Objectives/Goals: Conception to early childhood is reported to be one of the most critical developmental periods in human development. This study examines the role of adversity experienced by both mom and child during the pre-and post-natal periods on children’s cardiometabolic disease risk (CMDR) outcomes. Methods/Study Population: Data include responses from 852 biological mother-child dyads from the Family Life Project. Adversity during pregnancy was measured using the Life Experiences Survey. The number of life experiences that mothers reported as “bad” was included in the analyses. Children’s experiences with adversity were assessed using cumulative risk, a composite measure of adversity captured at four time points: 6, 15, 24, and 35 months. These variables were used to predict children’s obesity and mean arterial pressure, markers of cardiometabolic disease risk. Children’s obesity status was measured using standardized body mass index (BMIZ) values, assessed in children when they were 24, 35, 48, 58, 90, and 154 months. Mean arterial pressure was captured at 154 months. Results/Anticipated Results: Less than half of mothers (42.4%) and children (44.6%) identified as Black. Roughly half of the children (49.1%) were female. Most (78.2%) mothers were categorized as being of low economic status. Preliminary analyses revealed that number of negative life experiences reported by mothers were not significantly correlated with MAP. Children’s cumulative risk (CR) at 6 (r=0.11, p<0.01), 15 (r=0.11, p<0.01), 24 (r=0.11, p<0.01), and 35 (r=0.10, p<0.01) months were significantly correlated mean arterial pressure (MAP) at age 14. Associations between CR and MAP remained significant among girls at all time points and among boys only at months 6,15, and 24 months. There were no significant correlations between adversity experienced in utero on children’s BMIZ values at any timepoint. Discussion/Significance of Impact: The American Heart Association states that MAP is often used as an indicator of CMDR. Preliminary results from this study suggest a potential pathway from adversity experienced in infancy and adolescent MAP. Future studies should further explore these associations to better understand the pathways from early life adversity to high CMDR.

Objectives/Goals: Type 2 diabetes is a metabolic disease characterized by non-resolving inflammation. Our objective is to investigate how macrophages contribute to this dysregulation. We hypothesize that diabetic macrophages have impaired response mechanisms and are more sensitive to metabolic flux, limiting their ability to effectively resolve inflammation. Methods/Study Population: To study this, we isolated and cultured bone marrow-derived macrophages from WT and db/db mice in vitro and stimulated them with maturation, inflammatory, and resolving cues. We also isolated human monocytes from PBMCs from patients with type 2 diabetes and age-matched healthy controls and stimulated them ex vivo and cultured them in vitro. We assessed their timeline of maturation through changes in cell surface markers, their functional inflammatory response through phenotypic marker changes and cytokine release, and their sensitivity to metabolic flux by culturing in the presence or absence of extracellular glutamine. Together, these responses can allow us to understand intrinsic defects in diabetic macrophages’ ability to regulate inflammation. Results/Anticipated Results: Notably, diabetic and healthy macrophages display distinct maturation timelines. Overall, diabetic macrophages lag behind healthy macrophages in expression of CD45 and F4/80 but eventually acquire a similar level of mature cell surface markers by day 7-8 in culture. In addition, diabetic cells have a higher proportion of Ly6Chi cells earlier in culture, cells that are generally more poised to be pro-inflammatory. Both healthy and diabetic mature macrophages displayed similar levels of inflammatory response cytokines, inflammatory gene expression changes, and phenotypic marker expression. Interestingly, stimulating these macrophages in the absence of glutamine revealed underlying impairments in their response to inflammatory and resolving cues. Discussion/Significance of Impact: Patients with diabetes suffer significant complications, such as susceptibility to infections and non-healing wounds, driven by impairments in resolution of inflammation. This research begins to explore the cell-mediated inflammatory aberrations in type 2 diabetes and may reveal targetable mechanisms to improve patient outcomes.

