Objectives/Goals: The STEM-Coaching and Resources for Entrepreneurial Women (CREW) Program was developed to promote systemic change in entrepreneurship by engaging women faculty and post-doctoral fellows through educational opportunities, mentorship, and professional coaching to close the gender gap in entrepreneurial leadership. Methods/Study Population: We solicited applications from women at the junior faculty or post-doctoral fellowship stage. Applications were reviewed by the CREW leadership and mentors. Applicants accepted into the program participated in monthly large group coaching sessions, one-one-one coaching, and small group mentoring sessions. Applicants also completed an online entrepreneurship course and participated in a shark tank-like competition during annual innovation awareness month. Coaches were professionally credentialed and oriented to the biomedical context. Entrepreneurial experts served as mentors. Our program evaluation used the RE-AIM framework. The evaluation included assessments of the program’s ability to reach a diverse population, satisfaction with program offerings, and changes in entrepreneurship outcomes. Results/Anticipated Results: To date, three cohorts consisting of 35 women from 13 states participated in the program. Results from Cohort 1 show significant improvements in self-assessed confidence in entrepreneurial activities and high satisfaction with the program. All measures of confidence showed increases, with the largest gains in the areas of “estimating customer demand for new products or services”; “Clearly and concisely explaining my business idea in everyday terms”; and “Getting others to identify with and believe in my vision and plans for a new business”. The percentage of participants who have invention disclosures significantly increased from 33.3% to 83.3% after completing the program. The percentage who launched start-up companies also increased from 17% to 33%. Cohort 2 results will be available before the conference. Discussion/Significance of Impact: Participants in the CREW program showed improvement in all measures of evaluation. The program is unique in complementing mentoring with coaching. Because the coaching component takes a holistic approach by encouraging women to craft a vision for their work and life, it provides value that will last beyond entrepreneurship activities.

Objectives/Goals: Retention in care is vital for people living with HIV. We used human-centered design (HCD) to engage a community-based research panel over a 5-year period, allowing us to incorporate their insights on research guidance and interpretation of findings to investigate correlates of HIV care outcomes. Methods/Study Population: We recruited a diverse panel of individuals who were living with HIV, HIV clinicians, and/or providing non-clinical HIV services in Marion County, Indiana. We conducted biannual sessions using a variety of HCD tools and activities to engage participants. Each session took about three hours, and panelists were compensated for their participation. Due to the COVID-19 pandemic, sessions were initially held virtually. Sessions were designed for project discussion and to facilitate exploration of concerns and challenges facing receipt of HIV services. Our HCD approach put participants in the center of discussion and empowered them to externalize ideas and collaborate meaningfully with our team. Results/Anticipated Results: Since project inception, 48 individuals have joined the panel. Thirty-five are actively engaged, participating in one or more of six sessions conducted to date. We have learned much from the panel. One example is that a residential move might be a risk or protective factor for retention in care and the amount of time one had lived with HIV is a crucial factor. Panel insights have helped guide and prioritize analyses, aided in identification of data missing from our ecosystem, helped interpret results, provided feedback on future interventions, led to a quality improvement project with the local health department, and led to a presentation at a local health equity conference. Discussion/Significance of Impact: Community engagement is essential to impactful and sustainable research. HCD was a successful approach to engage our panel to inform interventions more relevant to the community. We anticipate these methods will be important for others conducting community-engaged research.

Objectives/Goals: Accurately stratifying patients with clinically isolated syndrome by risk of developing multiple sclerosis is of great clinical importance. Though numerous prediction models attempt to achieve this goal, no systematic review exists to independently evaluate these models. We aim to systematically identify and assess the risk of bias in all such models. Methods/Study Population: Studies developing or validating prediction models to assess risk of developing MS in patients with CIS who are not receiving an MS-indicated disease-modifying therapeutic will be identified via a systematic literature search. Studies will be evaluated for overall risk of bias using PROBAST (Prediction model Risk Of Bias Assessment Tool). Briefly, data sources, predictor, and outcome definition and assessment, applicability, and analysis will be assessed for each model in each identified study, and an overall risk of biased judgment will be assigned. Identified studies, predictors incorporated, results, and risk of bias assessment with accompanying rationale will be summarized in the final report. Results/Anticipated Results: Based on an initial exploratory search, we anticipate that most, if not all, identified prediction models will have high risk of bias. We anticipate that many studies will have limited applicability due to the use of outdated diagnostic criteria for definition of outcomes, or high risk of bias concerns originating from their analysis due to insufficient volume of included participants or poor model validation practices. We further anticipate that most, if not all, of the identified prediction models will have limited potential to be translated to use in a clinical setting. Discussion/Significance of Impact: Understanding how to identify patients with high-risk CIS may inform and improve clinician treatment decisions, patient outcomes, and future research study design. This work may also reveal flaws in current prediction models for CIS, opening new avenues of research and prompting development of improved prognostic models for patients with CIS.

