Objectives/Goals: Our goal for this project is to develop a metric that integrates the intersectional social and structural determinants of health and well-being into the existing policy development framework to impact the integration of such considerations on population mental health. Methods/Study Population: This project was developed from a case study module offered by the Translational Research Program at the University of Toronto. This course was designed to sharpen contextual inquiry skills and further develop a case through employing strategies, including outreach engagement with stakeholders, conducting informational interviews and formulating potential pathways forward based on the integration of insights from interdisciplinary perspectives. Results/Anticipated Results: The anticipated outcome would be improved mental health outcomes as measured by the Mental Health Commission of Canada’s Mental Health Indicators (Mental Health Commission of Canada, 2015) Discussion/Significance of Impact: Although there are established mental health indicators and policy development framework the two operate independently of each other. Our proposal bridge the gap between the sectors so that one may inform the other, and they can collectively formulate reflective and representative policies.

Objectives/goals: This project will focus on identifying the barriers that result in low adherence to quality care indicators that establish effective and efficient pediatric emergency care. The overall objective is to understand motivations behind adherence (or lack thereof) and find solutions to facilitate compliance. Methods/Study Population: This study will use a mixed-methods design to investigate the barriers. Quantitative data will be collected through a survey provided to healthcare providers involved in pediatric emergency care, including physicians, nurses, and administrative staff in both pediatric and general hospitals. Qualitative data will be collected through semi-structured interviews with a group of respondents to gain insight on their experience regarding compliance. Quantitative data will be analyzed using statistical analyses while qualitative data will undergo a thorough thematic analysis. Both sets of data will be reviewed to identify themes and differences in barriers across hospital types and healthcare roles. Results/Anticipated Results: We will have gathered insights and perspectives from key stakeholders that are relevant to our study to ensure a comprehensive understanding of any potential implications that may arise from our study. We anticipate that the specific results will highlight key differences in adherence between pediatric and general hospitals. The study is expected to identify specific barriers hindering compliance with established guidelines in both settings. The results may be used to increase adherence to critical quality indicators and improve patient care. Discussion/Significance of Impact: Pediatric injury care prioritizes the immediacy of care for children with acute illness and injury. With certain hospital protocols not being adhered to, there is a risk of wasting crucial time and resources that can affect patient care outcomes. The results would provide recommendations to improve and increase efficiency in pediatric injury care.

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

Objectives/Goals: To present findings from a focus group study that evaluate clinical research professionals’ (CRPs) team science learning preferences. The study aims to better understand CRPs’ experiential perceptions of team science skills, training gaps, team cohesion, conflict, and contributions for their preferred team science training. Methods/Study Population: This study targeted CRPs across various roles in Academic Health Centers via focus groups. The focus groups will assess current skills, identify training gaps, and share experiences on team cohesion, team conflict, team contribution, and their thoughts and perceptions about clinical research professional team science training. The focus groups will be held via Zoom in the Autumn of 2024 with volunteer participants from an initial survey that was conducted earlier in 2024. We will report on combined data from multiple 90-minute focus groups, with approximately 6 participants per session. Results/Anticipated Results: The focus group facilitator’s guide includes questions informed by the CRP team science learning needs assessment results and other questions on team issues that would benefit from focused training. Focus group methods and demographic characteristics of the participants by role and experience level will also be presented. Qualitative analyses of recorded focus-group discussions will present key themes by demographic groups, and as a whole, these data will contribute to the development of CRP team science educational programs and toolkits. Discussion/Significance of Impact: CRPs are vital members of clinical translational science teams. Overlooking CRP team science training can negatively affect the efficiency and effectiveness of the clinical translational science enterprise. CRP team science skills will foster a more collaborative and productive research environment.

Objectives/Goals: This research aims to harness electronic health records (EHR) combined with machine learning (ML) to predict necrotizing enterocolitis (NEC) in preterm infants using data up to their first 14 days of life. We aim to provide interpretable results for clinical decisions that can reduce infant mortality rates and complications from NEC. Methods/Study Population: Through a retrospective cohort study using data from the University of Florida Integrated Data Repository and One Florida, we will develop machine learning models suitable for sequential data to predict NEC. Our inclusion criteria include very low birth weight (VLBW; < 1500g) infants born < 32 weeks gestation and EHR data availability from the first 14 days of life. We will include infants with NEC and infants without NEC to train our ML model. Exclusion criteria include infants diagnosed with spontaneous intestinal perforation and severe congenital anomalies/defects requiring surgery. Results/Anticipated Results: We anticipate that our model will provide an accurate and dynamic prediction for the risk of NEC in neonates using data up to the first 14 days of life. Our model will be interpretable to identify key risk factors and can integrate real-world clinical insights to increase early detection and improve patient outcomes. Discussion/Significance of Impact: The development of a model to predict NEC could be used in neonatal intensive care guidelines and protocols and could ultimately decrease mortality, reduce complications, improve the overall quality of care, and lower healthcare costs associated with NEC.

