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: 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: 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: 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: Youth with IBD have preventive, psychosocial, and acute care needs beyond those of peers, yet receipt of services does not match those needs. Our objectives are to assess the feasibility of (1) an individualized care plan intervention to improve perceived and measured care quality and (2) a pragmatic trial design embedded in pediatric IBD practice. Methods/Study Population: This is a pilot rollout-design randomized trial (n = 60) at a regional academic medical center. Eligible patients are 13–19 years old with IBD for at least 3 months and scheduled for a follow-up visit during the trial. Research staff recruits from one cluster at a time until goal enrollment (14–16). Enrollees are randomized 1:1 to intervention (MyIBD now) or control (MyIBD after the trial). MyIBD combines a tabular summary of individualized acute, chronic, and preventive care needs with nurse facilitator support for patients to use the information. Surveys at baseline, 6 and 12 months measure care quality (Patient Assessment of Chronic Illness Care scale, vaccines, health services) and patient self-management skills (Partners in Health scale). Implementation outcomes are collected via chart review. Results/Anticipated Results: To date, 44 subjects have been randomized. Among subjects, the mean age is 16 years; 73% have Crohn’s disease, 77% have commercial insurance, 75% receive anti-TNF therapy, and 14% live in a rural area. Mean baseline perceived care quality (PACIC scale) is 76.9 (sd 16.3; out of 100); mean baseline perceived self-management skill (PIH scale) is 78.1 (sd 13.4; out of 96). On objective care quality measures, 59% have completed the HPV vaccine series, 32% have received an additional pneumonia vaccine; in the past year 68% have had a screening for mood disorders, 20% an emergency department visit for IBD, and 18% an IBD hospitalization. To date, the IBD clinical team has achieved 100% completion (intervention subjects receive MyIBD plus nurse facilitation) and 0% contamination (control subjects inappropriately receive MyIBD). Discussion/Significance of Impact: Study results to date support the feasibility of the pragmatic, embedded trial design and indicate opportunities for improvement in care quality as perceived by patients and as measured by common preventive and acute care quality indicators. An individualized care plan supported with nurse facilitation may improve pediatric IBD care quality.

Objectives/Goals: Micro-credentials (MCs) or digital badges are short programs designed to allow learners to gain knowledge and skills at their own pace to tailor their professional development. This study aims to examine the characteristics of learners completing MCs and explore their motivation for pursuing MCs through the University at Buffalo Clinical and Translational Science Institute (CTSI) program. Methods/Study Population: Currently, the CTSI offers five MCs in Effective Teaching, Good Clinical Practice, Responsible Research, Scientific Communication, and Translational Teamwork. Individuals who completed an MC (2019–2024) were identified by the UB Office of Micro-credentials. An invitation email and two reminders were sent to all individuals who received MCs asking them to complete a short online survey in July-August 2024. The survey included three questions about the type(s) of MCs completed, learners’ motivation for pursuing MCs, and perceived or actual benefits of completing an MC. The questions included multiple choice, select all that apply, and open-ended format, respectively. The survey was sent using Google Forms; data were analyzed using descriptive statistics. We received 25 completed surveys (29% response rate). Results/Anticipated Results: Since 2019, 85 individuals completed MCs at Buffalo CTSI including 21 faculty, 18 trainees, 26 students, and 20 staff. The most popular MC, Responsible Research (65% of completers), is based on the Responsible Conduct of Research series, which consists of modules on authorship ethics, ethical use of animals (IACUC) and human subjects (IRB), conflicts of interest/commitment, and responsible data acquisition and management. We found that 33% of responders were motivated to obtain the MC to advance their career and for professional development, 30% for lifelong learning, and 23% intended to use the badges to showcase their proficiency to potential employers. The greatest benefits reported were to obtain knowledge/skills for their professional career (46%) and improve their ability to receive research funding (14%). Discussion/Significance of Impact: Micro-credentials are valuable learning tools to stay current on changing research requirements, with ability to engage asynchronously. Badges also provide unique professional development opportunities for students and research workforce (staff and community stakeholders) who have limited resources (time and money).

