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Abstract Background The VPS50 protein functions in synaptic and dense core vesicle acidification, and perturbations of VPS50 function produce behavioral changes in Caenorhabditis elegans. Patients with mutations in VPS50 show severe developmental delay and intellectual disability, characteristics that have been associated with autism spectrum disorders (ASDs). The mechanisms that link VPS50 mutations to ASD are unknown. Results To examine the role of VPS50 in mammalian brain function and behavior, we used the CRISPR/Cas9 system to generate knockouts of VPS50 in both cultured murine cortical neurons and living mice. In cultured neurons, KO of VPS50 did not affect the number of synaptic vesicles but did cause mislocalization of the V-ATPase V1 domain pump and impaired synaptic activity, likely as a consequence of defects in vesicle acidification and vesicle content. In mice, mosaic KO of VPS50 in the hippocampus altered synaptic transmission and plasticity and generated robust cognitive impairments. Conclusions We propose that VPS50 functions as an accessory protein to aid the recruitment of the V-ATPase V1 domain to synaptic vesicles and in that way plays a crucial role in controlling synaptic vesicle acidification. Understanding the mechanisms controlling behaviors and synaptic function in ASD-associated mutations is pivotal for the development of targeted interventions, which may open new avenues for therapeutic strategies aimed at ASD and related conditions.

Abstract Background A vital step in analyzing single-cell data is ascertaining which cell types are present in a dataset, and at what abundance. In many diseases, the proportions of varying cell types can have important implications for health and prognosis. Most approaches for cell type annotation have centered around cell typing for single-cell RNA-sequencing (scRNA-seq) and have had promising success. However, reliable methods are lacking for many other single-cell modalities such as single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq), which quantifies the extent to which genes of interest in each cell are epigenetically “open” for expression. Results To leverage the informative potential of scATAC-seq data, we developed CAMML with the integration of chromatin accessibility (CAraCAl), a bioinformatic method that performs cell typing on scATAC-seq data. CAraCAl performs cell typing by scoring each cell for its enrichment of cell type-specific gene sets. These gene sets are composed of the most upregulated or downregulated genes present in each cell type according to projected gene activity. Conclusions We found that CAraCAl does not improve performance beyond CAMML when scRNA-seq is present, but if only scATAC-seq is available, CAraCAl performs cell typing relatively successfully. As such, we also discuss best practices for cell typing and the strengths and weaknesses of various cell annotation options.

Abstract We present a novel approach for computing a variant of eigenvector centrality for multilayer networks with inter-layer constraints on node importance. Specifically, we consider a multilayer network defined by multiple edge-weighted, potentially directed, graphs over the same set of nodes with each graph representing one layer of the network and no inter-layer edges. As in the standard eigenvector centrality construction, the importance of each node in a given layer is based on the weighted sum of the importance of adjacent nodes in that same layer. Unlike standard eigenvector centrality, we assume that the adjacency relationship and the importance of adjacent nodes may be based on distinct layers. Importantly, this type of centrality constraint is only partially supported by existing frameworks for multilayer eigenvector centrality that use edges between nodes in different layers to capture inter-layer dependencies. For our model, constrained, layer-specific eigenvector centrality values are defined by a system of independent eigenvalue problems and dependent pseudo-eigenvalue problems, whose solution can be efficiently realized using an interleaved power iteration algorithm. We refer to this model, and the associated algorithm, as the Constrained Multilayer Centrality (CMLC) method. The characteristics of this approach, and of standard techniques based on inter-layer edges, are demonstrated on both a simple multilayer network and on a range of random graph models. An R package implementing the CMLC method along with example vignettes is available at https://hrfrost.host.dartmouth.edu/CMLC/ .

Abstract How cells regulate gene expression in a precise spatiotemporal manner during organismal development is a fundamental question in biology. Although the role of transcriptional condensates in gene regulation has been established, little is known about the function and regulation of these molecular assemblies in the context of animal development and physiology. Here we show that the evolutionarily conserved DEAD-box helicase DDX-23 controls cell fate in Caenorhabditis elegans by binding to and facilitating the condensation of MAB-10, the C. elegans homolog of mammalian NGFI-A-binding (NAB) protein. MAB-10 is a transcriptional cofactor that functions with the early growth response (EGR) protein LIN-29 to regulate the transcription of genes required for exiting the cell cycle, terminal differentiation, and the larval-to-adult transition. We suggest that DEAD-box helicase proteins function more generally during animal development to control the condensation of NAB proteins important in cell identity and that this mechanism is evolutionarily conserved. In mammals, such a mechanism might underlie terminal cell differentiation and when dysregulated might promote cancerous growth.

Abstract Introduction: Clinical research requires a competent workforce of clinical research professionals (CRPs) who are well-trained to perform varied and complex tasks within their roles. The Joint Task Force for Clinical Trial Competency (JTF) framework established essential domains for conducting high-quality clinical research that can guide professional development of CRPs. The Research Professionals Network (RPN) Workshops were established in 2017 to focus on developing ongoing inter-institutional, peer-led, JTF-centric continuing education for CRPs. Four institutions and their affiliates are part of the collaboration. Methods: Workshop participant survey data and other metrics were collected over four academic years. Both quantitative and qualitative analyses were performed to assess participant experience and identify relevant themes. Results: Participants demonstrated overall high satisfaction with the workshops and significantly value the interpersonal, inter-institutional collaboration made possible through the workshops. Conclusions: These inter-institutional RPN Workshops have evolved into a Community of Practice, which can be expanded into future opportunities.