Objectives/Goals: The Standards for Reporting Implementation Studies (StaRI) are the Enhancing the Quality and Transparency of Health Research (EQUATOR) Network 27-item checklist for Implementation Science. This study quantifies StaRI adherence among self-defined Implementation Science studies in published Learning Health Systems (LHS) research. Methods/Study Population: A medical librarian-designed a search strategy identified original Implementation Science research published in one of the top 20 Implementation Science journals between 2017 and 2021. Inclusion criteria included studies or protocols describing the implementation of any intervention in healthcare settings. Exclusion criteria included concept papers, non-implementation research, or editorials. Full-text documents were reviewed by two investigators to abstract and judge StaRI implementation and intervention adherence, partial adherence, or non-adherence. Results/Anticipated Results: A total of 330 documents were screened, 97 met inclusion criteria, and 47 were abstracted including 30 research studies and 17 protocols. Adherence to individual StaRI reporting items ranged from 13% to 100%. Most StaRI items were reported in >60% of manuscripts and protocols. The lowest adherence in research studies was noted around economic evaluation reporting for implementation (16%) or intervention (13%) strategies, harms (13%), contextual changes (30%), or fidelity of either the intervention (34%) or implementation (53%) approach. Subgroup analyses were infrequently contemplated or reported (43%). In protocols, the implications of the implementation strategy (41%) or intervention approach (47%) were not commonly reported. Discussion/Significance of Impact: When leveraging implementation science to report reproducible and sustainable practice change initiatives, LHS researchers will need to include assessments of economics, harms, context, and fidelity in order to attain higher levels of adherence to EQUATOR’s StaRI checklist.

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

Objectives/Goals: Develop a cervicovaginal mucus replacement to prevent bacterial vaginosis (BV) in pregnant women. Our therapeutic, specialized hydrogel in natural enhancement for vaginal health (SHINE-VH), is formulated through polymer chemistry, tested for efficacy and safety through microbiology, and translated through clinical and translational science. Methods/Study Population: We will develop SHINE-VH with optimized viscoelastic and mucoadhesive properties intended to mimic healthy vaginal mucus. SHINE-VH will be synthesized via robust photoiniferter methods and investigated through shear rheology, sugar binding, and permeability studies. To evaluate the biocompatibility and safety profile of SHINE-VH, we will utilize a series of in vitro models to test its impact on the viability and cytotoxicity of human vaginal epithelial cells. In addition, we will assess the capacity of SHINE-VH to fortify vaginal barrier integrity and modulate anti-inflammatory activities in a 2D epithelial barrier model exposed to BV-associated pathogens. Lastly, employing organ-on-a-chip technology, vaginal swabs from both healthy and suspected BV pregnant patients will be treated with SHINE-VH. Results/Anticipated Results: SHINE-VH will mimic the protective, hydrophilic gel network of natural mucins. The viscoelastic properties of our formulation determined by shear rheology will be tuned through concentration and polymer composition to mimic vaginal mucus. We will also show the facile movement of small molecule nutrients through the SHINE-VH network via sugar-binding and permeability tests. Additionally, we anticipate that the introduction of SHINE-VH, due to their xenobiotic nature as synthetic mucins, will modulate the microbiota by diminishing inflammation, thereby reinforcing the cervicovaginal mucus and cultivating a vaginal microbiome that is more resilient to the disruptive impacts of BV. Such modulation could lead to a marked difference between the SHINE-VH-treated and untreated groups. Discussion/Significance of Impact: BV affects ~30% of women globally and is associated with severe gynecologic and obstetric complications, representing a significant unmet need in women’s health. SHINE-VH offers a novel approach to BV management, aiming to strengthen vaginal mucosal integrity, potentially reducing BV prevalence, and improving women’s health outcomes.

