Objectives/Goals: Pancreatic ductal adenocarcinoma (PDAC) is a deadly disease with a mean survival of only 11 months even with the most advanced treatment to date. The desmoplastic microenvironment of PDA is thought to play a critical role in therapy resistance. One pathway that might be responsible for resistance to immunotherapy is the CXCR4-CXCL12 axis. Methods/Study Population: In this study, we propose to evaluate the effect of CXCR4-CXCL12 inhibition on dual checkpoint inhibition in KPC mouse model of PDAC and patient-derived explants. PDAC mouse models are made with pancreatic cancer cells driven by loss of TP53 and activation of KRAS. These models are treated with PD1 inhibitor Balstilimab and an FC-modified CTLA4 Botensilimab with or without CXCR4 inhibitor BL8040. In addition, we make explants of patient tumors along with their tumors and autologous peripheral blood mononuclear cells and this model is similarly challenged with BOT/BAL and BL8040. Using immunofluorescence and flow cytometry, we quantify and evaluate the spatial relationships between different cell populations. Most notably, we evaluate the relative abundance of CD8+ T cells in control and treated conditions. Results/Anticipated Results: We expect the inhibition of CXCR4-CXCL12 axis, along with two new potent checkpoint blockers, will lead to infiltration of CD8+ T cells in both the mouse and human PDAC models. We also expect this to translate into more tumor cell killing as demonstrated by Caspase activities and tumor shrinkage. Discussion/Significance of Impact: If our hypothesis is proven in both mouse and human PDAC models, this study will serve as a basis for a phase I/II clinical trial testing this combination of drug.

Objectives/Goals: To develop a personalized computational framework integrating computational fluid dynamics (CFD) and topology optimization for designing intracranial aneurysm implants. The primary objective is to reduce intra-aneurysmal blood flow velocity and enhance thrombus formation for improved treatment outcomes. Methods/Study Population: Patient-specific aneurysm geometries were extracted from pre-treatment rotational angiograms. A CFD-driven topology optimization framework was employed to design implants that reduce intra-aneurysmal flow velocity. The fluid dynamics were modeled using Navier–Stokes equations and the structural integrity of the implants was ensured by linear elasticity equations. The solid isotropic material with penalization (SIMP) method was applied to optimize the implant’s porous architecture, balancing flow reduction with structural support. COMSOL Multiphysics software was used to implement the optimization. Results/Anticipated Results: The optimized implants demonstrated significant reductions in intra-aneurysmal blood flow velocity and improved hemodynamic conditions. Flow velocity within the aneurysm was reduced by 77%, and the fluid energy dissipation ratio showed a 78.9% improvement compared to pretreatment conditions. The optimized porous structures were tailored to the aneurysm’s specific geometry, providing personalized designs that improve flow stasis and thrombus formation. Further validation of the implants will be performed in vitro and in vivo to assess their effectiveness and biocompatibility. Discussion/Significance of Impact: This personalized implant design framework could lead to better treatment outcomes by reducing aneurysm recurrence and complications compared to current devices. It provides a pathway for improved occlusion rates and patient-specific solutions for intracranial aneurysms.

Objectives/Goals: Adolescence is a critical period where brain networks are thought to be influenced by environmental factors. This presentation examines violence exposure’s impact on brain connectivity and identifies potential protective factors. Methods/Study Population: A secondary data analysis was conducted using data from a subsample of the Adolescent Brain Cognitive Development Study (release 5.1). Youth who completed victimization questionnaires at two time points were eligible for inclusion, resulting in 2016 participants. Linear regression was utilized to analyze associations between violence exposure measured by the juvenile victimization questionnaire and functional connectivity of specified regions of interests using the Gordon functional parcellation for cortical regions and the Freesurfer parcellation for subcortical regions. Moderation analysis will be utilized to assess the effects of peer and caregiver support on the associations between violence exposure and functional connectivity, currently ongoing. Results/Anticipated Results: Between 18 and 59% of the sample reported experiencing at least one form of violence exposure, with racial differences noted in missing versus complete data. Multiple domains of violence and cumulative exposure were associated with both increased and decreased functional connectivity across within-network, between-network, and network-subcortical regions. At baseline, internet violence was linked to lower within-network connectivity, while peer victimization was associated with higher connectivity at both baseline and follow-up. Between network analysis showed lower connectivity with witnessing violence at baseline and higher connectivity with internet victimization at follow-up. Discussion/Significance of Impact: These findings emphasize the need for further exploration of the underlying mechanisms that link violence exposure to developmental trajectories and identification of protective factors such as caregiver and peer support, to inform interventions and promote resilience in affected youth.