Abstract Background: The knowledge, skills, and abilities needed for clinical research professionals (CRPs) are described in the Joint Task Force (JTF) for Clinical Trial Competencies Framework as a basis for leveled educational programs, training curricula, and certification. There is a paucity of literature addressing team science competencies tailored to CRPs. Gaps in training, research, and education can restrict their capability to effectively contribute to team science. Materials/Methods: The CRP Team Science team consisted of 18 members from 7 clinical and translational science awarded institutions. We employed a multi-stage, modified Delphi approach to define “Smart Skills” and leveled team science skills examples using individual and team science competencies identified by Lotrecchiano et al. Results: Overall, 59 team science Smart Skills were identified resulting in 177 skills examples across three levels: fundamental, skilled, and advanced. Two examples of the leveled skillsets for individual and team competencies are illustrated. Two vignettes were created to illustrate application for training. Discussion: This work provides a first-ever application of team science for CRPs by defining specific individual and team science competencies for each level of the CRP career life course. This work will enhance the JTF Domains 7 (Leadership and Professionalism) and 8 (Communication and Teamwork) which are often lacking in CRP training programs. The supplement provides a full set of skills and examples from this work. Conclusion: Developing team science skills for CRPs may contribute to more effective collaborations across interdisciplinary clinical research teams. These skills may also improve research outcomes and stabilize the CRP workforce.

Abstract Background: There have been a number of federal policies and guidance’s impacting diversity, equity, inclusion, and accessibility (DEI) in clinical research. While these are needed, they have not diminished the gaps related to clinical trial recruitment, research professional’s capacity for cultural competence, and clinical research professional role development. Mentoring and co-mentoring circles have traditionally been used in Medicine, but until now had not been used for workforce development of clinical research professionals (CRPs). Materials/Methods: We designed a six-session, monthly co-mentoring circle to take place at two academic medical centers to pilot an interinstitutional co-mentoring circle centered on storytelling videos of Black Voices in Clinical Research. This provided a DEI framework for discussions on role experiences, cultural competence, and role progression. Results: Seven CRPs completed the DRC pilot. The participants positively evaluated the experience and made recommendations for future iterations. Discussion: Co-mentoring circles can be useful tools to connect CRPs across complex research medical centers and provide support that may have a positive impact on role satisfaction and retention. Conclusion: This framework for developing co-mentoring circles can serve as a toolkit for future CRP co-mentoring circles within and across institutions for workforce development. The Black Voices in Clinical Research storytelling videos provide a rich foundation for future discussion on DEI issues for CRPs and collaborating with participants.

Abstract Background Over the past decades, approaches for diagnosing and treating cancer have seen significant improvement. However, the variability of patient and tumor characteristics has limited progress on methods for prognosis prediction. The development of high-throughput omics technologies now provides multiple approaches for characterizing tumors. Although a large number of published studies have focused on integration of multi-omics data and use of pathway-level models for cancer prognosis prediction, there still exists a gap of knowledge regarding the prognostic landscape across multi-omics data for multiple cancer types using both gene-level and pathway-level predictors. Methods In this study, we systematically evaluated three often available types of omics data (gene expression, copy number variation and somatic point mutation) covering both DNA-level and RNA-level features. We evaluated the landscape of predictive performance of these three omics modalities for 33 cancer types in the TCGA using a Lasso or Group Lasso-penalized Cox model and either gene or pathway level predictors. Results We constructed the prognostic landscape using three types of omics data for 33 cancer types on both the gene and pathway levels. Based on this landscape, we found that predictive performance is cancer type dependent and we also highlighted the cancer types and omics modalities that support the most accurate prognostic models. In general, models estimated on gene expression data provide the best predictive performance on either gene or pathway level and adding copy number variation or somatic point mutation data to gene expression data does not improve predictive performance, with some exceptional cohorts including low grade glioma and thyroid cancer. In general, pathway-level models have better interpretative performance, higher stability and smaller model size across multiple cancer types and omics data types relative to gene-level models. Conclusions Based on this landscape and comprehensively comparison, models estimated on gene expression data provide the best predictive performance on either gene or pathway level. Pathway-level models have better interpretative performance, higher stability and smaller model size relative to gene-level models.

