Using the Electronic Medical Record to Identify Community-Acquired Pneumonia: Toward a Replicable Automated Strategy

Background: Timely information about disease severity can be central to the detection and management of outbreaks of acute respiratory infections (ARI), including influenza. We asked if two resources: 1) free text, and 2) structured data from an electronic medical record (EMR) could complement each other to identify patients with pneumonia, an ARI severity landmark. Methods: A manual EMR review of 2747 outpatient ARI visits with associated chest imaging identified x-ray reports that could support the diagnosis of pneumonia (kappa score = 0.88 (95% CI 0.82∶0.93)), along with attendant cases with Possible Pneumonia (adds either cough, sputum, fever/chills/night sweats, dyspnea or pleuritic chest pain) or with Pneumonia-in-Plan (adds pneumonia stated as a likely diagnosis by the provider). The x-ray reports served as a reference to develop a text classifier using machine-learning software that did not require custom coding. To identify pneumonia cases, the classifier was combined with EMR-based structured data and with text analyses aimed at ARI symptoms in clinical notes. Results: 370 reference cases with Possible Pneumonia and 250 with Pneumonia-in-Plan were identified. The x-ray report text classifier increased the positive predictive value of otherwise identical EMR-based case-detection algorithms by 20–70%, while retaining sensitivities of 58–75%. These performance gains were independent of the case definitions and of whether patients were admitted to the hospital or sent home. Text analyses seeking ARI symptoms in clinical notes did not add further value. Conclusion: Specialized software development is not required for automated text analyses to help identify pneumonia patients. These results begin to map an efficient, replicable strategy through which EMR data can be used to stratify ARI severity

A new stepwise carbon cycle data assimilation system using multiple data streams to constrain the simulated land surface carbon cycle

Acknowledgements. This work was mainly funded by the EU FP7 CARBONES project (contracts FP7-SPACE-2009-1-242316), with also a small contribution from GEOCARBON project (ENV.2011.4.1.1-1-283080). This work used eddy covariance data acquired by the FLUXNET community and in particular by the following networks: AmeriFlux (U.S. Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program; DE-FG02-04ER63917 and DE-FG02-04ER63911), AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet-Canada (supported by CFCAS, NSERC, BIOCAP, Environment Canada, and NRCan), GreenGrass, KoFlux, LBA, NECC, OzFlux, TCOS-Siberia, USCCC. We acknowledge the financial support to the eddy covariance data harmonization provided by CarboEuropeIP, FAO-GTOS-TCO, iLEAPS, Max Planck Institute for Biogeochemistry, National Science Foundation, University of Tuscia, Université Laval and Environment Canada and US Department of Energy and the database development and technical support from Berkeley Water Center, Lawrence Berkeley National Laboratory, Microsoft Research eScience, Oak Ridge National Laboratory, University of California-Berkeley, University of Virginia. Philippe Ciais acknowledges support from the European Research Council through Synergy grant ERC-2013-SyG-610028 “IMBALANCE-P”. The authors wish to thank M. Jung for providing access to the GPP MTE data, which were downloaded from the GEOCARBON data portal (https://www.bgc-jena.mpg.de/geodb/projects/Data.php). The authors are also grateful to computing support and resources provided at LSCE and to the overall ORCHIDEE project that coordinate the development of the code (http://labex.ipsl.fr/orchidee/index.php/about-the-team).Peer reviewedPublisher PD

LLAMA : stellar populations in the nuclei of ultra-hard X-ray-selected AGN and matched inactive galaxies