Objectives/Goals: To assess the safety, tolerability, and adverse effects of adding acetazolamide to temozolomide in newly diagnosed MGMT-methylated malignant glioma, and to explore efficacy, survival outcomes, and Bcl-3 as a potential predictive biomarker. Methods/Study Population: Adults (>18 y) with newly diagnosed, MGMT-methylated, IDH-wildtype glioblastoma, and Karnofsky performance status > 60 receiving standard temozolomide (TMZ) + radiation (RT) were enrolled. Sixty patients (24 initial, 36 subsequent) received acetazolamide (ACZ) twice daily starting on the day of adjuvant TMZ initiation. ACZ began at 250 mg BID for 1 week, then escalated to 500 mg BID, given on days 1–21 of each 28-day cycle (TMZ days 1–5), for up to 6 cycles if not limited by tumor progression/toxicity. Clinical and MRI follow-up occurred every 2 months. Results/Anticipated Results: Preliminary data (initial 24 patients) have shown that no patient had a dose-limiting toxicity. Adverse events were consistent with known sequelae of acetazolamide and TMZ. In the 23 WHO Grade 4 patients, the median overall survival (OS) was 30.1 months, and the median progression-free survival was 16.0 months. The 2-year OS was 60.9%. In total, 37% of the study population had high BCL-3 staining and trended toward shorter OS (17.2 months vs N.R., P=.06) (Riley et al., 2024) All of these factors will be evaluated in a prospective study including 60 patients Discussion/Significance of Impact: Initial data in a smaller cohort showed that adding acetazolamide is safe and tolerable in GBM patients on standard temozolomide. Survival compares favorably to historical data in MGMT-methylated GBM. BCL-3 may be a prognostic biomarker. These findings will be assessed and discussed in a 60-patient prospective study.

Objectives/Goals: To develop a novel meta-analysis model that estimates pooled risk ratios (RR) at prespecified milestones, accounts for unequal follow-up across trials, and leverages between-time correlation, thereby providing clinically interpretable estimates under potential non-proportional hazards (PH). Methods/Study Population: Our model combines study-specific RRs – the ratios of cumulative event probabilities – from Kaplan-Meier curves at prespecified times (12, 24, 36 months, etc.). Using the delta method, we derive within-trial variances for log-RRs and cross-time covariances to reflect correlation among milestones. These study-level estimates and variance-covariance matrices enter a multivariate random effects model to obtain pooled RRs. We illustrate this method with a meta-analysis of progression-free survival in 7 randomized clinical trials of first-line therapy immunotherapy combinations in metastatic renal cell carcinoma. Results/Anticipated Results: Follow-up for PFS across the 7 trials was heterogeneous: all 7 trials contribute at 12 months, 6 at 24 months, 5 at 36 months, 4 at 48 months, and only 2 contributing at 54 and 60 months. This heterogeneity motivates a multivariate approach that borrows strength across times. PH diagnostics indicate deviations from PH for PFS in 3 trials, supporting the need for pooled effects at milestones rather than a single summary measure. We will report pooled RRs at 12, 24, 36, 48, 54, and 60 months. We expect the multivariate model to improve precision at shared milestones while honestly reflecting increasing uncertainty at sparse later times. Discussion/Significance of Impact: When follow-up differs across trials and PH is questionable, a multivariate RR meta-analysis preserves interpretability and efficiently uses all available milestones without forcing a single-number summary. This approach clarifies when benefits accrue and provide clinically interpretable results.