Objectives/Goals: Osteosarcoma (OS) is the most common primary bone malignancy in humans and dogs. >40% of children and >90% of dogs succumb to metastatic disease. We hypothesize MYC overexpression in metastatic canine and human OS contributes to an immunosuppressive tumor environment by driving tumor-associated macrophage influx and T lymphocyte exclusion. Methods/Study Population: To characterize the role of oncogenic MYC signaling in the canine metastatic tumor immune microenvironment (TIME), 42 archived FFPE lung metastatic canine OS samples were evaluated for MYC copy number variation (CNV), mRNA, and protein expression via ddPCR, nanostring analysis, and immunohistochemistry (IHC). Seven samples also underwent GeoMX spatial profiling to more specifically evaluate T cell and macrophage transcriptional profiles based on MYC status. To determine the role of MYC target modulation as a potential therapeutic option, canine and human OS cell lines were treated with a novel MYC inhibitor (MYCi975) and assessed for effects on survival, proliferation, and cytokine profiles. Results/Anticipated Results: We demonstrate that copy number gains are not a key driver of MYC hyperactivity in canine metastatic OS. However, stratification based on MYC protein expression demonstrates that “MYC-high” tumors are associated with downregulation of cytotoxic effector T-cell associated transcripts and upregulation of tumor-associated macrophage (TAM) and extracellular matrix remodeling transcripts. We also report that MYCi975 treatment of canine and human OS cell lines results in significant inhibition of OS cell survival and proliferation at concentrations that are pharmacologically achievable in mice. Furthermore, we demonstrate MYC inhibition by MYCi975 is associated with reduced pro-inflammatory cytokine secretion in OS cell culture models. Discussion/Significance of Impact: While MYC overactivity in metastatic canine OS may not be genomically driven, other mechanisms that lead to increased MYC protein expression are associated with transcriptomic profiles supportive of local immunosuppression. Pharmacologic targeting of MYC may serve as a strategy to bolster immunotherapeutic options in metastatic OS treatment.

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

Objectives/Goals: High-performing translational teams (TTs) effectively draw knowledge from empirical data to develop health solutions. However, some TTs lack rigorous data approaches, resulting in inefficiency. The ICTR data science initiative integrates team-oriented data science for more innovative and reproducible translational research. Methods/Study Population: To help TTs better leverage data science, the Institute for Clinical and Translational Research (ICTR) at the University of Wisconsin-Madison orchestrated a strategic initiative involving four main actions. • Assess needs. Determine how TTs are using data science and identify essential tools for success. • Establish partnerships. Develop strategic relationships to centralize resources and engage data scientists. Provide team science training to ensure effective integration. • Develop educational pathways. Design and implement workshops to demystify novel data science tools and upskill translational scientists. • Facilitate culture change. Identify ways that all ICTR services can help identify needs, foster educational pathways, and encourage partnerships to help TTs better leverage data science. Results/Anticipated Results: Initial assessments indicated that fewer than 25% of TTs receiving pilot awards used data science tools, and only 10% had a data scientist on their team. Data from collaboration planning sessions indicated that few TTs used data science, but all were interested in learning more. To address this deficiency, ICTR partnered with the Data Science Institute and the Section of Applied Clinical Informatics. This expertise informed resource development (e.g., a data science primer, websites) and generated workshops. Educational opportunities include tailored workshops to help TTs better curate data and create more efficient workflows, graduate course modules to improve rigor and reproducibility, and seminars illustrating translational applications of AI, visualizations, and large data integration. Discussion/Significance of Impact: The ICTR Data Science Initiative was designed to empower TTs to more effectively integrate data to power translation. As data science approaches and expertise are embedded within teams, we anticipate continued increases in interest and usage of data science tools, collaborative publications, and data rich applications for extramural funding.

Objectives/Goals: Community health workers (CHWs) are links between the community and healthcare. As primary care (PC) expands to address social drivers of health, CHWs are becoming part of PC teams, yet how the two integrate is not well understood. Using an input-mechanism-outcome (IMO) model, this research seeks to develop a model to expand CHW-PC integration efforts. Methods/Study Population: Participants were recruited from Roots Community Health Center (Roots), a CHC serving historically marginalized communities, that has successfully integrated a CHW role, Roots Health Navigators (RHNs), into PC services. The preliminary conceptual framework for this study was guided by an overarching IMO model and informed by social identity theory, team science, and the interprofessional care literature. A mixed methods study was conducted in three phases: 1) cross-sectional survey, 2) semi-structured interviews, and 3) model development. The survey identified team dynamics such as communication, trust, and shared understanding, and interviews explored how these collaborative teaming mechanisms take shape. Findings were merged into a final model of CHW-PC integration that was reviewed by Roots leaders. Results/Anticipated Results: Survey results (n  =  25) highlighted highly rated team dynamics including shared understanding and acting and feeling like a team. Qualitative findings (n  =  10) described how integration occurred through complex interactions that were community-responsive and collectively reduced burnout among the team. Joint findings noted the importance of RHNs to continuity of care, building trust, and enhancing PC team effectiveness. Findings informed the development of a model of CHW-PC integration. This expanded on the preliminary conceptual framework by highlighting the dynamic relationship between mechanisms, processes, and team emergent states, as well as providing evidence to support feedback loops between inputs, mechanisms, and outcomes with overarching influence from the contextual setting. Discussion/Significance of Impact: With a deeper understanding of the mechanisms of CHW-PC integration, findings informed the development of a model that can support other communities to replicate this approach to care and address critical patient needs. Teaming factors that sustain CHW-PC integration may be transferrable to other care teams integrating nontraditional roles.