Objectives/Goals: To explore how generative AI and chatbot technologies can transform clinical research administration by improving operational efficiency, reducing administrative burden, and thereby enhancing overall productivity and accuracy in clinical research environments. Methods/Study Population: This explores AI’s application in enhancing clinical research administration. We specifically address AI’s role in QCT/MCA activities, charge master data cleaning, and generating IRB consent forms from award documents. AI algorithms optimize charge master data for accuracy and compliance. Generative AI models are employed to produce IRB consent forms efficiently, incorporating key grant documents. AI also conducts thematic analyses of historical CTSA aims to identify trends and recurring themes. Furthermore, AI-assisted tools enhance study design through innovative approaches to hypothesis generation, sample size calculation, and protocol development. Integrating these AI methods aims to significantly improve efficiency, accuracy, and overall quality in clinical research administration. Results/Anticipated Results: Incorporating AI into clinical research administration will yield improvements in efficiency and accuracy. AI-driven QCT/MCA steps are expected to reduce human error and enhance data integrity. Chargemaster data cleaning via AI prompts will likely result in optimized, error-free data, ensuring compliance with regulations. The use of genAI for creating IRB consent forms from grant documents should significantly streamline the IRB approval process, reducing preparation time and administrative burdens. Thematic analysis of CTSA aims by AI will provide deep insights into historical trends and recurring themes, aiding in strategic planning. AI-assisted study design tools are anticipated to optimize sample estimation, protocol development, and advance the quality of clinical research administration. Discussion/Significance of Impact: The significance lies in enhancing efficiency, accuracy, and quality in clinical research administration. By streamlining processes, reducing errors, and providing strategic insights, AI supports the CTSA mission to accelerate translational research, thus improving public health outcomes and scientific innovation.

Objectives/Goals: Using secure systems for sharing documents with external collaborators is essential for all researchers. These documents may include protected health information (PHI) or sensitive materials like protocols, study reports, DSMB reports, publications, presentations, abstracts, and statistical analysis plans (SAPs). Methods/Study Population: We surveyed the ACTS Biostatistics, Epidemiology, and Research Design Special Interest Group (BERD-SIG) to gather information about the systems they are currently using or have used in the past for document sharing with external collaborators. The survey focused on the security of these systems, particularly in relation to sharing documents containing PHI. In addition, the survey included questions about various system features of interest. These features included version control, simultaneous editing by multiple users, and access rights management, such as the ability to assign different permissions (e.g., read-only, write, and download) to different individuals. We also invited participants to provide feedback on any additional positive or negative aspects of the systems they use. Results/Anticipated Results: We received 28 completed survey responses. Respondents had an option for choosing more than one system. The top current systems reported were Microsoft Teams (OneDrive, SharePoint) (n = 16), Box (n = 11), Google Docs/Drive (n = 10), and Dropbox (n = 6). Among other systems listed individually were Filelocker, REDCap, Slack, Website, Significant Media Shuttle, and Zulip. Notably, 15 responses indicated the respondents were unsure if their system is secure for sharing documents containing PHI. Respondents also offered feedback on both the positive and negative aspects of these systems. For example, a key advantage of Box was its password-controlled access. However, its incompatibility with office tools and the challenges for external collaborators attempting to access the system were noted as drawbacks. Discussion/Significance of Impact: Utilizing secure institutional document-sharing systems and understanding their features significantly affects the effectiveness and security of collaborations among researchers, particularly with external partners. This knowledge is especially crucial when sharing documents containing sensitive patient and study data.

