Objectives/Goals: The University of Illinois Chicago’s Center for Clinical and Translational Science has implemented an innovative approach to program evaluation. We blend high-impact quantitative and in-depth qualitative approaches to identify local and national impacts and areas for improvement that are not captured solely by traditional quantitative methods. Methods/Study Population: CCTS manages service requests and investigator demographics through an in-house system that our evaluation program utilizes to report on service requests, investigator satisfaction, and investigator demographics to service groups, CTSA and campus leadership, and other stakeholders throughout the year. Through this system, we are able to regularly survey and interview investigators about their experiences and solicit feedback about the service process. During interviews, we focus on questions about receiving services, recommendations for CCTS and colleagues, and plans to work with CCTS in the future. This mixed-methods approach helps us lay the foundation to expand evaluation beyond reporting and establish a robust CQI program that focuses both on CCTS staff needs and improving investigator experiences. Results/Anticipated Results: Soliciting both quantitative and qualitative feedback from investigators has enabled our service groups to make significant changes to their internal processes to ensure that investigators are aware of services and supports available. Our quantitative data show us that investigators return time and again to CCTS for services and supports. Yet the feedback we receive through short, targeted interviews also helps identify challenges that investigators experience that could improve the services they come to us to receive. We have already used this system to recommend improved marketing of existing services within certain service groups that were highly requested by investigators, which increased utilization of that service. Discussion/Significance of Impact: Our mixed-method approach to evaluation allows us to easily and rapidly identify areas for improvement within our service groups, an instrumental part of implementing a CQI program that is focused on staff-identified areas of improvement. This approach can be easily replicated by other CTSA hubs with minimal impact to existing resources.

Objectives/Goals: This study aims to explore the relationship between plasma biomarkers (GFAP, NF-L, and IL-1β) and cognitive impairment in moderate to severe TBI patients. We will assess biomarker levels and their link to neurocognitive outcomes at acute and chronic stages of injury. Methods/Study Population: We will recruit 100 patients aged 21 years and older with moderate to severe TBI (Glasgow Coma Score 3–12) from a trauma hospital. Blood samples will be collected at 24–72 hours post-injury and again at 3 and 6 months. Plasma levels of GFAP, NF-L, and IL-1β will be measured using multiplex ELISA. Neurocognitive tests will be administered at 3 and 6 months to assess cognitive function. Correlations will be made between biomarker levels, neurocognitive performance, and disability scores (Disability Rating Scale and Glasgow Outcome Scale). Exosome isolation from plasma will allow for detailed analysis of astrocyte-derived biomarkers and their association with long-term cognitive impairment and recovery. Results/Anticipated Results: We anticipate that plasma levels of GFAP, NF-L, and IL-1β will be elevated in the acute phase of moderate to severe TBI and will correlate with injury severity. At 3 and 6 months, higher levels of IL-1β, in particular, are expected to be strongly associated with cognitive deficits. We also anticipate that biomarkers in astrocyte-derived exosomes will provide more specific insights into long-term neuroinflammation and its impact on cognitive function. These findings could pave the way for targeted, personalized interventions to improve recovery in TBI patients. Discussion/Significance of Impact: This research focuses on inflammation’s role in cognitive impairment and disability in TBI patients. We propose using multiple biomarkers – GFAP, IL-1β, NF-L – paired with advanced techniques like exosomes and multiplex analyses to identify novel therapeutic targets, aiming for personalized treatment strategies, as well as prognosis.

Objectives/Goals: To identify gaps in policy that influence enrollment trends of patients with multimorbidity in Phase III clinical trials. We aim to propose policy recommendations for increasing use of real-world evidence (RWE) that increases safety and efficacy information for patients with multimorbidities. Methods/Study Population: Conduct a systematic policy analysis on the current regulatory landscape of RWE, referencing the 2020 FDA Guidance “Enhancing the Diversity of Clinical Trial Populations.” Evaluate guidelines using the Department of Health and Human Services’ (HHS) 2016 Regulatory Impact Assessment (RIA) Framework. Utilize the Center for Drug Evaluation and Research’s New Molecular Entity Database to identify novel hypertensive drugs approved after 2006, and assess clinical studies’ alignment with the 2020 Guidance. Review additional policies, FDA guidelines, and ICH documents to establish baseline compliance. Two case studies will evaluate past policy impacts on drug development. Assess costs and benefits of increasing multimorbid patient enrollment to inform a policy framework. Results/Anticipated Results: Anticipated results include all components of the HHS’s RIA and a policy framework informed by the assessment. To identify problems, an analysis of clinical trial exclusion criteria in novel hypertensive drugs will be conducted to show diversity and enrollment gaps in regulatory policy, referencing the FDA’s 2020 Guidance. The RIA’s cost–benefit analysis will highlight costs faced for utilizing RWE and expanding enrollment criteria in Phase III studies. The cost–benefit analysis, RIA, and case studies will inform a policy framework that explains dynamics between stakeholders and outline policies that increase clinical trial representation in ways that are less burdensome to sponsors and patients. Discussion/Significance of Impact: By understanding the barriers to enrolling participants with multimorbid conditions, we can outline incentives to increase diverse trial populations, helping healthcare providers choose more treatments for complex conditions. This research supports policy recommendations to make drugs more representative of conditions the population faces.