Abstract Background The infant intestinal microbiome plays an important role in metabolism and immune development with impacts on lifelong health. The linkage between the taxonomic composition of the microbiome and its metabolic phenotype is undefined and complicated by redundancies in the taxon-function relationship within microbial communities. To inform a more mechanistic understanding of the relationship between the microbiome and health, we performed an integrative statistical and machine learning-based analysis of microbe taxonomic structure and metabolic function in order to characterize the taxa-function relationship in early life. Results Stool samples collected from infants enrolled in the New Hampshire Birth Cohort Study (NHBCS) at approximately 6-weeks (n = 158) and 12-months (n = 282) of age were profiled using targeted and untargeted nuclear magnetic resonance (NMR) spectroscopy as well as DNA sequencing of the V4-V5 hypervariable region from the bacterial 16S rRNA gene. There was significant inter-omic concordance based on Procrustes analysis (6 weeks: p = 0.056; 12 months: p = 0.001), however this association was no longer significant when accounting for phylogenetic relationships using generalized UniFrac distance metric (6 weeks: p = 0.376; 12 months: p = 0.069). Sparse canonical correlation analysis showed significant correlation, as well as identifying sets of microbe/metabolites driving microbiome-metabolome relatedness. Performance of machine learning models varied across different metabolites, with support vector machines (radial basis function kernel) being the consistently top ranked model. However, predictive R2 values demonstrated poor predictive performance across all models assessed (avg: − 5.06% -- 6 weeks; − 3.7% -- 12 months). Conversely, the Spearman correlation metric was higher (avg: 0.344–6 weeks; 0.265–12 months). This demonstrated that taxonomic relative abundance was not predictive of metabolite concentrations. Conclusions Our results suggest a degree of overall association between taxonomic profiles and metabolite concentrations. However, lack of predictive capacity for stool metabolic signatures reflects, in part, the possible role of functional redundancy in defining the taxa-function relationship in early life as well as the bidirectional nature of the microbiome-metabolome association. Our results provide evidence in favor of a multi-omic approach for microbiome studies, especially those focused on health outcomes.

Obesity and diabetes are strongly associated not only with fatty liver but also cognitive dysfunction. Moreover, their presence, particularly in midlife, is recognized as a risk factor for Alzheimer’s disease (AD). AD, the most common cause of dementia, is increasingly considered as a metabolic disease, although underlying pathogenic mechanisms remain unclear. The liver plays a major role in maintaining glucose and lipid homeostasis, as well as in clearing the AD neuropathogenic factor amyloid‐β (Aβ) and in metabolizing cerebrosterol, a cerebral‐derived oxysterol proposed as an AD biomarker. We hypothesized that liver impairment induced by obesity contributes to AD pathogenesis. We show that the AD triple transgenic mouse model (3xTg‐AD) fed a chow diet presents a hepatic phenotype similar to nontransgenic controls (NTg) at 15 months of age. A high‐fat diet (HFD), started at the age of 6 months and continued for 9 months, until sacrifice, induced hepatic steatosis in NTg, but not in 3xTg‐AD mice, whereas HFD did not induce changes in hepatic fatty acid oxidation, de novo lipogenesis, and gluconeogenesis. HFD‐induced obesity was associated with a reduction of insulin‐degrading enzyme, one of the main hepatic enzymes responsible for Aβ clearance. The hepatic rate of cerebrosterol glucuronidation was lower in obese 3xTg‐AD than in nonobese controls (P

Abstract Background Genomic profiling of solid human tumors by projects such as The Cancer Genome Atlas (TCGA) has provided important information regarding the somatic alterations that drive cancer progression and patient survival. Although researchers have successfully leveraged TCGA data to build prognostic models, most efforts have focused on specific cancer types and a targeted set of gene-level predictors. Less is known about the prognostic ability of pathway-level variables in a pan-cancer setting. To address these limitations, we systematically evaluated and compared the prognostic ability of somatic point mutation (SPM) and copy number variation (CNV) data, gene-level and pathway-level models for a diverse set of TCGA cancer types and predictive modeling approaches. Results We evaluated gene-level and pathway-level penalized Cox proportional hazards models using SPM and CNV data for 29 different TCGA cohorts. We measured predictive accuracy as the concordance index for predicting survival outcomes. Our comprehensive analysis suggests that the use of pathway-level predictors did not offer superior predictive power relative to gene-level models for all cancer types but had the advantages of robustness and parsimony. We identified a set of cohorts for which somatic alterations could not predict prognosis, and a unique cohort LGG, for which SPM data was more predictive than CNV data and the predictive accuracy is good for all model types. We found that the pathway-level predictors provide superior interpretative value and that there is often a serious collinearity issue for the gene-level models while pathway-level models avoided this issue. Conclusion Our comprehensive analysis suggests that when using somatic alterations data for cancer prognosis prediction, pathway-level models are more interpretable, stable and parsimonious compared to gene-level models. Pathway-level models also avoid the issue of collinearity, which can be serious for gene-level somatic alterations. The prognostic power of somatic alterations is highly variable across different cancer types and we have identified a set of cohorts for which somatic alterations could not predict prognosis. In general, CNV data predicts prognosis better than SPM data with the exception of the LGG cohort.

