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

Objectives/Goals: To assess the feasibility, safety, and preliminary efficacy of implementing a supervised, outpatient aerobic and strength exercise regimen in newly diagnosed pediatric patients with acute lymphoblastic leukemia (ALL). We hypothesize that early implementation of exercise is feasible and may prevent well-known cardiometabolic late effects. Methods/Study Population: We will enroll 10–20 children (both males and females) with newly diagnosed ALL between the ages of 11–21 years to participate in a 12-month supervised, structured outpatient exercise regimen (STRONGER ALL). This regimen will consist of low- to moderate-intensity aerobic and strength exercises (either in person or coached virtually per patient preference) 3 times a week. This study will include 2 physical fitness assessments: 1) baseline and 2) end of study. Assessments will include resting energy expenditure, peak oxygen uptake, bone density, upper and lower extremity strength, flexibility, and questionnaires (feasibility and quality of life). Additionally, blood and urine specimens will undergo metabolomic analysis to identify biomarkers predictive of future cardiometabolic outcomes. Results/Anticipated Results: We expect that early implementation of STRONGER ALL in children undergoing chemotherapy will be feasible and preliminarily effective at mitigating risk factors for long-term cardiometabolic outcomes in survivors. Feasibility will be defined by recruitment capability (at least 50% of eligible patients agree to enroll), acceptance/compliance (at least 50% of participants complete the program with participation in at least 50% of sessions), data acquisition (collection and outcomes measures are appropriate), and practicability (program shows promise of being successful with pediatric ALL patients as measured by validated surveys administered to patients and caregivers). We anticipate that ALL patients participating in STRONGER ALL will have improved fitness and quality of life. Discussion/Significance of Impact: Evidence on the benefits of physical activity for ALL patients has not changed clinical practice. We aim to overcome the translational science barrier of patient- and system-level blockade in implementation of exercise in children with ALL. The evidence generated from this research may also be generalizable to other childhood cancer survivors.

Objectives/Goals: Both diabetes and obesity are major health issues in the USA. Though much focus is given on the impact of lifestyle modifications to control diabetes and obesity, more information needs to be established about the association of social determinants of health and them. This study explores these associations, focusing on the DMV area. Methods/Study Population: The data for this study were collected for 158 counties which cover two states Maryland and Virginia, and Washington DC from PolicyMap. PolicyMap is a geography information system (GIS) that aggregates different types of data from different sources for research purposes. County-level data on public health related to different SDoH like median age, and percentages proportions of different ethnicity (Hispanic or Latino), percentages of different race, and nativity (foreign born), gender (ratio of male to female), access to primary healthcare, social vulnerability index (SVI), and median household income was used in this study. Statistical methods like multiple regression, one way ANOVA, and Pearson’s correlation coefficients were used to determine which factors are associated with these two conditions. Results/Anticipated Results: For both diabetes prevalence and obesity, multiple linear regression model with backward elimination was used to select variables which associated with them. The backward elimination process selected the set of factors for which the adjusted R square was the highest. In both cases, median household income, median age of population, social vulnerability level, percentage of white population, and percentage of foreign-born population were found to be significant at 5% level of significant. Pearson’s correlation coefficients showed significant positive relationship between factors like obesity and diabetes, median age and access to health care, and negative relationship between obesity and foreign born. Income, healthcare access, and white population were found to be significantly different SVIs from ANOVA. Discussion/Significance of Impact: This research study found that some SDoH affect diabetes and obesity in the same direction. The association is positive for median age and negative for income, SVI, percentage of white population, and foreign born. The associations were found between actionable and non-actionable factors like percentage of white population with access to health care.