Objectives/Goals: Patients with multiple chronic conditions (MCCs) face care coordination challenges and poorer health outcomes. Outpatient telehealth may be an effective way to enhance MCC patient care given the need for multiple visits and specialists. This study seeks to describe telehealth utilization between 2013 and 2023 in Arkansas. Methods/Study Population: We utilized the Arkansas All-Payer Claims Database (APCD) to identify patients diagnosed with high-prevalence MCCs comprising diabetes with comorbid hypertension, hyperlipidemia, or asthma. We then measured telehealth utilization defined as any claim associated with a telehealth modifier code, a place of service code defining the service as occurring in the patient’s home, or remote patient monitoring. Finally, we created payer-specific (e.g., commercial or Medicaid) yearly measures of the number of any telehealth claims among MCC patients divided by the number of MCC patients for that year. Linear regression was used to measure the difference in utilization during the COVID-19 pandemic (i.e., 2020–2023) versus prior to the pandemic (i.e., 2013–2019). Results/Anticipated Results: Overall, the COVID-19 pandemic era was associated with an increase of telehealth utilization among commercial patients by 1.01 telehealth claims per MCC patient (95% CI: 0.39 to 1.62, p Discussion/Significance of Impact: Variations in telehealth uptake among MCC patients suggest heterogeneity in its suitability and necessity. We will later evaluate whether telehealth use is associated with different levels of inpatient and emergency department utilization. We expect the findings to provide clarity on the suitability of telehealth use by MCC disease status.

Objectives/Goals: Professional coaching greatly enhances faculty personal and professional development through fostered empowerment and a culture of continuous growth within the academic environment. The UMN Clinical and Translational Science Institute (CTSI)’s coaching program provides a variety of coaching formats (1:1, group, special programs). Methods/Study Population: CTSI provides professional coaching to faculty in the KAP, K12, KL2, and K-R01 and NLITeS programs. Typically, coaching begins with a HoganLead™ assessment and debrief. Scholars may pursue further coaching through individual sessions (up to 6 sessions during or 1-year post CTSI award) or a monthly peer coaching group facilitated by certified coaches. New URM faculty hires in the Early Career Research Awards (ECRA) program receive monthly coaching support to problem solve and attend to wellbeing. The NLITeS leadership development program for senior and mid-career faculty includes the HoganLead debriefing and 1–2 individual coaching sessions. All sessions are confidential. Results/Anticipated Results: Since 2016/2017, 80 scholars have taken the HoganLead assessment (72 debriefs), and 23 scholars have made use of 217 individual coaching sessions (most use between 6 and 12). Since 2021, 10 Scholars have participated in the Peer Coaching Group with 7 continuing over multiple years. Since 2021, 12 ECRA scholars have been supported in monthly coaching. Frequent coaching topics include self-awareness, work-life balance, overwhelm, negotiation, and leaving academic medicine. Scholar comments include: “I initially approached this professional coaching with some curiosity but fairly minimal expectations that it would change much. It has reshaped the way I approach my academic career and its associated challenges for the better, giving me confidence that I can handle the unique challenges that this career presents…” Discussion/Significance of Impact: The UMN CTSI coaching programs are extensively used and highly valued by participating faculty. Professional coaching with Hogan assessments provides faculty scholars with support that complements the mentoring they receive by going beyond a teach and learn model.

Objectives/Goals: Delving into the intricate web of translational research collaborations, this study analyzed the evolving landscape of the Hispanic Alliance of Clinical and Translational Research from 2020 to 2024 using cutting-edge social network analysis (SNA). SNA is a powerful tool for visualizing, understanding, and harnessing the power of networks. Methods/Study Population: We conducted a systematic document review of all the Alliance IDeA-CTR Network Calls for Pilot Projects from 2020 to 2024 including key attributes of the investigators and collaborators (e.g., academic institution, highest degree, collaborator type). Scientific collaboration was defined as two or more researchers working together in a grant proposal for a pilot project application. Study data was recorded and tracked using an Excel spreadsheet. R-Statistical software was used to analyze and map the networks resulting from collaboration interactions comparing the 2020 Call and 2024 Call. Network statistics were performed including nodes, isolates, edges, components, density, diameter, average degree, and the size of the main component. Results/Anticipated Results: Within a vibrant network comprising over 150 investigators from local and national academic institutions, clinicians (49.3%), and basic researchers (25.4%) are predominant. Initial findings showcase a remarkable surge in interdisciplinary collaborations and affiliations over time. Preliminary findings demonstrated that the number of nodes/actors increased from 16 to 75 comparing 2020 to 2024 and the edges/relationships from 12 to 66. Notably, the number of translational research clusters surged from 4 to 18, with mentorship emerging as a critical conduit bridging diverse research clusters; 16 to 78 nodes in comparison from 2020 to 2024. More extensive collaborative clusters occurred across time with over 20 researchers collaborating. A mentor was the main actor connecting these research clusters. Discussion/Significance of Impact: This study unveils the intricacies and power of translational research dynamics, showing a palpable surge in collaboration diversity and depth. By harnessing data-driven insights, our approach catalyzes informed decision-making to amplify collaboration, diversity, and network efficacy, offering invaluable guidance for policy and practice.