Abstract Background Atabecestat, a potent brain-penetrable inhibitor of BACE1 activity that reduces CSF amyloid beta (Aβ), was developed for oral treatment for Alzheimer’s disease (AD). The long-term safety and effect of atabecestat on cognitive performance in participants with predementia AD in two phase 2 studies were assessed. Methods In the placebo-controlled double-blind parent ALZ2002 study, participants aged 50 to 85 years were randomized (1:1:1) to placebo or atabecestat 10 or 50 mg once daily (later reduced to 5 and 25 mg) for 6 months. Participants entered ALZ2004, a 12-month treatment extension with placebo or atabecestat 10 or 25 mg, followed by an open-label phase. Safety, changes in CSF biomarker levels, brain volume, and effects on cognitive performance were assessed. Results Of 114 participants randomized in ALZ2002, 99 (87%) completed, 90 entered the ALZ2004 double-blind phase, and 77 progressed to the open-label phase. CSF Aβ fragments and sAPPβ were reduced dose-proportionately. Decreases in whole brain and hippocampal volumes were greater in participants with mild cognitive impairment (MCI) due to AD than in preclinical AD, but were not affected by treatment. In ALZ2004, change from baseline in RBANS trended toward worse scores for atabecestat versus placebo. Elevated liver enzyme adverse events reported in 12 participants on atabecestat resulted in dosage modification and increased frequency of safety monitoring. Treatment discontinuation normalized ALT or AST in all except one with pretreatment elevation, which remained mildly elevated. No case met ALT/AST > 3× ULN and total bilirubin > 2× ULN (Hy’s law). Conclusion Atabecestat was associated with trend toward declines in cognition, and elevation of liver enzymes. Trial registration ALZ2002: ClinicalTrials.gov , NCT02260674, registered October 9, 2014; ALZ2004: ClinicalTrials.gov , NCT02406027, registered April 1, 2015.

In 2015, we collected more than 60 000 scavenging amphipod specimens during two expeditions to the Clarion–Clipperton fracture zone (CCZ) in the Northeast (NE) Pacific and to the DISturbance and re-COLonisation (DisCOL) experimental area (DEA), a simulated mining impact disturbance proxy in the Peru Basin in the Southeast (SE) Pacific. Here, we compare biodiversity patterns of the larger specimens (>15 mm) within and between these two oceanic basins. Eight scavenging amphipod species are shared between these two areas, thus indicating connectivity. Overall diversity was lower in the DEA (Simpson index, D = 0.62), when compared to the CCZ (D=0.73), and particularly low at the disturbance site in the DEA and the site geographically closest to it. Local differences within each basin were observed too. The community compositions of the two basins differ, as evidenced by a non-metric dimensional scaling (NMDS) analysis of beta biodiversity. Finally, a single species, Abyssorchomene gerulicorbis (Schulenberger and Barnard, 1976), dominates the DEA with 60 % of all individuals.

Abstract Background Cancer prognosis prediction is valuable for patients and clinicians because it allows them to appropriately manage care. A promising direction for improving the performance and interpretation of expression-based predictive models involves the aggregation of gene-level data into biological pathways. While many studies have used pathway-level predictors for cancer survival analysis, a comprehensive comparison of pathway-level and gene-level prognostic models has not been performed. To address this gap, we characterized the performance of penalized Cox proportional hazard models built using either pathway- or gene-level predictors for the cancers profiled in The Cancer Genome Atlas (TCGA) and pathways from the Molecular Signatures Database (MSigDB). Results When analyzing TCGA data, we found that pathway-level models are more parsimonious, more robust, more computationally efficient and easier to interpret than gene-level models with similar predictive performance. For example, both pathway-level and gene-level models have an average Cox concordance index of ~ 0.85 for the TCGA glioma cohort, however, the gene-level model has twice as many predictors on average, the predictor composition is less stable across cross-validation folds and estimation takes 40 times as long as compared to the pathway-level model. When the complex correlation structure of the data is broken by permutation, the pathway-level model has greater predictive performance while still retaining superior interpretative power, robustness, parsimony and computational efficiency relative to the gene-level models. For example, the average concordance index of the pathway-level model increases to 0.88 while the gene-level model falls to 0.56 for the TCGA glioma cohort using survival times simulated from uncorrelated gene expression data. Conclusion The results of this study show that when the correlations among gene expression values are low, pathway-level analyses can yield better predictive performance, greater interpretative power, more robust models and less computational cost relative to a gene-level model. When correlations among genes are high, a pathway-level analysis provides equivalent predictive power compared to a gene-level analysis while retaining the advantages of interpretability, robustness and computational efficiency.

This exploratory study investigated perceptions of competent vs. contentious communication in the workplace as experienced by Clinical Research Professionals (CRPs) managing or coordinating clinical research. Qualitative data collected from a 90-min focus group interview were thematically analyzed using open and axial coding and constant comparison. Findings suggest CRPs associate contentious communication with uncertainty, stress, and emotional labor. Further, although many participants regularly utilize effective conflict and emotion management strategies, they lack confidence in both knowledge and efficacy of competent communication, stress management, and emotion management skills. Conclusions support revising “Wheel of Competencies” figure representing the Joint Task Force for Clinical Trial Competency framework. Study limitations and suggestions for future research and educational training are discussed.