Objectives/Goals: This study aims to evaluate common features of mobile health (mHealth) apps and their role in helping caregivers make health decisions for children. Methods/Study Population: A scoping review of literature on caregivers’ use of mHealth apps (published since 2008) was conducted across 5 databases (i.e., Embase, PubMed, CINAHL, Clinicaltrials.gov, and IEEE Xplore). Selected papers were categorized based on app purposes, target users, and mHealth agile development phases. Common features were also identified and analyzed along with users’ pros and cons. Further, primary feature requests were summarized to inform future development. Results/Anticipated Results: This review included 62 studies. Most apps were about maternity and infant care and specific diseases. Major users were caregivers and pregnant women. Around 20% of papers covered multiple phases in the mHealth agile development lifecycle. The effectiveness/clinical trial (phase III) was the most common. E-learning, personalization and customization, and health tracking features were the three most common features of mHealth apps included in this review. More positive feedback was found regarding features than concerns. Caregivers perceived apps as helpful and empowered them to make informed decisions. Concerns were mainly over 1) technical issues, 2) inappropriate design, and 3) ambiguous terms. Requested new features included content comprehensiveness, user engagement, and usage flexibility. Discussion/Significance of Impact: To our knowledge, this is the first review to investigate the usability of mHealth app features in this area. The results offer feasible strategies for developers to improve the effectiveness of apps for caregiver decision-making.

Objectives/Goals: Port-site metastasis (PSM), defined as the spread of malignancies to the abdominal wall at the site of surgical ports, poses a significant challenge in cancer management. The objective of this summary overview is to describe the prevalence of and risk factors associated with PSM in various gynecological cancers after laparoscopic surgery. Methods/Study Population: Study design: Systematic Review and Meta analysis Search strategy: All international databases, without language limitations, from January 1990 to December 2023. Inclusion/exclusion criteria: Cohort, case–control, or cross-sectional observational studies reporting the frequency of, or risk factors for PSM in young and middle-aged women will be included (using the PRISMA checklist). Data extraction: two reviewers independently extracting pertinent data (using the STROBE checklist). Quality assessment and risk of bias: The quality of each study will be assessed according to the Quality Assessment Tool for Observational Studies. Results/Anticipated Results: This meta-analysis of 36 studies evaluated the proportion of successes across various populations, with a pooled proportion of 0.02 (95% CI: 0.01–0.02) based on a random-effects model. Significant heterogeneity was identified (I²  =  88.12%), reflecting notable variability between studies. Despite this, the overall effect was statistically significant (p  =  0.00). A subgroup analysis will be conducted to explore potential sources of heterogeneity, considering factors such as cancer stage, diagnostic methods, surgical approach (conventional or robotic), and study type (retrospective/prospective). Discussion/Significance of Impact: By identifying the prevalence of, and the risk factors for, PSM, this study will better inform personalized treatment approaches, surveillance strategies, and surgical decision-making to improve patient-related outcomes and long-term survival in women with gynecological malignancies.

Objectives/Goals: To assess the effect on the immune response to COVID-19 in children exposed to pesticides. The hypothesis is that increased pesticide exposure results in different immunological response to COVID-19. The goal of the proposal is to improve scientific knowledge on factors affecting COVID-19 and identify a modifiable factor to reduce these disparities. Methods/Study Population: A cross-sectional analysis of children (aged 5–17 years) with asthma to assess pesticide exposure and immune markers of SARS-CoV-2. SARS-CoV-2 infection or vaccination was determined with blood exposome RNA analyses assessed from blood samples taken at baseline. Immunological response was measured using neutralizing, phagocytizing, and NK-activating antibody responses biomarkers using plasma antibody isotyping, effector functions, T-cell activation-induced marker (AIM), and recall cytokine secretion assays on lysed, whole blood. Pesticide exposure was assessed as concentration of four urinary metabolites in a spot urine sample adjusted for creatinine. Unadjusted regression models were created to assess the effect of 3-phenoxy benzoic acid, a common pyrethroid pesticide, on immune markers. Results/Anticipated Results: Children’s (N = 30) average age was 10 years (interquartile range: 8–11) A majority of children were male (63%) and Non-Hispanic Black (73%). The majority of children had markers of SARS-CoV-2 infection (77%). Of the 4 pesticide metabolites assessed, only 3-PBA was commonly found (77% of samples > LOQ). Higher urinary concentrations of 3-PBA are associated with a significant (p Discussion/Significance of Impact: Significant associations in cytokine and inflammatory marker may indicate a Th2-skewed response, and dysregulated cytokine responses can lead to severe disease. A suggested increase in T-cell activation markers (e.g., CD4, CD8) may indicate potential exhaustion if excessively activated.

