Children with congenital heart disease (CHD) can face neurodevelopmental, psychological, and behavioural difficulties beginning in infancy and continuing through adulthood. Despite overall improvements in medical care and a growing focus on neurodevelopmental screening and evaluation in recent years, neurodevelopmental disabilities, delays, and deficits remain a concern. The Cardiac Neurodevelopmental Outcome Collaborative was founded in 2016 with the goal of improving neurodevelopmental outcomes for individuals with CHD and pediatric heart disease. This paper describes the establishment of a centralised clinical data registry to standardize data collection across member institutions of the Cardiac Neurodevelopmental Outcome Collaborative. The goal of this registry is to foster collaboration for large, multi-centre research and quality improvement initiatives that will benefit individuals and families with CHD and improve their quality of life. We describe the components of the registry, initial research projects proposed using data from the registry, and lessons learned in the development of the registry.

OBJECTIVES/GOALS: Our overall goal is to identify the processes used by the human visual system to encode visual stimuli into perceptual representations. In this project, our objective is (i) to collect a dataset of human neural activity in response to 1000 naturalistic color images and (ii) to determine how image parameters drive different parts of the human brain. METHODS/STUDY POPULATION: We recorded iEEG data in 4 human subjects who had been implanted for epilepsy monitoring. Each subject was presented 10 sets of 100 naturalistic stimuli, taken from the Natural Scenes Dataset (Allen et al., 2021), on a screen for 1 second each with 1 second rest intervals between stimuli. The subjects were instructed to fixate on a red dot at the center of the screen and were prompted to recall whether they had seen 3 additional test stimuli at the end of each set to encourage attentiveness. We calculated significant neural responses at each electrode by comparing evoked potentials and high frequency power changes during each stimulus vs. rest. Electrodes with significant responses were then mapped to anatomic locations in each subjects brain and then collectively to a standard brain. RESULTS/ANTICIPATED RESULTS: The natural image set elicited significant evoked potentials and high frequency responses at electrodes in each subject. Response latencies, from 80 to 300 ms after stimulus onset, portrayed the evolution of visual processing along the visual pathways, through key sites such as the early visual cortex, ventral temporal cortex, intraparietal sulcus, and frontal eye field. These responses differed significantly from those elicited by simple patterns, which drove early visual cortex but less so in later regions. DISCUSSION/SIGNIFICANCE: These data show that the human brain responds differently to more complex images. Determining the human brains response to naturalistic images is essential for encoding models that describe the processing in the human visual system. These models may further future efforts for electrical neurostimulation therapies such as for restoring vision.

In April 2019, the U.S. Fish and Wildlife Service (USFWS) released its recovery plan for the jaguar Panthera onca after several decades of discussion, litigation and controversy about the status of the species in the USA. The USFWS estimated that potential habitat, south of the Interstate-10 highway in Arizona and New Mexico, had a carrying capacity of c. six jaguars, and so focused its recovery programme on areas south of the USA–Mexico border. Here we present a systematic review of the modelling and assessment efforts over the last 25 years, with a focus on areas north of Interstate-10 in Arizona and New Mexico, outside the recovery unit considered by the USFWS. Despite differences in data inputs, methods, and analytical extent, the nine previous studies found support for potential suitable jaguar habitat in the central mountain ranges of Arizona and New Mexico. Applying slightly modified versions of the USFWS model and recalculating an Arizona-focused model over both states provided additional confirmation. Extending the area of consideration also substantially raised the carrying capacity of habitats in Arizona and New Mexico, from six to 90 or 151 adult jaguars, using the modified USFWS models. This review demonstrates the crucial ways in which choosing the extent of analysis influences the conclusions of a conservation plan. More importantly, it opens a new opportunity for jaguar conservation in North America that could help address threats from habitat losses, climate change and border infrastructure.

Academic Medical Centers strive to create multidisciplinary research teams to produce impactful science. However, few faculty researchers receive training in “team science,” a well-established concept in business research and practice. Responding to demand for assistance developing effective research teams, the Collaboration and Team Science Program of the Clinical and Translational Science Institute (CTSI) at Wake Forest School of Medicine (WFSM) partnered with faculty from the Wake Forest University (WFU) School of Business with expertise in leadership, management, and team building. We initiated a needs assessment, including a written survey from a diverse set of 42 research scientists as well as semi-structured interviews with 8 researchers. In response to identified needs, we developed training sessions and consultations to teach teams to implement two tools known to enhance team dynamics: (1) Team charter, a document that defines the team’s purpose, goals, roles, and strategies; and (2) Responsible, Accountable, Consulted, Informed (RACI) matrix, a table or spreadsheet that clarifies tasks and accountability. Since 2018, 10 teams and over 100 individuals have attended training sessions and 6 teams received personalized team consults. We describe these tools, present a formal analysis of quantitative results, and highlight the next steps being taken in response to these findings.