Objectives/Goals: The goal of the Accelerated Staff Assist Program (ASAP) is to help fill staffing gaps in clinical and translational research. The program offers centralized staff to fill short-term needs including project startup prior to hiring, project implementation, parental leave, and Spanish-language research support. Methods/Study Population: Promotion of ASAP in the first year was targeted to Penn State College of Medicine faculty to determine demand. Current outreach includes promotion to all Penn State campuses through PSCTSI’s newsletter, seminars, and presentations. Consultation intake data includes a project summary, staffing needs, and funding information. A project agreement, charter, and budget are drafted and agreed to by the principal investigator before work begins. Assessments occur at 6 and 12 months to assess satisfaction of the consultation process and quality of staff support, Net Promoter Score, and qualitative feedback about the program. Results/Anticipated Results: In its first year, ASAP conducted 26 consultations and supported 10 projects. Approximately 75% of staff effort has been recovered through agreements during the most recent 6 months. In anticipation of project delays, we found that booking FTE up to 115% results in a consistent recovery of 75% FTE. Consultee needs include short-term, partial effort support (76% of requests), project start-up (12%), staff leave (4%), and other (8%). ASAP staff tasks include participant recruitment and retention, data collection and analysis in English and Spanish, and community engagement for recruitment. Program assessments with research teams are ongoing; preliminary qualitative and quantitative data are unanimously positive. Discussion/Significance of Impact: The ASAP program has demonstrated fiscal success and sustainability in its first year. Hiring of a well-qualified, bilingual staff person allowed for quick onboarding and project support within one month of hire. ASAP enables CTSI to fulfill our mission by providing critical support for research teams to meet objectives and achieve equity goals.

Objectives/Goals: Port-site metastasis (PSM), defined as the spread of malignancies to the abdominal wall at the site of surgical ports, poses a significant challenge in cancer management. The objective of this summary overview is to describe the prevalence of and risk factors associated with PSM in various gynecological cancers after laparoscopic surgery. Methods/Study Population: Study design: Systematic Review and Meta analysis Search strategy: All international databases, without language limitations, from January 1990 to December 2023. Inclusion/exclusion criteria: Cohort, case–control, or cross-sectional observational studies reporting the frequency of, or risk factors for PSM in young and middle-aged women will be included (using the PRISMA checklist). Data extraction: two reviewers independently extracting pertinent data (using the STROBE checklist). Quality assessment and risk of bias: The quality of each study will be assessed according to the Quality Assessment Tool for Observational Studies. Results/Anticipated Results: This meta-analysis of 36 studies evaluated the proportion of successes across various populations, with a pooled proportion of 0.02 (95% CI: 0.01–0.02) based on a random-effects model. Significant heterogeneity was identified (I²  =  88.12%), reflecting notable variability between studies. Despite this, the overall effect was statistically significant (p  =  0.00). A subgroup analysis will be conducted to explore potential sources of heterogeneity, considering factors such as cancer stage, diagnostic methods, surgical approach (conventional or robotic), and study type (retrospective/prospective). Discussion/Significance of Impact: By identifying the prevalence of, and the risk factors for, PSM, this study will better inform personalized treatment approaches, surveillance strategies, and surgical decision-making to improve patient-related outcomes and long-term survival in women with gynecological malignancies.