Objectives/Goals: Originally presented at TS24, we would like to discuss follow-up outcomes and preliminary findings“Building Empowerment Through Fitness” – objectives were designed to address the “whole women” in underserved segments of the population in impoverished and/or underprivileged communities with fewer opportunities and promote economic mobility. Methods/Study Population: A qualitative study design to understand unique cultural context and challenges faced by women residing in the Birmingham Housing Authority, regarding physical activity engagement, including sedentarism. The needs assessment approach examined barriers, support systems, and social networks. Semi-structured, pre, mid, and post program focus groups explored challenges and opportunities for health, such as diet and exercise, and are being analyzed by hand with a thematic analysis. The project framework used movement, home repair tools with a life-building/life repair curriculum to influence self-efficacy and program engagement. The study enrollment included 51 women over two cohorts in a 12-week project. Results/Anticipated Results: Preliminary are results showed the women did face heightened health risks due to sedentary lifestyles, educational gaps, and socioenvironmental barriers. We incorporated tool skills, healthy lifestyles, and social/emotional focus group to explore social/emotional perceptions, concerns, and needs. Although our results were on target, there were some unexpected outcomes related to family dynamics, literacy, housing stability, and peer support. Discussion/Significance of Impact: Women are more likely to be sedentary and have poor health. BeFit served as a solution to addressing problems related to economic mobility barriers, poor health, sedentariness, and low self-esteem/self-efficacy. Additionally, exercise/movement programs can be a powerful tool to address disparities and help prioritize health.

Objectives/Goals: This qualitative study evaluated facilitators and barriers to clinical research participation among lower-income, predominately racial/ethnic minority communities to inform a Co-Learning series. The Co-Learning series of community members, stakeholders, and researchers developed strategies to improve diversity in research. Methods/Study Population: Community focus group (FG) participants were recruited from urban communities experiencing poverty, whereas stakeholder FGs included diverse community leaders and researchers. The Social Ecological Model was used as the guiding theoretical framework throughout the qualitative design. Directed content analysis using three independent coders reaching 100% consensus identified prominent factors for increasing diversity in research. The co-learning series was comprised of community members, stakeholders, and researchers who discussed the prominent FG factors over seven in-person meetings to develop a toolkit to increase diversity in research. Results/Anticipated Results: Community (n = 51) and stakeholder (n = 50) FG participants were 54.0±16.0 years of age, 81.2% female, 39.6% Black/African American, 51.5% Hispanic, and 60% had Discussion/Significance of Impact: Due to the lack of inclusivity in clinical research, findings are typically not applicable to health disparity populations limiting the benefit of research to all. This study provides practical community-driven strategies to increase diversity in clinical research, highlighting the role of trust, relationships, and cultural relevancy.

