Citations

Objectives/Goals: To assess the attitudes toward social justice of residents and faculty following the didactic series and evaluate the impact of the longitudinal curriculum on resident engagement in social justice activities through community engagements. Methods/Study Population: Data were gathered through questionnaires collected from participating residents and faculty. The session topics were chosen based on “Precepting Toward Social Justice” curriculum from the University of Minnesota Department of Family Medicine and Community Health, including sessions on advocacy, diversity, and implicit bias, among others. The self-assessment questionnaires were specific to the topics of the lecture, assessing knowledge, skills, and attitudes before and after the education sessions. Participants were asked to rate these aptitudes of each topic from “none” to “expert.” Results/Anticipated Results: Out of 22 total participants, 16 returned surveys. Overall, there was a substantial improvement in aptitudes after the lecture. There was an increase in reported above average knowledge of topics: Agency (12.5% to 56.25%), Humility (18.75% to 62.5%), Dignity (12.5% to 62.5%), Partner (18.75% to 50%), Awaken (37.5% to 75%), Place (12.5% to 43.75%), Asset (0% to 37.5%), Sanctuary (6.25% to 50%), Belonging (0% to 37.5%), Whole (0% to 43.75%), Liberation (12.5% to 68.75%), and Heal (37.5% to 75%). 31% reported that the lectures alone had an above average influence on pursuing more social justice activities through community engagement. 44% reported that the lectures had an above average impact on their subsequent patient encounters. 69% stated that this series helped develop their overall social justice skills. Discussion/Significance of Impact: All patients deserve equitable care. Family physicians have a unique role in addressing social justice concerns to eliminate inequalities and drive for better health outcomes. By enforcing social justice in education and implementing it into practice, satisfaction, trust, and well-being of patient and provider will be improved.

Objectives/Goals: This proposal outlines the successful deployment of a research training initiative to support the formation of a Learning Healthcare System. Mayo Clinic Health System (MCHS) rural providers were offered the opportunity to the fundamentals of clinical research via Clinical and Translational Science Awards core curriculum, mentorship, and an online seminar series. Methods/Study Population: MCHS funded 4 key introductory research courses: 1) Manuscript Writing, 2) Grant Writing, 3) Basic Biostatistics, and 4) Essentials of Clinical and Translations Science Program. In addition to course offerings, a Research Interest Group was formed to guide novice rural researchers on topic selection and study design. This cultivated interest to create a 16-month clinical research webinar series offering CME credits. Subsequently, an internal MCHS RFA was launched seeking early-stage investigator pilot proposals focused on rural health. Results/Anticipated Results: In 2023, over 140 MCHS providers enrolled in 324 CCaTS research courses. This training led to the submission of 53 proposals to the inaugural MCHS 2023 RFA, of which 15 were awarded. Additionally, 14 MCHS extramural grants were submitted in 2023. Training efforts expanded in 2024 to include an online research seminar series covering various study topics and providing CME credit, with an approximate attendance up to 196 attendees per session. The second annual MCHS RFA resulted in 4 internal awards, with an additional 22 extramural grant submissions. These collective efforts have increased the number of MCHS first and last author publications and the number of MCHS providers with academic rank. Discussion/Significance of Impact: Leadership’s commitment of resources to educate, mentor, and engage clinicians was crucial to our success and demonstrated a strong return on investment. To maximize impact in community-based practice, continued commitment is needed in the form of protected research time, funding, and research administration support of projects of interest