Objectives/Goals: Early identification and profiling of planned studies is a critical administrative challenge in providing timely support for clinical trials. Here we describe the collaborative design and development of a clinical trial tracking dashboard to enhance support and quality improvement for investigator-initiated clinical trials at our institution. Methods/Study Population: Trial-CARE organized a workgroup with key stakeholders from WashU business units that manage grants, information technology, bioinformatics, data repository stewardship, and clinical trial support. The workgroup strategized next steps in a “proof-of-concept” effort to determine whether NIH investigator-initiated clinical trial metrics would be accessible via the WashU Data Warehouse. The WashU Data Warehouse is a data repository that pulls in pre-award and post-award data from sources such as the WashU Research-Grant Management System (RMS) and the NIH Reporter Tool. The proof-of-concept findings lead to implementing a plan for Phase 1 of the design, development, and piloting of a visual dashboard to track and offer targeted and timely support to NIH investigator-initiated clinical trials at WashU. Results/Anticipated Results: WashU currently has 217 grants submitted and 114 grants awarded for NIH clinical trials. In the proof of concept, we confirmed and successfully matched over 100 awarded NIH investigator-initiated clinical trials at WashU across RMS and the NIH Reporter Tool. We determined Phase I of the dashboard would track clinical trial data from these two sources via the WashU Data Warehouse. The pilot of Phase I of the dashboard will begin in February 2025. We also identified mission critical data elements not accessible via the WashU Data Warehouse (e.g., enrollment diversity, IND, and IDE). The plan to procure this data will require continued stakeholder support in Phase II of the dashboard to (1) expand data capture in RMS and (2) ingest additional data into the WashU Data Warehouse from RMS or new systems (e.g., ClinicalTrials.gov). Discussion/Significance of Impact: Early access to robust data about NIH investigator-initiated clinical trials via our newly created Phase I dashboard will better position our centralized service cores to support trial success, compliance, and quality improvement across the lifecycle of these clinical trials. In Phase II, we plan to expand the data available in the dashboard.

Objectives/Goals: The growing burden of hypertension in the USA disproportionately impacts individuals with lower socioeconomic status and those in rural communities. This study aims to investigate specific social determinants of health associated with uncontrolled hypertension among rural, underserved patients residing in Alabama. Methods/Study Population: A retrospective review of electronic health records data from the UAB Selma Family Medicine clinic was conducted. The deidentified data were entered into the Population Health Assessment Engine (PHATE) to render social characteristics and community vital sign (CVS) scores, a social deprivation index, by census tracts. We provide descriptive statistics and compare the stated factors between patients with controlled and uncontrolled hypertension using logistic regression models. We are conducting phone surveys to gather individualized data on social determinants of health to assess the perceived social needs of patients with hypertension. The Protocol for Responding to & Assessing Patients’ Assets, Risks & Experience tool was used to develop the survey, and survey responses will be compared with the PHATE results. Results/Anticipated Results: Among 2129 patients, 375 (17.6%) had uncontrolled hypertension with a mean age of 58.7 ± 14.4 years. Women comprised 66.7% (250) and 65.1% (1142) of the uncontrolled and controlled hypertension populations, respectively. The prevalence of uncontrolled hypertension was 19.1% among Black patients and 8.2% in White patients. Patients with uncontrolled hypertension had a CVS of 82.37 ± 7.31 and 81.81 ± 8.40 patients with controlled hypertension. Patients with uncontrolled hypertension lived in areas where an average of 46 ± 11% were not employed, 36 ± 9% rented, and 28 ± 1% lived below the federal poverty line (FPL). Adjusting for age, race, and sex, a unit increase in the proportion of people below the FPL was associated with 43% higher odds of uncontrolled versus controlled hypertension (OR  =  1.43, 95% CI 0.44, 4.64). Discussion/Significance of Impact: Rural, underserved patients with hypertension experience multiple adverse social determinants, such as nonemployment rates, low income, and rental housing. Survey results will allow us to compare assessed and individualized social determinants that may be important to address when caring for this population.