Objectives/Goals: The overarching goal of the GRAMM study is to address racial health disparities by increasing access to genetic counseling and testing among the Black community. Specific objectives are to determine patient acceptability of risk assessment at time of mammography and to evaluate subsequent access to and uptake of genetic counseling and testing. Methods/Study Population: All women presenting for screening mammography at the Ypsilanti Health Center under the University of Michigan were invited to enroll. After providing written informed consent, study participants entered family cancer and personal health information in the InheRET software tool which links to the National Comprehensive Cancer Network genetic testing guidelines. Upon completion, each participant was informed immediately if they did or did not meet the criteria to meet with a genetic counselor. For those who met the criteria, referral to genetic counseling was provided. All enrollees were invited to complete a post-assessment survey on acceptability of the service and genetics knowledge. Patients will be followed over time for completion of genetic counseling and testing. The study was approved by the Umich IRB. Results/Anticipated Results: As of 10/18/24, a total of 53 were enrolled, with 52 eligible for the study and were between the ages of 30–75 years. 51 identified as women and 1 identified as nonbinary. 21 (40.4%) identified as Black, 30 (57.7%) identified as White, 2 (3.8%) identified as Hispanic, and 1 (1.9%) identified as mixed race. Of the total enrolled, 25 (48.1%) met criteria to meet with a genetic counselor. Twelve (23.1%) have been scheduled to with meet with a genetic counselor and 2 (3.8%) of this group completed their appointment, but did not pursue genetic testing. 28 (53.8%) completed the survey and reported that they were satisfied with the service. Of the 16 people who screened positive and completed the survey, all 16 (100%) stated that they intended on proceeding with testing. Our study is still ongoing. Discussion/Significance of Impact: While this model has demonstrated acceptability so far, there are still possible barriers to genetic counseling and testing after the referral has been provided that need to be explored. However, this approach could provide a novel framework for combining risk assessment with screening mammography for all women nationwide.

Objectives/Goals: Present a framework for hosting Community Grand Rounds, where community and academic partners showcase completed community-engaged research (CEnR) projects. This highlights innovative dissemination methods, engages diverse audiences, elicits community responses, and advances the translational science of CEnR. Methods/Study Population: Our approach involves planning and outreach to collaborate with promotion of academic and community engaged grantees to develop community dissemination events that translate the science of CE into accessible, relatable, culturally relevant formats for diverse audiences. These events incorporate interactive presentations that encourage active participation and feedback from attendees. Following each event, an evaluation is completed to assess community impact. Key strategies for hosting, facilitating, and utilizing diverse marketing to ensure that events are tailored to culturally diverse community groups, including regional implementation when practical. This collaborative approach meets a critical need and strengthens the bond between researchers and the communities they aim to serve. Results/Anticipated Results: These events create a feedback loop between the community and academic researchers. It was not just about telling people what was found. We created opportunities for community members and academics to build trust, give us feedback, ask questions, and discuss how findings could be practically applied. By presenting the findings in an accessible way within the community, community members are more informed and empowered to make decisions or advocate for changes in their own lives based on the research. Academics also benefited from community feedback, which provided new insights to help refine future research questions and methods. The goal is for shared conversation and understanding between community members and academics to inspire real-world applications and policy change directly informed by the research. Discussion/Significance of Impact: Community Grand Rounds are one dissemination strategy to leverage community–academic collaboration to present tailored research, fostering engagement, understanding, and action between researchers and community members. This approach effectively enhances the translational science of CEnR by involving and benefiting the community.

Objectives/Goals: Glucagon-like peptide-1 (GLP1) use prior to bariatric surgery may represent a novel approach to treating obesity. The objectives of this study were to describe trends in pre-bariatric GLP1 use, investigate social and clinical factors associated with their use, and evaluate differences in clinical outcomes based on preoperative GLP1RA use. Methods/Study Population: Patients who underwent bariatric surgery at three Indiana hospitals from 2018 to 2023 were identified. Patients who utilized GLP1 in the year preceding surgery were compared to those who did not. Social determinants of health included insurance, income, and unemployment. Outcomes included rates of GLP1 use, 30-day postoperative readmissions, ED visits, and percent total weight lost (%TWL) at one year. Associations between preoperative GLP1 use and outcomes of interest were evaluated using multivariable logistic and linear regressions. Results/Anticipated Results: Of 2,169 patients who underwent surgery, 293 (13.5%) utilized GLP1 preoperatively. The rate of GLP1 utilization increased threefold from 2018 to 2023. Males were more likely to receive preoperative GLP1 (20.1% vs, 12.2%, p<0.001). There were no significant differences in social determinants of health or 30-day postoperative outcomes between patients who did and did not use GLP1RA preoperatively. Similarly, there were no significant differences in %TWL at one year postoperatively between groups (median 25.5% vs. 27.3%, coefficient: -0.78, 95%CI: -2.26–0.70). Discussion/Significance of Impact: Utilization of GLP1 in the year prior to bariatric surgery has significantly increased. Preoperative GLP1 use is not associated with worse 30-day outcomes or differences in %TWL at one year postoperatively. Further work is needed to evaluate whether GLP1 dosing and duration of treatment impact postoperative outcomes.