Objectives/Goals: This study aims to evaluate diversity of participants in GLP-1 T2DKM clinical research with regard to sex, race, and ethnicity by using results data available through the ClinicalTrials.gov database. Sample population estimates for studies were calculated using the 2020 Census and compared within groups with respect to sex, race, and ethnicity. Methods/Study Population: The public ClinicalTrials.gov database was searched for interventional studies with GLP1 inclusion as treatment (n = 2,397). This search was then filtered to studies where results were reported (n = 772). From these studies, 466 studies focused on type 2 diabetes as a condition and thus became the analysis dataset. Participant and protocol information for these 466 studies were obtained from the clinical trials transformation initiative (CTTI) as an AACT data download. Observed to expected ratios were calculated for each subgroup-based population estimates from the 2020 Census and using the baseline counts of participants for studies where sex, race, and ethnicity were provided. In addition to within group comparisons, study characteristics (e.g. phase) were included in models to assess influence of covariates. Results/Anticipated Results: Of the 466 studies, 430 (92%) reported sex, 171 (37%) reported race, and 145 (31%) reported Hispanic ethnicity. Among those found to be underrepresented in studies (defined as a ratio < 1): females (mean  =  0.89, median  =  0.92); Black/African Americans (mean  =  0.88, median  =  0.39). Hispanic or Latinos mean ratio was 1.16 (95% CL: 0.97, 1.35) but had the least available data. When including covariates in the models, there were statistically significant differences in ratios with respect to sex as females had significantly lower odds compared to males (ratio > =  1), with the odds being about 21% of those for males. With respect to race, Black or African American individuals had significantly lower odds (about 32% of those of White individuals) (ratio > =  1). Discussion/Significance of Impact: This study reveals significant underrepresentation of females (mean ratio 0.89) and Black/African Americans (mean ratio 0.88) in clinical trials for GLP-1 drugs in type 2 diabetes. These disparities highlight the need for more inclusive research to ensure diverse populations benefit equally from medical advancements.

Objectives/Goals: This study aims to uncover immuno-endotypes in sepsis-associated pediatric acute respiratory distress syndrome (SA-PARDS) by using single-cell RNA sequencing (scRNA seq) to analyze the immune cell populations of the lower respiratory tract of intubated pediatric subjects with SA-PARDS. Methods/Study Population: Inclusion criteria are age less than 18 years, admission to the PICU, diagnosis of SA-PARDS, and intubation. Both sepsis and PARDS will be defined using the most recent consensus definitions. Exclusion criteria include an order of limited resuscitation and clinician discretion. After informed consent is obtained, a tracheal aspirate and blood sample will be obtained on days 1, 3, and 7. Both samples will be processed for single-cell RNA seq via the HIVE platform per manufacturer protocol. cDNA libraries will then be sent for 150 base pair paired-end sequencing. Sequences will be aligned to a reference genome, and count matrices will be generated. The Seurat package in R will be used for cell-type annotation and analysis of differential gene expression. Clinical variables, labs, and outcomes will be recorded in REDCap. Results/Anticipated Results: We expect to find that subjects with nonresolving SA-PARDS, defined as intubation and mechanical ventilation, will have a monocyte/macrophage transcriptome characterized by continued hyper-inflammation (M1-like phenotype) that does not transition over time to an anti-inflammatory and pro-repair phenotype (M2-like). Additionally, we expect to see that subjects with non-resolving SA-PARDS will have evidence of continued inflammation driven by hyper-inflammatory neutrophils. Finally, we expect that subjects with non-resolving SA-PARDS will have epithelial cells characterized by continued upregulation of canonical pathways of innate immunity including interferon signaling and the damage associated molecular pattern recognition pathway. Discussion/Significance of Impact: The discovery of immuno-endotypes in SA-PARDS would represent a major step toward developing precision medicine therapies for this group of patients. It would simultaneously provide a strategy to reduce biological heterogeneity and identify novel pathways and targets for therapy.

