Objectives/Goals: PASC affects 6%#_msocom_1 of individuals recovering from SARS-CoV-2 infection. The primary objective of this study was to explore the underlying neuroimmune changes which are responsible for the chronic widespread pain and fatigue that these patients often experience. #_msoanchor_1 Methods/Study Population: We recruited eight post-acute sequelae of SARS-CoV-2 (PASC) patients from the PASC and physical medicine and rehabilitation clinics. Patients were included if they had daily, chronic pain, rated at least 5/10 intensity on the numeric rating scale. Patients were excluded if they had pre-existing pain or autoimmune conditions. Healthy age-matched controls were also recruited. We obtained blood samples from both groups of patients and purified IgG from the plasma. The IgG was reconstituted and transferred to 48 mice via intraperitoneal injection. After IgG transfer, we completed behavioral, flow cytometry, immunofluorescence, and degranulation assays to quantify the effects of the IgG on the animal’s behavior and mast cell activity. Results/Anticipated Results: IgG from PASC patients selectively binds mast cells and induces greater mast cell activation and degranulation than IgG from healthy control patients (p<0.001). This increase in mast cell activation is dependent on mas-related G-protein coupled receptor member X2 signaling. Transferring IgG from PASC patients to mice produces increased sensitivity to cold (p<0.001) in the animals and also decreases their locomotor activity (p<0.01). IgG from healthy patients did not induce any changes cold sensitivity in the animals, nor did it affect their locomotor activity (p<0.001). Lastly, transferring IgG from PASC patients to mice increases the mast cell population in the animals’ hindpaws (p<0.05). #_msocom_2 Discussion/Significance of Impact: This work elucidates a pathophysiological mechanism involved in the development of PASC-associated chronic pain. It also provides insights that may be useful in understanding the pain that is often associated with other autoimmune conditions.

OBJECTIVES/GOALS: Having a strong leader in the form of an operations manager is crucial to lead and motivate teams. They're an additional set of problem-solving eyes to identify and address challenges. This poster demonstrates coordination techniques involved to work with teams of researchers, ensuring effective communication, deadlines met, and impact. METHODS/STUDY POPULATION: Stories, course corrections, publications, presentations and other metrics related to various projects and studies in the Lab will show such as the National Drug Early Warning System (NDEWS), Program to Alleviate National Disparities in Ethnic and Minority Immunizations in the Community (PANDEMIC, CDC), Polysubstance Use Study (PSU), and All of Us Consortium of CTSA/PACER Community Network. Additional data will be collected with project managers and students from each respective project to evaluate the effectiveness of an Operations Manager on the team across all studies in Our Lab. RESULTS/ANTICIPATED RESULTS: By sharing these results, showing the benefit to having an Operations Manager and the stories collected and shared for this poster, course corrections will set an example for future operations managers and their teams to continue to optimize efforts. Tis Could be a Special Interest Group (SIG)-related effort that would facilitate success to many labs. DISCUSSION/SIGNIFICANCE: Operations management focuses on effectively managing resources, ensuring that we meet deadlines, reduce delays, and maximize team productivity. By sharing our experiences, this can be a more standard practice among research labs to have smooth operations, and increase overall reputation of our team among those in the field.

Objectives/Goals: This work identifies ordinary and novel ingredients of a recipe for a learning community created by translational scientists to support their mutual interests in broadly engaged team science. The goal of creating this recipe is to share our findings, enabling the replication of this work at other CTSAs. Methods/Study Population: Inspired by O’Brien et al. (2025), our MICHR CoLab+ learning community (N = 8) is cooking up a “community recipe” for collaborative learning. Our multidisciplinary mix includes members from six MICHR teams. In our first guided session, we blended open dialog and reflection to identify key ingredients and tools, including metaphors for our team’s strengths, values, and goals. Using Teams, Miro, and generative AI, we captured early insights to refine over time. Results/Anticipated Results: By co-creating a community recipe, members of the MICHR CoLab+ deepen their understanding of shared strengths, values, and purpose. The recipe showcases what makes our community unique while fostering unity and belonging. Once complete, it will help us overcome barriers, accelerate discovery, and deliver real-world impact in translational science. Discussion/Significance of Impact: This work extends research helping translational scientists cross boundaries in universities. Building on work on learning communities for learning health systems (Ferguson, et al., 2024; Wenger, 1998), it shows how co-created “recipes” foster collaboration across disciplines, institutions, and cultures to strengthen translational science.