Objectives/Goals: This study examines prevalence of complete sample size justifications in publications in the top five clinical neurology journals. Secondary goals include comparing study designs and clinical populations to explore whether some may be more likely to include inadequate sample size considerations. Methods/Study Population: Recent studies (n  =  125) in Lancet Neurology, Alzheimer’s and Dementia, JAMA Neurology, Acta Neuropathology, and Brain will be evaluated. For each journal, the 25 most recent empirical articles between 2022 and 2023 will be examined for their inclusion of a justification and reproducible sample size calculation. Inclusion of components of an ideal sample size justification will be evaluated: effect size to be detected (standardized or unstandardized), alpha, power, and from where values were derived. Prevalence and completeness will be compared among study designs, clinical populations, and with regard to journal reporting requirements. Results/Anticipated Results: At the pilot review stage, 17 of 25 included studies had any kind of sample size justification, and only 3 studies had enough information to reproduce their sample size calculations. Retrospective studies included a sample size justification more frequently (81.8% vs. 57.1%), but prospective studies had more complete sample size justifications, when present. We hypothesize that sample size calculations will be more complete in reports of clinical trials and prospective cohort studies, compared to retrospective and cross-sectional designs. Based on our previous research, we do not expect that journal reporting requirements will affect completeness of sample size justifications. Discussion/Significance of Impact: Translational decision-making is informed in part by the robustness of current research. Transparency of sample size considerations in publications can contribute to the formation of less biased opinions of translational readiness and, subsequently, more efficient and effective translation.

Objectives/Goals: NAD+ synthesis is enhanced in glioblastoma (GBM) allowing GBM to resist chemotherapy. NQO1 is upregulated in GBM and may be targeted by β-lapachone (β-lap) to induce NAD-depletion and cell death. This project investigates NQO1 as a selective target for GBM and the contributions of glucose and uridine to NAD+ synthesis. Methods/Study Population: Survival Studies and NQO1 expression. RNA-seq and survival data from TCGA of glioma patients (n = 667) was obtained using the UCSC Xena platform. Western blots were utilized to determine expression levels of NQO1 and NAMPT in normal human astrocytes, U87 cells, and patient-derived GBM cell lines. Immunocytochemistry: γ-H2AX staining was used to evaluate β-lap induced DNA damage. NQO1-dependence was evaluated with the NQO1-inhibitor dicoumarol. Cytotoxicity measurements. Cells were exposed to β-lap and other inhibitors, and cell survival was determined by trypan-blue exclusion assay. Co-culturing experiments were performed with fluorescently labeled U87 cells and unlabeled astrocytes. NAD+ quantification. Intracellular NAD+ was acid extracted and quantified by an enzyme-cycling reaction. Results/Anticipated Results: NQO1 overexpression is linked to decreased survival in glioma patients. In glioma patients, high NQO1 expression was associated with a decreased overall survival and high-grade tumors. β-lap induces selective NAD+ depletion and cell death in NQO1-expressing GBM cells. Western blots demonstrate NQO1 expression to be elevated in GBM cell lines compared to normal human astrocytes. β-lap induces NQO1-dependent NAD+ depletion and cell death in GBM compared to astrocytes in mono- and co-culture experiments. Glucose and uridine facilitate NAD+ regeneration in GBM. We demonstrate extracellular glucose and uridine facilitate NAD+ regeneration and cell survival in β-lap exposed GBM cells. Utilizing inhibitors, we determined that glucose and uridine facilitate NAD+ regeneration through the NAD+ salvage pathway. Discussion/Significance of Impact: GBM is the most common primary adult CNS tumor with a median survival of 14 months. Despite significant research in therapeutic strategies, treatment has not improved in 2 decades. There is a significant need to discover new targets that may improve GBM treatment. We demonstrate here that targeting NQO1 with β-lap induces selective GBM toxicity.