Objectives/Goals: To evaluate equity in utilization of free initial health evaluation (IHE) services among members of a limited health care program, the World Trade Center (WTC) Health Program (Program), to inform intervention development and provide insights for similar healthcare programs. Methods/Study Population: We included Program members who newly enrolled during 2012–2022, and who had an IHE or were alive for ≥ 1 year after enrollment. Program administrative and surveillance data collected from January 2012 to February 2024 were used. We evaluated two outcomes: timely IHE utilization (proportion of members completing an IHE within 6 months of enrollment) and any IHE utilization (proportion completing an IHE by February 2024). We described IHE utilization by enrollment year and various members’ characteristics and conducted multivariable logistic regression models to estimate adjusted odds ratios for IHE utilizations to identify factors related to potential inequities for the two member types: Responders, who performed support services, vs. Survivors, who did not respond but were present in the New York disaster area. Results/Anticipated Results: A total of 27,379 Responders and 30,679 Survivors were included. Responders were 89% male, 70% 45–64 years old at enrollment and 76% White. Survivors were 46% female, 54% 45–64 years old at enrollment, and 57% White. Timely IHE utilizations remained relatively stable (~65%) among Responders across time and increased from 16% among Survivors who enrolled in 2017 to 68% among Survivors who enrolled in 2021. Timely IHE utilization was lower for younger members (enrolled Discussion/Significance of Impact: This study highlights Program achievements and gaps in providing equitable IHE services. Strategies to improve members’ equitable IHE utilization can include: adopt/expand flexible scheduling; increase non-English language capacity and cultural competency; and facilitate transportation/assistance for members with accessibility barriers.

Objectives/Goals: Large-scale tumor sequencing efforts have led to annotations of novel cancer hotspot mutations that may underlie driver or cooperative function. We have sought to define the molecular consequences of such hotspots associated with pediatric DICER1 syndrome cancers, with the ultimate goal of revealing novel targets that may inform new standards of care. Methods/Study Population: We have performed genomic analysis to identify tumor types (in TCGA and MSK-IMPACT patient data) for which mutations in the Dicer1 gene (encoding Dicer protein) emerge as the dominant signature of driver function. As Dicer is a critical RNA processing factor responsible for the generation of microRNAs, which are posttranscriptional gene regulatory molecules, we have modeled these mutations in human embryonic stem cells in order to study the direct effects on miRNAs and their target genes in an isogenic background. In addition to providing the required setting for unambiguous attribution of function to specific mutations, clonal human ES cells offer an opportunity for modeling of both developmental and cancer requirements associated with altered Dicer function. Results/Anticipated Results: Through generation of genomics and functional datasets from matched genotypes in Dicer mutated human ES cells, we have identified specific alterations in miRNAs and their effects on target genes. Unexpectedly, we found direct evidence for both loss of function and gain of function attributable to Dicer mutations. In addition, through integrated analysis of genomic data from tumor sequencing datasets and our human ES cell models, we have identified potential miRNA and target gene alterations that underlie tumorigenic potential, nominating gene candidates for targeted therapy in DICER1 syndrome. Direct mouse modeling of such candidate gene targets has revealed evidence for driver function of identified miRNA and their targets. Discussion/Significance of Impact: DICER1 syndrome cancers comprise a wide variety of rare pediatric tumor types. Presently, we still lack an effective standard of care. Furthermore, the previous lack of molecular profiling precluded targeted therapy opportunities. Our precise knock-in modeling of Dicer hotspots and deep profiling of relevant tumors now provide candidate targets.

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: This study will integrate scientific evidence to create messaging about the modifiable risk factors for Alzheimer’s disease (AD) and examine how culturally tailoring elements in message content, such as text and visualizations in infographic messaging, impacts cognitive processing of AD prevention messages among Black adults. Methods/Study Population: This study is guided by the two-dimensional theory of cultural sensitivity and the elaboration likelihood model (ELM). The two-dimensional theory distinguishes between surface structure (visualizations) and deep structure (text with embedded cultural features) in messaging. The ELM considers how message attributes influence cognitive processing. A 2 × 2 factorial experiment will test the impact of cultural features (surface vs. deep) and message type (text-based vs. infographic) on persuasive outcomes regarding modifying AD risk factors. Black adults will be recruited from local churches and randomly assigned to one of four conditions, after which they will complete post-test measures. Statistical analyses will determine the effects of cultural tailoring and message effects on outcome variables. Results/Anticipated Results: Guided by previous literature (Resnicow et al., 1999; Lazard & Atkinson, 2015; Lam et al., 2022), we hypothesize an interaction effect of cultural tailoring and message type, wherein surface structure infographic messages and deep structure text-based messages will outperform the other two message conditions, resulting in greater cognitive processing and more positive attitudes and behavioral intentions toward modifying AD risk factors. In addition, a research question asks whether there will be differences between surface structure infographic messages and deep structure text-based messages on outcome variables. The study will advance understanding of the effects of cultural sensitivity and visual vs. text-based messaging by integrating these literatures. Discussion/Significance of Impact: This research will contribute to the literature on culturally tailored health messages and persuasive effects of text vs. visual messages. The findings can inform the development of more effective, culturally relevant public health campaigns for AD prevention by reducing risk for AD through modifiable risk factors in diverse populations.