Abstract Background: Identification of evidence-based factors related to status of the clinical research professional (CRP) workforce at academic medical centers (AMCs) will provide context for National Center for Advancing Translational Science (NCATS) policy considerations and guidance. The objective of this study is to explore barriers and opportunities related to the recruitment and retention of the CRP workforce. Materials and Methods: Qualitative data from a series of Un-Meeting breakout sessions and open-text survey questions were analyzed to explore barriers and recommendations for improving AMC CRP recruitment, retention and diversity. Results: While certain institutions have established competency-based frameworks for job descriptions, standardization remains generally lacking across CTSAs. AMCs report substantial increases in unfilled CRP positions leading to operational instability. Data confirmed an urgent need for closing gaps in CRP workforce at AMCs, especially for attracting, training, retaining, and diversifying qualified personnel. Improved collaboration with human resource departments, engagement with principal investigators, and overcoming both organizational and resource challenges were suggested strategies, as well as development of outreach to universities, community colleges, and high schools raising awareness of CRP career pathways. Discussion: Based on input from 130 CRP leaders at 35 CTSAs, four National Institute of General Medical Sciences’ Institutional Development Award (IDeA) program sites, along with industry and government representatives, we identified several barriers to successful recruitment and retention of a highly trained and diverse CRP workforce. Results, including securing institutional support, champions, standardizing and adopting proven national models, improving local institutional policies to facilitate CRP hiring and job progression point to potential solutions.

The BH3-only family of proteins is key for initiating apoptosis in a variety of contexts, and may also contribute to non-apoptotic cellular processes. Historically, the nematode Caenorhabditis elegans has provided a powerful system for studying and identifying conserved regulators of BH3-only proteins. In C. elegans, the BH3-only protein egl-1 is expressed during development to cell-autonomously trigger most developmental cell deaths. Here we provide evidence that egl-1 is also transcribed after development in the sensory neuron pair URX without inducing apoptosis. We used genetic screening and epistasis analysis to determine that its transcription is regulated in URX by neuronal activity and/or in parallel by orthologs of Protein Kinase G and the Salt-Inducible Kinase family. Because several BH3-only family proteins are also expressed in the adult nervous system of mammals, we suggest that studying egl-1 expression in URX may shed light on mechanisms that regulate conserved family members in higher organisms.

OBJECTIVES/GOALS: Last year, we reported on storytelling events highlighting the experiences of Black biomedical professionals. The goal of this continuation study was to put Black Voices into action through a companion curriculum, instructional materials, and facilitated meaningful discussions around racial justice. METHODS/STUDY POPULATION: We developed instructional materials and pilot-implemented the curriculum in a 250-student Healthcare Leadership class. Prior to viewing the video, participants were asked to provide a definition of diversity, inclusion, and equity. Afterwards, the students reflected and suggested changes to the definition. Throughout the class, instructors facilitated group discussions about the role of diversity. As a culminating activity, students submitted a written reflection summarizing their understanding of the role of diversity, inclusion, and equity in healthcare. RESULTS/ANTICIPATED RESULTS: Instructional materials included videos, a facilitators guide, a reflection worksheet, and online course modules. The facilitators guide included an overview of best practices in the facilitation of group discussions, common rules groups can establish for open dialogue, and discussion questions specific to the Black Voices videos. In-class and lab discussions brought up several prominent metaphors for diversity and inclusion. For example, students first defined diversity as pieces of the puzzle that somehow fit together, but later surmised that the pieces do not need to fit, or be from the same puzzle. DISCUSSION/SIGNIFICANCE: Our pilot showed that participants experienced the power of storytelling, particularly for amplifying Black voices, gained a vehicle to expand awareness and consciousness of diversity, equity, and inclusion, and identified plans to promote and facilitate stories of race, equity, and diversity.

BackgroundCirrhosis and hepatic encephalopathy (HE) are linked with an altered gut-liver-brain axis, however, the relative contribution of hepatic vagal innervation is unclear. We aimed to determine the impact of hepatic vagotomy on the gut microbiome, brain, and liver in murine cirrhosis.Methods10–15-week-old male C57BL/6 mice with and without hepatic vagotomy underwent carbon tetrachloride (CCl4) gavage for 8 weeks. Frontal cortex [inflammation, glial/microglial activation, BDNF (brain-derived neurotrophic factor)], liver [histology including inflammation and steatosis, fatty acid synthesis (sterol-responsive binding protein-1) SREBP-1, insulin-induced gene-2 (Insig2) and BDNF], and colonic mucosal microbiota (16srRNA microbial sequencing) were evaluated on sacrifice. Conventional mice with and without cirrhosis were compared to vagotomized counterparts.ResultsConventional control vs. cirrhosis: Cirrhosis resulted in dysbiosis, hepatic/neuro-inflammation with glial/microglial activation, and low brain BDNF vs. controls. Conventional control vs. vagotomy controls: Vagotomized control mice had a lower colonic dysbiosis than conventional mice but the rest of the hepatic/brain parameters were similar. Conventional cirrhosis vs. vagotomized cirrhosis: After vagotomy + cirrhosis, we found lower dysbiosis but continuing neuroinflammation in the absence of glial/microglial activation vs. conventional cirrhosis. Vagotomy + Cirrhosis groups showed higher hepatic steatosis due to higher SREBP1 and low Insig2 protein and altered activation of key genes involved in hepatic lipid metabolism and inflammation. BDNF levels in the brain were higher but low in the liver in vagotomy + cirrhosis, likely a protective mechanism.ConclusionsHepatic vagal innervation affects the gut microbial composition, hepatic inflammation and steatosis, and cortical inflammation and BDNF expression and could be a critical modulator of the gut-liver-brain axis with consequences for HE development.