Objectives/Goals: We hypothesized that the bulk transcriptomic profiling of blood collected from within the ischemic vasculature during an acute ischemic stroke with large vessel occlusion (LVO) will contain unique biomarkers that are different from the peripheral circulation and may provide much-needed insight into the underlying pathogenesis of LVO in humans. Methods/Study Population: The transcriptomic biomarkers of Inflammation in Large Vessel Ischemic Stroke pilot study prospectively enrolled patients ≥ 18 years of age with an anterior circulation LVO, treated with endovascular thrombectomy (EVT). Two periprocedural arterial blood samples were obtained (DNA/RNA Shield™ tubes, Zymo Research); 1) proximal to the thrombus, from the internal carotid artery and 2) immediately downstream from the thrombus, by puncturing through the thrombus with the microcatheter. Bulk RNA sequencing was performed and differential gene expression was identified using the Wilcoxon signed rank test for paired data, adjusting for age, sex, use of thrombolytics, last known well to EVT, and thrombolysis in cerebral infarction score. Bioinformatic pathway analyses were computed using MCODE and reactome. Results/Anticipated Results: From May to October 2022, 20 patients were screened and 13 were enrolled (median age 68 [SD 10.1], 47% male, 100% white). A total of 608 differentially expressed genes were found to be significant (p-value) Discussion/Significance of Impact: These results provide evidence of significant gene expression changes occurring within the ischemic vasculature of the brain during LVO, which may correlate with larger ischemic infarct volumes and worse functional outcomes at 90 days. Future studies with larger sample sizes are supported by this work.

Objectives/Goals: Persistent gaps in inclusive research demand new approaches. We propose the Individualized and Differential Benefit (IDB) framework to develop tools that prioritize balance and elevate underrecognized voices within today’s research landscape. Methods/Study Population: The IDB framework ensures research benefits all, including individuals within underserved communities. To apply IDB, three criteria must be met: (1) inclusivity: work must apply to all and exclude none; (2) utility: work must benefit all stakeholders; and (3) differential benefit: work must offer greater advantages to individuals from any group who are most in need. This approach aims to elevate everyone while offering a tool to achieve equity. Results/Anticipated Results: Within the poster, we use two examples to illustrate IDB. In the first example, Health Outcome and Population Engineering, or HOPE, exemplifies how health outcomes are achieved with an individualized approach while population differences are modified. In the second example, Population Conscious Analysis, or PCA, is used to display a nuanced approach to analysis that yields an individual benefit while again yielding the opportunity for population-level differences. Discussion/Significance of Impact: IDB reframes public health research by prioritizing individual-level insights to drive precision, equity, and upstream interventions. It enables tailored strategies, community engagement, and scalable solutions that benefit all, but specifically those most in need.