Objectives/Goals: To generate phenotype-specific insights that support tailored prevention strategies and advance precision cardiovascular risk management within Gulf health systems. Methods/Study Population: We analyzed collected primary care records and retained 14,616 complete cases. A composite CV risk index was constructed using a Framingham-based general CVD algorithm from standard clinical variables. “High risk” was defined as the top cohort quartile. Between-group differences were tested with the Kruskal–Wallis test followed by Dunn’s multiple comparisons with Benjamini–Hochberg adjustment. We then modeled (i) the binary high-risk outcome using multivariable logistic regression and (ii) the continuous index using linear regression. Adjusted models included body mass index (BMI), log(ESR + 1), log(CRP + 1), and statin use; variables embedded in the index were not re-adjusted to avoid over-adjustment. Results/Anticipated Results: The proportion above the high-index threshold differed by group: RA 29.4%, no autoimmune 25.7%, multiple-autoimmune 23.9%, SLE 19.8%, and Hashimoto’s 12.7%. The Kruskal–Wallis test was significant (H=68.6, df=4, p<10−13), with Dunn tests (BH-adjusted) showing RA > no autoimmune and SLE, and Hashimoto < all groups. In adjusted logistic regression, odds of high index were higher in RA (OR 1.20, 95% CI 1.06–1.37), lower in Hashimoto (OR 0.49, 95% CI 0.40–0.60), and not clearly different in SLE or multiple-autoimmune. Higher BMI (OR/unit 1.08), ESR (OR/log 1.06), and statin use (OR 4.97) were strongly associated. Discussion/Significance of Impact: In a large primary care cohort, RA showed modestly higher CV risk than non-autoimmune patients after adjustment, while Hashimoto’s showed lower burden. Findings support targeted control of risk factors, especially blood pressure, weight, and inflammation in autoimmune populations.

Objectives/Goals: Discharges before medically advised (BMA) – also known as “against medical advice” – after an asthma exacerbation are associated with adverse outcomes, including recurrent hospitalization, but the reasons for this are unclear. We sought to evaluate whether gaps in prescribing maintenance inhalers were associated with recurrent hospitalization. Methods/Study Population: All asthma exacerbations, defined by ICD-10 codes, among adults requiring an emergency department (ED) visit or hospitalization at any of 5 hospitals in our health system were classified as BMA or non-BMA (i.e., planned) discharges using EHR data. We evaluated whether an inhaled corticosteroid and long-acting beta-agonist (ICS/LABA) inhaler was prescribed on discharge, and whether they had a recurrent exacerbation within 30 days. We used logistic regression models adjusted for age, sex, exacerbation history, medical center, encounter type (ED or admission), BiPAP use, insurance, prior ICS/LABA prescription to evaluate risk of 30-day re-exacerbation by ICS/LABA prescription, BMA discharge, and the interaction between those variables. Results/Anticipated Results: This cohort included 13,064 exacerbations, and 330 (2.5%) resulted in BMA discharge. Compared to non-BMA discharges, those discharging BMA were younger (40 vs 43 years) and less often female (48% vs 64%). Those discharging BMA were less likely to receive an ICS/LABA prescription (16% vs 23%, p=0.01) and more likely to experience 30-day re-exacerbation (12% vs 7%, p=0.001). In adjusted analyses, BMA discharge increased the risk of 30-day re-exacerbation (OR 1.79, 95% CI: 1.22-2.64) and ICS/LABA prescription was protective (OR 0.79, 95% CI: 0.65-0.96). There was a significant interaction (OR for interaction: 0.11, 95% CI 0.01-0.85), indicating a stronger protective association of ICS/LABA among those discharging BMA. Discussion/Significance of Impact: Prescribing an ICS/LABA at discharge protects against recurrent severe asthma exacerbations within 30 days. This association is strongest among those discharging BMA, highlighting this susceptible population as requiring further attention to address gaps in care.

