ABSTRACT IMPACT: As newborn screening is now available for X-linked adrenoleukodystrophy, there is a need to establish meaningful disease markers to detect the onset of the severe demyelinating cerebral form of this disease at the earliest possible stage, and to quantify early disease progression to evaluate the relative efficacy of therapies. OBJECTIVES/GOALS: Longitudinal testing of neurocognitive and motor function using smartphone and tablet-based applications holds promise for early detection and quantification of brain white matter changes in patients with adrenoleukodystrophy (ALD) and other rare demyelinating diseases, but this methodology requires validation in pediatric populations. METHODS/STUDY POPULATION: We developed an iPad application with a game-like interface to assess interhemispheric transfer across the corpus callosum, the brain structure where cerebral demyelinating disease typically begins in patients with ALD. Feasibility data from remote test administrations with healthy children were collected to analyze and speed and timing of finger tapping movements requiring bimanual coordination on a touchscreen. RESULTS/ANTICIPATED RESULTS: Among our pilot sample of healthy school-aged children, age-related improvements in finger tapping speed were observed in both single-hand and alternating-hand conditions. Results indicate that remote testing using iPad applications is a viable way to collect psychometric testing data rapidly in pediatric populations and is feasible during a pandemic. Next steps in this research project will be: (1) evaluating the stability of repeated test administrations (test-retest reliability), (2) assessing agreement between performance on our iPad application and validated measures of interhemispheric transfer and fine motor function, and (3) comparing performance of children with known corpus callosum white matter abnormality to performance of healthy children. DISCUSSION/SIGNIFICANCE OF FINDINGS: Brief neurocognitive tests that can be frequently administered may have the ability to capture subtle brain changes in developing children. Approaches enabling remote (virtual) testing will facilitate research during the covid-19 pandemic and are especially well-suited for data collection in rare disease populations.

Objectives/Goals: Pregnancy increases vulnerability to stress and mental health symptoms, particularly among Hispanic women in Puerto Rico (PR), a population with unique socioenvironmental adversities, such as poverty and natural disasters. This study examined the relationships between life adversities and psychological distress in this at-risk population. Methods/Study Population: Participants (n = 50) in this cross-sectional study were recruited from an obstetrician’s office in Southern PR. All participants provided written consent and completed the Adverse Life Experiences Scale (ALES, Cronbach’s alpha = 0.71) to identify lifelong adversities faced and the overall duration (chronicity). Measures of psychological distress included the Perinatal Anxiety Screening Scale (PASS, Cronbach’s alpha = 0.96), the Edinburg Postnatal Depression Scale (EDPS, Cronbach’s alpha = 0.87), the Perceived Stress Scale (PSS, Cronbach’s alpha = 0.79), and the Brief Resilience Scale (BRS, Cronbach’s alpha = 0.86). Descriptive and Spearman’s rho correlation analyses were conducted. Results/Anticipated Results: The mean age of the participants was 27.90 years (SD = 6.05), with most in the first trimester (66.0%). On average, participants reported 4.32 (SD = 3.1) out of 23 lifetime adversities. The most common adversities were natural disasters (60.0%), loss of a beloved (58.0%), and financial difficulties (38.0%). Nearly half (44.0%) experienced five or more adversities. A significant number of participants met the clinical threshold for anxiety (38.0%, PASS), depression risk (22.0%, EPDS), moderate-to-severe perceived stress (52.0%, PSS), and low resilience (24.0%, BRS). The overall duration of adversities was significantly associated with anxiety (rs = 0.50, p = 0.001) and stress (rs = 0.50, p = 0.007). Discussion/Significance of Impact: Hispanic pregnant women in PR face high levels of adversity and distress, which can negatively affect both maternal health and fetal development, influencing long-term child outcomes. Early identification and targeted interventions addressing adversities, can improve maternal mental health and child health-development outcomes.

In this paper, we address how the COVID-19 pandemic has impacted informed consent for clinical research through examining experiences within Clinical and Translation Science Award (CTSA) institutions. We begin with a brief overview of informed consent and the challenges that existed prior to COVID-19. Then, we discuss how informed consent processes were modified or changed to address the pandemic, consider what lessons were learned, and present research and policy steps to prepare for future research and public health crises. The experiences and challenges for CTSA institutions offer an important perspective for examining what we have learned about informed consent and determining the next steps for improving the consent process.