Objectives/Goals: The objective of the Clinical and Translational Science Awards (CTSA) Program Collaborative and Innovative Acceleration (CCIA) Award Initiative is to support synergistic collaborations to develop, demonstrate, and sustainably implement innovative solutions across and beyond the CTSA Consortium. Methods/Study Population: All CCIA awards between 2016 and 2022 were reviewed and analyzed by Fiscal year, activity code, and research area using NIH analytical tools and platforms. Subject matter experts categorized each award by research topics, study populations, stage of translational science, and innovation type. The number and type of collaborating organizations were noted and major accomplishments and expected outcomes were summarized. Results/Anticipated Results: Between FY2016 and FY2022, NCATS funded 37 U01 and 18 R21 CCIA awards including >90 different public and private partnering organizations. CCIA awards spanned all stages of translation including preclinical (26%), clinical (36%), implementation (31%), and public health research (7%). Of the 55 CCIA awards, 31% focused on urgent public health needs and 25% were designed to address health disparities. Broadly, types of innovations included: Data science-related projects (18%), clinical care innovations (15%), biomarker or clinical outcome assessments (13%), digital health solutions (11%), therapeutic development (11%), therapeutic discovery (9%), education and training (7%), diagnostic tools (5%), software tools (5%), or tools for clinical research (5%). In total, >735 publications cited CCIA awards. Discussion/Significance of Impact: For >8 years, the CCIAs have brought together researchers from diverse scientific disciplines across the nation to speed the development of new health solutions with broad impact. Advancements in genomic screening, for example, have led to policy changes while new delivery approaches have improved the quality of care for underserved populations.

Objectives/Goals: An association has been found between maternal diabetes and neurodevelopmental disorders (NDDs), such as autism spectrum disorders (ASD), attention-deficit/hyperactivity disorder (ADHD), and intellectual disabilities. Our objective is to observe the effects of type 2 diabetes mellitus (T2DM) on the neurodevelopment of infants. Methods/Study Population: A prospective study was performed on thirty infants who were evaluated using four neonatal neurodevelopmental assessments. Thirteen of these infants were from mothers with T2DM and seventeen of them were from mothers without diabetes. We used the Hammersmith Neonatal Neurological Examination (HNNE), Dubowitz exam, The Capute Scales, and The General Movement Assessment (GMA) to assess the neurodevelopment of these infants. HNNE assesses posture, reflexes, tone, and movement of infants. The Dubowitz exam is used to measure tone and reflexes to get an estimated gestational age (GA) of the infant. The Capute Scales has two subsections, one measures language (receptive and expressive) and the other measures visual-motor development. Lastly, the GMA was used to observe the general movements of the infant. Results/Anticipated Results: Cochran–Mantel–Haenszel determined between-group differences. HNNE, Dubowitz, and the Capute Scales had no significant difference between groups. HNNE results: 4 T2DM below cutoff; 9 controls below cutoff. Discussion/Significance of Impact: Offspring of T2DM mothers show a risk of motor delays in infancy and later language/cognition delays. Offspring of T2DM mothers should be followed due to the risk of motor delays. Early intervention could mitigate delays. This would be the first novel use of these four tools to evaluate 1-month-olds.