Objectives/Goals: This study investigates racial differences in white matter hyperintensity (WMH) burden across the Alzheimer’s disease spectrum, adjusting for demographic and clinical variables, to clarify mechanisms driving disparities and improve equity in diagnosis and prevention. Methods/Study Population: We analyzed cross-sectional MRI and clinical data from 1,649 participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI): 682 cognitively normal (CN), 584 with mild cognitive impairment (MCI), and 383 with AD. Of these, 124 participants (7.5%) identified as African American: CN (n=70), MCI (n=39), and AD (n=15). Linear mixed effects models were used to evaluate the effect of race, cognitive status, time since first MRI, age, sex, education, intracranial volume (ICV), MRI acquisition type, and APOE ε4 status on total WMH volume. Results/Anticipated Results: Older age, greater time since MRI, and larger ICV were significantly associated with increased WMH burden across cognitive groups. Use of FLAIR imaging was negatively associated with WMH volume, reflecting differences in image acquisition sensitivity. Higher educational attainment was linked to lower WMH burden, suggesting a possible neuroprotective effect. The most pronounced associations were observed within the AD subgroup. After adjusting for all covariates, race was not a statistically significant independent predictor of WMH burden. Discussion/Significance of Impact: Although race did not independently predict WMH burden, structural and demographic factors – such as age, education, and MRI technique – significantly influenced WMH volume. Findings underscore the interplay of biological, social, and technical variables in brain aging and the need for greater African American inclusion.

Objectives/Goals: Our aim is to determine the pathogenesis of intramammary infection of H5N1. First, we must induce lactation, and our aim was to create a protocol to induce lactation without impregnating mice. We hypothesize that the immunological milieu of a lactating mammary gland is highly conducive for influenza viral infection. Methods/Study Population: Nine 10-week-old female mice of unidentified strain were placed in cohorts of lactating versus non-lactating versus control (undeveloped mammary glands) groups. Animals were co-housed within their group. Lactogenic hormones were used to induce mammary development and lactation, including estradiol, progesterone, oxytocin, and prolactin. Mice were inoculated with a comparative strain to H5N1, H1N1, due to its increased availability and safety standards. Immunopathology of mammary tissues and lungs will be assessed by histology, viral titration, and flow cytometry, and data analysis is pending. Results/Anticipated Results: All seven mice that were chosen to be injected with lactogenic hormones developed mammary tissue beyond the pubertal stage and into the reproductive stage, as expected if they were pregnant. Of those seven mice, the three that were given prolactin and oxytocin for milk production and let down were able to lactate. Plaque assays of mammary and lung tissue revealed no viral titers. Flow cytometry of innate surface markers showed varying results and were deemed inconclusive. Based on the preliminary data, it is inconclusive whether the mammary tissue was able to support H1N1 virus replication. Discussion/Significance of Impact: Better understanding of the immunopathology of the mammary gland and how it contributes to disease and disease transmission of influenza in mammalian species will be essential for the development of measures to control disease outbreak and minimize economic loss, especially in species such as cattle and goats.

Objectives/Goals: The aim of this study is to create a profile of Puerto Rican adults that either developed auditory or balance problems after contracting or being vaccinated against COVID-19 or whose symptoms got worse after the infection or vaccination against the coronavirus. Methods/Study Population: This research has two arms: a descriptive explorative survey designed arm and experimental profiling. Four cohorts of Puerto Rican adults between 21 and 64 years old were profiled; subjects that developed auditory or balance disorders after contracting COVID-19, subjects who’s auditory and balance conditions got worse after contracting COVID-19, subjects who developed auditory or balance disorders after being vaccinated against COVID-19 and subjects who’s auditory and balance conditions got worse after being vaccinated against COVID-19. Subjects were recruited, assessed, and interviewed at the University of Puerto Rico-Medical School Intramural Clinic after the research protocol was approved by the Office of Protection of Research Participants of the University of PR-Medical Sciences Campus. Results/Anticipated Results: Results reflected that fifty-seven percent of the subjects experienced hearing difficulty which worsen after contracting or being vaccinated against COVID-19. Seven percent of the subject’s that were vaccinated developed constant Tinnitus which was bilateral in the majority of the subjects (55%). Fourteen percent of the subjects that already had Tinnitus reported that the level of their Tinnitus increased after either contracting or being vaccinated against COVID-19. Discussion/Significance of Impact: This pilot research study adds to the evidence of the impact of COVID-19 infection and vaccination against the coronavirus on the inner ear of Hispanics of Puerto Rican ethnicity. Its significance lies in documenting the different auditory pathologies that can emerge or that can become worse by the contraction of the coronavirus.