Interventions to foster inclusive learning environments may benefit college STEMM instructors (NASEM, 2019). We investigated the impact of a social inclusion intervention (SII) on scientific self-efficacy, identity, community values, and persistence intentions in a large and diverse sample of biomedical college instructors (n = 116) in the USA. The results indicated that the SII group developed stronger scientific community values than the control group, and the effect was the strongest for instructors who had initially expressed lower values. From a mentoring perspective, the intervention helps boost feelings of community values, which is linked to increased persistence in STEMM careers.

OBJECTIVES/GOALS: To compare the opioid drug requirements amongst those individuals with high levels of catecholamines in blood and acute post-procedural pain, by ICD9/10 codes (experimental) to those with normal levels of catecholamines and acute post-procedural pain (AP-PP) only (controls) METHODS/STUDY POPULATION: In collaboration with both the Informatics and the Biostatistics Departments at CTSI and under the auspices of the IRB at the University of Rochester, we completed the collection of ~8,000 electronic health records(EHRs) of adults 18 years and older with surgical appointments at Strong Memorial Hospital (SMH), who met inclusion criteria, from January 2006 to September 2019 and received Fentanyl therapy for AP-PP management. Subjects were categorized in a two-arm-matched case-control fashion. A ratio of 1(Experimental):1(Control) was utilized. Analytic comparisons were completed using normal distribution statistical methods with p >0.1 for significance. RESULTS/ANTICIPATED RESULTS: After removal of duplicates and exclusion of EHRs, a total of 17 subjects met inclusion criteria for the experimental group. We matched controls (n = 17) with experimental subjects for age, gender and surgical procedure for accurately compare opioid requirements in the postoperative recovery. Mean age of subjects was 69(+/-10.1235) years old. Most of subjects were females (70%). Mean Fentanyl requirement was significantly different in the experimental group 466.17(625.621)mcg compared to 215.58(353.323)mcg in the controls (p value 0.07832) DISCUSSION/SIGNIFICANCE OF IMPACT: It is suggested that healthy individuals with genetic variations in pain pathways including; the COMT and MAOA rendered individuals with higher levels of catecholamines in the body driving abnormal responses to pain sensitivity. We emulated this genetic variation for clinical purposes using ICD10/9 codes of those with conditions related to higher catecholamine levels in the body. Based on our preliminary results, we suggest that COMT and MAOA genetic variations could impact opioid drug use and the current opioid dependency and epidemics in the U.S. This study will address remarkable questions and identify strategies about this topic.

OBJECTIVES/GOALS: 1) Investigate the utility of pragmatic communication profiles in a sample of children with autism at baseline to predict response to treatment in a randomized clinical trial (RCT) of oxytocin augmentation and social cognitive skills training at week 12. 2) Determine if levels of anxiety or hyperactivity moderate child outcome performance. METHODS/STUDY POPULATION: 40 children (37M, 3F), aged 8-11(M=9.25, SD=1.10), with confirmed autism spectrum disorder (ASD), enrolled in an RCT(NCT02918864) were evaluated at baseline on: an assessment of ASD (Autism Diagnosis Observation Schedule, ADOS-2), a task of perspective taking, Theory of Mind ToM, (Reading the Mind from the Eyes Task), pragmatic communication (Pragmatic Rating Scale-School Aged; PRS-SA), IQ (WAIS_I, WISC-V) and anxiety and hyperactivity (Behavior Assessment Scales for Children-3; BASC-3). A Tobii T60 XL was used for eye-tracking visual patterns and attention during the RMET. The PRS-SA was coded by trained, reliable clinicians. Parent ratings indicated over half of the participants’ had At Risk levels or higher on anxiety and hyperactivity on the BASC-3. Week 12 measures included all but the PRS-SA and ADOS-2. RESULTS/ANTICIPATED RESULTS: Baseline preliminary analysis indicated the participants spent more time looking at words (.41ms) than eye images on the RMET(.15ms, p DISCUSSION/SIGNIFICANCE: Findings at baseline suggest pragmatic communication skills are more related to ToM than gaze and attention on the RMET. This relationship will be further investigated over the time of the trial. Mental health indicators need to be considered further in this population. Child profiles at baseline may inform appropriate triage and treatment targets.