Objectives/Goals: The National Research Mentoring Network Coordination Center (NRMN CC) received funding from NIH to create an Online Community of Practice (OCoP) for Research Managers (RM). These RM contributed to advancing the research on the science of mentorship in STEMM. In a Proof of Concept, RM explored various aspects of their mentorship research support work. Methods/Study Population: An OCoP met 18 times across the 5-year grant to share experiences working to advance the science of mentorship in STEMM. Topics, frequency, and length of meetings were selected based upon several needs assessments surveys from the RM community. RM were invited to join the OCoP based on their roles as the point people for administrative activities in research projects (e.g., finances, budgets, training, and project management). RM often supervised staff, collected data, monitored IRB protocol compliance, and conducted research. RM played a pivotal role in the gathering and sharing of common measures across the 11 U01 studies to allow for greater confidence in research findings on mentorship (McConnell, 2021). Results/Anticipated Results: Our primary goal was to provide a supportive community for RM contributing to mentorship research and data sharing. The results from several needs assessments exemplified a request for this support from the community to engage in an OCoP focused on their professional development. Therefore, the OCoP served as a starting point to explore the duties, functions, roles and responsibilities of RM, and extended into providing professional development. Although the number of RM attending decreased as the grant entered the no-cost extension phase, a subgroup of RM expressed interest in continuing the OCoP to focus on dissemination of research findings, further supporting the need for this community. Discussion/Significance of Impact: RM supported 11 research projects and contributed to the data collection for over 6,000 participants. Few opportunities exist to create an OCoP for large scale data collection on experiences with mentorship in STEMM. RM were pivotal in their role with the NRMN to enhance the training and career development of individuals from diverse backgrounds.

Objectives/Goals: This project (1) assesses provider behavior at the Galveston Secure Against the Fentanyl Epidemic (G-SAFE) Clinic in providing evidence-based care for underserved patients in our community and (2) implements evidence-based anti-stigma intervention in local health care. Methods/Study Population: The efficacy and impact of G-SAFE on healthcare utilization, health outcomes, and patient satisfaction will be determined. Evaluations assessing provider behavior will be made across at least 25 clinic patient visits, taking note of medical students, clinicians, and health providers’ interactions with patients related to decision-making, care plan creation, and communication. Health provider discussion groups will provide essential data in understanding the successful management of SUDs, management of safety and risk, and how best to pilot and assess interventions that promote greater trust-building and a harm-reduction approach to clinical care for patient empowerment and positive outcomes. Results/Anticipated Results: Observations in the clinic will be turned into interventions to improve diagnostics and therapeutics for SUD medical care and behavioral change. We will recruit 40 medical students (with/without exposure to UTMB’s free clinics) as well as 20 clinicians in the G-SAFE Clinic, Emergency Medicine, and Primary Care. Baseline stigma will be measured with the Medical Condition Regard Scale and the Drug and Drug Problems Questionnaire alongside measures of care approaches. The data collected and the educational intervention for medical students and clinicians will make a positive impact on the lives of those affected by SUDs and serve as a model for future interventions on a larger scale. Discussion/Significance of Impact: Health provider’s SUDs stigma undermines both care quality, patient empowerment, and recovery success. Addressing provider stigma is crucial for necessitating a shift toward collaborative, responsive, and creative clinical decision-making to tackle the ethical challenges posed by the opioid crisis.

Objectives/Goals: Objectives/Goals (300 characters): Sarcopenia is a progressive skeletal muscle disorder associated with adverse outcomes. There is a gab of having objective measures upon performing interventions in patients with muscular dystrophies. The object of the present study is to describe the severity of sarcopenia in DMD patients in Puerto Rico. Methods/Study Population: Methods/Study Population (700 characters): Forty to 30 patients with DMD who are followed in MDA Care Center in the “Instituto De Rehabilitacion del Caribe.” Diagnosis will be confirmed with genetic testing and/or muscle biopsy. Lean muscle mass will be measured with a Whole Body Dexa (WBD) in a Nuclear Medicine Lab. Hand grip, elbow flexor, and knee extensor muscles strength will be measures with an isometric dynamometer. Patients’ functionality will done using the North Star Ambulatory Assessment scale and Brook and Vignos scales, which have been validated for patients with DMD and neuromuscular disease respectively. Correlations will be made with lean body mass (independent variable) and muscle strength and functionality (dependent variable). Results/Anticipated Results: Results/Anticipated Results (700 characters): We expect to find severe sarcopenia in patients with DMD in PR and that it will be more severe with older age. There will be a direct correlation between lean muscle mass and muscle strength, and functionality in DMD patients. Discussion/Significance of Impact: Discussion/Significance of Impact (300 characters): The findings of our study can help us to explore the possibility that Whole Body DEXA can serve as a potential biomarker for future studies since there is a need to develop noninvasive biomarkers that correlate with disease progression and interventions in DMD patients.