The relation between nuclear (.50 pc) star formation and nuclear galactic activity is still elusive; theoretical models predict a link between the two, but it is unclear whether active galactic nuclei (AGNs) should appear at the same time, before, or after nuclear star formation activity. We present a study of this relation in a complete, volume-limited sample of nine of the most luminous (log L14−195 keV > 1042.5 erg s−1 ) local AGNs (the LLAMA sample), including a sample of 18 inactive control galaxies (six star-forming; 12 passive) that are matched by Hubble type, stellar mass (9.5 . log M?/M . 10.5), inclination, and distance. This allows us to calibrate our methods on the control sample and perform a differential analysis between the AGN and control samples. We performed stellar population synthesis on VLT/X-shooter spectra in an aperture corresponding to a physical radius of ≈150 pc. We find young (.30 Myr) stellar populations in seven out of nine AGNs and in four out of six star-forming control galaxies. In the non-star-forming control population, in contrast, only two out of 12 galaxies show such a population. We further show that these young populations are not indicative of ongoing star formation, providing evidence for models that see AGN activity as a consequence of nuclear star formation. Based on the similar nuclear star formation histories of AGNs and star-forming control galaxies, we speculate that the latter may turn into the former for some fraction of their time. Under this assumption, and making use of the volume completeness of our sample, we infer that the AGN phase lasts for about 5% of the nuclear starburst phase

Persistent currents in carbon nanotubes based rings

Persistent currents in rings constructed from carbon nanotubes are investigated theoretically. After studying the contribution of finite temperature or quenched disorder on covalent rings, the complexity due to the bundle packing is addressed. The case of interacting nanotori and self-interacting coiled nanotubes are analyzed in details in relation with experiments.Comment: 7 sections, 9 figure

KDM6B drives epigenetic reprogramming associated with lymphoid stromal cell early commitment and immune properties

Mature lymphoid stromal cells (LSCs) are key organizers of immune responses within secondary lymphoid organs. Similarly, inflammation-driven tertiary lymphoid structures depend on immunofibroblasts producing lymphoid cytokines and chemokines. Recent studies have explored the origin and heterogeneity of LSC/immunofibroblasts, yet the molecular and epigenetic mechanisms involved in their commitment are still unknown. This study explored the transcriptomic and epigenetic reprogramming underlying LSC/immunofibroblast commitment. We identified the induction of lysine demethylase 6B (KDM6B) as the primary epigenetic driver of early immunofibroblast differentiation. In addition, we observed an enrichment for KDM6B gene signature in murine inflammatory fibroblasts and pathogenic stroma of patients with autoimmune diseases. Last, KDM6B was required for the acquisition of LSC/immunofibroblast functional properties, including the up-regulation of CCL2 and the resulting recruitment of monocytes. Overall, our results reveal epigenetic mechanisms that participate in the early commitment and immune properties of immunofibroblasts and support the use of epigenetic modifiers as fibroblast-targeting strategies in chronic inflammation

KDM6B drives epigenetic reprogramming associated with lymphoid stromal cell early commitment and immune properties

Mature lymphoid stromal cells (LSCs) are key organizers of immune responses within secondary lymphoid organs. Similarly, inflammation-driven tertiary lymphoid structures depend on immunofibroblasts producing lymphoid cytokines and chemokines. Recent studies have explored the origin and heterogeneity of LSC/immunofibroblasts, yet the molecular and epigenetic mechanisms involved in their commitment are still unknown. This study explored the transcriptomic and epigenetic reprogramming underlying LSC/immunofibroblast commitment. We identified the induction of lysine demethylase 6B (KDM6B) as the primary epigenetic driver of early immunofibroblast differentiation. In addition, we observed an enrichment for KDM6B gene signature in murine inflammatory fibroblasts and pathogenic stroma of patients with autoimmune diseases. Last, KDM6B was required for the acquisition of LSC/immunofibroblast functional properties, including the up-regulation of CCL2 and the resulting recruitment of monocytes. Overall, our results reveal epigenetic mechanisms that participate in the early commitment and immune properties of immunofibroblasts and support the use of epigenetic modifiers as fibroblast-targeting strategies in chronic inflammation

Ionized outflows in local luminous AGN : what are the real densities and outflow rates?