Objectives/Goals: To develop an informatics framework that will allow study of environmental effects on stillbirth at large scale (i.e., US-level) and leverage recent advances in machine learning and artificial intelligence to produce reproducible results that can be compared across multiple institutional settings. Methods/Study Population: Experimental exposure data are often available in “absolute time,” where a clinical event can be anchored using a timeline transformation. We associate each stillbirth event with a set of {ti…ti+1}L shapelets [1] associated with a location, L, and time intervals for the entire dataset. These shapeless are aggregated using a state-of-the-art shapelet classifier [2]. An autoencoder is used to reduce the dimensionality of the stillbirth classification and to cluster stillbirth events according to their corresponding exposure patterns. The stillbirth cluster can be analyzed for other nonexposure (i.e., genetic, SDoH, and demographics) factors, which may be enriched and/or depleted. Results/Anticipated Results: The framework we are developing leverages a shapelet-based approach to produce clusters of stillbirth events according to their corresponding exposure patterns. These clusters can be analyzed for depletion or enrichment of nonenvironmental factors. This analysis will inform how to formulate (or not) class models of exposure that can be more informative and have better predictive power than overall population models. Moreover, the finding of depletion and enrichment of physiological properties of the individuals may lead to novel physiological hypotheses to better understand the injury mechanisms that the environmental exposure profile produces. Discussion/Significance of Impact: Nearly 20,000 babies are stillborn in the USA each year [3]. Environmental exposures, usually studied as time averages over certain periods of time, have produced mixed results for stillbirth risk [4]. However, temporal profiles matter [1], and we argue that they can be assessed using shapelet technology.

OBJECTIVES/SPECIFIC AIMS: The current study is the first investigation of frontal alpha asymmetry in distressed violent (DV) and distressed nonviolent (DNV) partners during a placebo-controlled alcohol administration and emotion-regulation study. Because this is the first study of the pharmacological effects of alcohol on FAA, the first portion of the study was conducted to characterize alcohol effects in DV and DNV partners during the baseline condition. The subsequent portions of the study were conducted to characterize the effects of alcohol and evocative stimuli on FAA in DV and DNV partners. We hypothesized that DV partners would demonstrated greater left frontal alpha asymmetry when intoxicated and viewing evocative partner stimuli than DNV partners. Lastly, we attempted to replicate previous research that has found associations between baseline measures of FAA and the State-Trait Anger Expression Inventory – 2 (Spielberger, 1999) subscales of Trait Anger, Anger Expression-Out, Anger Expression-In, Anger Control-Out, Anger Control-In (Hewig, Hagemann, Seifert, Naumann, & Bartussek, 2004). METHODS/STUDY POPULATION: Partners in the present study were drawn from a larger study investigating over-arousal as a mechanism between alcohol use and intimate partner violence (AA022367). Couples were recruited from the community via radio, television and newspaper advertisements, and eligibility screening occurred at the couple level. Participants included in the present analysis were 23 DV partners (12 female, 11 male), and 15 DNV partners (7 female, 9 male). The mean age of the sample was 32 (SD 4.8 years, range 23-40 years). Data from two DV partners were not included in the analyses of the FAA in the emotion-regulation tasks due to movement artifacts during the alcohol condition leaving too little data for analysis. RESULTS/ANTICIPATED RESULTS: The expected beverage by couple type interaction did not reach significance [F (1, 36) = 3.93, p = .055], but the between-subjects effects of couple type revealed a significant difference [F (1, 36) = 4.425, p = .042]. Contrary to our hypothesis, however, these results suggest that under conditions of alcohol, DV partners evidenced significantly greater relative right frontal alpha power asymmetry whereas DNV partners evidenced greater relative left frontal alpha power asymmetry. Although there was no significant between-subjects effect, there was a nearly significant interaction between beverage type and emotion regulation condition [F = (1, 36) = 4.032, p = .052] and a significant main effect of emotion regulation condition [F (1, 36) = 7.579, p = .009]. It appears that asking the participants to “not react” to their partners’ evocative stimuli caused significantly greater right frontal alpha asymmetry. Because intimate partner violence is best understood in the context of conflict between two partners, we also examined partner-reported experiences of anger as predictors of DV participant’s FAA. The model as a whole predicted 67.4% of the variance in DV partner FAA, R squared change =.674, F Change (5, 15) = 6.21, p = .003. Three anger experience scales were statistically significant. The partner Anger Control-Out (B = -1.23, p =.001) scale recorded a higher standardized beta value and accounted for 40% of the variance in this model. Anger Control-In (B = .63, p = .022) accounted for 14% of the variance in the model, and Anger Expression-Out scale (B = .57, p = .024) accounted for 13.7% of the variance in the model. DISCUSSION/SIGNIFICANCE OF IMPACT: The current study is the first pharmacological study of the effects of alcohol on frontal alpha asymmetry in distressed violent and distressed nonviolent partners. Contrary to our hypothesis, under acute alcohol intoxication during the baseline condition, DV partners exhibited significantly greater relative right FAA compared to DNV partners who exhibited significantly greater relative left FAA. Because intimate partner violence is best understood in the context of couple conflict, we examined the ability of partners’ anger experiences to predict DV and DNV partners’ FAA, and a very interesting pattern emerged among our DV participants and their partners. The anger experiences of our DV participants’ partners accounted for 67% of the variance in the FAA of our DV participants when they were intoxicated and viewing evocative stimuli.