Objectives/Goals: Manual skin assessment in chronic graft-versus-host disease (cGVHD) can be time consuming and inconsistent (>20% affected area) even for experts. Building on previous work we explore methods to use unmarked photos to train artificial intelligence (AI) models, aiming to improve performance by expanding and diversifying the training data without additional burden on experts. Methods/Study Population: Common to many medical imaging projects, we have a small number of expert-marked patient photos (N = 36, n = 360), and many unmarked photos (N = 337, n = 25,842). Dark skin (Fitzpatrick type 4+) is underrepresented in both sets; 11% of patients in the marked set and 9% in the unmarked set. In addition, a set of 20 expert-marked photos from 20 patients were withheld from training to assess model performance, with 20% dark skin type. Our gold standard markings were manual contours around affected skin by a trained expert. Three AI training methods were tested. Our established baseline uses only the small number of marked photos (supervised method). The semi-supervised method uses a mix of marked and unmarked photos with human feedback. The self-supervised method uses only unmarked photos without any human feedback. Results/Anticipated Results: We evaluated performance by comparing predicted skin areas with expert markings. The error was given by the absolute difference between the percentage areas marked by the AI model and expert, where lower is better. Across all test patients, the median error was 19% (interquartile range 6 – 34) for the supervised method and 10% (5 – 23) for the semi-supervised method, which incorporated unmarked photos from 83 patients. On dark skin types, the median error was 36% (18 – 62) for supervised and 28% (14 – 52) for semi-supervised, compared to a median error on light skin of 18% (5 – 26) for supervised and 7% (4 – 17) for semi-supervised. Self-supervised, using all 337 unmarked patients, is expected to further improve performance and consistency due to increased data diversity. Full results will be presented at the meeting. Discussion/Significance of Impact: By automating skin assessment for cGVHD, AI could improve accuracy and consistency compared to manual methods. If translated to clinical use, this would ease clinical burden and scale to large patient cohorts. Future work will focus on ensuring equitable performance across all skin types, providing fair and accurate assessments for every patient.

Objectives/Goals: A summer research program for medical students was implemented using real-world evidence (RWE) – electronic health record (EHR) databases to develop and answer research questions. Medical students were trained in capabilities of traversing the large RWE-EHR so they may query, extract, and analyze data as well as refine their research questions. Methods/Study Population: Ten medical students and 9 non-data scientist mentors underwent training in how to use the IU School of Medicine-Evansville RWEdataLab (CRC/Sidus Insights) national real-world cardiology and psychiatry deidentified EHR databases. The program began with students attending introductory training teaching database, spreadsheet, and statistical program usage. During the remainder of the program, a weekly best practices meeting took place among mentors and a weekly cohort meeting of students and mentors discussed student presented findings. At the end of the program, students generated abstracts and poster or podium presentations to share their findings at local symposia. A survey was also distributed to students to assess the impact of the tools, trainings, and program. Results/Anticipated Results: All students were able to define a question of interest, query and extract data related to their research question, and analyze multiple aspects of their data. Projects were well received at local symposia, with 2 receiving special honors, and 2 projects have been presented at regional/national conferences. Students rated the program highly and were likely to recommend the program to other students. They self-rated improvements in asking scientific questions, using excel, data presentations, and problem-solving. Students valued weekly “check-in” meetings and interactions with mentors more than lectures or technical “help desk” support. Discussion/Significance of Impact: The program provides mechanisms for non-data scientists and medical trainees, to learn and access RWE-EHR databases to address research questions. The cohort interactions fostered discussion among mentors and students promoting research question refinement and clarity findings. The program also introduces a new tool for potential patient care.