The perinatal period is a vulnerable time for the development of psychopathology, particularly mood and anxiety disorders. In the study of maternal anxiety, important questions remain regarding the association between maternal anxiety symptoms and subsequent child outcomes. This study examined the association between depressive and anxiety symptoms, namely social anxiety, panic, and agoraphobia disorder symptoms during the perinatal period and maternal perception of child behavior, specifically different facets of development and temperament. Participants (N = 104) were recruited during pregnancy from a community sample. Participants completed clinician-administered and self-report measures of depressive and anxiety symptoms during the third trimester of pregnancy and at 16 months postpartum; child behavior and temperament outcomes were assessed at 16 months postpartum. Child development areas included gross and fine motor skills, language and problem-solving abilities, and personal/social skills. Child temperament domains included surgency, negative affectivity, and effortful control. Hierarchical multiple regression analyses demonstrated that elevated prenatal social anxiety symptoms significantly predicted more negative maternal report of child behavior across most measured domains. Elevated prenatal social anxiety and panic symptoms predicted more negative maternal report of child effortful control. Depressive and agoraphobia symptoms were not significant predictors of child outcomes. Elevated anxiety symptoms appear to have a distinct association with maternal report of child development and temperament. Considering the relative influence of anxiety symptoms, particularly social anxiety, on maternal report of child behavior and temperament can help to identify potential difficulties early on in mother–child interactions as well as inform interventions for women and their families.

A primary barrier to translation of clinical research discoveries into care delivery and population health is the lack of sustainable infrastructure bringing researchers, policymakers, practitioners, and communities together to reduce silos in knowledge and action. As National Institutes of Healthʼs (NIH) mechanism to advance translational research, Clinical and Translational Science Award (CTSA) awardees are uniquely positioned to bridge this gap. Delivering on this promise requires sustained collaboration and alignment between research institutions and public health and healthcare programs and services. We describe the collaboration of seven CTSA hubs with city, county, and state healthcare and public health organizations striving to realize this vision together. Partnership representatives convened monthly to identify key components, common and unique themes, and barriers in academic–public collaborations. All partnerships aligned the activities of the CTSA programs with the needs of the city/county/state partners, by sharing resources, responding to real-time policy questions and training needs, promoting best practices, and advancing community-engaged research, and dissemination and implementation science to narrow the knowledge-to-practice gap. Barriers included competing priorities, differing timelines, bureaucratic hurdles, and unstable funding. Academic–public health/health system partnerships represent a unique and underutilized model with potential to enhance community and population health.

Species distribution models (SDMs) are statistical tools used to develop continuous predictions of species occurrence. ‘Integrated SDMs’ (ISDMs) are an elaboration of this approach with potential advantages that allow for the dual use of opportunistically collected presence-only data and site-occupancy data from planned surveys. These models also account for survey bias and imperfect detection through the use of a hierarchical modelling framework that separately estimates the species–environment response and detection process. This is particularly helpful for conservation applications and predictions for rare species, where data are often limited and prediction errors may have significant management consequences. Despite this potential importance, ISDMs remain largely untested under a variety of scenarios. We performed an exploration of key modelling decisions and assumptions on an ISDM using the endangered Baird’s tapir (Tapirus bairdii) as a test species. We found that site area had the strongest effect on the magnitude of population estimates and underlying intensity surface and was driven by estimates of model intercepts. Selecting a site area that accounted for the individual movements of the species within an average home range led to population estimates that coincided with expert estimates. ISDMs that do not account for the individual movements of species will likely lead to less accurate estimates of species intensity (number of individuals per unit area) and thus overall population estimates. This bias could be severe and highly detrimental to conservation actions if uninformed ISDMs are used to estimate global populations of threatened and data-deficient species, particularly those that lack natural history and movement information. However, the ISDM was consistently the most accurate model compared to other approaches, which demonstrates the importance of this new modelling framework and the ability to combine opportunistic data with systematic survey data. Thus, we recommend researchers use ISDMs with conservative movement information when estimating population sizes of rare and data-deficient species. ISDMs could be improved by using a similar parameterization to spatial capture–recapture models that explicitly incorporate animal movement as a model parameter, which would further remove the need for spatial subsampling prior to implementation.

