MARCKSlevelswouldbeincreasedinBALcelllysatesfromhorseswith EAS,andthatinhibitionofMARCKSinzymosan-stimulatedBALcells (ex vivo) would diminish respiratory burst. METHODS/STUDY POPULATION: Lysates were prepared from BAL cells isolated from horseswithno,mild/moderateandsevereEAS.RelativeMARCKSpro- tein levels were determined using equine specific MARCKS ELISA (MyBioSource). Cultured BAL cells were pretreated with a MARCKS inhibitor peptide (MANS), control peptide (RNS) or vehicle control and stimulated with zymosan for 5 hours. Reactive oxygenspe- cies levels were determined by luminescence to evaluate respiratory burst. Data were analyzed by One-way ANOVA (p<0.05). RESULTS/ANTICIPATED RESULTS: We determined that normal- ized MARCKS protein expression is significantly increased in BAL cell lysates from horses with mild/moderate or severe EAS, compared to horses with normal BAL cytology. Preliminary findings also suggest that MANS treatment of zymosan-stimulated equine BAL cells ex vivo attenuateslevelsrespiratoryburst.DISCUSSION/SIGNIFICANCEOF IMPACT: These findings point to a possible role for MARCKS protein in the pathophysiology of EAS and support MARCKS inhibition as a potential therapeutic strategy. 4377 Missed Opportunities to Prevent Homicide: An Analysis of the National Violent Death Reporting System Justin Cirone1, Jennifer Cone1, Brian Williams1, David Hampton1, Priya Prakash1, and Tanya Zakrison1 1University of Chicago OBJECTIVES/GOALS: The goal of this study is to better understand the homicide victim population who were institutionalized within 30 days prior to their death. Improved knowledge of this population can potentially prevent these future homicides. METHODS/STUDY POPULATION: A retrospective analysis of the 36 states included in the 2003-2017 National Violent Death Reporting System was per- formed. Demographics of recently institutionalized homicide vic- tims (RIHV) in the last 30 days were compared to homicide victims who were not recently institutionalized. Circumstances of the homicide, such as suspected gang involvement, were also com- pared. Parametric and non-parametric statistical analyses were per- formed. Significance was set at p<0.05. RESULTS/ANTICIPATED RESULTS: There were 81,229 homicides with 992 (1.2%) RIHV. The majority of RIHV were Black (49.6%) and older than victims who were not recently institutionalized (37.2 vs. 34.8, p<0.001). RIHV had a high school degree or higher in 54.8% of cases and the primary homicide weapon was a firearm in 67% of the deaths. They were more likely to be homeless (3.1% vs. 1.5%), have a mental health diagnosis (9.2% vs. 2.3%), abuse alcohol (6.1% vs. 2.2%), or abuse other substances (15.2% vs. 5.8%) [all p <0.001]. These victims were most commonly institutionalized in a correctional facility or a hospital compared to other facilities such as nursing homes. Homicide circumstances for RIHV were more likely to involve abuse/neglect (4.3% vs. 2.2%, p<0.001), gang violence (7.6% vs. 5.6%, p = 0.002), or a hate crime (1.0% vs. 0.1%. p<0.001). DISCUSSION/SIGNIFICANCE OF IMPACT: Contact with an institution such as a hospital or prison provides high-risk patients the opportunity to potentially participate in violence intervention programs. These institutions should seek to identify and intervene on this population to reduce the risk of violent homicides. 4141 Molecular Signatures of Cocaine Toxicity in Postmortem Human Brain and Neurons Emily Frances Mendez1, Laura Stertz1, Gabriel Fries1, Ruifeng Hu1, Thomas Meyer1, Zhongming Zhao1, and Consuelo Walss-Bass1 1The University of Texas Health Science Center at Houston OBJECTIVES/GOALS: The goal of this project is to identify new therapeutic targets and biomarkers to treat or prevent cocaine tox- icity by investigating proteomic, transcriptomic and epigenetic sig- natures of cocaine exposure in human subjects. METHODS/ STUDY POPULATION: Cocaine is a highly addictive neurotoxic substance, and it is estimated that 1.9 million Americans are current users of cocaine. To study the molecular effects of cocaine, we gen- erated preliminary proteomics and next-generation RNA sequencing (RNAseq) data from human postmortem dorsolateral prefrontal cortex (Broadmann area 9 or BA9) of 12 cocaine-exposed subjects and 17 controls. Future directions for this project include RNAseq and DNA methylation analysis of neuronal nuclei sorted from human postmortem BA9 and a human induced pluripotent stem cell-derived neuron (hiPSN) model of cocaine exposure from the same postmortem subjects from whom we have brain samples. RESULTS/ANTICIPATED RESULTS: We found alterations in neu- ronal synaptic protein levels and gene expression, including the sero- tonin transporter