Objectives/Goals: Nearly 42% of adults in the USA have obesity; women are disproportionately affected. Women with obesity that become pregnant are especially prone to developing health condition; thus, aid is needed to achieve appropriate gestational weight gain (GWG). GWG interventions would benefit from examining the effects of social support and stress has on GWG. Methods/Study Population: The proposed study will examine whether expecting mothers’ social support predicts their perceived stress. Also, examine whether receiving aid, in the form of weekly meal delivery, changes perceived stress. Lastly, this study will explore if social support mediates the relationship between meal delivery and perceived stress. The study will use data gathered from a pilot GWG intervention focused on providing pregnant women weekly meal delivery. Participants (N = 14) will complete 2 visits at 16–20- and 35–36-weeks gestation, while receiving weekly meal deliveries. Data from both visits will be used for the purpose of this study. Women’s social support will be measured using the Multidimensional Scale of Perceived Social Support. While stress will be measured via the Perceived Stress Scale. Results/Anticipated Results: Previous behavioral weight loss studies have found that individual who endorse experiencing social support report less perceived stress. Although the relationship has seldomly been examined in pregnant women, similar results are anticipated. Often aid, such as meal delivery, can impact perceived stress and is likely to cause a positive change. To our knowledge, this is the first study to explore whether social support mediates the changes in perceived stress after receiving weekly meal delivery. Therefore, there is no known literature to suggest anticipatory results. Discussion/Significance of Impact: Few studies have examined the association between social support and perceived stress in pregnant women. This study will examine the effects social support has on a pregnant women’s stress. The proposed study will aim to identify if meal delivery changes perceived stress. If so, the study will explore if perceived social support mediates this change.

Objectives/Goals: This study aims to evaluate the performance of a third-party artificial intelligence (AI) product in predicting diagnosis-related groups (DRGs) in a community healthcare system. We highlight a use case illustrating how clinical practice leverages AI-predicted information in unexpected yet advantageous ways and assess the AI predictions accuracy and practical application. Methods/Study Population: DRGs are crucial for hospital reimbursement under the prospective payment model. The Mayo Clinic Health System (MCHS), a network of clinics and hospitals serving a substantial rural population in Minnesota and Wisconsin, has recently adopted an AI algorithm developed by Xsolis (an AI-focused healthcare solution provider). This algorithm, a 1D convolutional neural network, predicts DRGs based on clinical documentation. To assess the accuracy of AI-generated DRG predictions for inpatient discharges, we analyzed data from 930 patients hospitalized at MCHS Mankato between March 2 and May 13, 2024. The Xsolis platform provided the top three DRG predictions for the first 48 hours of each inpatient stay. The accuracy of these predictions was then compared against the final billed DRG codes from the hospital’s records. Results/Anticipated Results: In our validation set, Xsolis achieved a top-3 DRG prediction accuracy of 71% at 24 hours and 81% at 48 hours, which is lower than the originally reported accuracy of 81.1% and 83.3%, respectively. Interestingly, discussions with clinical practice leaders revealed that the most valuable information derived from the AI predictions was the expected geometric mean length of stay (GMLOS), which Xsolis was perceived to predict accurately. In the Medicare system, each DRG is associated with an expected GMLOS, a critical factor for efficient hospital flow planning. A subsequent analysis comparing predicted GMLOS with the actual length of stay showed variances of -0.10 days on day 1 and 0.14 days on day 2, indicating a high degree of accuracy and aligning with clinical practice perceptions. Discussion/Significance of Impact: Our research underscores that clinical practice can leverage AI predictions in unexpected yet beneficial ways. While initially focused on DRG prediction, the associated GMLOS emerged as more significant. This suggests that AI algorithm validation should be tailored to specific clinical needs rather than relying solely on generalized benchmarks.