Objectives/Goals: Cerebral amyloid angiopathy-related inflammation (CAA-ri) is a spontaneous inflammatory cerebral vasculopathy that mimics complications of Alzheimer’s disease immunotherapies. Our objective is to evaluate imaging and cerebrospinal fluid (CSF) markers of blood–brain barrier (BBB) impairment and inflammation in CAA-ri. Methods/Study Population: We plan to enroll 20 patients total: 1) 10 patients with CAA-ri as defined by Auriel et al (JAMA Neurology 2016) (exposure group). 2) 10 patients with non-inflammatory CAA defined using Boston criteria 2.0 that do not also meet criteria for CAA-ri (control group). The primary outcome will be Ktrans, a parameter of BBB impairment calculated from dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) of the brain. Secondary outcomes will include DCE-MRI parameter VL, CSF albumin index, CSF fibrinogen, CSF sPDGFR-β, CSF MMP-2, CSF MMP-9, CSF C3, CSF IL1β, CSF IL6, IL8, and TNFα. Statistical comparisons between the exposure and control groups will be made using Wilcoxon rank sum test. Results/Anticipated Results: We anticipate significantly higher levels of BBB impairment and inflammatory biomarkers from DCE-MRI and CSF in subjects with CAA-ri relative to control subjects with non-inflammatory CAA. Discussion/Significance of Impact: Biomarkers are essential to characterize risk factors, pathophysiology, and possible treatment targets in CAA-ri. We plan to use the results of the current study to inform longitudinal studies that will test whether these markers are useful in identifying not only the presence of CAA-ri but also severity, progression, and response to treatment.

Objectives/Goals: To identify the genomic mechanisms underlying cross-species regulation of longevity among mammals and birds and to characterize the impact of those conserved pathways on human aging. More broadly, this study aims to develop a novel evolutionary approach to understand the genetics of complex traits. Methods/Study Population: High-quality genome sequences for 194 bird species and 295 mammal species with reliable longevity and body size data were obtained from publicly available resources. The data include coding sequence alignments of 16,863 mammalian and 14,565 avian one-to-one orthologous genes. Gene-wise relative evolutionary rates (RERConverge) and maximum likelihood phylogenetics (PAML) were computed to assess for evidence of purifying selection and positive selection for longevity. As part of ongoing analysis, human orthologs of selected results will be examined in the UK Biobank for validation. Results/Anticipated Results: Preliminarily, we have found a signal of concordant positive selection between two classes of vertebrates separated by hundreds of millions of years. Several genes show signals of positive selection in long-lived species of both birds and mammals. Ongoing work focuses on elucidating the relationship between relative evolutionary rates and positive selection, the overlap in selection signature between long-lived animals with large body sizes and those who are exceptionally long lived for their body size, and further elaborating on convergence between mammals and birds. Discussion/Significance of Impact: Currently, most scientific knowledge about aging is from experiments on short-lived model organisms. By systematically studying the genomes of long-lived mammals and birds, we aim to develop a new method for studying complex traits and uncover novel insights into the mechanisms of longevity.

Objectives/Goals: We evaluated the implementation of a peer-facilitated research best practices training for Community Health Workers and Promotoras (CHW/Ps) at four new partner sites to increase the capacity and capability of a workforce increasingly involved in community-engaged research. Methods/Study Population: Staff were trained using a train-the-trainer model, and materials were disseminated to partners at three academic institutions and one community-based organization. Each site delivered the training virtually or in-person in English and/or Spanish. CHW/P learners at all sites completed online evaluation surveys about the impact of the training on their knowledge and skills for participating in research-related work, and two CHW/Ps from each site participated in follow-up interviews to gather feedback about their experiences. Staff completed fidelity monitoring, follow-up interviews, and three brief surveys regarding feasibility, acceptability, and appropriateness of implementing the training. Results/Anticipated Results: The four sites conducted six trainings with a total of 42 CHW/Ps. Two sites each conducted one in-person training in English while the other two sites each conducted two virtual trainings, one in English and one in Spanish. Staff noted facilitators to successful implementation, including providing a facilitator guide and course materials in both languages and tips sheets for navigating REDCap; using the train-the-trainer model; and compensating CHW/P learners for attendance. The primary barrier noted was not having a budget for in-person trainings (e.g., refreshments, printed materials). CHW/P learners reported positive experiences with few suggestions for improving the training. Discussion/Significance of Impact: Preliminary results suggest the research best practices training for CHW/Ps is feasible, acceptable, and appropriate for implementation by partners at academic institutions and community-based organizations, regardless of language (i.e., English or Spanish) or delivery (i.e., virtual or in-person).