SLC6A4, and synaptic proteins SNAP25, SYN2, SYNGR3. Pathway analysis of our results revealed alterations in spe- cific pathways involved with neuronal function including voltage- gated calcium channels, and GABA receptor signaling. In the future, we expect to see an enhancement in neuron-specific gene expression signatures in our sorted neuronal nuclei and our hiPSN model of cocaine exposure. The hiPSN model will help elucidate which effects are due to acute versus chronic exposure of cocaine. DISCUSSION/ SIGNIFICANCE OF IMPACT: Neuronal signatures found with this analysis can help us understand mechanisms of cognitive decline in long-term cocaine users as well as the acute effects on the brain of cocaine taken in overdose. With this work and future proposed stud- ies, we can discover novel clinical biomarkers for cocaine neurotox- icity in patients with cocaine use disorder and determine readouts for future therapeutic development on cocaine addiction and overdose. 4488 Neural Network of the Cognitive Model of Reading† Joseph Posner1, Vivian Dickens, Andrew DeMarco, Sarah Snider, Peter Turkeltaub, and Rhonda Friedman 1Georgetown - Howard Universities OBJECTIVES/GOALS: A particularly debilitating consequence of stroke is alexia, an acquired impairment in reading. Cognitive mod- els aim to characterize how information is processed based on behav- ioral data. If we can concurrently characterize how neural networks process that information, we can enhance the models to reflect the neuronal interactions that drive them. METHODS/STUDY POPULATION: There will be 10 unimpaired adult readers. Two functional localizer tasks, deigned to consistently activate robust lan- guage areas, identify the regions of interest that process the cognitive reading functions (orthography, phonology, semantics). Another task, designed for this experiment, analyses the reading-related 140 JCTS 2020 Abstract Supplement https://www.cambridge.org/core/terms. https://doi.org/10.1017/cts.2020.415 Downloaded from https://www.cambridge.org/core. Carnegie Mellon University, on 06 Apr 2021 at 01:18:22, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms https://doi.org/10.1017/cts.2020.415 https://www.cambridge.org/core functional-connectivity between these areas by presenting words classified along the attributes of frequency, concreteness, and regu- larity, which utilize specific cognitive routes, and a visual control. Connectivity is analyzed during word reading overall vs. a control condition to determine overall reading-related connectivity, and while reading words that have high vs. low attribute values, to deter- mine if cognitive processing routes bias the neural reading network connectivity. RESULTS/ANTICIPATED RESULTS: The localizer analysis is expected to result in the activation of canonical reading areas. The degree of functional connectivity observed between these regions is expected to depend on the degree to which each cognitive route is utilized to read a given word. After orthographic, phonologic, and semantic areas have been identified, the connectivity analysis should show that there is high correlation between all three types of areas during reading compared to the control condition. Then the frequency, regularity, and concreteness of the words being read should alter the reliance on the pathways between these area types. This would support the hypothesized pattern of connectivity as pre- dicted by the cognitive reading routes. Otherwise, it will show how the neural reading network differs from the cognitive model. DISCUSSION/SIGNIFICANCE OF IMPACT: The results will deter- mine the relationship between the cognitive reading model and the neural reading network. Cognitive models show what processes occur in the brain, but neural networks show how these processes occur. By relating these components, we obtain a more complete view of reading in the brain, which can inform future alexia treatments. 4341 Neuroclinical fingerprints of risk for psychosis: Profiles of neurophysiology, symptom severity, and cognitive function Keisha Novak1, Sam Buck1, Roman Kotov2, and Dan Foti1 1Purdue University; 2Stony Brook University OBJECTIVES/GOALS: The study aims to utilize event-related potentials (ERPs) coupled with observable reports of symptoms to comprehensively understand neurological and symptomatic profile of individuals at risk for developing psychosis. The study is a short- term longitudinal design which allows for examination of course as well as structure of illness. METHODS/STUDY POPULATION: This study uses a combination of well-validated ERPs (P300, N400, ERN) and symptom data to predict variation in symptoms over time. We parse heterogeneity within a high-risk