OBJECTIVES/GOALS: Globally, diabetes affects 537 million people and 15-25% will develop a foot ulcer in their lifetime. Diabetic foot ulcers (DFU) tend to be chronic and non-healing due to the poor wound healing environment, leading to infection or amputation. Our study aims to develop a method to predict and prevent DFU formation. METHODS/STUDY POPULATION: Our preliminary plan is to develop a method to detect high plantar pressures, coupled with the ability to automatically adjust an orthotic device to offload excess pressure. Our current aim is to create a “smart orthotic” which will link with foot mapping technology to automatically offload high pressure areas, reducing the need for a separate clinic visit for orthotic adjustment. We aim to prove that our device will normalize plantar pressure distribution, which will prevent callus and subsequent DFU formation. The current target population includes those with diagnosed diabetes and are ambulatory. RESULTS/ANTICIPATED RESULTS: With our technology, we anticipate normalization of plantar pressure distribution in a more frequent fashion than is currently done. Because annual orthotic fittings, which is current standard of care, do not provide regular enough adjustments to match the rate of diabetic foot structural changes and peak plantar pressure redistribution, our device will address two gaps in management. One, patients will receive near-instantaneous changes in plantar pressure offloading, allowing for near continuous orthotic customization. Secondly, our device would reduce the clinical appointment burden, which would be especially important for patients with multiple medical comorbidities or experience other barriers to accessing healthcare. DISCUSSION/SIGNIFICANCE: While DFUs are commonplace and their complications are well recognized, there still exists a gap in ulcer prevention. Our proposed solution will redistribute pathologic plantar pressures, allow for more frequent monitoring, automatic therapy, and aid in the management of high ulcer risk patients.

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.

ABSTRACT IMPACT: Through its interdisciplinary, tailored approach, the FLOW program could change the way that we approach promoting healthy lifestyle changes in the primary care field. OBJECTIVES/GOALS: The goal of this project is to assess patient outcomes associated with the implementation of the Fitness, Lifestyle, and Optimal Wellness (FLOW) Program. The ultimate aim of this program is two-fold: increasing patient-reported wellness and improving objective health measurements. METHODS/STUDY POPULATION: The FLOW program consists of a multidisciplinary team of sports medicine physicians, nutritionists, fitness trainers, and clinical psychologists. Patients who choose to participate in the program undergo a comprehensive physician-guided assessment, including lifestyle and metabolic evaluation, biomarker profile, and body composition analysis. Based on the patient’s goals and results of evaluation, he/she is then connected with other members of the FLOW team to develop a comprehensive plan and offer resources for potential improvements in physical activity, nutrition, and/or behavior. The patient will undergo follow-up assessments and questionnaires at three and six months to track their objective measurements and reported progress. RESULTS/ANTICIPATED RESULTS: The anticipated results of the FLOW program are an overall improvement in patient health and wellbeing. More specifically, we anticipate seeing increased levels of exercise from initial reported levels, as well as better nutrition habits. We expect to see improvements in follow-up body composition assessments, with gains in fat-free mass and decreased body fat, in addition to patient-reported improvements in behavioral health as measured by PHQ-9, GAD-2, and the Perceived Stress Scale. We will also assess reported sleep health with the hopes to see improvement in follow-up assessments. DISCUSSION/SIGNIFICANCE OF FINDINGS: The FLOW program is designed to address health inequities that disproportionately affect the Deep South. Through this program, we propose a new role of the primary care team in promoting healthy lifestyle habits and disease prevention through exercise, nutrition, and behavioral health services.