Objectives/Goals: We aim to understand how estradiol (E2) modulates proliferation and migration in distinct breast cancer subtypes within a collagen-based 3D platform that serves to better recapitulate human tissue architecture. This work seeks to bridge in vitro hormone biology with translational modeling of hormone-driven tumor behaviors. Methods/Study Population: MDA-MB-231 (triple-negative) and MCF-7 (hormone receptor-positive) breast cancer cells, tagged with red fluorescent protein, were exposed to varying E2 concentrations (0 to 10-4 M) in both 2D and 3D culture. In 2D, 2,000 cells/well were seeded in 96-well plates. Wells were imaged on Day 1 using confocal fluorescent microscopy, treated with E2, and reimaged on Day 5 to assess post-treatment counts. Normalized proliferation was calculated as Day 5/Day 1 cell count. In 3D, per well, 60,000 cells were embedded in a 12 µL base layer of 0.3% type I collagen, overlaid with 40 µL plain collagen, and topped with 150 µL E2-containing media. On Day 5, microscopy and a machine learning algorithm assessed cell counts and migration, defining migratory cells as those >1 standard deviation from the mean z-position of the tumor body. Results/Anticipated Results: In 2D, MCF-7 cells demonstrated significant dose-dependent proliferation to E2. Normalized cell counts increased progressively from 0 M to 10-10 M, at which point proliferation peaked, followed by a significant decline at higher concentrations. In contrast, MDA-MB-231 cells showed stable proliferation across the 0 to 10-6 M range, with a marked reduction in count at 10-4 M. In 3D, MDA-MB-231 cell proliferation remained stable across low and intermediate E2 doses, with a marked reduction at 10-4 M. MCF-7 cells, however, showed no significant differences in normalized proliferation across any E2 concentration in 3D. Quantitative migration analysis revealed that the percentage of migratory cells remained statistically unchanged across all E2 concentrations for both MCF-7 and MDA-MB-231 cells in the 3D matrix. Discussion/Significance of Impact: Dimensionality influences hormone responsiveness in breast cancer, highlighting limitations of 2D assays in modeling clinical behaviors and predicting outcomes. Advancing biomimetic 3D platforms like these may ultimately enable patient-specific screening of endocrine response and guide personalized therapy for hormone-sensitive cancers.

Objectives/Goals: The study’s objective was to use real-world data to compare machine learning approaches for predicting colorectal cancer (CRC) screening status: (1) a Random Forest model optimized for overall accuracy and (2) Feasible Solution Algorithm (FSA) models focused on interpretability and identifying subgroups at risk of being unscreened. Methods/Study Population: The data included 22,549 adults aged 45–75 who visited a UK King’s Daughters Medical Center (UKKD) primary care site between 12/1/2023–11/30/2024, across five Appalachian counties. Patients with total colectomy, colon cancer, advanced illness, hospice care, dementia, and/or frailty were excluded. After complete-case analysis, 18,533 records remained and were split 80/20 for training/testing. Two machine learning methods, random forests and FSA, were applied to identify key predictors of CRC screening status. Within the FSA framework, logistic regression models were fitted using the training data, and model performance metrics were subsequently evaluated using the testing dataset. Results/Anticipated Results: Overall (n=22,549), 65.6% of patients completed CRC screening. The mean age was 59 years (SD = 8.2); most were White (97%), 40% had Medicare insurance, and 68% had multiple non-primary care provider (PCP) visits. The Random Forest model demonstrated the highest overall accuracy of 69% and had notably high sensitivity, correctly identifying approximately 9 of 10 screened patients. On the other hand, the FSA model offered greater specificity (65%) and interpretability, with the 2-predictor model identifying smokers and those with 0 non-PCP visits as the vulnerable subgroups who are least likely to be screened. Discussion/Significance of Impact: FSA identified smoking status, insurance type, number of non-PCP clinic visits, and age as key factors relating to CRC screening behavior. These findings can help clinicians and public health teams identify unscreened patients, guide targeted outreach, and advance translational strategies to improve population health.