Objectives/Goals: The expanding emphasis on translational science necessitates a rethinking of traditional academic formats. To align with the central themes of CTS, we have redesigned our PhD journal club and WIP sessions, introducing novel and innovative approaches that enhance the relevance of these activities to real-world scientific and clinical challenges. Methods/Study Population: The newly adapted journal club format for CTS Predoctoral students at Mayo Clinic maintains the traditional focus on literature review but now incorporates a structured analysis of the clinical implications and potential applications of the research. This innovation aims to foster a deeper understanding of how basic research findings can be translated into improved patient outcomes and healthcare practices. Similarly, the WIP sessions have been restructured to offer an engaging and dynamic learning environment designed to empower clinical and translational science predoctoral students to effectively present their research while emphasizing the challenges they have overcome, demonstrating the translational potential of their findings, and enhancing their communication skills. Results/Anticipated Results: Feedback from participants demonstrates strong support for the new format. Students report a greater engagement with the material and a clearer understanding of how their research can contribute to improving patient outcomes. Discussion/Significance of Impact: These changes accommodate the diverse projects in CTS and embody a commitment to pushing the boundaries of knowledge in CTS. This dual transition marks a significant advancement in preparing PhD students for careers in translational science, ensuring that their research is not only rigorous but also impactful in the real world.

Objectives/Goals: Community-based practices have limited research opportunities for providers. As a rural community-based health system, Mayo Clinic Health System (MCHS) sought to create intramural funding mechanisms to help early-stage researchers conduct pilot research so they are more competitive to compete for more robust extramural funding opportunities. Methods/Study Population: We created a Research Seed Grant Program infrastructure across our four MCHS regions (Southwest and Southeast Minnesota, Northwest and Southwest Wisconsin). This model program featured an initial research funding announcement call based on 6 prioritized programs (AI Validation & Stewardship, Cancer, Health Equity, Population Health, Rural Health, Learning Healthcare System [LHS]), with submissions uploaded to a central electronic repository. Proposal review and ranking was organized on a regional basis, with ranking of all proposals by at least 2 clinical scientist reviewers according to the NIH domain-specific framework (i.e., 1.0 best > 9.0 worst). Awards were competitively selected by conformity to prioritized research areas and through ranking of most competitive overall application scores. Results/Anticipated Results: For our inaugural RFA, we received 55 grant application submissions across the MCHS regions. Fifteen of the most highly ranked applications were selected for awards on a per region basis, providing direct funding as well as protected investigator research time of 10% for up to six months. The selected projects address several research priorities including improving access, reducing health disparities, improving behavioral health in our communities, increasing cancer screening and prevention, and community-based pragmatic trials and interventions. Outcomes from these now completed pilot projects remain pending at this time. Funding for this seed grant program was supported by philanthropy, Mayo Clinic Research Administration, Mayo Clinic Comprehensive Cancer Center, and the Mayo Clinic CCaTS Rural Core. Discussion/Significance of Impact: We present this framework for a LHS-focused Seed Grant program model for consideration of adoption by other national/international LHS. Future plans include tracking of outcome metrics (e.g., published peer review articles, extramural grant applications) of this initial cycle and future expansion of this program to support the goals of our LHS.

Objectives/Goals: Longitudinal studies capture dynamic host–environment interactions crucial to microbiome research. Commonly used mixed-effects models can struggle with small clinical samples, like many endometrial cancer studies. We will compare them to simpler fixed-effects models, aiming to develop a new fixed-effects differential abundance alternative. Methods/Study Population: Starting with simulated data for linear models with a single treatment effect, we will incrementally increase complexity to reflect real-world microbiome data. To observe conditions of misspecification, simulated data of repeated measures will be generated using different distributions, while varying parameters and inter-class correlation. In each condition, linear fixed- and mixed-effects models will be fitted 1000 times to empirically determine p-value, type 1 error rate, and power. We will increase the verisimilitude of our approach by using endometrial cancer data from our lab as a real background, while adding simulated signals. This data will be used to assess extant differential abundance models against our novel fixed-effects model. Results/Anticipated Results: Our initial findings indicate that fixed-effects models maintain control over type 1 error rates in small samples, while mixed-effects models do not perform as reliably. We are now exploring the effects of confounders on type 1 error rates and power in linear models, while our next step will evaluate generalized linear models in a differential abundance context. We expect that the fixed-effects models will continue to be as reliable as mixed-effects models, while being less computationally complex. After establishing our theoretical basis, our novel model should perform comparably to mixed-effects models on pseudo-simulated endometrial cancer data and better at small sample sizes. We will finally apply our model to real endometrial cancer data to identify microbial markers of disease predisposition. Discussion/Significance of Impact: By characterizing and improving these statistical tools, we seek to increase the robustness and power of microbiome study results (especially at small sample sizes), ultimately supporting better-informed translational research decisions. This work underscores the importance of statistical methods in advancing microbiome research.