Objectives/Goals: Our study’s objective is to evaluate RadOnc-GPT, a GPT-4o powered LLM, in generating responses to in-basket messages related to prostate cancer treatment in the Radiation Oncology department. By integrating it with electronic health record (EHR) systems, the goal is to assess its impact on clinician workload, response quality, and efficiency in healthcare communication. Methods/Study Population: RadOnc-GPT was integrated with patient EHRs from both hospital-wide and radiation-oncology-specific databases. The study examined 158 pre-recorded in-basket message interactions from 90 non-metastatic prostate cancer patients. Quantitative natural language processing analysis and two randomized single-blinded grading studies, involving four clinicians and four nurses, were conducted to evaluate RadOnc-GPT’s response quality in completeness, correctness, clarity, empathy, and estimated editing time. Response times were measured to estimate the time saved for clinicians and nurses. The study population included patient messages across all phases of care (pre-, during, and post-treatment) for those undergoing radiotherapy. Results/Anticipated Results: In the single-blinded grader study, clinician graders evaluated 316 responses (158 from human care teams and 158 from RadOnc-GPT). Results showed RadOnc-GPT outperformed human responses in empathy and clarity, while humans excelled in completeness and correctness. Sentiment analyses using TextBlob and VADER revealed RadOnc-GPT responses had a positive mean score of 0.25, whereas human responses clustered around neutral. VADER analysis indicated a high median score for RadOnc-GPT, nearing 1.0, reflecting predominantly positive sentiment, while human responses displayed a broader sentiment range, indicating sensitivity to context. Clinicians averaged 3.60 minutes (SD 1.44) to respond, compared to 6.39 minutes (SD 4.05) for nurses, highlighting RadOnc-GPT’s efficiency in generating timely responses. Discussion/Significance of Impact: RadOnc-GPT effectively generated responses to individualized patient in-basket messages, comparable to those from radiation oncologists and nurses. While human oversight is still necessary to avoid errors, RadOnc-GPT can speed up response times and reduce pressure on care teams, shifting their role from drafting to reviewing responses.

Objectives/Goals: This study objective is to evaluate the prevalence and risk factors of burnout in practicing radiologists, with a focus on personal as well as systemic factors. It aims to identify and assess the existing strategies to mitigate burnout, enhance radiologist performance, and improve the quality of patient care. Methods/Study Population: The present study is a systematic review that summarizes existing literature on burnout in radiology, examining its prevalence, risk factors, and effect on diagnostic accuracy, decision-making, and job satisfaction. The review will synthesize validated evidence for emotional exhaustion, depersonalization, and professional fulfillment. The review discusses trends and solutions that have emerged from analysis of data within differing countries, subspecialties, and career stages, focusing on elevated risk of burnout in radiologists. It also assesses downstream effects on patient care quality such as missed diagnoses and increased medical errors. The review also discusses potential strategies for mitigating these negative effects on healthcare delivery. Results/Anticipated Results: The anticipated results of this review are expected to reveal significant variability in burnout rates across radiology subspecialties and practice settings, with prevalence ranging from 33% to 88% (Fawzy et al., 2023). Emotional exhaustion and depersonalization emerge as the most reported symptoms as consistently highlighted in previous studies. Major contributors such as workload, administrative burdens, and technological isolation (e.g., remote work and reduced face-to-face interaction) are anticipated. Radiologists in high-demand areas like interventional radiology and those in private practice may show higher burnout levels than those in academic settings. Protective factors, like exercise, supportive environments, and work-life balance, are expected to reduce burnout levels. Discussion/Significance of Impact: This study calls attention to the importance of addressing radiologist burnout as a key institutional priority. Early and effective interventions are essential for improving job satisfaction, reducing medical errors resulting in enhanced patient care. Addressing burnout is crucial for maintaining a sustainable and effective radiology workflow.