Objectives/Goals: Safely and effectively translating AI classification models requires robust post-deployment monitoring. Yet there is little guidance about how to do so. Here, we outline how standard machine learning model development study designs are insufficient for post-deployment monitoring, and what specific study designs are needed. Methods/Study Population: We made original linkages between machine learning methodology and biostatistics, particularly to diagnostic testing, for study design guidance on post-deployment model performance and fairness assessment. Results/Anticipated Results: The kind of case–control sampling typically used for model development cannot give valid estimates of the Positive Predictive Value (precision) and may suffer from verification bias; in a pragmatic clinical trial, or under deployment, only the PPV can be measured, unless there is random confirmatory testing of predicted negatives. This is important for measuring sensitivity, specificity, and False Omission Rate as a fairness metric. Discussion/Significance of Impact: By linking well-understood biostatistics principles (e.g., diagnostic testing) to machine learning classifier evaluation, we show what is required for rigorous evaluation of models in clinical practice. This will establish clear guidance and rigorous standards of practice for study design and analytic aspects of post-deployment monitoring.

Objectives/Goals: 1. Determine if adverse childhood experiences in our novel database are associated with adverse mental and physical health outcomes. 2. Assess differences in developmental and neuropsychological functioning in children with PME and/or opioid exposure. 3. Predict long-term impact of prenatal METH, opioid, and co-use exposures on cognitive development. Methods/Study Population: The Minnesota Foster Care and Adoption Population-level Database includes demographics, birth data (date of birth, gestational age, birth weight, birth length), medical visits and hospital admissions, growth measures over time (height, weight, BMI, and head circumference),vitals, labs, ICD diagnoses, type of prenatal substance exposure (PSE), ACEs (PEARL standards), caregiver placement types (adoption, traditional foster care, kinship care, institutional care, orphanage care, respite care), number of caregiver transitions, and risky behaviors (being detained, suicidal ideation or attempt, self-injurious behaviors, and substance use). Results/Anticipated Results: The study includes 2,725 participants, comprising both adopted children and those in various foster care settings. Transitions are frequent, with only 17% of participants experiencing no transitions. The most common numbers of transitions are two (10%), four (10%), five (9.8%), and six (9.7%). The leading adverse childhood experiences are household substance abuse, mental illness, physical neglect, domestic violence, and physical abuse. Alcohol, tobacco, and methamphetamine are the most frequently used substances during pregnancy, a trend that persists with polysubstance exposure. Adverse childhood experiences are linked to ADHD, conduct disorders, depression, anxiety, mood disorders, and adjustment disorders. Discussion/Significance of Impact: Our findings could help identify a comprehensive profile of developmental and neuropsychological functioning in PSE populations. Our strongest asset is our database, which controls environmental factors better than the general population when we study neurodevelopmental outcomes of PSE.

Objectives/Goals: To meet the shortage of trained clinical research personnel, the IDeA State Consortium for Clinical Research Resource Center (ISCORE-RC) developed the Clinical Research Coordinator Development Program (CRCDP). This comprehensive program addresses themes previously identified as challenges to clinical workforce professional development. Methods/Study Population: CRCDP is offered at 13 academic medical centers in IDeA states and is designed to train clinical research professionals who have minimal or no prior