Objectives/Goals: The overarching goal of the GRAMM study is to address racial health disparities by increasing access to genetic counseling and testing among the Black community. Specific objectives are to determine patient acceptability of risk assessment at time of mammography and to evaluate subsequent access to and uptake of genetic counseling and testing. Methods/Study Population: All women presenting for screening mammography at the Ypsilanti Health Center under the University of Michigan were invited to enroll. After providing written informed consent, study participants entered family cancer and personal health information in the InheRET software tool which links to the National Comprehensive Cancer Network genetic testing guidelines. Upon completion, each participant was informed immediately if they did or did not meet the criteria to meet with a genetic counselor. For those who met the criteria, referral to genetic counseling was provided. All enrollees were invited to complete a post-assessment survey on acceptability of the service and genetics knowledge. Patients will be followed over time for completion of genetic counseling and testing. The study was approved by the Umich IRB. Results/Anticipated Results: As of 10/18/24, a total of 53 were enrolled, with 52 eligible for the study and were between the ages of 30–75 years. 51 identified as women and 1 identified as nonbinary. 21 (40.4%) identified as Black, 30 (57.7%) identified as White, 2 (3.8%) identified as Hispanic, and 1 (1.9%) identified as mixed race. Of the total enrolled, 25 (48.1%) met criteria to meet with a genetic counselor. Twelve (23.1%) have been scheduled to with meet with a genetic counselor and 2 (3.8%) of this group completed their appointment, but did not pursue genetic testing. 28 (53.8%) completed the survey and reported that they were satisfied with the service. Of the 16 people who screened positive and completed the survey, all 16 (100%) stated that they intended on proceeding with testing. Our study is still ongoing. Discussion/Significance of Impact: While this model has demonstrated acceptability so far, there are still possible barriers to genetic counseling and testing after the referral has been provided that need to be explored. However, this approach could provide a novel framework for combining risk assessment with screening mammography for all women nationwide.

Objectives/Goals: Engage the research professional (RP) workforce in assessing job satisfaction, motivators, barriers, and levels of support throughout the research enterprise. The goal of this collaboration is to foster a positive culture, inform manager training, ensure RP retention, and enhance career mobility pathways. Methods/Study Population: Methods include a HR data compilation/analysis and focus groups for new RP’s (Results/Anticipated Results: This initiative will articulate the current culture and climate of the research enterprise and identify key strategic areas for growth. The UMN Clinical and Translational Science Institute (CTSI) will build off the design of an internal survey at Vanderbilt (2018) to encompass organization-specific challenges, the post-pandemic research landscape, and the UMass Diversity Engagement Survey. This process will also generate specific insights including RP sentiment statements, trends in how RP’s describe their day-to-day work, assessment of barriers, analysis of retention benchmarks, and defining employee hopes/motivators. The CTSI will also identify salient RP growth opportunities, leadership competencies, and areas of non-monetary compensation to improve satisfaction and career mobility. Discussion/Significance of Impact: Targeted interventions will be developed to address RP satisfaction barriers and leverage opportunities for KPI improvement. Results will be disseminated to managers, administrators, and the CTSI network. Resource development will include RP personas, job description/hiring templates, and strategic guides for key operational challenges.

Objectives/Goals: To determine the heterogeneity in CD4:CD8 ratio in a well-characterized cohort of PWH and to investigate the predictors of intestinal CD4:CD8 ratio reconstitution (CD4:CD8>1) and its impact on systemic inflammation. Methods/Study Population: We enrolled 52 PWH on ART and with peripheral HIV-RNA Results/Anticipated Results: PWH had a lower CD4:CD8 ratio both in the peripheral blood [p1. This subset of PWH was more likely female (62% vs. 38%, p = 0.0158), diagnosed with HIV for a longer time [p = 0.0347] have longer duration of most recent viral suppression [p = 0.0365] higher CD4+ T cells at enrollment [p =  0.0262] and higher CD4+ T cell nadir. Multiple logistic regression showed that duration of HIV infection [OR 1.13 (95% C.I. 1.02–1.3)] and CD4 =  T cell nadir[OR 1.01 (95% C.I. 1.001–1.016)] were associated with colonic CD4:CD8 >1. Colonic CD4:CD8 ratio partially correlated with the peripheral blood CD4:CD8 ratio (r = 0.274, p = 0.068) and with the pro-inflammatory cytokines IL-20 (r =  -0.413, p = 0.036) and SLAMF-1 (r =  -0.329, p = 0.074). Discussion/Significance of Impact: In PWH, CD4:CD8 ratio

