187 research outputs found

    A Calculus for Dynamic Loading

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    We present the load-calculus, used to model dynamic loading, and prove it sound. The calculus extends the polymorphic λ-calculus with a load primitive that dynamically loads terms that are closed, with respect to values. The calculus is meant to approximate the process of dynamic loading in TAL/Load [4], a version of Typed Assembly Language [7] extending with dynamic linking. To model the key aspects of TAL, the calculus contains references and facilities for named types. Loadable programs may refer to named types defined by the running program, and may export new types to code loaded later. Our approach follows the framework initially outlined by Glew et. al [3]. This calculus has been implemented in the TALx86 [6] version of Typed Assembly Language, and is used to implement a full-featured dynamic linking library, DLpop [4]

    Design Principles for Data Analysis

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    The data science revolution has led to an increased interest in the practice of data analysis. While much has been written about statistical thinking, a complementary form of thinking that appears in the practice of data analysis is design thinking -- the problem-solving process to understand the people for whom a product is being designed. For a given problem, there can be significant or subtle differences in how a data analyst (or producer of a data analysis) constructs, creates, or designs a data analysis, including differences in the choice of methods, tooling, and workflow. These choices can affect the data analysis products themselves and the experience of the consumer of the data analysis. Therefore, the role of a producer can be thought of as designing the data analysis with a set of design principles. Here, we introduce design principles for data analysis and describe how they can be mapped to data analyses in a quantitative, objective and informative manner. We also provide empirical evidence of variation of principles within and between both producers and consumers of data analyses. Our work leads to two insights: it suggests a formal mechanism to describe data analyses based on the design principles for data analysis, and it provides a framework to teach students how to build data analyses using formal design principles.Comment: arXiv admin note: text overlap with arXiv:1903.0763

    miQC : An adaptive probabilistic framework for quality control of single-cell RNA-sequencing data

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    Single-cell RNA-sequencing (scRNA-seq) has made it possible to profile gene expression in tissues at high resolution. An important preprocessing step prior to performing downstream analyses is to identify and remove cells with poor or degraded sample quality using quality control (QC) metrics. Two widely used QC metrics to identify a 'low-quality' cell are (i) if the cell includes a high proportion of reads that map to mitochondrial DNA (mtDNA) encoded genes and (ii) if a small number of genes are detected. Current best practices use these QC metrics independently with either arbitrary, uniform thresholds (e.g. 5%) or biological context-dependent (e.g. species) thresholds, and fail to jointly model these metrics in a data-driven manner. Current practices are often overly stringent and especially untenable on certain types of tissues, such as archived tumor tissues, or tissues associated with mitochondrial function, such as kidney tissue [1]. We propose a data-driven QC metric (miQC) that jointly models both the proportion of reads mapping to mtDNA genes and the number of detected genes with mixture models in a probabilistic framework to predict the low-quality cells in a given dataset. We demonstrate how our QC metric easily adapts to different types of single-cell datasets to remove low-quality cells while preserving high-quality cells that can be used for downstream analyses. Our software package is available at https://bioconductor.org/packages/miQC. Author summary We developed the miQC package to predict the low-quality cells in a given scRNA-seq dataset by jointly modeling both the proportion of reads mapping to mitochondrial DNA (mtDNA) genes and the number of detected genes using mixture models in a probabilistic framework. We demonstrate how our QC metric easily adapts to different types of single-cell datasets to remove low-quality cells while preserving high-quality cells that can be used for downstream analyses.Peer reviewe

    Acute glycogen synthase kinase-3 inhibition modulates human cardiac conduction

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    Glycogen synthase kinase 3 (GSK-3) inhibition has emerged as a potential therapeutic target for several diseases, including cancer. However, the role for GSK-3 regulation of human cardiac electrophysiology remains ill-defined. We demonstrate that SB216763, a GSK-3 inhibitor, can acutely reduce conduction velocity in human cardiac slices. Combined computational modeling and experimental approaches provided mechanistic insight into GSK-3 inhibition-mediated changes, revealing that decreased sodium-channel conductance and tissue conductivity may underlie the observed phenotypes. Our study demonstrates that GSK-3 inhibition in human myocardium alters electrophysiology and may predispose to an arrhythmogenic substrate; therefore, monitoring for adverse arrhythmogenic events could be considered

    Effect of a Motivational Interviewing–Based Intervention on Initiation of Mental Health Treatment and Mental Health After an Emergency Department Visit Among Suicidal Adolescents