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: Primary sclerosing cholangitis (PSC) manifests with an inflammatory milieu that leads to fibrotic scarring of the liver. Human PSC liver bile ducts are enriched with neutrophils; however, their infiltration and functional role is unexplored. Our goal is to investigate the mechanism and impact of peribiliary neutrophil infiltration observed in PSC. Methods/Study Population: Primary cholangiocytes (bile duct cells) isolated from WT and mouse models of PSC (3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC)-fed mice and Mdr2-/- mice) were analyzed by RNA-sequencing. Immunofluorescence (IF) was performed on liver tissues from PSC patients and mouse models of PSC for markers of bile ducts and neutrophils (KRT19 and MPO). Intrahepatic leukocytes (IHL) isolated from mice livers were evaluated for neutrophil abundance and activation state. Anti-Ly6G antibody-mediated neutrophil depletion in Mdr2-/- mice was analyzed by IF, histology, and cytometry by time-of-flight (CyTOF). Cholangiocytes stimulated with TNFα (to induce an inflammatory phenotype) were analyzed for neutrophil chemoattractants with genetic and pharmacological interventions. Results/Anticipated Results: RNA-seq analysis of primary cholangiocytes from PSC mouse models revealed enrichment in inflammatory and neutrophil degranulation pathways. Flow cytometry and RT-PCR analysis revealed an increase in the neutrophil population in PSC mice with activated phenotype. Peripheral depletion of neutrophils in Mdr2-/- mice alleviated liver injury and inflammation, along with a reduction in peribiliary neutrophil infiltration and attenuated bridging fibrosis. CyTOF analysis showed a significant reduction in CD8+ T cells upon neutrophil depletion, implying neutrophils sustain CD8+ T cells in PSC liver. Mechanistically in cholangiocytes, TNFα mediates expression of neutrophil chemoattractants, CXCL1 and CXCL8, through the cyclic GMP-AMP synthase stimulator of interferon genes (cGAS-STING) pathway. Discussion/Significance of Impact: Our findings suggest that activation of the STING pathway in cholangiocytes in cholestatic liver disease triggers an immune response resulting in peri-portal neutrophil infiltration via CXC chemokines. The sustained presence of these activated neutrophils engages the adaptive immune system to perpetuate the inflammation and fibrosis seen in PSC.

Objectives/Goals: In January 2023, Mayo Clinic set a goal to have 10% of studies open for six months or more without accrual. At that time, Mayo Clinic Florida had 19% non-accruing studies and 18% non-accruing clinical trials. Research administration implemented strategies to improve accrual outcomes. Methods/Study Population: Two strategies were developed to address non-accruing trials: a clean-up approach and a proactive approach. The clean-up approach involves escalating studies that haven’t been enrolled in over 6 months, identifying barriers, and escalating communication with the principal investigator (PI) and research administration alongside a physician partner. The proactive approach targets studies at the 3-month mark to address issues before reaching 6 months without accrual. Both strategies aim to reduce the cost and effort of non-accruing studies by either creating an enrollment plan or closing the study. Results/Anticipated Results: Since implementation, Mayo Clinic Florida’s non-accruing study portfolio decreased by 10%, and its clinical trials non-accruing portfolio decreased by 7% as of October 2024. Research Administration tracks key metrics (reasons for no enrollment, justifications, and actions) to identify trends and mitigate future accrual risks. A REDCap electronic data capture tool hosted at Mayo Clinic (supported by CCaTS grant UL1TR002377)1 notifies principal investigators when their studies are non-accruing. Future plans include establishing an API with Mayo Clinic’s portfolio management system to streamline the process while maintaining awareness and collaboration. Discussion/Significance of Impact: Through increased monitoring, enhanced communication, and deeper collaboration, Mayo Clinic Florida effectively reduced non-accruing studies in its research portfolio. This approach minimizes effort and costs associated with under-enrolled studies while tracking key metrics to inform future study development.