Regulatory Science

OBJECTIVES/GOALS: The Monte Carlo dose calculation method is often considered the “gold standard” for patient dose calculations and can be as radiation dose measurements. Our study aims to develop a true Monte Carlo model that can be implemented in our clinic as part of our routine patient-specific quality assurance. METHODS/STUDY POPULATION: We have configured and validated a model of one of our linear accelerators used for radiation therapy treatments using the EGSnrc Monte Carlo simulation software. Measured dosimetric data was obtained from the linear accelerator and was used as the standard to compare the doses calculated with our model in EGSnrc. We will compare dose calculations between commercial treatment planning systems, the EGSnrc Monte Carlo model, and patient-specific measurements. We will implement the Monte Carlo model in our clinic for routine second-checks of patient plans, and to recalculate plans delivered to patients using machine log files. RESULTS/ANTICIPATED RESULTS: Our Monte Carlo model is within 1% agreement with our measured dosimetric data, and is an accurate representation of our linear accelerators used for patient treatments. With this high level of accuracy, we have begun simulating more complex patient treatment geometries, and expect the level of accuracy to be within 1% of measured data. We believe the Monte Carlo calculation based on machine log files will correlate with patient-specific QA analysis and results. The Monte Carlo model will be a useful tool in improving our patient-specific quality assurance protocol and can be utilized in further research. DISCUSSION/SIGNIFICANCE OF IMPACT: This work can be implemented directly in clinical practice to ensure patient doses are calculated as accurately as possible. These methods can be used by clinics who do not have access to more advanced dose calculation software, ensuring accuracy for all patients undergoing radiotherapy treatments.

OBJECTIVES/GOALS: Compare metabolic health of type 2 diabetics on GLP-1 to those on traditional therapy METHODS/STUDY POPULATION: Outcomes of interest of this study include analyzing GLP-1 agonists on overall metabolic health, focusing primarily on weight loss and ability to wane off insulin without rebounding metabolic health. The data will be collected in a retrospective chart review from medical records of type II diabetics from Children’s of Alabama and will follow patients over two years. The charts have been narrowed to those patients prescribed GLP-1 agonists who have been on the medication for at least one year with consistent visits to the endocrinology clinic.The following data will be collected from the charts:race/ethnicity, date of visit, BMI/weight, A1C, insulin therapy, lipids, LFTs (AST/ALT), and insurance coverage RESULTS/ANTICIPATED RESULTS: With these results, we hope to study the metabolic health effects of GLP-1 agonists on type II diabetes in the pediatric population. It is known that obesity is a risk factor for type II diabetes, and that GLP-1 agonists aid in weight-loss in adults. Further research is needed to see the real world health effects, and with these results we hope to assess if GLP-1 agonist have an affect on metabolic health within the pediatric population by collecting data on values aforementioned. We also hope to compare and contrast the different GLP-1 agonists being used based on adherence, insurance coverage, adverse effects, and patient preference. Currently, only Liraglutide and Exetanide are approved for pediatric type II diabetics. DISCUSSION/SIGNIFICANCE: Insulin use can lead to weight gain; metformin does not aidin weight reductions. If GLP-1 agonists aid in weight loss, it could potentially help slow complications of diabetes in the pediatric population. B-cell function in children declines more rapidly; and, as a result, insulin resistance occurs more rapidly.