Objectives/Goals: Patients with multiple chronic conditions (MCCs) face care coordination challenges and poorer health outcomes. Outpatient telehealth may be an effective way to enhance MCC patient care given the need for multiple visits and specialists. This study seeks to describe telehealth utilization between 2013 and 2023 in Arkansas. Methods/Study Population: We utilized the Arkansas All-Payer Claims Database (APCD) to identify patients diagnosed with high-prevalence MCCs comprising diabetes with comorbid hypertension, hyperlipidemia, or asthma. We then measured telehealth utilization defined as any claim associated with a telehealth modifier code, a place of service code defining the service as occurring in the patient’s home, or remote patient monitoring. Finally, we created payer-specific (e.g., commercial or Medicaid) yearly measures of the number of any telehealth claims among MCC patients divided by the number of MCC patients for that year. Linear regression was used to measure the difference in utilization during the COVID-19 pandemic (i.e., 2020–2023) versus prior to the pandemic (i.e., 2013–2019). Results/Anticipated Results: Overall, the COVID-19 pandemic era was associated with an increase of telehealth utilization among commercial patients by 1.01 telehealth claims per MCC patient (95% CI: 0.39 to 1.62, p Discussion/Significance of Impact: Variations in telehealth uptake among MCC patients suggest heterogeneity in its suitability and necessity. We will later evaluate whether telehealth use is associated with different levels of inpatient and emergency department utilization. We expect the findings to provide clarity on the suitability of telehealth use by MCC disease status.

Objectives/Goals: Here, we utilize deep learning to automate the analysis of dual X-ray absorptiometry (DEXA) scans in the UK Biobank (UKB) imaging dataset to enable a large-scale assessment of lumbar spine disc degeneration, low back pain, and socioeconomic status. Methods/Study Population: Study Population: The UKB is a biomedical database that includes lateral spine DEXA imaging for 50,000 participants. Deep Learning Model Development: A computer vision model was developed that receives a DEXA scan as input and outputs a quadrilateral that corresponds to the corners of 5 lumbar vertebral bodies. The model is a deep, fully convolutional, encoder–decoder network using DeepLabV3. Statistical Analysis: To determine our preliminary model accuracy, we used the intersection over union (IoU) metric.We analyzed data using an ordinal regression model to determine the relationship between income/ neighborhood level multiple deprivation index (MDI) and low back pain (LBP), as well as a mixed effects model to estimate the relationship between income/MDI and disc height index (DHI). Results/Anticipated Results: Our model predicted vertebral body quadrilaterals in training and unseen test data (train IoU  =  0.96, test IoU  = .91) and was used to infer data for 10,440 participants. Confirming previous studies, there were significant relationships (p0.05) between income or MDI and DHI (Figure 2). Discussion/Significance of Impact: Low back pain is the world’s leading cause of disability, and socioeconomic factors play an important role. We found no relationship between disc height index and socioeconomic status. Thus, disc degeneration may not be a factor in this low back pain phenotype.

