Broussardlauesen0055

Actigraphy, a method for inferring sleep/wake patterns based on movement data gathered using actigraphs, is increasingly used in population-based epidemiologic studies because of its ability to monitor activity in natural settings. Using special software, actigraphic data are analyzed to estimate a range of sleep parameters. To date, despite extensive application of actigraphs in sleep research, published literature specifically detailing the methodology for derivation of sleep parameters is lacking; such information is critical for the appropriate analysis and interpretation of actigraphy data. Reporting of sleep parameters has also been inconsistent across studies, likely reflecting the lack of consensus regarding the definition of sleep onset and offset. In addition, actigraphy data are generally underutilized, with only a fraction of the sleep parameters generated through actigraphy routinely used in current sleep research. The objectives of this paper are to review existing algorithms used to estimate sleep/wake cycles from movement data, demonstrate the rules/methods used for estimating sleep parameters, provide clear technical definitions of the parameters, and suggest potential new measures that reflect intraindividual variability. Utilizing original data collected using Motionlogger Sleep Watch (Ambulatory Monitoring Inc., Ardsley, NY), we detail the methodology and derivation of 29 nocturnal sleep parameters, including those both widely and rarely utilized in research. By improving understanding of the actigraphy process, the information provided in this paper may help ensure appropriate use and interpretation of sleep parameters in future studies; enable the recalibration of sleep parameters to address specific goals; inform the development of new measures; and increase the breadth of sleep parameters used. © Published by Oxford University Press on behalf of The British Occupational Hygiene Society 2020.SUMMARY We contribute this opinion letter to raise awareness on the fact that very few of the peer-reviewed articles reporting structural models make these models available, and that most modern databases/datasets of models do not allow sequence searches. Free model availability is, like any other methodological material, critical for reproducibility, reuse, reanalysis and criticism, while methods for sequence-based model search are necessary to facilitate model discovery, accessibility and reuse. We argue that model availability should be no exception to science-opening and FAIR policies, and suggest that (i) model deposition should be encouraged, if not made mandatory, by journals and funding bodies, and (ii) the community would benefit from a centralized hub where protein models are discoverable through sequence searches. The main challenge is probably to have all actors (i.e. databases, publishers, funding bodies, possibly even structure prediction competitions and the wwPDB) working together, as the technological and monetary impediments on such endeavor are minor. We have in fact setup, with modest resources and effort, a palliative solution that enables sequence searches for over 5000 protein sequence entries from integrative models, models based on contact predictions, CASP models, and more, linked to the corresponding structural models. Properly managed, a global hub for protein models will allow for deeper capitalization on the recent improvements in protein structure prediction, the rise in tools for and applications of integrative modeling, and the power of modern molecular simulations. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online. © The Author(s) (2020). Published by Oxford University Press. All rights reserved. For Permissions, please email journals.permissions@oup.com.OBJECTIVES This study aimed to identify the histological characteristics associated with bridge to recovery using Berlin Heart EXCOR® (BHE) in paediatric patients less then 10 kg with dilated cardiomyopathy. METHODS Of the 10 consecutive patients less then 10 kg with dilated cardiomyopathy who underwent BHE implantation between 2013 and 2018, 4 patients showed improvement in left ventricular (LV) function, resulting in successful BHE explantation (recovery group). The remaining 6 patients showed persistent LV dysfunction and underwent heart transplantation (non-recovery group). selleck chemicals The following variables were compared between the 2 groups (i) histological findings in LV myocardium obtained at BHE implantation and (ii) LV function after BHE implantation assessed with echocardiography and cardiac catheterization. RESULTS The degree of myocardial fibrosis was significantly lower, and the capillary vascular density was significantly higher in the recovery group than in the non-recovery group [16% (standard deviation 5.9%) vs 28% (5.9%), P = 0.021, and 65 (11) vs 43 (18) units/high-power field, P = 0.037, respectively]. The changes during 3 months after BHE implantation in LV diastolic dimension (z-score) and ejection fraction were significantly greater in the recovery group than in the non-recovery group [-9.6 (3.5) vs -3.6 (4.5), P = 0.045, and 36% (13%) vs 13% (13%), P = 0.032, respectively]. CONCLUSIONS In paediatric patients less then 10 kg with dilated cardiomyopathy, bridge to recovery with BHE implantation was achieved in patients with less injured LV myocardial histology at BHE implantation. © The Author(s) 2020. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.SUMMARY Modified nucleotides play a crucial role in gene expression regulation. Here we describe methplotlib, a tool developed for the visualization of modified nucleotides detected from Oxford Nanopore Technologies sequencing platforms, together with additional scripts for statistical analysis of allele-specific modification within-subjects and differential modification frequency across subjects. AVAILABILITY AND IMPLEMENTATION The methplotlib command-line tool is written in Python3, is compatible with Linux, Mac OS and the MS Windows 10 Subsystem for Linux and released under the MIT license. The source code can be found at https//github.com/wdecoster/methplotlib and can be installed from PyPI and bioconda. Our repository includes test data and the tool is continuously tested at travis-ci.com. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online. © The Author(s) 2020. Published by Oxford University Press.