Objectives/Goals: To assess the feasibility, safety, and preliminary efficacy of implementing a supervised, outpatient aerobic and strength exercise regimen in newly diagnosed pediatric patients with acute lymphoblastic leukemia (ALL). We hypothesize that early implementation of exercise is feasible and may prevent well-known cardiometabolic late effects. Methods/Study Population: We will enroll 10–20 children (both males and females) with newly diagnosed ALL between the ages of 11–21 years to participate in a 12-month supervised, structured outpatient exercise regimen (STRONGER ALL). This regimen will consist of low- to moderate-intensity aerobic and strength exercises (either in person or coached virtually per patient preference) 3 times a week. This study will include 2 physical fitness assessments: 1) baseline and 2) end of study. Assessments will include resting energy expenditure, peak oxygen uptake, bone density, upper and lower extremity strength, flexibility, and questionnaires (feasibility and quality of life). Additionally, blood and urine specimens will undergo metabolomic analysis to identify biomarkers predictive of future cardiometabolic outcomes. Results/Anticipated Results: We expect that early implementation of STRONGER ALL in children undergoing chemotherapy will be feasible and preliminarily effective at mitigating risk factors for long-term cardiometabolic outcomes in survivors. Feasibility will be defined by recruitment capability (at least 50% of eligible patients agree to enroll), acceptance/compliance (at least 50% of participants complete the program with participation in at least 50% of sessions), data acquisition (collection and outcomes measures are appropriate), and practicability (program shows promise of being successful with pediatric ALL patients as measured by validated surveys administered to patients and caregivers). We anticipate that ALL patients participating in STRONGER ALL will have improved fitness and quality of life. Discussion/Significance of Impact: Evidence on the benefits of physical activity for ALL patients has not changed clinical practice. We aim to overcome the translational science barrier of patient- and system-level blockade in implementation of exercise in children with ALL. The evidence generated from this research may also be generalizable to other childhood cancer survivors.

Objectives/Goals: Identifying and indexing rare disease studies is labor intensive, especially in research centers with a large number of trials. To address this gap, we applied natural language processing (NLP) and visualization techniques to develop an efficient pipeline and user-friendly web interface. Our goal is to offer the rare disease study identification (RDSI) tool for adoption by other sites. Methods/Study Population: The RDSI retrieves study information (short and long titles, study abstract) from the IRB system. These descriptive fields are then processed by the MetaMap Lite NLP program for identifying disease terms and standardizing them to UMLS concepts. By terminology identifier mapping, the diseases intersecting with concepts in rare disease databases (Genetic and Rare Disease program and Orphanet) are further scored to pinpoint studies that focus on a rare disease. The web interface displays a scatter bubble chart as an overview of all the rare diseases, with each bubble size proportional to the number of studies for that disease. In addition to the visual navigation, users can search studies by disease name, PI, or IRB number. Search results contain detailed study information as well as the evidence used by algorithms of the pipeline. Results/Anticipated Results: The RDSI identification results and functions were verified manually and spot-checked by several study investigators. The web interface is a self-contained solution available to our staff for various use cases like reporting or environment scan. We have built in a versioning mechanism that logs the date of each major result in the process. Therefore, even as the rare disease data sources evolve over time, we will be able to preserve any historical context or perform updates as needed. The RDSI outputs are replicated to Mayo Clinic’s enterprise data warehouse daily, allowing tech-savvy users to leverage any useful intermediate results at the backend. We anticipate the performance of the rare disease identification to be further enhanced by employing the advancements in AI technology. Discussion/Significance of Impact: The RDSI represents an informatics solution that offers efficiency in identifying and navigating rare disease clinical studies. It features the use of public databases and open-source tools, manifesting return on investment from the broad translational science ecosystem. These considerations are informative and adoptable by other institutions.