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: Tacrolimus (TAC) is an immunosuppressant used after hematopoietic stem cell transplant (HSCT). Recently, TAC was found to be metabolized to a novel, less active metabolite by common gut microbiota. Our objective is to determine a microbiome signature that influences oral TAC pharmacokinetic (PK) and to develop a clinical tool to select the TAC dose. Methods/Study Population: This is an observational IRB approved microbiome-pharmacogenomic study using banked biospecimens and clinical data, TAC dose, and PK information from the electronic health record. Adult HSCT patients with pre-transplant DNA and stool specimens were included in this analysis if they received TAC in the first 100 days post-HSCT. A global diversity array was used for DNA pharmacogenomic (PGx) genotyping, and metagenomic shotgun sequencing was used for stool microbiome analysis. Spearman correlation will be used to identify potential stool microbiota associated with TAC PK. TAC trough concentrations at steady state will be modeled using nonlinear mixed effects (NLME) modeling to identify potential genetic and microbiota covariates that influence TAC clearance. Results/Anticipated Results: We identified 53 eligible patients who had available DNA and 90 stool samples. The majority (n = 49, 92.5%) were of European ancestry. These patients had 920 (oral  =  622, IV infusion  =  298) TAC trough blood concentrations. We expect that patients who have high abundance of bacteria that metabolize or reduce the absorption of TAC will have lower blood concentrations and will require a higher IV to oral dose conversion ratio than those with lower abundance. Those patients will also require higher oral TAC daily doses. Low stool microbial diversity is expected to be associated with high oral TAC trough intra-patient variability in the first 100 days post-transplant. In the NLME model, PGx when combined with potential bacterial signature will better explain variability in TAC clearance. Discussion/Significance of Impact: Combining PGx and microbiome biomarkers will provide a better understanding of the factors influencing TAC PK and lead to models for individualized dosing. To our knowledge, this is the first study to investigate the combined influence of microbiome and PGx on drug PK. The study is limited to the availability of samples in the biobank.

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: 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: 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: 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: 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: Infectious keratitis is the leading cause of corneal blindness worldwide, causing two million cases of monocular blindness per year. Of these cases, developing countries are disproportionately affected, in part due to sociodemographic disparities. Our study examined risk factors for severe keratitis presentation in a South Indian population. Methods/Study Population: 156 patients aged ≥ 16 years with clinically diagnosed infectious keratitis presenting to Aravind Eye Hospital in Pondicherry, India, from January 1, 2023 to July 31, 2024, were retrospectively reviewed. Univariate logistic regression was used to evaluate associations between specific potential risk factors (including age, sex, awareness of keratitis, travel distance to hospital, education level, missed work wages, and ability to afford care) and keratitis clinical severity (defined using thresholds of poor visual acuity, size of stromal infiltrate measured on slit lamp examination, occurrence of perforation, and need for corneal transplant surgery). Individual risk factors found to be significant were incorporated into a multivariable logistic regression model. Results/Anticipated Results: We anticipate that the results of this study will identify multiple risk factors for more severe keratitis presentations among patients at baseline. We expect these factors to include increased travel distance from the patient’s home to the base hospital, delays between time of diagnosis and initiation of treatment, treatment nonadherence, lower educational levels, lack of familiarity with keratitis, treatment and transportation costs, increased time off work, and missed work wages, among others. Discussion/Significance of Impact: This study elucidates barriers to early keratitis diagnosis in a low-resource setting. Study findings can inform strategies to improve keratitis prevention using decentralized care approaches such as community eye screenings and expanding outreach via vision centers. Such strategies can improve timely access to care for vulnerable populations.