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    Abstract IMPORTANCE Emergency department (ED) visits present opportunities to identify and refer suicidal youth for outpatient mental health care, although this practice is not routine. OBJECTIVE To examine whether a motivational interviewing–based intervention increases linkage of adolescents to outpatient mental health services and reduces depression symptoms and suicidal ideation in adolescents seeking emergency care for non–mental health–related concerns who screen positive for suicide risk. DESIGN, SETTING, AND PARTICIPANTS In this randomized clinical trial, adolescents aged 12 to 17 years who screened positive on the Ask Suicide Screening Questions (ASQ) during a nonpsychiatric ED visit at 2 academic pediatric EDs in Ohio were recruited from April 2013 to July 2015. Intention-totreat analyses were performed from September 2018 to October 2019. INTERVENTIONS The Suicidal Teens Accessing Treatment After an Emergency Department Visit (STAT-ED) intervention included motivational interviewing to target family engagement, problem solving, referral assistance, and limited case management. The enhanced usual care (EUC) intervention consisted of brief mental health care consultation and referral. MAIN OUTCOMES AND MEASURES Primary outcomes were mental health treatment initiation and attendance within 2 months of ED discharge and suicidal ideation (assessed by the Suicidal Ideation Questionnaire JR) and depression symptoms (assessed by the Center for Epidemiologic Studies– Depression scale) at 2 and 6 months. Exploratory outcomes included treatment initiation and attendance and suicide attempts at 6 months. RESULTS A total of 168 participants were randomized and 159 included in the intention-to-treat analyses (mean [SD] age, 15.0 [1.5] years; 126 [79.2%] female; and 80 [50.3%] white). Seventy-nine participants were randomized to receive the STAT-ED intervention and 80 to receive EUC. At 2 months, youth in the STAT-ED group had similar rates of mental health treatment initiation compared with youth in the EUC group as assessed by parent report (29 [50.9%] vs 22 [34.9%]; adjusted odds ratio [OR], 2.08; 95% CI, 0.97-4.45) and administrative data from mental health care agencies (19 [29.7%] vs 11 [19.3%]; adjusted OR, 1.77; 95% CI, 0.76-4.15). At 2 months, youth in the STAT-ED group and the EUC group had similar rates of treatment attendance (1 appointment: 6 [9.7%] vs 2 [3.6%]; adjusted OR, 2.97; 95% CI, 0.56-15.73; 2 appointments: 10 [16.1%] vs 7 [12.7%]; adjusted OR, 1.43; 95% CI, 0.50-4.11). There were no significant group × time differences in suicidal ideation (F = 0.28; P = .72) and depression symptoms (F = 0.49; P = .60) during the 6-month follow-up period. In exploratory analyses, at 6 months, STAT-ED participants had significantly higher rates of agencyreported mental health treatment initiation (adjusted OR, 2.48; 95% CI, 1.16-5.28) and more completed appointments (t99.7 = 2.58; P = .01). CONCLUSIONS AND RELEVANCE This study’s findings indicate that no differences were found on any primary outcome by study condition. However, STAT-ED was more efficacious than EUC at increasing mental health treatment initiation and attendance at 6 months. TRIAL REGISTRATION ClinicalTrials.gov identifier: NCT01779414 JAMA Network Open. 2019;2(12):e1917941. doi:10.1001/jamanetworkopen.2019.1794

    Human cardiac pericytes are susceptible to SARS-CoV-2 infection

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    COVID-19 is associated with serious cardiovascular complications, with incompletely understood mechanism(s). Pericytes have key functions in supporting endothelial cells and maintaining vascular integrity. We demonstrate that human cardiac pericytes are permissive to SARS-CoV-2 infection in organotypic slice and primary cell cultures. Viral entry into pericytes is mediated by endosomal proteases, and infection leads to up-regulation of inflammatory markers, vasoactive mediators, and nuclear factor kappa-B-dependent cell death. Furthermore, we present evidence of cardiac pericyte infection in COVID-19 myocarditis patients. These data demonstrate that human cardiac pericytes are susceptible to SARS-CoV-2 infection and suggest a role for pericyte infection in COVID-19

    Chamber-specific transcriptional responses in atrial fibrillation

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    Atrial fibrillation (AF) is the most common cardiac arrhythmia, yet the molecular signature of the vulnerable atrial substrate is not well understood. Here, we delineated a distinct transcriptional signature in right versus left atrial cardiomyocytes (CMs) at baseline and identified chamber-specific gene expression changes in patients with a history of AF in the setting of end-stage heart failure (AF+HF) that are not present in heart failure alone (HF). We observed that human left atrial (LA) CMs exhibited Notch pathway activation and increased ploidy in AF+HF but not in HF alone. Transient activation of Notch signaling within adult CMs in a murine genetic model is sufficient to increase ploidy in both atrial chambers. Notch activation within LA CMs generated a transcriptomic fingerprint resembling AF, with dysregulation of transcription factor and ion channel genes, including Pitx2, Tbx5, Kcnh2, Kcnq1, and Kcnip2. Notch activation also produced distinct cellular electrophysiologic responses in LA versus right atrial CMs, prolonging the action potential duration (APD) without altering the upstroke velocity in the left atrium and reducing the maximal upstroke velocity without altering the APD in the right atrium. Our results support a shared human/murine model of increased Notch pathway activity predisposing to AF
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