Objectives/Goals: The operation of a clinical trials unit involves multifaceted tasks and stakeholders. A competent information system is critical to daily operations while ensuring smooth conduct of clinical research. We share 15 years of experience in the design and implementation of such a system at Mayo Clinic to inform other institutions with similar interests. Methods/Study Population: The Informatics team collaborated closely with nurse leaders and elicited input from additional stakeholders including nurse unit coordinators, lab managers, schedulers, investigators, study coordinators, and regulatory specialists throughout the phases of system design, development and continuous enhancements, and expansion. The stakeholders offered insights on the corresponding requirements throughout the study life cycle, from engaging with the study sponsor, operational review for protocol execution, development of study budgets, human subject protection and risk mitigation, data management and integration, to outcome monitoring, and regulatory reporting. The activities were then translated into functional components and implemented as a seamless and effective solution. Results/Anticipated Results: Patient safety, scientific rigor, operation automation, efficiency, and regulatory requirements were all considered in developing an integrated system, or the clinical research trials unit (CRTU) Tools. Our institution has leveraged the system for essential tasks from the study start-up, visit scheduling and execution, specimen collection and tracking, to individual protocol metrics and billing. We adopted a measure-as-we-go methodology so that data such as visit census, resource usage, and protocol deviation are tracked and collected during routine use of the system. Specifically, an issues/concerns/exceptions (ICE) tool is used for quality control and patient safety. Moreover, data quality greatly benefits from a task dictionary, standardizing the study activities that can be ordered and executed. Discussion/Significance of Impact: The implementation of a well-rounded clinical trials unit information system not only improves the operation efficiency and team productivity but also ensures scientific rigor and contributes to patient safety. We believe the experience can be informative to other institutions. More details will be shared in the poster.

Objectives/Goals: Mayo Clinic’s Clinical Trials Beyond Walls™ (CTBW) program collaborates with study teams to implement decentralized elements in clinical trials, enabling participation from home or local settings. In cancer treatment trials, traditional paper pill diaries are replaced with real-time digital tracking solutions to monitor chemotherapy adherence. Methods/Study Population: The CTBW team developed a solution to deliver electronic pill diaries to research participants using the electronic health record (EHR) system Epic and patient portal MyChart1. The solution includes a portal message to remind participants to take chemotherapy. Medication dose, date taken, and reasons for missed doses (e.g., “I forgot” or “side effects were bothersome”) are captured. An automated in-basket notification system alerts the study team when predefined conditions are met. Configurable medication schedules ensure diaries are sent according to the prescribed frequency. Reports were generated to allow study teams to monitor all participant diaries. Results/Anticipated Results: The CTBW team implemented this digital pill diary in neuro-oncology trial NCT066250472. We anticipate the pill diary in the patient portal will enhance chemotherapy adherence by capturing real-time data in a platform widely used by Mayo Clinic patients. This patient-reported data is stored in the EHR, where it is accessible to providers and study teams. This allows for continuous monitoring, which facilitates a streamlined review of potential adverse events, improved compliance visibility, and timely treatment adjustments compared to paper-based or external solutions. The system also streamlines data entry, reducing human error and eliminating manual transcription. The created language and workflow templates allow the CTBW to scale this approach to future cancer trials Discussion/Significance of Impact: Decentralized clinical trial participants may never visit Mayo Clinic, making digital recording essential. The EHR-based digital pill diary enables continuous monitoring within a familiar system for providers and patients, increasing study team visibility, and allowing for earlier intervention in cases of non-compliance or adverse events.