Objectives/Goals: Mathematical models of airborne virus transmission lack supporting field and clinical data such as viral aerosol emission rates and airborne infectious doses. Here, we aim to measure inhalation exposure to influenza aerosols in a room shared with persons with community-acquired influenza and estimate the infectious dose via inhalation. Methods/Study Population: We recruited healthy volunteer recipients and influenza donors with polymerase chain reaction (PCR)-confirmed community-acquired infection. On admission to a hotel quarantine, recipients provided sera to determine baseline immunity to influenza virus, and donor infections were confirmed by quantitative real-time polymerase chain reaction. Donors and recipients were housed in separate rooms and interacted in an “event room” with controlled ventilation (0.2 – 0.5 air changes/hour) and relative humidity (20–40%). We collected ambient bioaerosol exposure samples using NIOSH BC-251 samplers. Donors provided exhaled breath samples collected by a Gesundheit-II (G-II). We analyzed aerosol samples using dPCR and fluorescent focus assays for influenza A and sera by hemagglutinin inhibition assay (HAI) against donor viruses and vaccine strains. Results/Anticipated Results: Among two cohorts (24b and 24c), we exposed 11 recipients (mean age: 36; 55% female) to 5 donors (mean age: 21; 80% female) infected with influenza A H1N1 or H3N2. Eight G-II and two NIOSH bioaerosol samples (1–4 µm and ≥4 µm) were PCR positive. We cultured virus from one G-II sample. Based on previous literature, we hypothesized that ~50% of immunologically naïve people (HAI Discussion/Significance of Impact: We demonstrated that it is feasible to recruit donors with community-acquired influenza and expose recipients to measurable virus quantities under controlled conditions. However, baseline immunity was high among volunteers. Our work sets the stage for designing studies with increased sample sizes comprising immunologically naïve volunteers.

Objectives/Goals: To identify the most impactful regulations regarding the approval and marketing of TMs in the U.S., E.U., Japan, Australia, China, and India enacted between the years 2000 and 2022. To explore TM-related regulations in new countries, Japan and Australia, for their novel regulatory approaches in intersecting Western and Eastern medical practices. Methods/Study Population: International regulatory bodies included in this study were chosen based on the country’s long history with TM and/or the existence of review processes specific to TM. TM-related regulatory changes that were enacted between the years 2000 and 2022 were identified and categorized into special departments, changes in clinical trials, or specialized tracks. The impact of these TM policies was measured via the number of TM-related INDs, approved applications, marketed drugs, and rejected applications per decade since 2000. This data was then organized alongside policies to draw conclusions about the influence of these regulatory changes. All data was collected using official government websites and journals published by independent, external research institutions accessed via USC’s library services. Results/Anticipated Results: Previous research revealed each country made efforts to integrate TMs into existing drug practices, such as clinical trials and safety requirements, although the extent and methods for the integration differed. Countries with a longer history with TMs are predicted to have regulatory systems that are more accommodating to the unconventional nature of TMs, making the approval and marketing of TMs much easier in these countries. As TM-related policies are more refined and increase in number in a given country, the number of TM-related applications and TMs marketed as legitimate, prescribable medications will also increase. Discussion/Significance of Impact: Timelines and charts displaying the impact of new TM-related regulatory changes will help identify a successful model for increasing TM IND submissions, approvals, and marketed TM drugs.

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: To design a flexible, comprehensive framework for Data Science Units to cultivate sustainable, long-term relationships with Clinical and Translational Science Research Units. Best practices for managing Data Science collaborations are presented to improve the quality and efficiency of research conducted throughout academic health centers. Methods/Study Population: Leaders of Data Science Units across six institutions formed a workgroup to develop guidance and best practices for Data Science Units to establish long-term, sustainable collaborations with Clinical and Translational Science Research Units. This guidance is based on tools and protocols developed and employed by the participating units, which range from larger groups with over 20 partnerships to a unit with three partnerships that is actively working to expand. Importantly, partnerships are highly variable, with some partnerships at one institution representing engagement with over 500 faculty, whereas some partnerships at another institution involve the lab of a single investigator. Results/Anticipated Results: We offer guidance in three domains: (1) Identifying the needs for a new partnership, including assessing required effort and data science expertise, setting partnership priorities, developing formal agreements, and identifying goals and metrics; (2) managing data science teams by implementing regular meetings, creating project intake and prioritization processes, and effort monitoring; and (3) evaluating the successes and failures/gaps of the collaboration by measuring the metrics mapped to the goals. For each domain, we provide specific suggestions on which parties should be involved and how frequently the processes should occur. This guidance is applicable both to larger collaborative partnerships and to smaller, single faculty or staff partnerships, whether they are new or well-established. Discussion/Significance of Impact: Effective collaboration between data scientists and clinical and translational investigators is key to advancing data-driven research. The guidance and resources are presented to support Data Science Units in successfully managing long-term collaborations through goal-development, evaluation, and adapting to evolving research needs.