Objectives/Goals: This study aims to first understand the expression of the L-type amino acid transporter, Slc7a5, in demyelinated plaques in postmortem multiple sclerosis (MS) CNS tissue. It also seeks to understand the effect of a novel inhibitor of Slc7a5 on remyelination in mice with experimental autoimmune encephalomyelitis. Methods/Study Population: Using single-cell RNA sequencing (scRNA-seq), we will examine the expression of Slc7a5 in demyelinated plaques in postmortem CNS tissue of patients with MS compared to non-lesioned regions (n  =  3/group). Using visually evoked potential (VEP) on mice with experimental autoimmune encephalomyelitis (EAE), we will determine the ability of the Slc7a5 allosteric inhibitor OKY-034 to promote remyelination compared to EAE-only controls (n  =  10/group). Lastly, we will use spatial transcriptomics with scRNA-seq to map transcriptional activity within different populations of cells to determine how OKY-034 changes gene expression in specific cell types compared to EAE-only controls (n  =  3/group). Results/Anticipated Results: A conditional knockout of Slc7a5 showed that microglial activation and oligodendrocyte differentiation were affected in demyelinated lesions. This suggests that it plays a role in numerous cell types in active demyelinated plaques, which is what we expect to find from our scRNA-seq data in post-mortem CNS tissue of patients with MS. Measuring VEP is a noninvasive way to measure remyelination in both clinical and research settings. OKY-034 increases oligodendrocyte differentiation suggesting remyelination, so we expect that administration of OKY-034 in mice with EAE will lead to restored VEP compared to control and EAE-only mice. Lastly, because OKY-034 reduces inflammation, we expect to see a decrease in gene expression for genes involved in an immune response. Discussion/Significance of Impact: Completion of this study will lead to understanding what the effect the allosteric Slc7a5 inhibitor OKY-034 has on remyelination and whether it may serve as a novel therapeutic drug that can be administered orally for the treatment of MS. This could lead to its further development as a treatment for progressive MS.

OBJECTIVES/SPECIFIC AIMS: Glioblastoma (GBM) is a brain cancer with a devastatingly short overall survival of under two years. The poor prognosis of GBM is largely due to cell invasion and maintenance of cancer initiating cells that evade the brain’s innate and adaptive immune responses which enables escape from surgical resection and drives inevitable recurrence. While targeting the brain’s immune microenvironment has long been proposed as a strategy for treating GBM, translational progress has been slow, underscoring the need to investigate the brain’s immune microenvironment for therapeutic avenues. METHODS/STUDY POPULATION: Recent advancements in tunable synthetic immunomodulatory gene circuits targeting metastatic cancers has demonstrated the novel ability to use engineering principles to induce infiltrative cancer cells to express combinatorial immunomodulatory outputs that enable T-cell killing4. Our central hypothesis is: we will be able to significantly improve survival with a lasting immune-mediated control of GBM by using synthetic immunomodulatory gene circuits driving GBM cells to express a local combination of immunomodulatory proteins: human IL15, a surface T-cell engager, PD-L1-CD3 bispecific antibody, and the protein, LIGHT (TNFRSF14). Importantly, the co-expression of LIGHT and anti-PD-L1 therapies was recently shown to rescue PD-L1 checkpoint blockage in the preclinical models of brain tumors and significant enhance survival outcomes highlighting the benefits of novel combinations of immunomodulatory proteins for treatment of GBM. To identify genes whose expression is dramatically upregulated in GBM compared to normal human brain cells, a pooled of six thousand lentiviral oncogene promoters that drive expression of a red-fluorescent protein has been infected into three human GBM cell lines. RESULTS/ANTICIPATED RESULTS: We have successfully infected our GBM cells and are preparing samples for next generation DNA sequencing to determine highly active promoters in GBM that are not expressed in multiple normal brain cells types, astrocytes and neurons. These chosen promoters will then be used to drive an AND gate logic gene circuit immunotherapy outputs which is currently under development for both in-vitro and in-vivo experiments. DISCUSSION/SIGNIFICANCE OF IMPACT: We anticipate that local expression of multiple immune effectors proteins will significantly enhance tumor control and survival in both synergistic murine and human-murine xenograft pre-clinical models of GBM. Ultimately, our goal is to rapidly translate this technology advance into the clinical trial for adult GBM patients.