experience in clinical research coordination. This comprehensive training comprises the following core components: Didactic Learning, Competency-Based Experiential Learning, Objective Competency Evaluation, Mentorship, and Continued Professional Development. Trainees complete > 400 hours of experiential learning. Each trainee is paired with one or more designated preceptors who evaluate and verify proficiency in 28 essential clinical research skills. To ensure successful implementation and institutional engagement, each site designates a program champion responsible for promoting program adoption and local execution. Results/Anticipated Results: Launched in March 2024, the CRCDP has received 171 certificate applications, accepted 114 trainees, and graduated 60 trainees. The anticipated results of this project will include outcome findings from post certificate structured interviews that describe impact of CRCDP components on continuation of research and trainee perceptions of value provided by the various program components. Discussion/Significance of Impact: Availability of trained CRCs is limited and a barrier to expansion of clinical trials in IDeA states. ISCORE-RC is addressing this workforce development gap through an innovative program. Programmatic data will provide insight and better understanding of the facilitators of program implementation and impact on clinical research infrastructure.

Objectives/Goals: This study aims to assess perceptions of children with insulin-dependent diabetes and their guardians on the perceived benefits and challenges on the use of a diabetes-specific generative pretrained transformer to assist with diabetes care in insulin administration. Methods/Study Population: The study involved one-on-one semi-structured interviews with both adolescents aged 14-19 with insulin-dependent diabetes and their guardians. An interview guide was developed utilizing the constructs from the health information technology acceptance model. We have completed 1 interview with a caregiver with a child with diabetes. A total of 10 interviews are planned. All interviews have been or will be recorded utilizing a video conferencing platform and transcribed verbatim. The interview content will then be organized and coded using NVivo software. Thematic analysis was conducted in accordance with analysis guidelines. Results/Anticipated Results: From initial interviews, 3 key themes have arisen regarding the use of artificial intelligence for diabetes care. First, use of large language models has been utilized in their daily life; however, there is hesitancy to utilize these resources for medical advice. A second important theme that surfaced several times was the importance of trust in the source of the artificial intelligence that she would be using since it was for medical care. Another theme was the importance of ease of use of a large language model. This theme was illustrated by being able to share with family and friends since children are often involved with multiple caregivers. It would also have to have an easy-to-use interface, such as pre-programmed personal settings and recognizable picture icons to make her more likely to use it. Discussion/Significance of Impact: Users emphasized trust in AI sources for diabetes care, noting that clear visuals and personalization improve usability. Further interviews may reveal broader perspectives on adoption, challenges, and barriers among adolescents and caregivers with insulin-dependent diabetes.

Objectives/Goals: This poster provides an overview of a new curriculum, “Entering Mentoring for Research Professionals,” that is designed for research professional mentors who provide research support. The presentation will highlight the curriculum adaptation process and evaluation results from beta testing. Methods/Study Population: The new curriculum was adapted from the Entering Mentoring base curriculum with support from the National Organization of Research Development Professionals in collaboration with the Center for the Improvement of Mentored Experiences in Research. Modules and activities were revised for use with research professionals (RP) across career stages and research areas. The adapted curriculum was beta tested with RP mentors at several sites, including CTSA and CTR hubs, and ISCORE-RC. Evaluation surveys were administered to mentors immediately following the training. Surveys were also administered to facilitators to collect information on their experience implementing the new curriculum. Results/Anticipated Results: The anticipated results of this project include beta test data from 40 participants and their facilitators across four implementation sites. Key outcomes include data on how well the newly adapted curriculum aligns with the intended audience and participant workshop satisfaction. Data on workshop impact, including intended behavioral changes, will also be reported, along with recommendations for curricular modifications. Data from facilitators of the training will also be shared. Discussion/Significance of Impact: RPs, who primarily operationalize research studies aimed at improving human health, play a critical role in the translational science workforce. This curriculum is designed specifically for this group and helps promote mentorship excellence across the academic enterprise. The curriculum will be disseminated widely after beta testing.

