applied to the validation sample to confirm their capacity to support new observations. Preliminary results will be reported, including the F1 score and area under the curve (AUC), with 95% confidence intervals. A unique feature of this study is the large sample, which contrasts with prior research in stroke rehabilitation using machine learning approaches. This study will produce powerful models that will inform the design of a clinical decision-support tool for application into clinical practice in a future study. Discussion/Significance of Impact: By using CMS-mandated quality metrics that are collected as part of standard clinical practice in IRFs, results will support clinical interpretation and application of metrics and inform the development of a clinician-facing intervention to support personalized rehabilitation approaches.

Objectives/Goals: The goal of this work is to understand the physiological profile of phage susceptibility and identify candidate phage defense mechanisms. Additionally, it aims to determine the host receptors targeted by bacteriophages to infect E. coli O157:H7 through random bar code transposon-site sequencing (RB-TnSeq). Methods/Study Population: A collection of 109 E. coli O157:H7 strains from environmental, food, and animal sources were analyzed, representing phylogenetic lineages corresponding to clades 2, 3, 5, 6, 7, and 8. Phage susceptibility profiles were determined using 23 bacteriophages, assessing plaque morphology. Using the O157:H7 genomes, a genomic analysis was conducted with the Prokaryotic Antiviral Defense Locator (PADLOC), which identified putative phage defense systems through sequence homology. Additionally, 5 RB-TnSeq libraries were generated in representative strains to study loss-of-function mutations. These libraries will be screened against a subset of diverse phage to identify the receptors involved in phage adsorption. Results/Anticipated Results: The phage resistance patterns showed susceptibility varied across clades, suggesting distinct mechanisms. Several defense systems were identified using PADLOC, including restriction-modification, Cas, Lamassu, and Druantia. Phage defense candidate (PDC) systems were identified, showing homology to known systems, though their specific function remains unknown. Clade 7.2 exhibited higher phage resistance and a greater presence of PDCs compared to the other clades. Five saturated RB-TnSeq libraries were constructed in O157:H7, achieving 84.5–89% gene coverage. These libraries will facilitate the identification of receptors involved in phage adsorption and resistance. Discussion/Significance of Impact: This study deepens our understanding of phage resistance in E. coli O157:H7 by identifying key defense systems and receptors. The discovery of novel antiviral mechanisms offers promising targets for phage-based interventions, potentially enhancing strategies for controlling this dangerous pathogen.

Objectives/Goals: Evaluate the effectiveness of ChatGPT as a complementary tool for addressing the mental health needs of Hispanic LGBTTQI+ young adult patients. We will also explore the experience of clinical healthcare providers with the integration of ChatGPT as a complementary tool in psychotherapy with Hispanic LGBTTQI+ young adults. Methods/Study Population: In this mixed-method study, we will create hypothetical clinical cases that reflect common mental health challenges experienced by LGBTTQI+ Hispanic population. These cases will be presented to three groups: 1) ChatGPT app, 2) clinical mental health care providers, and 3) clinical mental health care providers collaborating with ChatGPT. Each group will provide a diagnosis and a treatment plan based on the case information. A panel of experts will evaluate each plan using a standardized rubric to provide a score on clinical accuracy and on the ability to address specific needs of Hispanic LGBTTQI+ patients. Statistical analysis will be used to evaluate the differences in the scores of each domain and qualitative content analysis to evaluate the experience of clinical mental health care providers using ChatGPT. Results/Anticipated Results: The results will provide evidence of the effectiveness of ChatGPT as a supportive tool in mental health care. We anticipated that the combination of a clinical mental health care provider and ChatGPT to develop a diagnosis and treatment plan would produce better outcomes than either ChatGPT or the clinical mental health care provider working independently. We will also expect to find a positive attitude toward the integration of ChatGPT applications, viewing them as useful tools that complement traditional psychological interventions for Hispanic LGBTTQI+ young adults. The study will provide evidence of the effectiveness of ChatGPT to complementing clinical practice involving Hispanic LGBTTQI+ young adults. Those results in a preclinical phase are preconditions to a more applied intervention. Discussion/Significance of Impact: We aim to improve the quality of life for LGBTTQI+ Hispanics by developing innovative psychological treatments enhanced by AI apps. By developing innovative treatments, we are addressing and mitigating health disparities within the LGBTTQI+ Hispanic community in Puerto Rico and contributing to a broader effort of inclusivity and health equity.