Objectives/Goals: We investigate how the gut microbiome protects against arsenic toxicity, showing antibiotic perturbation increases toxicity and causes interindividual susceptibility to a sepsis-like disease state in mice. Here, we aim to understand how baseline microbiomes from various mouse vendors impact these outcomes and characterize the observed disease. Methods/Study Population: We developed a novel mouse model where mice are exposed to an antibiotic (cefoperazone) for 2 days, followed by co-exposure to the antibiotic and 100 ppm arsenate. So far, we have evaluated C57BL/6N mice from MSU’s in-house colony, Taconic Biosciences (TAC), and Jackson Labs (JAX), along with C57BL/6J mice from JAX. To determine if the baseline microbiome drives inter-vivarium differences, we established in-house breeding colonies of TAC- and JAX-origin mice at MSU. This allowed us to assess whether, when housed under identical conditions, these mice still show differences in mortality based on their original microbiomes. To characterize the arsenic-induced sepsis-like disease, we performed blood biochemistry assays to quantify the white blood cell populations, and sepsis biomarkers used in clinical settings. Results/Anticipated Results: We observed differences in survival rates between genetically identical mice from MSU (45%), TAC (30%), and JAX (2.5%) in our model. From this, we characterized the baseline composition of the gut microbiomes of these mice and found they were significantly different from each other. We are still awaiting results from our in-house TAC and JAX experiments but expect them to have similar gut microbiome compositions to those directly purchased from TAC and JAX and respond similarly. In our blood biochemistry analysis, we found sick mice presented with low WBC counts and notable biomarkers indicative of liver, heart, and kidney distress. We also anticipate that 16S sequencing results of cecal contents will further support findings by providing evidence of a bacterial infection in the ceca of sick mice. Discussion/Significance of Impact: Collectively, our work demonstrates that antibiotic perturbation of the gut microbiome induces an inter-individual and inter-vivarium susceptibility to an arsenic-induced sepsis-like disease state. This work highlights the importance of considering antibiotic use in the risk assessment of arsenic to better protect the health of those exposed.

Objectives/Goals: Engage the research professional (RP) workforce in assessing job satisfaction, motivators, barriers, and levels of support throughout the research enterprise. The goal of this collaboration is to foster a positive culture, inform manager training, ensure RP retention, and enhance career mobility pathways. Methods/Study Population: Methods include a HR data compilation/analysis and focus groups for new RP’s (Results/Anticipated Results: This initiative will articulate the current culture and climate of the research enterprise and identify key strategic areas for growth. The UMN Clinical and Translational Science Institute (CTSI) will build off the design of an internal survey at Vanderbilt (2018) to encompass organization-specific challenges, the post-pandemic research landscape, and the UMass Diversity Engagement Survey. This process will also generate specific insights including RP sentiment statements, trends in how RP’s describe their day-to-day work, assessment of barriers, analysis of retention benchmarks, and defining employee hopes/motivators. The CTSI will also identify salient RP growth opportunities, leadership competencies, and areas of non-monetary compensation to improve satisfaction and career mobility. Discussion/Significance of Impact: Targeted interventions will be developed to address RP satisfaction barriers and leverage opportunities for KPI improvement. Results will be disseminated to managers, administrators, and the CTSI network. Resource development will include RP personas, job description/hiring templates, and strategic guides for key operational challenges.

Objectives/Goals: Primary care physicians (PCPs) have limited awareness of assistive technology (AT) devices that can improve the daily functioning of older adults. This study aimed to assess the quality of the My Assistive Technology Guide (MATG), an informative web app, among PCPs and to describe their experiences using it. Methods/Study Population: In this pilot project, our team – comprising an established researcher, an undergraduate faculty member, and a graduate student – enrolled ten PCPs. In Phase I, the PCPs received training on how to use the MATG and were encouraged to utilize it for 30 days. At the end of this usage period, we implemented a concurrent parallel mixed-method design to collect both quantitative and qualitative data. Quantitative data were gathered using the User Mobile Application Scale (uMARS), while qualitative data was obtained through interviews. Data analysis involved descriptive statistics and thematic content analysis. Results/Anticipated Results: The mean score for the subjective quality of the MATG was high, 4.1 ± 1.1. The information domain received the highest rating, with a mean score of 4.6 ± 0.51, while the engagement domain received the lowest rating, at 3.3 ± 1.5. Overall, subjective quality was rated moderately high (mean 3.9, interquartile range 1.2), with perceived impact rated the highest at 4.8 ± 0.4. PCPs reported increased awareness, knowledge, attitude, intention, and behaviors to learn about AT and to inform and recommend AT devices to older adults. In addition, PCPs provided suggestions to improve the MGAT and its integration into their medical practice. Discussion/Significance of Impact: The results demonstrated the high quality and utility of the MATG, indicating that it could serve as a valuable resource for PCPs in addressing functional disabilities among older adults. Future research should evaluate the effectiveness of the MATG in enhancing older adults’ function in daily living activities.