Abstract Background and aims Non-high-density (HDL)-cholesterol, low-density lipoprotein (LDL)-particle number, apolipoprotein B, lipoprotein(a) (Lp(a)), and small-dense (sdLDL) and large-buoyant (lbLDL) LDL-subfractions are emerging apo B-containing atherosclerotic cardiovascular disease (ASCVD) risk factors. Current guidelines emphasize lifestyle, including weight loss, for ASCVD risk management. Whether weight change affects these emerging risk factors beyond that predicted by traditional triglyceride and LDL-cholesterol measurements remains to be determined. Method Regression analyses of fasting ∆apo B-containing lipoproteins vs. ∆BMI were examined in a large anonymized clinical laboratory database of 33,165 subjects who did not report use of lipid-lowering medications. Regression slopes (±SE) were estimated as: *∆mmol/L per ∆kg/m2, †∆g/L per ∆kg/m2, ‡∆% per ∆kg/m2, and §∆μmol/L per ∆kg/m2. Results When adjusted for age, ∆BMI was significantly related to ∆nonHDL-cholesterol (males: 0.0238 ± 0.0041, P = 7.9 × 10− 9; females: 0.0330 ± 0.0037, P

Reduced insulin-like signaling is required for C. elegans response to many environmental stressors, but how distinct outcomes are achieved is unknown. The authors show that the cytosolic sulfotransferase SSU-1 controls neurohormonal signaling via NHR-1 to specify the animals’ osmotic stress response.

Abstract Background Cancer develops when pathways controlling cell survival, cell fate or genome maintenance are disrupted by the somatic alteration of key driver genes. Understanding how pathway disruption is driven by somatic alterations is thus essential for an accurate characterization of cancer biology and identification of therapeutic targets. Unfortunately, current cancer pathway analysis methods fail to fully model the relationship between somatic alterations and pathway activity. Results To address these limitations, we developed a multi-omics method for identifying biologically important pathways and genes in human cancer. Our approach combines single-sample pathway analysis with multi-stage, lasso-penalized regression to find pathways whose gene expression can be explained largely in terms of gene-level somatic alterations in the tumor. Importantly, this method can analyze case-only data sets, does not require information regarding pathway topology and supports personalized pathway analysis using just somatic alteration data for a limited number of cancer-associated genes. The practical effectiveness of this technique is illustrated through an analysis of data from The Cancer Genome Atlas using gene sets from the Molecular Signatures Database. Conclusions Novel insights into the pathophysiology of human cancer can be obtained from statistical models that predict expression-based pathway activity in terms of non-silent somatic mutations and copy number variation. These models enable the identification of biologically important pathways and genes and support personalized pathway analysis in cases where gene expression data is unavailable.

Underrepresentation of Black biomedical researchers demonstrates continued racial inequity and lack of diversity in the field. The Black Voices in Research curriculum was designed to provide effective instructional materials that showcase inclusive excellence, facilitate the dialog about diversity and inclusion in biomedical research, enhance critical thinking and reflection, integrate diverse visions and worldviews, and ignite action. Instructional materials consist of short videos and discussion prompts featuring Black biomedical research faculty and professionals. Pilot evaluation of instructional content showed that individual stories promoted information relevance, increased knowledge, and created behavioral intention to promote diversity and inclusive excellence in biomedical research.

A substantial fraction of patients with stage I–III colorectal adenocarcinoma (CRC) experience disease relapse after surgery with curative intent. However, biomarkers for predicting the likelihood of CRC relapse have not been fully explored. Therefore, we assessed the association between tumor infiltration by a broad array of innate and adaptive immune cell types and CRC relapse risk. We implemented a discovery-validation design including a discovery dataset from Moffitt Cancer Center (MCC; Tampa, FL) and three independent validation datasets: (1) GSE41258 (2) the Molecular Epidemiology of Colorectal Cancer (MECC) study, and (3) GSE39582. Infiltration by 22 immune cell types was inferred from tumor gene expression data, and the association between immune infiltration by each cell type and relapse-free survival was assessed using Cox proportional hazards regression. Within each of the four independent cohorts, CD4+ memory activated T cell (HR: 0.93, 95% CI: 0.90–0.96; FDR = 0.0001) infiltration was associated with longer time to disease relapse, independent of stage, microsatellite instability, and adjuvant therapy. Based on our meta-analysis across the four datasets, 10 innate and adaptive immune cell types associated with disease relapse of which 2 were internally validated using multiplex immunofluorescence. Moreover, immune cell type infiltration was a better predictors of disease relapse than Consensus Molecular Subtype (CMS) and other expression-based biomarkers (Immune-AICMCC:238.1–238.9; CMS-AICMCC: 241.0). These data suggest that transcriptome-derived immune profiles are prognostic indicators of CRC relapse and quantification of both innate and adaptive immune cell types may serve as candidate biomarkers for predicting prognosis and guiding frequency and modality of disease surveillance.