Objectives/Goals: Acute myeloid leukemia (AML) is the second most common leukemia among pediatric populations. Approximately 15% of pediatric AML cases have KMT2A gene rearrangements (KMT2A-r), which confers a worse prognosis. Our goal is to better characterize the biologic landscape of KMT2A-r pediatric AML. Methods/Study Population: This study utilizes deidentified peripheral blood and/or bone marrow samples banked in the Children’s Mercy Tumor Bank Biorepository. We investigated four KMT2A-r pediatric AML patients and six patients with other AML subtypes using samples collected at diagnosis and remission that were stored in the “tumor bank.” In addition, we assessed 47 tumor bank samples from patients with other leukemia subtypes. We performed differential expression (DE) analysis on bulk RNA sequencing comparing KMT2A-r and all other AML subtypes, as well as single-cell RNA sequencing and proteomic analysis on the larger cohort. We then coalesced these data to better identify processes and pathways that are dysregulated in KMT2A-r AML, specifically aiming to find those that were contributing to leukemogenesis. Results/Anticipated Results: Transcriptomic analysis showed that HOXA10 and MEIS1, two genes associated with immature myeloid populations and KMT2A-r leukemias, were more highly transcribed in AMLs than other leukemias. In addition, our DE analysis showed significantly higher transcription of ITGA7, a gene shown to correlate with poorer prognosis in AML, in our KMT2A-r samples when compared to other AML subtypes. FAM46C, a tumor suppressor gene contributing to mRNA stabilization, was less highly expressed in KMT2A-r AML when compared to other AML subtypes. Of note, low expression of FAM46C is associated with poorer survival and treatment response in multiple myeloma, and our findings suggest it may also be relevant to AML. Proteomic analysis is currently in process. Discussion/Significance of Impact: Transcriptomic analysis identifies unique molecular features of pediatric KMT2A-r AML. We anticipate that our proteomic data will do the same and will also corroborate our RNA findings. Taken in combination, these results will provide a more complete picture of the specific mechanisms contributing to this aggressive leukemic subtype.

Objectives/Goals: This study aims to harmonize quality indicators (QIs) across University of Toronto-affiliated microbiology labs to establish universal benchmarks that enhance performance, patient safety, and health outcomes. Harmonized QIs will enable effective comparisons and enhance the consistency of care. Methods/Study Population: The study employed the Delphi method, a structured and iterative process to build consensus. An expert panel of clinical microbiology trainees, medical microbiologists, trainees, and site leads from five University of Toronto-affiliated microbiology labs was assembled. Initial insights were gathered through surveys and a comprehensive scoping review of the literature. The study involved two rounds of feedback, a SurveyMonkey-based survey, with a defined consensus of 75% agreement among participants. Followed by an implementation survey conducted through REDCap to assess how these QIs were adopted in practice and identify barriers to implementation. Results/Anticipated Results: The study achieved consensus on nine high-impact quality indicators, including blood culture volume and contamination rates, cerebrospinal fluid transport time, and turnaround times for Gram stain results. Blood culture contamination and positivity rates garnered the highest agreement, at 100% and 91%, respectively. While some indicators were widely accepted and implemented, others faced resistance due to feasibility concerns. The study also identified significant variability in the level of adoption across the participating laboratories, pointing to operational challenges and the need for further efforts to address these barriers. Discussion/Significance of Impact: This study highlights the importance of QI harmonization in improving lab services and patient safety. It reveals challenges in standardizing practices but promotes uniformity in QIs, laying the groundwork for better inter-lab collaboration, consistent outcomes, and improvements in microbiology.