Objectives/Goals: Our study team won a Public Health Answers to Speed Tractable Results (PHASTR) contract to conduct a target trial emulation to answer “Does metformin show a reduction of severe outcomes of COVID-19 or of Long COVID in the N3C Data Enclave?” We quickly delivered an answer due to productive technical and collaboration support in the N3C. Methods/Study Population: Our analytic plan was updated based on helpful feedback from the PHASTR program. We performed a trial emulation analysis using the N3C data, comparing adult new users of metformin to controls prescribed fluvoxamine, fluticasone, ivermectin, or montelukast. The composite outcome was Long COVID or Death (LC/D) within 180 days of COVID infection. We used entropy balancing to estimate the average treatment effect with a weighted log-linear model. Productivity was enhanced by reusing code workbooks and validated codesets from related N3C projects. The team of 4 (physician, informaticist, data programmer, and statistician) and key unpaid advisors spent 10 weeks developing and analyzing the data. Results/Anticipated Results: Totally, 9,660 patients were identified for analysis. After weighting, there were 248 in the metformin and control groups. In the metformin group, 4.0% developed LC/D vs. 8.5% in the control group, with an adjusted risk ratio (aRR) of 0.47 (95% CI 0.25 to 0.89). Results were consistent across subgroups and sensitivity analyses. The PHASTR contract structure helped produce high-quality results quickly by not only providing funding but also requiring a compressed timeline for a small team to focus on the study. The most time was spent on contract execution, enclave provisioning, and too many last-minute download requests. A project final report was submitted in March and a full manuscript was submitted in September. Discussion/Significance of Impact: The analysis was productive because the environment made reuse easy and supported rich collaborations among clinicians, informaticists, epidemiologists, statisticians, and data developers. Advice from PHASTR advisors (Axel) and N3C diabetes domain team members was also key to a faster completion.

Objectives/Goals: Using secure systems for sharing documents with external collaborators is essential for all researchers. These documents may include protected health information (PHI) or sensitive materials like protocols, study reports, DSMB reports, publications, presentations, abstracts, and statistical analysis plans (SAPs). Methods/Study Population: We surveyed the ACTS Biostatistics, Epidemiology, and Research Design Special Interest Group (BERD-SIG) to gather information about the systems they are currently using or have used in the past for document sharing with external collaborators. The survey focused on the security of these systems, particularly in relation to sharing documents containing PHI. In addition, the survey included questions about various system features of interest. These features included version control, simultaneous editing by multiple users, and access rights management, such as the ability to assign different permissions (e.g., read-only, write, and download) to different individuals. We also invited participants to provide feedback on any additional positive or negative aspects of the systems they use. Results/Anticipated Results: We received 28 completed survey responses. Respondents had an option for choosing more than one system. The top current systems reported were Microsoft Teams (OneDrive, SharePoint) (n = 16), Box (n = 11), Google Docs/Drive (n = 10), and Dropbox (n = 6). Among other systems listed individually were Filelocker, REDCap, Slack, Website, Significant Media Shuttle, and Zulip. Notably, 15 responses indicated the respondents were unsure if their system is secure for sharing documents containing PHI. Respondents also offered feedback on both the positive and negative aspects of these systems. For example, a key advantage of Box was its password-controlled access. However, its incompatibility with office tools and the challenges for external collaborators attempting to access the system were noted as drawbacks. Discussion/Significance of Impact: Utilizing secure institutional document-sharing systems and understanding their features significantly affects the effectiveness and security of collaborations among researchers, particularly with external partners. This knowledge is especially crucial when sharing documents containing sensitive patient and study data.