Objectives/Goals: Clinical relevance of preclinical animal models is commonly in question. Herein, we investigated locoregional tumor immune microenvironment (TIME) differences in tumor-bearing murine oral cancer models, unresponsive to traditional immunotherapy, and also developed an oral tumor resection model to ultimately enhance translational relevance. Methods/Study Population: Here, we utilized carcinogen-induced, HPV-negative preclinical oral cancer models. For TIME studies, ROC1 cells were maintained as published. ROC1 tumors were established in the murine flank and oral cavity of wildtype C57Bl/6 mice, and tumor growth kinetics were assessed at each site. At distinct stages of tumor growth, tumors were harvested, as well as their respective corresponding inguinal and cervical tumor-draining lymph nodes (tdLNs). Multiparameter 28-marker spectral flow cytometry was performed to analyze immune cell populations at each site. For tumor resection studies, MOC2 tumors were similarly maintained and established in the oral cavity. MOC2 tumors were accessed via midline transcervical incisions. Upon tumor excision, wounds were closed with multiple interrupted Vicryl sutures. Results/Anticipated Results: We anticipated no differences between heterotopic and orthotopic tumor sites. Both sites displayed an initial period of delayed ROC1 tumor growth followed by rapid progression. Comprehensive analyses revealed low T cell infiltration overall and increases in select myeloid cells (i.e., macrophages and dendritic cells) over time in both models. Other immune cell types, however, generally increased over time in the flank. Differences between corresponding tdLNs further indicate deviating changes in immunosuppressive phenotypes (i.e., regulatory T cells and macrophages) and immune checkpoint marker expression. Additionally, MOC2 oral tumors were successfully resected with no visible remaining tumor. No subsequent healing complications were observed, and tumor recurrence occurred within 1 week post-surgery. Discussion/Significance of Impact: Tissue-specific TIME and tdLN differences may impact antitumor treatment and response. Ability to resect orthotopic tumors allows for modeling of standard-of-care treatment for oral cancer. These studies can enable tailoring of therapeutic strategies and provide insight into model selection and data interpretation from translational studies.

Objectives/Goals: The neighborhoods children grow up in are critical drivers of social, emotional, and cognitive development. This study utilized factor scores of environment, education, and socioeconomic variables in the Adolescent Brain Cognitive Development Study (ABCD) and its association with cognitive functioning in youth. Methods/Study Population: This study used ABCD (n  =  9,543) linked external data, cognitive performance, and self-reported data from youth (ages 9–10) and their caregivers. We utilized four factor scores of the Child Opportunity Index 2.0 (COI), including socioeconomic attainment, poverty, neighborhood enrichment, and child education. Furthermore, this study investigated the association between the COI factors and youth cognitive functioning via the NIH Toolbox. Covariates included age, sex, county level crime rates, perceptions of neighborhood threat, parent education, and family income; site and family relationship were held as random effects. Results/Anticipated Results: Increased Socioeconomic Attainment and Child Education factor scores were distinctly associated with increased cognitive performance across all subscales and composite scores that include aspects of overall cognitive ability, executive functioning, and learning and memory. Increased poverty factor scores were significantly associated with decreased cognitive performance across all substances and composite scores. Finally, increased neighborhood enrichment factor scores were significantly associated with increased oral reading recognition task scores only and no other cognitive task. Discussion/Significance of Impact: Findings suggest distinct dimensions of neighborhood opportunity associated with aspects of cognition. The present study can help to inform public health efforts and policy on improving modifiable built and natural environmental structures that may aid in supporting cognitive development.

Objectives/Goals: To describe the evaluation processes of screening services implemented in community pharmacies. Methods/Study Population: A systematic literature review will be conducted from the last 20 years in Ovid Medline, APA PsycINFO, Clinialtrials.gov, and International Pharmaceutical Abstracts. Inclusion criteria are written in English, describes a clinical or health-related screening service in a community pharmacy, and evaluation of said health screening service is included. Approximately 950 articles have been initially identified. Two authors will screen each title, abstract, and full text for inclusion. Subsequent data extraction will occur including elements of 1) evaluation framework, 2) evaluation outcomes assessed, and 3) evaluation results. All elements of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist will be followed. Quality of articles will be assessed using the MMAT. Results/Anticipated Results: Results are expected to show limited evaluation of screening services in pharmacies. Clinical conditions included in the screening services are expected to vary greatly. High-quality evaluations will be noted as templates for future evaluation of screening services in community pharmacies. Discussion/Significance of Impact: This systematic review will describe the current literature on evaluation of health screening services in community pharmacies. This will give readers an overview of how evaluations are currently being carried out in this setting, as well as provide them with templates of high-quality evaluations for future evaluation of screening services.