OBJECTIVES/SPECIFIC AIMS: Negative symptoms of schizophrenia, including motivational deficits, social withdrawal, poverty of speech, decreased emotional reactivity, and psychomotor retardation, have been shown to be most predictive of functional impairment and poor outcome in patients with schizophrenia. Furthermore, these symptoms tend not to be responsive to antipsychotic medications. Inflammation could be one mechanism underlying these difficult to treat symptoms. METHODS/STUDY POPULATION: Three cohorts of patients, reflecting different phases of disease, were studied. One cohort was comprised of a sample of patients with deficit schizophrenia (characterized by primary and enduring negative symptoms; n=17), nondeficit patients (n=39), and healthy controls (n=28). ANOVA and multivariate general linear models were used to compare groups, and linear regression models were used to examine relationships between inflammatory cytokines and negative symptoms. The second cohort was comprised of 80 individuals at clinical high risk for psychosis from the North American Prodromal Longitudinal Study. Linear regression models examined the relationship between baseline inflammatory markers and subsequent negative symptoms at follow-up visits up to 2 years. The third cohort consisted of patients with treatment-resistant schizophrenia (TRS) on clozapine (n=10). Correlations were performed to examine relationships between inflammatory markers and negative symptoms. In a subgroup of patients from this third sample, resting state functional connectivity analyses were performed on fMRI data to explore relationships between inflammatory markers and connectivity in brain reward circuitry. RESULTS/ANTICIPATED RESULTS: In a sample of patients with the deficit syndrome of schizophrenia (n=17), a subtype of the disorder characterized by primary and enduring negative Symptoms, tumor necrosis factor (TNF) was significantly increased relative to nondeficit patients (n=39) and healthy controls (n=28; F2,57=3.51, p=0.036), and predicted total negative symptoms (β=0.31, p=0.012), alogia (β=0.30, p=0.024), and blunted affect (β=0.31, p=0.018) items of the Positive and Negative Symptom Scale in linear regression models while controlling for antipsychotics. In another sample of individuals at clinical-high risk for psychosis (n=80), baseline concentrations of TNF significantly predicted negative symptoms, including anhedonia, apathy, and loss of interest in linear regression models, at the 6-month (β=0.25, p=0.011) and 12-month follow-up (β=0.39, p=0.001). Interleukin (IL)-1 receptor antagonist also predicted these symptoms at the 6-month follow-up (β=0.21, p=0.037). In a third sample (n=10) of patients with TRS treated with clozapine, IL-1β was correlated with passive/apathetic social withdrawal (r=0.657, p=0.039) and disturbance of volition (r=0.686, p=0.029) items of the Positive and Negative Symptom Scale and the global avolition-apathy scores of the Scale for the Assessment of Negative Symptoms (r=0.751, p=0.012). Finally, in a small subsample (n=5) of patients from this TRS cohort for whom we collected fMRI data, we found resting-state functional connectivity from a right nucleus accumbens seed to a cluster in medial prefrontal cortex. We found relationships between higher inflammation and decreased connectivity for TNF (r=−0.64) and CRP (r=−0.89). DISCUSSION/SIGNIFICANCE OF IMPACT: Taken together, these preliminary data show the predicted relationship between inflammatory markers and negative symptoms and demonstrate the reproducibility of TNF and other monocytic-derived cytokines as reliably elevated in schizophrenia and associated with negative symptoms across samples of patients with schizophrenia and individuals at high risk for psychosis. Cytokines may exert their effects via their impact on brain reward circuitry, and could represent novel treatment targets for motivational deficits and negative symptoms of schizophrenia.

Ralph Waldo Emerson is known to have said, “the greatest wonder is that we can see these trees and not wonder more.” As industrial and organizational (I-O) psychologists, we often encounter this very dilemma when we examine how numerous professions rise and fall in relevance. More recently, however, we have encountered this dilemma from an existential perspective as we strive to understand the evolution of our own profession and the situational characteristics making change inevitable. We have fallen into a trap—we, too, now look at all of our practices, aiming to reconfigure the makeup of our profession while losing sight of the macrotrends affecting more than just our evolved existence. Rather than focusing on the smaller issue first, we need to start by examining the broader issues affecting it.

Good education requires student experiences that deliver lessons about practice as well as theory and that encourage students to work for the public good—especially in the operation of democratic institutions (Dewey 1923; Dewy 1938). We report on an evaluation of the pedagogical value of a research project involving 23 colleges and universities across the country. Faculty trained and supervised students who observed polling places in the 2016 General Election. Our findings indicate that this was a valuable learning experience in both the short and long terms. Students found their experiences to be valuable and reported learning generally and specifically related to course material. Postelection, they also felt more knowledgeable about election science topics, voting behavior, and research methods. Students reported interest in participating in similar research in the future, would recommend other students to do so, and expressed interest in more learning and research about the topics central to their experience. Our results suggest that participants appreciated the importance of elections and their study. Collectively, the participating students are engaged and efficacious—essential qualities of citizens in a democracy.