Objectives/Goals: The World Trade Center (WTC) Health Program (Program) Data Group was formed to address the increasing volume and complexity of analytics requests and to improve the Program’s data management capacity. Over time, the Group’s role expanded to include comprehensive data leadership and providing data-based support for decision-making. Methods/Study Population: The Program provides medical monitoring and treatment for WTC-related conditions to those directly affected by the 9/11 attacks. These activities generate an abundance of administrative and surveillance data. The Data Group was formed to establish structures and processes that would be adaptable and efficient in leveraging these data. We created a unified workflow including a shared inbox, a standardized request form, and a request-managing tracker. We established communication channels to distribute requests efficiently. We designed a request form to balance the administrative burden on requestors with the need to gather useful information for analyses. We also developed a documentation system to extract key details from forms and incorporate other relevant data to support evaluation and record-keeping. Results/Anticipated Results: From November 2021 through the end of 2023, the Data Group processed and fulfilled 93 data requests. These requests covered a multitude of functional areas essential to the administration of a limited health benefits program. The following top five functional areas made up two-thirds of all requests: Contract Management (n = 30), Research and Quality (n = 15), Operations (n = 11), Medical Policy (n = 10), and Communications (n = 7). Leveraging data collected through our request tracker, the Group conducted annual evaluations and developed visualizations to analyze trends in these requests. The evaluations helped us identify knowledge gaps, highlight areas for improvement – across the Program and within our own processes, and continue to guide and support future Program priorities. Discussion/Significance of Impact: The creation of the Data Group and unified workflow fulfilled the Program’s increasing analytic needs, enhanced oversight of data quality and usage, and facilitated data-driven Program decision-making. Continual optimization of the group’s processes enables opportunities to identify gaps in and support a range of health care delivery initiatives.

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: Radiation nephropathy results in morbidity and mortality in patients receiving cancer treatment. In addition, low birth weight and low nephron number are associated with increased risk for chronic kidney disease. This study examined the development and severity of radiation-induced renal hemodynamic dysfunction in a low renal mass mouse model. Methods/Study Population: Male mice (C57Bl/6, 8–12-weeks) were used to determine a suitable radiation dose regimen. Mice were subjected to fractionated bilateral kidney irradiation with 5–6 fractions of an X-ray dose of 0, 6, 8, and 10 Gy at 24-hr intervals using a CT-image-guided irradiator. Body weight and mortality were monitored for 5 weeks in mice. In a separate set of experiments, the low renal mouse model, ROP Os/+, and their normal counterpart, ROP +/+ mice were subjected to 5 fractionated bilateral kidney irradiations at 24-hr intervals with an X-ray dose of 6 Gy. Renal blood flow was assessed from renal artery resistive index (RRI) over 5 weeks post-irradiation using an ultrasound system. Transcutaneous measurement of FITC-sinistrin clearance was used to determine glomerular filtration rate (GFR). Results/Anticipated Results: The C57Bl/6 mice that received 5–6 fractions of 8 and 10 Gy had more than 50% mortality, while 100% of the mice exposed to 5 fractions of 6 Gy survived for 5 weeks. Body weight was also significantly decreased in mice exposed to 5 or 6 fractions of 8 or 10 but not 6 Gy radiation. Nonirradiated C57Bl/6, ROP +/+, and ROP Os/+ mice had similar baseline GFR and RRI. Irradiation of 5 fractions at 6 Gy decreased GFR and increased RRI in C57Bl/6 and ROP +/+ mice. Interestingly, following 5 fractions at 6 Gy irradiation ROP Os/+ mice had 25% lower GFR than wild-type ROP +/+ mice (946.3 ± 50.3 vs. 1232.9 ± 69.3 µL/min/100g BW, p Discussion/Significance of Impact: Our study determined a suitable fractionated bilateral kidney irradiation dose regimen to evaluate radiation nephropathy. Data demonstrated that fractionated bilateral kidney irradiation leads to decreased renal hemodynamics in mice. We also demonstrated that irradiation caused greater renal hemodynamic dysfunction in low renal mass mice.