Objectives/Goals: We hypothesized that adding cytomegalovirus (CMV) viral Fc gamma receptors (vFcγRs) to a glycoprotein B (gB) protein subunit vaccine would improve vaccine-elicited Fc mediated effector functions such as antibody dependent cellular phagocytosis (ADCP) and cytotoxicity (ADCC), over gB subunit alone. Methods/Study Population: We immunized rabbits (n = 4 per group) at Weeks 0, 4, and 8 with 20μg gB alone or with one vFcgR (gp34, gp68, or gp95) at 20μg or 40μg, adjuvanted with squalene emusion, Addavax. Plasma from immunized rabbits was analyzed for antigen-specific IgG binding via enzyme-linked immunosorbent assays (ELISAs). ADCP was measured by conjugating whole virions to a fluorescent marker (AF647), incubating the fluorescent virus with rabbit plasma, and measuring uptake of virus by THP-1 monocytes via flow cytometry. ADCC was measured by natural killer cell degranulation via flow cytometric detection of CD107a expression following co-incubation with CMV-infected fibroblasts and rabbit plasma. Results/Anticipated Results: Each vFcγR demonstrated immunogenicity, although average vFcγR-binding IgG titers were between 4- to 10-fold higher in animals receiving the 40μg dose of each vFcγR compared to the 20μg dose. We observed similar IgG binding responses against gB among all vaccine groups. Comparing groups at peak immunogenicity (Week 10), ADCP responses were improved over gB alone by approximately twofold in animals receiving 40ug of each vFcγR. This effect was maintained across several human CMV strains with variable vFcγR genes. ADCC responses were undetectable in all animals immunized with gB alone, yet those receiving 40μg gp34 or gp95 demonstrated detectable ADCC. Discussion/Significance of Impact: HCMV-specific ADCP and ADCC are associated with protection against vertical CMV transmission, so a vaccine including vFcγRs which can improve vaccine-elicited Fc-effector responses is promising toward reducing the immense global impact of congenital CMV and associated neurologic birth defects.

Objectives/Goals: Given the challenges that early career research scientists face, especially preparing for promotion and tenure, the decision on whether to join a research team can be fraught. We developed a novel training to support informed decision-making regarding new scientific teaming opportunities. Methods/Study Population: A team science workshop entitled “Should I join this research team” was designed for early career investigators from varied disciplinary backgrounds. Learning objectives for attendees included 1) describing the role of team science in translational research, 2) determining if teaming opportunities are a good fit, and 3) crafting thoughtful responses to requests. The training was initially delivered to 38 attendees (11 K scholars) during a virtual national meeting. We adapted this training for in-person delivery to K and T scholars at our CTSA regional partners. Instructional methods shared across virtual and in-person modalities included self-reflection, think and share activities, and scenario application. In-person delivery also included short video clips and small group discussions. Results/Anticipated Results: Multiple Likert-scale items were completed by workshop participants before and after completing the workshop to evaluate attendees’ confidence in their perceived abilities to explain strengths and limitations of team science, identify characteristics of effective science teams, evaluate a team invitation, assess costs and benefits, negotiate collaborative team invitations, etc. Preliminary data from the virtual workshop suggests that 54.6% of scholars were either not at all or only slightly confident in evaluating a teaming invitation. After the workshop, 45.5% reported being very confident, and 9.1% reported extreme confidence in evaluating a team invitation. Evaluation of the in-person training, along with a comparison of virtual and in-person learning outcomes will also be presented. Discussion/Significance of Impact: Our multimodal training is designed to equip early career investigators with the tools needed to evaluate and respond effectively to research team invitations. We believe this novel training will result in informed teaming decisions for early career research scientists.