Objectives/Goals: Germinal matrix hemorrhage (GMH) is a devastating disease of infancy that results in brain-related pathologies. Following rupture of vasculature in the brain, red blood cell (RBC) lysis, and hemoglobin breakdown results in heme/iron-related toxicities. We hypothesize that these cellular pathologies are mediated in part by the complement system. Methods/Study Population: Post-natal mice on day 4 (P4) were subjected to collagenase induced-GMH and treated with various complement inhibitors that function at different points in the complement pathway and differentially prevent the generation of specific complement activation products. The principle bioactive complement activation products are C3 opsonins (C3b, iC3b, and C3d), the proinflammatory anaphylatoxins (soluble C3a and C5a peptides), and the terminal cytolytic membrane attack complex (MAC). Experimental groups consisted of: Wild-type (WT) naïve mice, and WT GMH-mice treated with either PBS (vehicle), CR2-Crry (C3 inhibitor that blocks all activation products), anti-C5 mAb (blocks C5a and MAC), C5aRA (blocks C5a-C5a receptor interaction), or anti-C7 mAb (blocks MAC). Study endpoints were P7 or P14. Results/Anticipated Results: Following GMH, CR2-Crry treatment decreased MAC deposition on RBC and additionally decreased heme oxygenase-1 expression, heme deposition, and iron-induced inflammation measured at P7. In support of a specific role for the MAC, anti-C7 mAb treatment resulted in similar outcomes and was similarly protective. Anti-C7 mAb treatment also reduced hydrocephalus development at a later time point (P14). A similar result was obtained using C7 deficient mice and with anti-C5 mAb treatment. On the other hand, no protective effect was seen with C5aR blockade, and double knock out of C3aR/C5aR also did not provide protection, indicating no role for the anaphylatoxins C3a and C5a and their receptors expressed on leukocytes and endothelial cells in exacerbating deteriorating outcomes. Discussion/Significance of Impact: Our data indicate a key role for the MAC in RBC induced hemolysis after GMH which serves as a driver of inflammation and early GMH pathogenesis. We further show that we can effectively increase precision by targeting solely the MAC complex acutely. Future work will be undertaken to determine temporal roles of individual complement activation products.

Objectives/Goals: To identify clinical trial teams that are at risk of not meeting their recruitment goals as early in the recruitment period as possible, this project aims to provide timely accrual information and projected forecasts for accruals by the end of the recruitment period across all trials at USC. Methods/Study Population: This project aggregates recruitment accrual data periodically from OnCore to create per-study accrual pages that contain an up-to-date accrual chart, metrics like expected and actual accrual per month, and projected recruitment based on an X-month moving average (3 months by default). Trials at risk are identified as early as possible by using these projections to classify risk. In this initial phase, we’ve classified trials as medium risk (80%–99% accrual) or high risk (less than 80% accrual). The dashboard is currently available for all clinical trials at USC and users are automatically restricted to the studies that they administer or work on depending on their role. Results/Anticipated Results: The dashboard will provide visibility across the institution for the current accrual for all clinical trials in a standard, user-friendly format and use the same metrics and definitions of risk for trial accruals not meeting their targets. This will allow the institution to identify trials that need intervention to get back on track using a single set of criteria across all research teams. Users in different roles, whether department heads, principal investigators, or study coordinators can view the current accrual for all the trials that they administer or work on in one central location. The dashboard will also help to identify quality issues in OnCore by performing data quality checks nightly. Discussion/Significance of Impact: By providing a central location for role-based access to timely clinical trial accrual for the institution, the dashboard helps to identify trials at risk of not meeting their recruitment targets as early as possible to provide corrective advice/measures.

Objectives/Goals: To investigate interventional clinical trial participation overall and by race, gender, and age. Methods/Study Population: We used Epic Cosmos, an aggregated, de-identified EHR platform including over 270 million patients, to examine overall clinical trial participation and the race, gender, and age composition of participants versus non-participants. Patients ≥5 years old with known race and gender and at least one healthcare encounter between 2021 and 2024 were included. Interventional trial enrollment was identified by a “research flag” indicating current or past participation in an interventional study within an Epic system contributing data to Cosmos. Race was categorized as American Indian, Asian, Black, Native Hawaiian, or White. Age-adjusted relative representation (RR) ratios were used to compare participation, with RR >1 indicating over-representation and RR Results/Anticipated Results: Of 130,455,189 patients meeting eligibility criteria, 0.52% (673,425) of patients were active or inactive in an interventional clinical trial. Results are shown in the figure below. The poorest representation was from Asian and NH/PI persons. Representation was most similar to the patient population for whites and AI/AN persons. Black males participated less and women, more than predicted by patient composition. Older patients participated more frequently than younger (age, mean (SD), y, 53 (22) vs. 46 (23); p Discussion/Significance of Impact: This is the first study we know of describing interventional trial participation in the USA across millions and millions of patients. Further research is needed to clarify whether these differences are due to the nature of the studies themselves (e.g., OB/GYN trials including only women, etc.) versus disparities in recruitment or otherwise.