Objectives/Goals: Given the challenges that early career research scientists face, especially preparing for promotion and tenure, the decision on whether to join a research team can be fraught. We developed a novel training to support informed decision-making regarding new scientific teaming opportunities. Methods/Study Population: A team science workshop entitled “Should I join this research team” was designed for early career investigators from varied disciplinary backgrounds. Learning objectives for attendees included 1) describing the role of team science in translational research, 2) determining if teaming opportunities are a good fit, and 3) crafting thoughtful responses to requests. The training was initially delivered to 38 attendees (11 K scholars) during a virtual national meeting. We adapted this training for in-person delivery to K and T scholars at our CTSA regional partners. Instructional methods shared across virtual and in-person modalities included self-reflection, think and share activities, and scenario application. In-person delivery also included short video clips and small group discussions. Results/Anticipated Results: Multiple Likert-scale items were completed by workshop participants before and after completing the workshop to evaluate attendees’ confidence in their perceived abilities to explain strengths and limitations of team science, identify characteristics of effective science teams, evaluate a team invitation, assess costs and benefits, negotiate collaborative team invitations, etc. Preliminary data from the virtual workshop suggests that 54.6% of scholars were either not at all or only slightly confident in evaluating a teaming invitation. After the workshop, 45.5% reported being very confident, and 9.1% reported extreme confidence in evaluating a team invitation. Evaluation of the in-person training, along with a comparison of virtual and in-person learning outcomes will also be presented. Discussion/Significance of Impact: Our multimodal training is designed to equip early career investigators with the tools needed to evaluate and respond effectively to research team invitations. We believe this novel training will result in informed teaming decisions for early career research scientists.

Objectives/Goals: Team science (TS) competency is important for translational science team collaboration. However, there are few educators available to assist teams. Asynchronous learning is an effective strategy for delivering TS content. The goal of this project is to expand TS education by providing online access to our learners using online modules. Methods/Study Population: The Collaboration and Team Science (CaTS) team at the University of Cincinnati provides a robust TS education and training program. As the need for team science gains recognition, CaTS has received increased requests for services, leading to a need to broaden TS offerings. To address this demand, the CaTS team created “Team Science 101,” an online, asynchronous, series of 15 modules covering basic team science concepts. Each module consists of an educational recording lasting an average of 20 minutes, optional topic resources, pre- and post-module surveys assessing learners’ confidence and satisfaction, post-module knowledge checks, and evaluation questions. Upon completing all modules, participants receive a completion certificate. Results/Anticipated Results: TS 101 will be piloted with a group of participants who expressed interest in asynchronous TS content and will be adjusted based on the feedback received. The associated pre- and post-module survey, post-module knowledge check, and evaluation questions will be monitored to determine learning levels and improve TS 101 overall. Canvas is the educational platform that houses these modules, allowing for participant follow-up and scalable dissemination. The CaTS team plans to disseminate TS 101 nationally and internationally for anyone interested in this resource. Discussion/Significance of Impact: There is a national effort to collect and curate TS education, training, and toolkits. TS 101 will be a useful educational tool that will expand the reach of team science educators, provide the foundation for educators to explore topics more deeply by building on the module topics, and provide education to broader audiences who lack access to TS experts.

Objectives/Goals: Multiple sclerosis (MS) is a chronic demyelinating disease of the central nervous system that affects 2 million people worldwide causing severe disability. This study uses the Gamt-GFP transgenic mouse line as a novel approach to track oligodendrocyte lineage cell regeneration in inflammatory demyelination for identifying potential therapies. Methods/Study Population: We previously showed that Gamt, an enzyme required for creatine synthesis, is essential for oligodendrocyte (OL) maturation and survival using the Gamt-Green Fluorescent Protein (Gamt-GFP) reporter line. In this study, we capitalize on this finding and track OL lineage cells in an experimental autoimmune encephalomyelitis (EAE) mouse model by inducing immune-mediated demyelination in the Gamt-GFP reporter line. At 7 days postimmunization (dpi), both control and EAE mice receive 4 mg/kg tamoxifen for 4 consecutive days to induce GFP expression. GFP+ cells and those also expressing OL lineage markers [Olig2 (pan-OL lineage cell marker), NG2 (OL precursor cells; OPCs), and CC1 (mature OL)] are quantitated by immunofluorescent staining of spinal cord sections collected at 28 dpi. Results/Anticipated Results: Preliminary data using immunofluorescent staining demonstrated GFP was expressed in Olig2+ cells in the inflammatory ventral white matter lesions of mice with EAE, whereas no GFP labeling was present in the control mice. Moreover, GFP+ cells also expressed NG2+. In contrast, few CC1+ cells were detected in the inflammatory lesions. The low number of dual labeled GFP+CC1+ cells in these lesions suggests OPCs under the EAE environment are unable to efficiently differentiate into mature OL. Therefore, the Gamt-GFP reporter mouse can be used to identify and track activated OL lineage cell populations (i.e., GFP+CC1) in inflammatory lesions in the EAE mouse model. Discussion/Significance of Impact: The Gamt-GFP reporter line identifies activated OL lineage cells responding to inflammatory demyelination, making it a valuable tool for testing potential therapeutics aimed at enhancing remyelination. This model helps bridge the gap between preclinical and clinical research to guide MS therapy development.