Objectives/Goals: Planning research studies can be daunting for early-career investigators. The UW Madison Institute for Clinical and Translational Research (ICTR) has many services to assist, but navigating them can be convoluted. Therefore, we developed a method to streamline services for investigators. Methods/Study Population: Investigators were reaching out to ICTR research support services for assistance in the wrong order, delaying their study progress. To streamline ICTR services and improve investigator support, we developed the ICTR COllaborative Network (ICON) that meets weekly to discuss investigator needs and how best ICTR services can assist them. This group consists of members from ICTR’s Research and Protocol Development Program, the Recruitment and Retention Resource Center, and the Collaborative Center for Health Equity. After discussion and decision-making, a member of the group schedules a studio, bringing key services together at one time to help investigators more efficiently. Results/Anticipated Results: The group has worked with 22 investigators, decreasing the time to study implementation. One investigator indicated ICON saved her team over four months of work. Other investigators indicated the assistance with finding community partners and collaborators was essential to their success. We expect ICON, with its goal to streamline regulatory submissions and study planning, will continue to help investigators improve organization during study start up and execution, while enhancing recruitment strategies. This will result in quicker study completion and the capability to move forward with future projects and grant submissions. Discussion/Significance of Impact: ICON streamlined the consult process, improved efficiency of study planning, and brought together various experts for studio meetings with investigators. This efficient method can improve study function and execution for early-career investigators resulting in improved study success.

Objectives/Goals: Substantial evidence supports the use of community engagement in CTS. Yet, there is a lack of empirical basis for recommending a particular level of community engagement over others. We aimed to identify associations between level of community involvement and study process outcomes, focusing on procedures to promote enrollment and inclusion. Methods/Study Population: Using manifest content analysis, we analyzed community engagement (CEn) strategies of studies indexed in ClinicalTrials.gov, focusing on studies 1) associated with 20 medical schools located in 8 southern states in the Black Belt, 2) conducted in 2015–2019, and 3) on 7 topics: cancer, depression, anxiety, hypertension, substance use disorder, cardiovascular disease, and HIV/AIDS. Data source was the ClinicalTrials.gov entry and publication for each study. We categorized each study on level of community involvement as described by the study protocol CTSA Consortium Community Engagement Key Function Committee Task Force on the Principles of Community Engagement continuum. Outcomes included recruitment and representativeness. Other codes included funder type, study phase, study status, and time to enrollment. Results/Anticipated Results: Of 890 studies that met inclusion criteria, only 493 had published findings. 286 studies (58%) met enrollment targets. Only 9 studies described any level of CEn (1 outreach, 3 consult, 1 involvement, 3 collaboration, and 1 shared leadership). Time to enrollment for these 9 studies (mean 28.78 mos.) was shorter than for studies without CEn (mean 37.43 months) (n.s.). CEn studies reached significantly higher enrollment (CEn mean  = 2395.11, non-CEn mean  = 463.93), p Discussion/Significance of Impact: Results demonstrate the substantial effect of CEn on enrollment and inclusion in clinical studies. However, the infinitesimal number of studies that reported CEn did not allow comparisons of level of engagement on the outcomes. Findings highlight ethical questions surrounding the lack of publishing incomplete studies.

Objectives/Goals: Rural disparities in chronic disease burden are well documented. However, the impact of individual socioeconomic status on these rural disparities in prevalence and control status of chronic diseases remains less understood. We aim to assess the association of prevalence and control status of chronic diseases among adults with rurality and socioeconomic status (SES). Methods/Study Population: The Expanded Rochester Epidemiology Project medical records linkage system identified prevalence of asthma, diabetes, hypertension, and mood disorder using ICD codes between 2014 and 2019 among adults in 27 Upper Midwest counties. Uncontrolled status was defined by presence of ED visit or hospitalization with corresponding ICD-9/10 codes. SES was measured by HOUSES index, a validated individual-level SES measure, and rural status was defined by primary Rural Urban Commuting Area codes of 4–10. Hierarchical logistic regression models were used to examine the association of rurality with prevalence and control status of the four chronic diseases, adjusting for age, sex, race/ethnicity, and presence of general medical exam extracted by CPT codes (Model 1) and additionally SES measured by HOUSES (Model 2). Results/Anticipated Results: Among 455,802 adults, 42.8% were rural residents and 87.4% were Non-Hispanic White. Model 1 (without HOUSES) showed higher prevalence and lower control rates of chronic diseases in rural residents, except for asthma. In Model 2, accounting for SES, urban residents were more likely to have an uncontrolled mood disorder, hypertension, and diabetes, and there were no differences in prevalence of chronic diseases that existed between rural and urban residents. Lower SES measured by HOUSES was consistently and significantly associated with higher prevalence and uncontrolled status of chronic diseases (p-value Discussion/Significance of Impact: Patient’s SES explains rural disparities in prevalence (null association with rurality once SES is accounted) and changes the directionality of association for uncontrolled status in Upper Midwest, highlighting the importance of considering SES in rural disparities research.