OBJECTIVES/GOALS: a. Summarize barriers and best practices related to effective CRP onboarding, training and professional development b. Identify challenges with the assessment of and mentoring for CRP competency growth. c. Describe opportunities to improve the training and professionalization of the CRP career pathway. METHODS/STUDY POPULATION: Qualitative data from a series of UnMeeting breakout sessions and open-text survey questions were analyzed to explore the complex issues at play when developing high-quality onboarding and continuing education opportunities for CRPs at academic health centers. RESULTS/ANTICIPATED RESULTS: Results suggest there are several barriers to providing training to the CRP workforce, including: balancing foundational onboarding with role-based training, managing logistical challenges and institutional contexts, the need for institutional champions, assessing competency, and providing high-quality mentorship. Several of these themes are interrelated. One common thread present throughout all of these themes is the challenge of effective communication and team science training. DISCUSSION/SIGNIFICANCE: Few institutions have solved all of the issues related to training a competent and adaptable CRP workforce, although some have addressed one or more. This study illustrates the need to work collaboratively within and across institutions to overcome training barriers and support a vital and well-qualified workforce.

Abstract Alzheimer's disease (AD) is a continuum consisting of a preclinical stage that occurs decades before symptoms appear. As researchers make advances in investigating the continuum, the importance of developing drugs for secondary prevention is garnering increased discussion. For efficacious drug development for secondary prevention it is important to define what are the earliest biological stages of AD. The Alzheimer's Association Research Roundtable convened November 27 to 28, 2018 to focus on pre‐clinical AD. This review will address the biological approach to defining pre‐clinical AD, detection, identification of at‐risk individuals, and lessons learned from trials such as A4 and TOMMORROW.

IntroductionA lack of standardized clinical research coordinator (CRC) training programs requires determining appropriate approaches for content delivery. The purpose of this study was to assess CRCs preferred training delivery methods related to the 8 designated Joint Task Force Clinical Trial Competency domains.MethodsRepeated measures analysis of variance and split-plot analysis of variance were adopted to compare the group means among 5 training delivery methods by 8 competency content domains and to examine whether demographic variables caused different preference patterns on the training delivery methods.ResultsParticipants reported a preference for online video; mentoring/coaching was the least preferred. Significant training delivery method preferences were reported for 3 content domains: participant safety considerations, medicines development and regulation, and clinical trials operations.DiscussionObserved statistical differences in the training delivery methods by the content domains provides guidance for program development. Ensuring that standardized educational training is aligned with the needs of adult learners may help ensure that CRCs are appropriately prepared for the workforce.

IntroductionThe Best Practices in Social and Behavioral Research Course was developed to provide instruction on good clinical practice for social and behavioral trials. This study evaluated the new course.MethodsParticipants across 4 universities took the course (n=294) and were sent surveys following course completion and 2 months later. Outcomes included relevance, how engaging the course was, and working differently because of the course. Open-ended questions were posed to understand how work was impacted.ResultsParticipants rated the course as relevant and engaging (6.4 and 5.8/7 points) and reported working differently (4.7/7 points). Participants with less experience in social and behavioral trials were most likely to report working differently 2 months later.DiscussionThe course was perceived as relevant and engaging. Participants described actions taken to improve rigor in implementing trials. Future studies with a larger sample and additional participating sites are recommended.

Heart attacks kill more Americans than all cancers combined. Fatal heart attack victims have no symptoms until minutes before they die, hence early detection of high-risk asymptomatic individuals is needed. Even though heart attacks kill and cost more than cancers, as a nation we spend over 20 times more on screening for asymptomatic cancer than for asymptomatic atherosclerotic cardiovascular disease (ASCVD), the underlying cause of heart attacks. Currently, payers only cover screening for risk factors of ASCVD such as blood pressure and blood cholesterol. This approach tends to miss high-risk and over-treat low-risk individuals. Although treadmill stress testing with ECG is not indicated for ASCVD detection in asymptomatic individuals, it is done often, and frequently leads to misleading conclusions or unnecessary downstream diagnostic procedures. For example, former President Clinton had passed his treadmill stress tests for several years during his presidential annual checkup but had a heart attack shortly after his presidency. This common practice is a waste of our limited resources. Instead, a more accurate risk assessment using coronary artery calcium (CAC) testing is available; and has just been adopted by ACC/AHA guidelines, however payers do not cover it. CAC is measured non-invasively with a 5-minute CT-scan of the heart, and costs less than $200, whereas cancer screening with colonoscopy and mammography costs over $3000. There is an opportunity to save lives and dollars if CAC testing is covered for appropriately selected individuals. Texas has already passed HB1290 to mandate CAC coverage. Other states must step up and take actions. Keywords: Cardiovascular disease (CVD), Coronary artery calcium (CAC)