Objectives/Goals: Personalized cancer therapy based on genomic testing is advancing patient care. Genomic alterations in fibroblast growth factor receptor (FGFR) predict response to FGFR inhibitors; however, the role of RNA expression and protein activation is not known. We propose to examine the phospho-proteomic signature in FGFR-altered cancers to identify new candidates for FGFR-targeted therapies. Methods/Study Population: In our preliminary study, we have curated a cohort of FGFR2 mutants (13 FGFR2-fusions and 4 FGFR2 point mutations) with known clinical outcomes to FGFR inhibitors and 8 FGFR2 wild-type (WT) cholangiocarcinoma tumor samples to investigate the phospho-proteomic fingerprint using a clinical grade reverse phase protein array (RPPA). RPPAs are high throughput quantitative antibody-based proteomics assays that can quantify hundreds of proteins in thousands of patient tissues providing a high degree of sensitivity through laser tumor microdissection (LCM). We have selected proteins in the FGFR signaling pathway including FGFR2, AKT, ERK1.2, STAT1/3, FRS2, and PLCg to define the range of phospho-proteomic signal between FGFR2 WT and mutant cancers. All samples will undergo evaluation with RNASeq for gene expression. Results/Anticipated Results: Our initial analysis defined the range of RNA expression of FGFR2 and pFGFR2 protein signal (Y653/654 and Y769) between FGFR2 WT and FGFR2 mutant samples. On average, the FGFR2 mutant cohort displayed higher FGFR2 RNA expression compared to the FGFR2 WT cohort. There is no apparent correlation between RNA expression and clinical response to FGFR-targeted therapy. However, in this small cohort, there is no significant difference in FGFR2 phosphorylation between FGFR2 WT and mutant cancers. RPPA analysis of FGFR downstream signaling proteins reveals a wide range of phosphorylation, but no significant difference between FGFR2 WT and mutant cancers. Discussion/Significance of Impact: These findings illustrate the complexities of FGFR signaling between FGFR2 WT and mutant cancers. These data suggest that tumors with genomically WT FGFR may display increased pFGFR2 and downstream signaling phospho-proteins. We propose a larger study of cholangiocarcinoma to evaluate evidence of FGFR pathway activation in WT tumors.

OBJECTIVES/SPECIFIC AIMS: Objective: Approximately 86 million people in the US have prediabetes, but only a fraction of them receive proven effective therapies to prevent diabetes. Further, the effectiveness of these therapies varies with individual risk of progression to diabetes. We estimated the value of targeting those individuals at highest diabetes risk for treatment, compared to treating all individuals meeting inclusion criteria for the Diabetes Prevention Program (DPP). METHODS/STUDY POPULATION: METHODS: Using a micro-simulation model, we estimated total lifetime costs and quality-adjusted life expectancy (QALE) for individuals receiving: (1) lifestyle intervention involving an intensive program focused on healthy diet and exercise, (2) metformin administration, or (3) no intervention. The model combines several components. First a Cox proportional hazards model predicted onset of diabetes from baseline characteristics for each pre-diabetic individual and yielded a probability distribution for each alternative. We derived this risk model from the Diabetes Prevention Program (DPP) clinical trial data and the follow-up study DPP-OS. The Michigan Diabetes Research Center Model for Diabetes then estimated costs and outcomes for individuals after diabetes diagnosis using standard of care diabetes treatment. Based on individual costs and QALE, we evaluated NMB of the two interventions at population and individual levels, stratified by risk quintiles for diabetes onset at 3 years. RESULTS/ANTICIPATED RESULTS: Results: Compared to usual care, lifestyle modification conferred positive benefits for all eligible individuals. Metformin’s NMB was negative for the lowest population risk quintile. By avoiding use among individuals who would not benefit, targeted administration of metformin conferred a benefit of $500-$800 per person, depending on duration of treatment effect. When treating only 20% of the population (e.g., due to capacity constraints), targeting conferred a NMB of $14,000-$18,000 per person for lifestyle modification and $16,000-$20,000 for metformin. DISCUSSION/SIGNIFICANCE OF IMPACT: Conclusions: Metformin confers value only among higher risk individuals, so targeting its use is worthwhile. While lifestyle modification confers value for all eligible individuals, prioritizing the intervention to high risk patients when capacity is constrained substantially increases societal benefits.

Understanding patient and caregiver experiences is a critical component of the conception, design, and implementation of clinical research studies. The “Database of Individual Patient Experiences” (DIPEx) is an innovative, evidence-based approach for eliciting rich information about health experiences. We conducted a formative evaluation with 14 pediatric oncology researchers to assess the value of using data from a DIPEx study on patient and caregiver experiences with childhood cancer to inform patient-centered research in pediatric oncology. Participants identified barriers to incorporating patient perspectives and experiences into their research and how the DIPEx approach could be leveraged to facilitate this practice.

The Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) Cross-Trial Statistics Group gathered lessons learned from statisticians responsible for the design and analysis of the 11 ACTIV therapeutic master protocols to inform contemporary trial design as well as preparation for a future pandemic. The ACTIV master protocols were designed to rapidly assess what treatments might save lives, keep people out of the hospital, and help them feel better faster. Study teams initially worked without knowledge of the natural history of disease and thus without key information for design decisions. Moreover, the science of platform trial design was in its infancy. Here, we discuss the statistical design choices made and the adaptations forced by the changing pandemic context. Lessons around critical aspects of trial design are summarized, and recommendations are made for the organization of master protocols in the future.

OBJECTIVES/SPECIFIC AIMS: Suggestibility, defined as the inclination to accept and internalize messages, has not been assessed much in relation to alcohol use. Prior research has shown that suggestibility to social cues and peer influence may play a role in driving alcohol consumption. Our previous work has shown associations between suggestibility and alcohol consumption in social drinkers. This study aims to examine how suggestibility and social susceptibility are related to ideas alcohol consumption and consequences across the spectrum of alcohol use and misuse. We hypothesize that those with higher suggestibility and social susceptibility reports will also have higher alcohol consumption and consequences, and that the impact of susceptibility is lower in dependent compared to non-dependent drinkers. METHODS/STUDY POPULATION: Study participants enrolled in the NIAAA screening and assessment protocol (N=157) completed questionnaires on suggestibility and alcohol consumption, The Multidimensional Iowa Suggestibility Scale (MISS) is a 95-question self-report assessment of suggestibility which draws from subcategories of consumer suggestibility, perceivability, physiological suggestibility, physiological reactivity, and peer conformity. Alcohol measures included 90-day Timeline Followback interviews and the Alcohol Use Disorder Identification Test (AUDIT). Participants also underwent the Structured Clinical Interviews for DSM-IV or DSM-5 disorders, and were stratified into two groups: alcohol dependent (N = 86) and non-dependent (N=71). Median split by age was additionally used to explore age’s relationship with suggestibility and alcohol with the under 36 (N = 45) and over 36 (N = 26) non-dependent groups. RESULTS/ANTICIPATED RESULTS: Initial analyses showed marked differences between the dependent and non-dependent groups in the relationship between the MISS total score and AUDIT total score. The non-dependent group showed significant positive correlations between MISS and AUDIT scores (r = 0.460, p < 0.001), while the dependent group did not show any correlation between MISS and AUDIT scores. Further examination of these relationships in the nondependent group revealed that MISS scores were also significantly positively correlated with AUDIT subscores of consumption, harm, and dependence. Age was found to have a significant negative correlation with MISS score (r = −0.354, p < 0.01). To better understand the role of age, the sample was split based on the median age (36 yrs), and analyzed separately. Results indicated robust relationships between MISS score and AUDIT (r = 0.457, p < 0.01) in the younger age group. In addition, the younger age group also showed significant relationships between MISS score and 90-day TLFB measures of total drinks, days drinking, and heavy drinking days. DISCUSSION/SIGNIFICANCE OF IMPACT: In non-dependent individuals, there was a significant positive relationship between suggestibility and alcohol measures, and these effects were amplified in younger individuals. No relationship was found between suggestibility and alcohol measures in the alcohol dependent individuals. This may be related to a greater impact of social and external contextual cues in younger social drinkers compared to dependent drinkers where tolerance and craving may have greater impact on alcohol consumption. These findings have important implications for traits that may put individuals at risk for developing harmful patterns of alcohol use and misuse. Future analyses will aim to examine biobehavioral underpinnings of the relationship between suggestibility and alcohol consumption.