Objectives/Goals: We aim to predict and rank conserved, immunogenic targets within key malaria proteins using computational tools. These tools incorporate parasite protein diversity and regional HLA allele frequencies to prioritize antigens for further validation and inclusion in a malaria vaccine targeting circulating strains. Methods/Study Population: We identified 42 conserved malaria proteins with nonredundant functions for P. falciparum invasion and transmission as vaccine targets. Protein sequence datasets were constructed from samples collected in highly endemic areas. We predicted targets most likely to be presented to CD4+ and CD8+ T cells. We designed and used heuristic-based and AI-weighting models that integrated predicted binding affinities to HLA alleles, HLA allele frequency data, and sequence conservation to score and rank targets. We validated our model by comparing predicted epitope distributions with published in vitro and in vivo immunogenicity data available in the Immune Epitope Database and Tools repository. Results/Anticipated Results: We successfully predicted and ranked targets within the vaccine candidate proteins, identifying conserved and HLA-nonspecific targets that correspond to positive immunogenicity data, validating our approach. We are currently analyzing model performance by comparing predictions to over 5,800 experimentally validated P. falciparum targets from clinical trials and immune assays. We will evaluate each models’ accuracy and ability to prioritize targets and compare their performances as measured quantitatively by precision and area under the curve metrics. We expect the AI-based model to significantly outperform the heuristic approach, improving the identification of effective vaccine targets. Discussion/Significance of Impact: By incorporating parasite diversity and regional HLA allele frequencies, our approach addresses the challenge of directing the human immune response against genetically diverse P. falciparum strains in highly endemic areas. This strategy could significantly enhance malaria vaccine efficacy and can be adapted for use against other pathogens.

Objectives/Goals: To assess the effect on the immune response to COVID-19 in children exposed to pesticides. The hypothesis is that increased pesticide exposure results in different immunological response to COVID-19. The goal of the proposal is to improve scientific knowledge on factors affecting COVID-19 and identify a modifiable factor to reduce these disparities. Methods/Study Population: A cross-sectional analysis of children (aged 5–17 years) with asthma to assess pesticide exposure and immune markers of SARS-CoV-2. SARS-CoV-2 infection or vaccination was determined with blood exposome RNA analyses assessed from blood samples taken at baseline. Immunological response was measured using neutralizing, phagocytizing, and NK-activating antibody responses biomarkers using plasma antibody isotyping, effector functions, T-cell activation-induced marker (AIM), and recall cytokine secretion assays on lysed, whole blood. Pesticide exposure was assessed as concentration of four urinary metabolites in a spot urine sample adjusted for creatinine. Unadjusted regression models were created to assess the effect of 3-phenoxy benzoic acid, a common pyrethroid pesticide, on immune markers. Results/Anticipated Results: Children’s (N = 30) average age was 10 years (interquartile range: 8–11) A majority of children were male (63%) and Non-Hispanic Black (73%). The majority of children had markers of SARS-CoV-2 infection (77%). Of the 4 pesticide metabolites assessed, only 3-PBA was commonly found (77% of samples > LOQ). Higher urinary concentrations of 3-PBA are associated with a significant (p Discussion/Significance of Impact: Significant associations in cytokine and inflammatory marker may indicate a Th2-skewed response, and dysregulated cytokine responses can lead to severe disease. A suggested increase in T-cell activation markers (e.g., CD4, CD8) may indicate potential exhaustion if excessively activated.

Objectives/Goals: Summarize literature on parenting stress and treatment outcomes among postpartum women with opioid use disorder (OUD). Describe the causes of parenting stress identified by postpartum women who received medication for OUD (MOUD) and service providers. Discuss recommendations for parenting support services for postpartum women receiving MOUD in outpatient treatment settings. Methods/Study Population: We will conduct focus groups with postpartum women who received MOUD up to one-year after childbirth (2 groups; n  =  10) and service providers (e.g., obstetrics, psychiatry, pediatrics, primary care; 2 groups; n  =  10) to identify causes of and contributors to parenting stress to inform the adaptation of a parenting intervention for postpartum women receiving MOUD in an outpatient clinic setting. Participants will be recruited via flyers, email, and social media reach-outs, clinic staff and patient group meetings, and community-based outreach methods. Participants will be compensated for their participation. Focus groups will be audio-recorded and transcribed. Data will be analyzed via rapid analytic procedures using a summary template matrix. Results/Anticipated Results: We will use parenting-related stressors identified by mothers with substance use disorders in previous research to guide our interview questions. We expect to hear participants speak about their knowledge and experiences with stigma, guilt and shame, mental health symptoms, neonatal opioid withdrawal or neonatal opioid withdrawal syndrome (NOWS), fear of being reported to child protective services, and difficulties with mother–infant bonding and attachment. We will also ask participants about structural barriers that are known to increase parenting stress, such as housing instability, financial strain, and availability and cost of childcare. We will also report on new themes that emerge from the data that are shown to increase stress, challenge sobriety, and hinder continued engagement in the treatment. Discussion/Significance of Impact: Discontinuation of MOUD in the postpartum period is high and can lead to opioid recurrence and overdose. Outpatient treatment programs who offer psychiatric and behavioral health care, and parenting programs that target contributors of early postpartum parenting stress could improve health and MOUD treatment outcomes for mothers with OUD.