Renal clear cell carcinoma (RCC) is the most common type of kidney cancer and has a high propensity for metastasis. While treatment with immune checkpoint inhibitors, such as anti-PD-1, have shown modest improvements in survival for RCC, it is difficult to identify responders from non-responders. Attempts to elucidate the mechanisms associated with differential response to checkpoint inhibitors have been limited by small sample size making it difficult to detect meaningful associations. We utilized existing large datasets from The Cancer Genome Atlas (TCGA) to first find predictors of disease aggressiveness in the tumor microenvironment (TME) and hypothesized that these same predictors may influence response to immunotherapy. We found primary metastatic (M1-stage IV) tumors exhibit high immune infiltration, and high TP53-inactivation induced senescence activity compared to non-metastatic (M0-Stage I/II) tumors. Moreover, some TME features inferred from deconvolution algorithms, which differ between M0 and M1 tumors, also influence overall survival. A focused analysis identified interactions between tumor TP53-inactivation induced senescence activity and expression of inflammatory molecules in pre-treatment RCC tumors, which predict both change in tumor size and response to checkpoint blockade therapy. We also noted frequency of inactivating mutations in the protein polybromo-1 (PBRM1) gene was found to be negatively associated with TP53-inactivation induced senescence enrichment. Our findings suggest a mechanism by which tumor TP53-inactivation induced senescence can modulate the TME and thereby influence outcome from checkpoint blockade therapy.

Although spaces once reserved for cisgender women are becoming increasingly accessible to trans women, few studies have examined cisgender women’s responses to such changes. Informed by social identity perspectives, we examined if heterosexual cisgender women’s reactions to two types of women’s college admissions policies pertaining to trans women depended on their appraisals of intergroup threat—or the degree to which they perceived trans women as a threat to cisgender women. Four-hundred-and-forty heterosexual cisgender women completed a measure of intergroup threat and then read 1 of 2 articles about a women’s college’s admissions policy (accept trans women vs. reject trans women). Following the article, they indicated their support for the policy they read about. Overall, participants were significantly more supportive of the admissions policy when it was framed as being inclusive of trans women. The effect of policy type on policy support was moderated by intergroup threat. Specifically, women who were not particularly threatened by trans women expressed significantly more policy support when the policy was described as being inclusive of trans women, rather than as exclusionary. Alternatively, highly threatened women were significantly more likely to show support when the policy was described in terms of excluding trans women.

OBJECTIVES/GOALS: The goal of this project was to develop and evaluate a pilot mentor training program for clinical research professionals. This project presents an evidence- and theory-based mentoring program that has been developed, implemented, and evaluated for this group of translational research professions. METHODS/STUDY POPULATION: The curriculum for the program was designed for aspiring mentors and aligned with the topics of existing Entering Mentoring curriculum for translational workforce (Pfund, Branchaw & Handelsman, 2015). Eleven experienced CRPs participated in the pilot training program. The training was delivered in two-hour meetings over eight weeks. Qualitative e-mail interviews and a validated mentoring competency assessment (Fleming et al., 2013) and mentor role assessment (Dilmore, 2010) tool were used for process and outcome evaluation. Cases studies specific to the CRPs work environment were developed and used to facilitate discussions throughout the training. RESULTS/ANTICIPATED RESULTS: Pre- and post-training scores for mentoring competency assessment were compared across six sub-indexes. Paired t-tests showed a significant difference for the maintaining effective communication competency, p = 0.0202. Comparisons of individual items also showed positive changes in the promoting professional development competency, p = 0.0161). Qualitative assessment revealed that most mentor trainees recognized a distinction between a mentor and a supervisor or on-the-job-trainer. Furthermore, most have been informal mentors without a formal role assignment, the need for ongoing mentoring, and potential of mentoring networks. DISCUSSION/SIGNIFICANCE OF IMPACT: CRPs is a diverse group of research support professionals who may hold the roles of research study coordinators, research nurses, regulatory and compliance specialists. Tailored mentoring can provide essential infrastructure for ongoing professional development and support talent retention.

Using concepts from social identity theory (Tajfel and Turner, 1979), we examined whether racial/ethnic majority group members' reactions to future demographic shifts is a function of the degree to which they perceive their ingroup's higher-status in society to be legitimate. In two studies, participants who varied in the degree to which they perceived their group's status to be legitimate were either exposed to real projections for 2060 (i.e., large decline in proportion of population that is the “majority” group), or fake projections for 2060—that resembled current figures (i.e., small decline). In Study 1, White Americans who perceived their status to be highly legitimate expressed greater intergroup threat, and negative feelings (anger and fear) toward minorities after exposure to projections with a large decline in the relative size of the White American population. In contrast, demographic shift condition had no effect on intergroup threat and negative feelings toward minorities among White Americans who perceived their status to be relatively illegitimate; negative feelings and threat remained low across both conditions. Similarly, in Study 2, ethnic Portuguese people in Portugal exposed to projections in which there was a large decline in the relative size of the ethnic Portuguese population experienced more intergroup threat and expressed a greater desire to engage in anti-immigration behaviors. The effect of demographic shift condition on intergroup threat and anti-immigration behaviors was stronger among ethnic Portuguese who perceived their status to be legitimate compared to ethnic Portuguese people who perceived their status to be relatively illegitimate. These results highlight that across different cultural contexts, majority group members' beliefs about the legitimacy of intergroup relations can affect their reactions to the prospect of increased diversity.