OBJECTIVES/GOALS: A Mayo Clinic in Florida committee completes 100+ Scientific Reviews annually through manual e-mail and Excel tracking, placing a manual burden on reviewers and coordinators. REDCap, an electronic data capture system, was leveraged to reduce the administrative burden.#_ftn1 #_ftnref2 METHODS/STUDY POPULATION: Historically, emails were sent by a coordinator to physicians, requesting their initial review and following up with reminders. This process was tracked using Excel, presenting a need to make this process more efficient, so a workgroup was created. To ensure all perspectives were accounted for, the workgroup included the review coordinator, a physician reviewer, and study team members who submit development requests for studies. The process was mapped using the existing Excel spreadsheet, and email templates. Critical data elements were identified, ensuring the database would identify bottlenecks. Two REDCap instruments were then created: one to outline the coordinator workflow and a survey for physician reviewers to complete the scientific reviews. #_ftn2#_ftnref1 RESULTS/ANTICIPATED RESULTS: The workflow is live in REDCap and has effectively processed over 100 scientific reviews in <1 year. The system captures the review status and guides the coordinator through the workflow, capturing dates when tasks are completed. When review criteria are met, the database sends an email to the assigned reviewer. The email includes a link to a REDCap survey, containing all pertinent documents. The reviewer uploads their completed review form within the survey, if this is not completed within a given period, the database sends email reminders. Once the review is complete, a notification is sent to the review coordinator. The review workflow is accessible to the study team who requested scientific review, making them aware of their request status ad giving them access to the review the moment it is completed. DISCUSSION/SIGNIFICANCE: Leveraging REDCap has increased visibility, reduced overall manual processes, and simplified the reviewer burden by providing all the information needed in a single notification. REDCap is a cost-effective, impactful solution to simplifying administrative burden in managing committee reviews.

Objectives/Goals: To investigate renin–angiotensin system (RAS) modulation as a therapeutic target for uterine fibroids using a xenograft model, translating insights from cardiometabolic–fibroid comorbidity into accessible treatment strategies for underserved populations. Methods/Study Population: We established a xenograft model by implanting matched human fibroid and myometrial tissue into NOG mice (n=6 per group) supplemented with estrogen pellets. This translational model mimics the clinical context of hypertensive patients with fibroids treated with RAS-modulating drugs. Mice were randomized to receive angiotensin II, losartan, enalapril, or vehicle control. Tumor volumes were measured weekly by caliper. At endpoint, xenografts are analyzed for proliferation (Ki67), fibrosis (α-SMA, collagen), and immune composition using flow cytometry and immunofluorescence. Results/Anticipated Results: Preliminary data from all 24 mice reveal variable fibroid xenograft growth across treatment groups, with no consistent dose–response pattern in gross tumor volumes. Ongoing molecular and cellular analyses may uncover treatment effects not reflected in volume measurements alone. Final analyses will integrate proliferative indices, fibrotic markers, and immune cell profiles to determine whether RAS modulation influences fibroid biology at the cellular level despite heterogeneous morphological responses. Discussion/Significance of Impact: Fibroids disproportionately affect Black women and are closely linked to cardiovascular disease. Repurposing FDA-approved antihypertensives offers an accessible, low-cost therapeutic avenue and exemplifies translational science by bridging mechanistic discovery with equitable treatment innovation.

Objectives/Goals: This work seeks to elucidate the upstream and downstream circuitry of the Keap1–Nrf2 axis in natural killer (NK) cells. We aim to define how the Keap1–Nrf2 axis sets a redox license to calibrate NK function and metabolic fitness, and in turn, to translate these findings into new strategies for metabolically enhancing NK and CAR-NK-based immunotherapy. Methods/Study Population: Keap1 and Nrf2 were investigated primarily in murine models, by using NK-specific knockouts of each gene (Ncr1Cre-Nrf2fl/fl and Ncr1Cre-Keap1fl/fl) in C57BL/6 mice. Flow cytometry was used to profile knockout versus wild-type differences in lymphocyte populations and subpopulations, including receptor repertoire, maturation, and effector function. In vitro and ex vivo experiments were performed by sorting cells from the spleens of knockout mice and their wild-type littermates. Human NK cells from healthy donors were analyzed with collaborators to validate the importance of the axis for human patients. Results/Anticipated Results: Transcriptomics analysis of NK cells during murine cytomegalovirus (MCMV) infection revealed reciprocal regulation of Nrf2 and Keap1, with Nrf2 transcripts downregulated and Keap1 upregulated at day 4 post-infection, highlighting the potential contribution of this pathway to NK cell responses during viral challenge. We demonstrate that both insufficient and excessive ROS buffering impair host survival in response to MCMV and acute myeloid leukemia (AML) and compromise control of tumor metastasis in melanoma models. Importantly, both knockout models also exhibited defects in NK cell expansion, maturation, and cytotoxicity. Ongoing studies map the metabolic, epigenetic and transcriptional programs downstream of this pathway in both murine and human NK cells. Discussion/Significance of Impact: As immunotherapies are developed and optimized, a rigorous understanding of the mechanisms through which immune cells kill pathogens is critical. Collectively, our work thus far identifies the Keap1–Nrf2 axis as a critical regulator of NK cell fitness that can be used to promote cell therapeutic development.