Objectives/Goals: Personalized cancer therapy based on genomic testing is advancing patient care. Genomic alterations in fibroblast growth factor receptor (FGFR) predict response to FGFR inhibitors; however, the role of RNA expression and protein activation is not known. We propose to examine the phospho-proteomic signature in FGFR-altered cancers to identify new candidates for FGFR-targeted therapies. Methods/Study Population: In our preliminary study, we have curated a cohort of FGFR2 mutants (13 FGFR2-fusions and 4 FGFR2 point mutations) with known clinical outcomes to FGFR inhibitors and 8 FGFR2 wild-type (WT) cholangiocarcinoma tumor samples to investigate the phospho-proteomic fingerprint using a clinical grade reverse phase protein array (RPPA). RPPAs are high throughput quantitative antibody-based proteomics assays that can quantify hundreds of proteins in thousands of patient tissues providing a high degree of sensitivity through laser tumor microdissection (LCM). We have selected proteins in the FGFR signaling pathway including FGFR2, AKT, ERK1.2, STAT1/3, FRS2, and PLCg to define the range of phospho-proteomic signal between FGFR2 WT and mutant cancers. All samples will undergo evaluation with RNASeq for gene expression. Results/Anticipated Results: Our initial analysis defined the range of RNA expression of FGFR2 and pFGFR2 protein signal (Y653/654 and Y769) between FGFR2 WT and FGFR2 mutant samples. On average, the FGFR2 mutant cohort displayed higher FGFR2 RNA expression compared to the FGFR2 WT cohort. There is no apparent correlation between RNA expression and clinical response to FGFR-targeted therapy. However, in this small cohort, there is no significant difference in FGFR2 phosphorylation between FGFR2 WT and mutant cancers. RPPA analysis of FGFR downstream signaling proteins reveals a wide range of phosphorylation, but no significant difference between FGFR2 WT and mutant cancers. Discussion/Significance of Impact: These findings illustrate the complexities of FGFR signaling between FGFR2 WT and mutant cancers. These data suggest that tumors with genomically WT FGFR may display increased pFGFR2 and downstream signaling phospho-proteins. We propose a larger study of cholangiocarcinoma to evaluate evidence of FGFR pathway activation in WT tumors.

Objectives/Goals: To determine the acceptability of a mobile/school-based diabetes and prevention clinic to overcome transportation barriers and improve attendance at endocrinology appointments for youth with type 1 diabetes, type 2 diabetes, MODY diabetes, and obesity living in socially vulnerable communities Methods/Study Population: This study utilized a 3-phase implementation process focused on feasibility, demand, and acceptability. Phase 1: identified high-need areas using patient volume and disease control metrics. Collaborated with school districts to define needs, enrolled them through a memorandum of understanding, and subsequently recruited and consented existing patients attending these schools. Phase 2 piloted the program to refine logistics and workflows. Semi-structured interviews and surveys were conducted with caregivers to assess program acceptability and satisfaction. Phase 3 is ongoing and will track clinical outcomes including glycemic control, appointment attendance, hospital admissions, emergency department visits, and self-management metrics. Results/Anticipated Results: Demand for the program was high with 91% (10/11) of approached districts agreeing to participate. District enrollment was staggered, starting with 1 district in August 2023, expanding to 5 in September, 7 in October, and reaching 8 districts by May 2024. From August 2023 to July 2024, the school-based mobile clinic conducted 355 individual clinical encounters addressing diabetes and obesity. The encounters included 180 for type 1 diabetes, 69 for type 2 diabetes, 8 for MODY diabetes, and 98 for obesity. Interviews and surveys with 36 caregivers are ongoing to evaluate program satisfaction. Discussion/Significance of Impact: The data suggest that this innovative healthcare delivery model is feasible. District-level enrollment demonstrates a demand for the program. Results from the interviews and surveys will further characterize the program’s acceptability among caregivers and lay the groundwork for future efficacy testing.