Objectives/Goals: With qualitative interviews we aim to 1-Describe barriers and facilitators for post-transplant lymphoproliferative disease (PTLD) survivors’ access to late effects (LE) care. 2-Investigate clinicians’ perceptions of current and ideal PTLD LE care. Our long-term goal is to develop and pilot implementation strategies to standardize PTLD LE care. Methods/Study Population: Study population: We will recruit 20–25 PTLD survivors or their caregivers and 10–15 health care workers (HCW) from oncology, LE, and solid organ transplant (SOT) teams at St. Louis Children’s Hospital (SLCH). PTLD is a lymphoma-like cancer that occurs in solid organ transplant (SOT) recipients. PTLD survivors experience LE from cancer, yet many do not receive LE care. Research strategy: We will conduct qualitative semi-structured interviews based on the Consolidated Framework for Implementation Research (CFIR). A preliminary codebook will be based on CFIR and refined through transcript review. Team-based coding includes double coding and checking for intercoder reliability. We will generate coding reports to understand themes and identify barriers and facilitators of LE care. Results/Anticipated Results: We hypothesize survivors, caregivers, and HCWs will identify actionable factors to inform future studies to optimize LE care. We will examine the CFIR inner setting (resources, communication, and structural characteristics), outer setting (local attitudes and external pressures), innovation domain (adaptability, evidence base, and relative advantage), individuals domain (need, opportunity, and motivation), and implementation process domain. Our contribution will be novel. 1-This is the first assessment of barriers and facilitators for LE care in pediatric PTLD survivors. 2-We will consider input from HCWs across various disciplines delivering care to PTLD survivors. 3-We anticipate identifying unique contextual factors in PTLD survivors that will influence implementation of evidence-based LE care. Discussion/Significance of Impact: Pediatric cancer survivors experience LE. Coordinated care mitigates LE. PTLD survivors experience a high burden of LE, but less than 10% of PTLD survivors at SLCH follow in LE clinic. No studies have evaluated ideal delivery of LE care for PTLD survivors. Our findings will inform an implementation trial to improve delivery of LE care for PTLD survivors.

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

Objectives/Goals: Pediatric inguinal hernia (PIH) is a common diagnosis managed by pediatric surgeons. Patients typically present in the outpatient setting for evaluation. However, a subset present emergently with hernia incarceration, which has a higher risks. Our research aims to identify and address disparities in access to care of PIHR. Methods/Study Population: This study has a sequential multi-methods approach. First, we will perform a retrospective cohort study of pediatric patients (ages 0–18) who have undergone PIHR at St Louis Children’s Hospital (SLCH) over the past 5 years (n =  3,421). We will assess the impact of demographic and system-based factors on patient outcomes. Second, we will conduct interviews with caregivers of patients who have undergone PIHR. Qualitative interviews will be coded to prospectively identify themes in barriers and facilitators to accessing care, understanding of disease, and effectiveness of risk factor education by the pediatric care team. Finally, we will analyze the readability index (RI) of patient provided materials to assess the impact of health literacy on access to care and PIHR outcomes. Results/Anticipated Results: We hypothesize that demographic factors and socioeconomic status (SES) impact outcomes in PIHR. We anticipate higher rates of incarceration and emergent presentation of children from low SES and racial/ethnic racial minorities in our dataset, with longer time from initial presentation to definitive repair. Moreover, we anticipate identifying significant barriers to accessing care for non-white patients and patients with low SES, with gaps in understanding about the risk factors, presentation, and management of PIH. Finally, we hypothesize that the RI of our patient provided materials do not match community literacy rates, and there will be opportunities to implement new patient provided materials to improve parental education and communication in the perinatal space. Discussion/Significance of Impact: More than 600 patients undergo PIHR annually at a large tertiary care pediatric hospital, with those who are born premature being at higher risk. Using a mixed-methods approach, we aim to implement targeted interventions to facilitate access to care and improve patient outcomes in PIHR.