Objectives/Goals: Unhealthy lifestyle habits may increase medical students’ risk for metabolic dysfunction-associated fatty liver disease (MAFLD) and non-alcoholic fatty pancreatic disease (NAFPD). This study aims to investigate how these lifestyle factors affect liver and pancreas health in preclinical medical students using diagnostic ultrasound imaging. Methods/Study Population: Using diagnostic ultrasound imaging, we propose a research study to evaluate the anatomical changes of the liver and pancreas associated with lifestyle among medical students in UCC. Forty-two (42) medical students from the Central University of the Caribbean who are in their preclinical years will be recruited to perform an abdominal ultrasound. To measure the diameter of the right liver lobe, we will employ the craniocaudal measurement method established by Riestra. et al. (2018). The parameter established by Rumack et al. (2011) will be utilized to assess liver texture and categories by Lee JS et al. (2009) to pancreas fat infiltration grades. Results/Anticipated Results: This study expects to reveal a significant correlation between the lifestyles of preclinical medical students and the health of their liver and pancreas, particularly in size and texture. We anticipate identifying specific lifestyle factors – such as dietary habits and physical activity levels – that contribute to the prevalence of hepatic and pancreatic steatosis. Additionally, we expect to highlight the need for targeted interventions to promote healthier lifestyles among medical students to mitigate risks associated with MAFLD and NAFPD. Discussion/Significance of Impact: This study is significant for monitoring changes in liver and pancreas health, preventing complications, and improving health quality while reducing future costs. It may guide the creation of tailored wellness programs for medical students, enhancing their well-being and contributing to better healthcare practices and educational strategies.

Objectives/Goals: This review evaluates recent advancements in artificial intelligence (AI)-driven radiomics for detecting early metabolic and structural changes via imaging techniques like PET-CT and magnetic resonance imaging (MRI). It aims to assess AI’s potential to predict disease progression and explore its implications for personalized preventative medicine. Methods/Study Population: This review analyzed studies from the past five years that explored AI applications in radiomics for early disease detection. The studies primarily focused on patients at risk for metabolic, cardiovascular, and oncological diseases. AI algorithms, including deep learning models, were evaluated for their ability to detect subtle metabolic and structural changes in imaging data from modalities like PET-CT and MRI. We categorized methodologies based on imaging biomarkers targeted, AI model architecture, and the clinical populations involved. The review highlights the methods used across studies to assess AI’s effectiveness in predicting disease progression. Results/Anticipated Results: The review found that AI models consistently demonstrated superior performance in detecting early metabolic and structural changes compared to traditional radiology methods. Across multiple studies, AI was able to identify biomarkers associated with disease progression months before clinical symptoms appeared, particularly in metabolic, cardiovascular, and cancer patients. Deep learning algorithms showed high accuracy in analyzing imaging data, improving predictive outcomes. The findings suggest that integrating AI into clinical practice could enable earlier interventions, offering personalized preventative care, and reducing the progression of late-stage diseases. Discussion/Significance of Impact: AI-driven radiomics holds great promise for transforming healthcare by enabling life-saving early detection and precision-based interventions. This technology could significantly reduce mortality in diseases like cancer, heart disease, and diabetes by allowing for earlier, targeted preventative strategies.