group to create innovative profiles and predict variation in course of symptoms. Data collection is ongoing (n = 35; target N = 100). Methods include a battery of ERP tasks tracking neural processes associated with attention, language processing, and executive function (P300, N400, ERN), along with assessment of symptom type and severity. Analyses include how ERPs correlate with severity of risk and symp- tom dimensions (positive, negative, disorganized). We examine whether individual versus global ERP aberrations (P300, N400, ERN) predict individual versus global symptom domain severity (positive, negative, disorganized), or vice versa. RESULTS/ ANTICIPATED RESULTS: Symptom domain scores were elevated compared to general population on positive (M = 1.65, SD = .36), negative (M = 1.9 SD = .42), and depressive (M = 1.94, SD = .40) domains. Small to medium effect sizes emerged for P300 profile (r’s = −.001 to −.41) and ERN profile (r’s = −.03 to −.37), though small effect sizes for N400 profile (r’s = −.06 to .29). Analyses were run to determine the degree to which profiles of risk were similar: P300/ERN (r = −.09), ERN/N400 (r = −.39), and N400/P3 (r = −.20). Additional analyses suggest potential mediating effects of cognition on neural activity and symptoms. DISCUSSION/ SIGNIFICANCE OF IMPACT: We use a combination of well-vali- dated ERPs (i.e. P300, N400, ERN) with behavioral and symptom data to predict variation in symptoms over time. A “fingerprint” physiologic aberration may be exhibited within high-risk individuals and can be used as biomarkers to identify those at risk even before onset of observable symptoms. 4532 Pancreatic Cyst Risk Stratification for Early Detection of Pancreatic Cancer Using Quantitative Radiomics and Activity-Based Biomarkers Sophia Hernandez1, Andre Luiz Lourenco, Evan Calabrese, Tyler York, Alexa Glencer, Spencer Behr, Zhen Jane Wang, Eugene Koay, Charles Craik, and Kimberly Kirkwood 1University Of California, San Francisco OBJECTIVES/GOALS: Pancreatic cysts are comprised ofboth precan- cerous mucinous lesions and non-mucinous lesions with minimal malignant potential. Our goal is to improve our ability to classify the type of cyst using a combination of novel radiomic features and cyst fluid proteolytic activity. METHODS/STUDY POPULATION: Preoperative pancreatic protocol CT images from 30 patients with proteolytic assay characterization, followed by surgical resection with a pathologically confirmed pancreatic cyst diagnosis between 2016- 2019will be usedinthisstudy.We will contour imagesusing thewidely available software 3D Slicer, and extract radiomic features using IBEX software. We will analyze area under the ROC curves to identify the radiomicfeatures thatbestdifferentiatemucinousfromnon-mucinous cysts,andidentifyfeaturestobecrossvalidated.Thepredictiveabilityof identified radiomic features combined with proteolytic assay will be determined by performing multiple logistic regression analysis and comparing AUROC analysis. We will determine sensitivity and speci- ficity for individual, as well as combinations of, analytes to determine the optimal classifier. RESULTS/ANTICIPATED RESULTS: We anticipate that the predictive ability, sensitivity, and specificity of uti- lizing radiomic features combined with proteolytic assay data will exceed the performance of any individual test. DISCUSSION/ SIGNIFICANCE OFIMPACT:This work isdesignedto provide a pre- dictive radiomic model that will enable us to better identify mucinous cysts that require further evaluation, and potentially prevent unneces- sary surgery inother patients. Ultimately, we would like to improve the accuracyofnoninvasive radiographicevaluation using radiomicmark- ers.CONFLICTOFINTERESTDESCRIPTION:Dr.CharlesCraikisa co-founder of Alaunus Biosciences, Inc. 4340 Piloting Implementation and Dissemination of Best Practice Guidelines Using BPMþHealth James McClay, MD, MS, FACEP, FAMIA1, and Pawan Goyal2 1University of Nebraska Medical Center - Great Plains IDeA-CTR; 2American College of Emergency Physicians OBJECTIVES/GOALS: Clinical translational studies inform clinical practice patterns through dissemination of clinical practice guidelines (CPG). In EM practices change to rapidly for timely local EHR imple- mentation. We test the OMG BPMþHealth specification for rapid deployment of best practices relevant to EM. METHODS/STUDY JCTS 2020 Abstract Supplement 141 https://www.cambridge.org/core/terms. https://doi.org/10.1017/cts.2020.415 Downloaded from https://www.cambridge.org/core. Carnegie Mellon University, on 06 Apr 2021 at 01:18:22, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms https://doi.org/10.1017/cts.2020.415 https://www.cambridge.org/core