Objectives/Goals: Pediatric obesity is a public health issue. Many youths in lifestyle obesity treatments do not improve their weight. Sequential Multiple Assignment Randomized Trial (SMART) study designs can support slow responders (e.g., youth who do not initially lose weight). SMARTs have limited use in pediatric obesity and lack data-driven adaptive rules. Methods/Study Population: This study leveraged an ongoing 6-month family-based health behavior pediatric obesity treatment for children and their parents. Parents with obesity and their children (6–11years) with overweight/obesity (body mass index >85th%ile) who lived in rural areas and were a part of the larger pediatric obesity treatment trial were invited to this study. During the treatment, parent/child dyads were asked to complete additional surveys across nine time points (weeks 1, 2, 3, 4, 6, 8, 12, 16, and 20). Surveys assessed the child’s physical activity, diet, and pain, along with the family environment and parental stress. The child’s anthropometrics were measured each month. Results/Anticipated Results: Data collection will be completed in December 2025. Anticipated results will include analyses to identify responders (i.e., children who reduce their weight outcomes [body mass index (BMI) z-score, BMI percentile, or weight]) and slow responders (i.e., children who do not reduce their weight outcomes) to the pediatric obesity treatment; based on preliminary work, we expect ~50% of the sample to be responders. Once responders/slow responders are identified, survey data will be used to define the adaptive rules, including the tailoring variable (e.g., physical activity or junk foods, or early-response weight outcomes) and decision time point for second randomization. Discussion/Significance of Impact: Data from this study will lay the groundwork for developing data-driven criteria for SMART rules (tailoring variable and decision time point for second randomization). This, in turn, will support the development of adaptive interventions to identify and support the many youths who are slow responders to lifestyle pediatric obesity treatments.

Objectives/Goals: Our team has developed Specialized Hydrogel In Natural Enhancement for Vaginal Health (SHINE-VH), a synthetic mucin-mimetic, to strengthen the cervicovaginal mucus barrier and mitigate microbial colonization to prevent bacterial vaginosis. Methods/Study Population: We formulated SHINE-VH via polymer chemistry and evaluated its efficacy through translational assays. Polymers were synthesized in ultra-high molecular weights and engineered to exhibit hydrophilicity, mucoadhesion, and high viscosity, thus replicating the physical properties of healthy mucus. SHINE-VH readily dissolved in water and was safety-tested using human vaginal (VK2/E6E7) and endocervical (End1/E6E7) epithelial cell lines. Following confirmation of biocompatibility, we characterized its physicochemical properties through shear rheology and sugar permeability. To examine barrier integrity and anti-inflammatory activity, VK2/E6E7 cells were cultured on transwell inserts and pre-treated with SHINE-VH prior to 24-hour exposure to lipopolysaccharide (LPS) (10 µg/mL). Results/Anticipated Results: SHINE-VH maintained a high molecular weight (Mn > 1.0 MDa) and narrow dispersity (Đ = 1.0–1.4), indicating uniform polymer length. The formulation exhibited viscoelastic behavior (η* = 0.1–1 Pa•s) comparable to native vaginal mucus. SHINE-VH supported high biocompatibility across vaginal and endocervical cell lines (> 90% viability), with no tested dose falling below ISO 10993-5 safety thresholds. SHINE-VH enhanced epithelial barrier integrity by restricting LPS translocation (p = 0.03, g = –1.26) and attenuated inflammation through reduced IL-6 secretion (p = 0.009, g = –1.97). Lastly, while blocking toxins, SHINE-VH preserved nutrient exchange, permitting glucose/maltose diffusion (> 90% in 72 h). Collectively, these findings confirm SHINE-VH preserves epithelial health. Discussion/Significance of Impact: Bacterial vaginosis affects ~30% of women globally and contributes to severe gynecologic and obstetric complications. SHINE-VH offers a novel, non-antibiotic approach to BV management by strengthening vaginal mucosal integrity and limiting bacterial invasion, potentially reducing recurrence and improving women’s reproductive health.