ABSTRACT IMPACT: Alterations in mitochondrial metabolism affect any tissue, especially those with the highest demand for energy. As the symptoms and clinical manifestations are heterogenous, disease diagnosis is challenging. The implementation of genetic-first approach in the diagnosis of mitochondrial diseases will expedite confirmation, treatment, management, and counseling of affected Puerto Rican individuals. OBJECTIVES/GOALS: Mitochondrial diseases are rare, and diagnosis is complex due to the heterogeneity of clinical manifestations. We aim to develop and implement a testing algorithm using a genetics-first approach, facilitating the identification of variants that contribute to mitochondrial disease’s etiology and influence onset and progression in Puerto Ricans. METHODS/STUDY POPULATION: This is a cross-sectional study for characterizing clinical laboratory results from profiles used to evaluate metabolic diseases in individuals with suspected mitochondrial disorders from 2018 to 2021. A subset of 25 individuals from biochemical profile will be recruited to analyze their medical and family history, metabolic biomarkers in blood and urine, hearing test, imaging and chromosomal microarray. The implementation of a genetic testing algorithm using whole exome and mitochondrial DNA sequencing will be performed in a subset of 11 randomized individuals. Descriptive analysis will be reported, including a catalog of all variants. Multivariate analysis will be performed to estimate the statistical association between variants and phenotypes reported and adjusting for potential confounders. RESULTS/ANTICIPATED RESULTS: The biochemical profile of pediatric Puerto Rican individuals suspected of having mitochondrial diseases will be altered and can be used to differentiate among other metabolic causes. We expect to find altered levels of lactate, pyruvate and carnitines in serum, as well as altered organic acids in urine. The implementation of a testing algorithm using both, mitochondrial DNA and whole exome sequencing as first approach will be enabling the identification of disease-causing variants, thus enhancing and confirming the diagnosis of mitochondrial disease in Puerto Ricans. We will be able to identify rare/novel variants specific to our Hispanic population, for both nuclear and mitochondrial DNA. DISCUSSION/SIGNIFICANCE OF FINDINGS: This study will help to characterize the metabolic profile of pediatric Puerto Ricans. No previous study has been reported that describes testing algorithms for genetic diagnosis of mitochondrial disease in our population. Variants found will contribute to a deep understanding of the genetic contribution to phenotypes and disease susceptibility.

OBJECTIVES/GOALS: Our purpose is to promote traffic toward the NJ ACTS Regulatory Cores recently launched website and increase investigator engagement through marketing strategies on LinkedIn. Landscaping to characterize the profiles of researchers on LinkedIn was also completed to estimate the feasibility of engaging with a target population on LinkedIn. METHODS/STUDY POPULATION: Insight gathering was performed to analyze what percentage of researchers possessed a LinkedIn profile and actively used their accounts. A sample population consisting of 284 NJ ACTS members were analyzed to summarize the type of researchers on LinkedIn, and their likelihood of responding to LinkedIn marketing campaigns. Efforts to launch a company LinkedIn page and collect followers were completed. Different methods of promotion were evaluated, including direct vs. mass email outreach to over 600+ researchers at Rutgers. Effectiveness of our platform was measured by comparing/overlaying Regulatory website traffic with LinkedIn traffic, as well as tracking the metrics of LinkedIn posts. RESULTS/ANTICIPATED RESULTS: Among 284 NJ ACTS members, 76% (n=215) possess a LinkedIn profile, but only 21% (n=59) are actively interacting with material on LinkedIn, such as creating, commenting, or sharing posts. Among the NJ ACTS LinkedIn users, 27% of individuals (n=57/215) responded to a direct outreach. Retention of the created organizational page was strong, as most users who visited the Regulatory Core page were likely to become followers. Massive email outreach to 600+ researchers within RBHS did not yield a strong LinkedIn following, however it did result in strong signals of website traffic during the days after the promotion was sent. Engagement with posts on LinkedIn can also be amplified and messaging proliferated when colleagues reshare Regulatory posts on their personal feeds. DISCUSSION/SIGNIFICANCE: 3/4 of academic researchers are likely to be on LinkedIn but may not be active users of the platform. The most effective outreach is through direct messaging as opposed to broader, less individualized tactics (including mass email outreach). Evidence suggests potential to utilize LinkedIn to proactively engage in regulatory-related activities.