We report on the determination of electron densities, and their impact on the outflow masses and rates, measured in the central few hundred parsecs of 11 local luminous active galaxies. We show that the peak of the integrated line emission in the active galactic nuclei (AGN) is significantly offset from the systemic velocity as traced by the stellar absorption features, indicating that the profiles are dominated by outflow. In contrast, matched inactive galaxies are characterized by a systemic peak and weaker outflow wing. We present three independent estimates of the electron density in these AGN, discussing the merits of the different methods. The electron density derived from the [S II] doublet is significantly lower than that found with a method developed in the last decade using auroral and transauroral lines, as well as a recently introduced method based on the ionization parameter. The reason is that, for gas photoionized by an AGN, much of the [S II] emission arises in an extended partially ionized zone where the implicit assumption that the electron density traces the hydrogen density is invalid. We propose ways to deal with this situation and we derive the associated outflow rates for ionized gas, which are in the range 0.001–0.5 M yr−1 for our AGN sample. We compare these outflow rates to the relation between M˙ out and LAGN in the literature, and argue that it may need to be modified and rescaled towards lower mass outflow rates

Phylotyping and Functional Analysis of Two Ancient Human Microbiomes

Background: The Human Microbiome Project (HMP) is one of the U.S. National Institutes of Health Roadmap for Medical Research. Primary interests of the HMP include the distinctiveness of different gut microbiomes, the factors influencing microbiome diversity, and the functional redundancies of the members of human microbiotas. In this present work, we contribute to these interests by characterizing two extinct human microbiotas. Methodology/Principal Findings: We examine two paleofecal samples originating from cave deposits in Durango Mexico and dating to approximately 1300 years ago. Contamination control is a serious issue in ancient DNA research; we use a novel approach to control contamination. After we determined that each sample originated from a different human, we generated 45 thousand shotgun DNA sequencing reads. The phylotyping and functional analysis of these reads reveals a signature consistent with the modern gut ecology. Interestingly, inter-individual variability for phenotypes but not functional pathways was observed. The two ancient samples have more similar functional profiles to each other than to a recently published profile for modern humans. This similarity could not be explained by a chance sampling of the databases. Conclusions/Significance: We conduct a phylotyping and functional analysis of ancient human microbiomes, while providing novel methods to control for DNA contamination and novel hypotheses about past microbiome biogeography. We postulate that natural selection has more of an influence on microbiome functional profiles than it does on the species represented in the microbial ecology. We propose that human microbiomes were more geographically structured during pre-Columbian times than today

COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.

Funder: Bundesministerium für Bildung und ForschungFunder: Bundesministerium für Bildung und Forschung (BMBF)We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective

DNA methylation signatures of aggression and closely related constructs : A meta-analysis of epigenome-wide studies across the lifespan

DNA methylation profiles of aggressive behavior may capture lifetime cumulative effects of genetic, stochastic, and environmental influences associated with aggression. Here, we report the first large meta-analysis of epigenome-wide association studies (EWAS) of aggressive behavior (N = 15,324 participants). In peripheral blood samples of 14,434 participants from 18 cohorts with mean ages ranging from 7 to 68 years, 13 methylation sites were significantly associated with aggression (alpha = 1.2 x 10(-7); Bonferroni correction). In cord blood samples of 2425 children from five cohorts with aggression assessed at mean ages ranging from 4 to 7 years, 83% of these sites showed the same direction of association with childhood aggression (r = 0.74, p = 0.006) but no epigenome-wide significant sites were found. Top-sites (48 at a false discovery rate of 5% in the peripheral blood meta-analysis or in a combined meta-analysis of peripheral blood and cord blood) have been associated with chemical exposures, smoking, cognition, metabolic traits, and genetic variation (mQTLs). Three genes whose expression levels were associated with top-sites were previously linked to schizophrenia and general risk tolerance. At six CpGs, DNA methylation variation in blood mirrors variation in the brain. On average 44% (range = 3-82%) of the aggression-methylation association was explained by current and former smoking and BMI. These findings point at loci that are sensitive to chemical exposures with potential implications for neuronal functions. We hope these results to be a starting point for studies leading to applications as peripheral biomarkers and to reveal causal relationships with aggression and related traits.Peer reviewe