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  • 2017-2021
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  • Canadian Institutes of Health Resea...
  • ZENODO

  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/

    Funding: This work was supported by CIHR Foundation grant FDN 143312 (DWA), CIHR grant PJT 156167 (LZP), the European Union's Seventh Framework Programme (FP7/2008–2013) under Grant Agreement 627951 (Marie Curie IOF to PM), the German Academic Exchange Service (DAAD) with funds from the German Federal Ministry of Education and Research (57212163 to PM), and in part by the Bundesministerium für Bildung und Forschung, Germany (BMBF, grant no. 16GW0191 to PM). JMP is recipient of the Queen Elizabeth II graduate scholarship in science and technology. PM has been supported by the BIH‐Charité Clinical Scientist Program funded by the Charité – Universitätsmedizin Berlin and the Berlin Institute of Health. DWA holds a Tier 1 Canada Research Chair (CRC) in Membrane Biogenesis. LZP holds a Tier 1 CRC in Molecular Oncology. 3D confocal image stacks of primary cortical neurons under different treatment conditions to test the functionality of Phindr3D. Explanatory .txt file contained in the ZIP file. Please see the manuscript for details and on how to access the full data set: Rapid 3D phenotypic analysis of neurons and organoids using data-driven cell segmentation-free machine learning Philipp Mergenthaler*, Santosh Hariharan*, James M. Pemberton, Corey Lourenco, Linda Z. Penn, David W. Andrews PLOS Computational Biology, DOI: 10.1371/journal.pcbi.1008630 Phindr3D is available on GitHub: GitHub - DWALab/Phindr3D

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Bernhardt, Boris C.; Fadaie, Fatemeh; Liu, Min; Caldairou, Benoit; +6 Authors

    OBJECTIVE. To assess whether HS severity is mirrored at the level of large-scale networks. METHODS. We studied preoperative high-resolution anatomical and diffusion-weighted MRI of 44 TLE patients with histopathological diagnosis of HS (n=25; TLE-HS) and isolated gliosis (n=19; TLE-G), and 25 healthy controls. Hippocampal measurements included surface-based subfield mapping of atrophy and T2 hyperintensity indexing cell loss and gliosis, respectively. Whole-brain connectomes were generated via diffusion tractography and examined using graph theory along with a novel network control theory paradigm which simulates functional dynamics from structural network data. RESULTS. Compared to controls, we observed markedly increased path length and decreased clustering in TLE-HS compared to controls, indicating lower global and local network efficiency, while TLE-G showed only subtle alterations. Similarly, network controllability was lower in TLE-HS only, suggesting limited range of functional dynamics. Hippocampal imaging markers were positively associated with macroscale network alterations, particularly in ipsilateral CA1-3. Systematic assessment across several networks revealed maximal changes in the hippocampal circuity. Findings were consistent when correcting for cortical thickness, suggesting independence from grey matter atrophy. CONCLUSIONS. Severe HS is associated with marked remodeling of connectome topology and structurally-governed functional dynamics in TLE, as opposed to isolated gliosis which has negligible effects. Cell loss, particularly in CA1-3, may exert a cascading effect on brain-wide connectomes, underlining coupled disease processes across multiple scales. Data_phen_conn_dryadPhenotypic information and mean connectome feature data for Bernhardt et al. (2019) Temporal lobe epilepsy: hippocampal pathology modulates white matter connectome topology and controllability. Neurology

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    DANS-EASY
    Dataset . 2019
    Data sources: B2FIND
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    NARCIS; ZENODO; DRYAD
    Dataset . 2019
    License: CC 0
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      DANS-EASY
      Dataset . 2019
      Data sources: B2FIND
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      NARCIS; ZENODO; DRYAD
      Dataset . 2019
      License: CC 0
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    Authors: Kember, Allan J.; Scott, Heather M.; O'Brien, Louise M.; Borazjani, Ali; +6 Authors

    Supplementary File 1: R Code and output - Demographic AnalysisThis is a stand alone report containing the code and output of an R script, which was generated by the "Compile Report" function in RStudio (R Statistical Software package (version 3.2.4 (2016-03-10))). This code summarizes the demographic, obstetric, and sleep behaviour of the participants (collected via a questionnaire completed by each participant on her first sleep test) and compares these data between all participants whose first sleep test was PrenaBelt (followed by sham-PrenaBelt on the second sleep test) versus all participants whose first sleep test was sham-PrenaBelt (followed by PrenaBelt on the second sleep test).Code and output - Demographic Analysis.docxSupplementary File 2: R Code and output - PSG AnalysisThis is a stand alone report containing the code and output of an R script, which was generated by the "Compile Report" function in RStudio (R Statistical Software package (version 3.2.4 (2016-03-10))). This code processes the polysomnography (PSG) sleep reports in full, making within-participant (paired) comparisons and between-participant (unpaired) comparisons. The sleep reports were generated by Embla Sandman Elite sleep diagnostic software (Natus Medical Incorporated, Pleasanton, USA). The data in the PSG sleep reports was collected via Pro-Tech zRIP Durabelts (Philips Respironics, Murrysville, USA) for respiration, PT1 pressure transducers (BRAEBON Medical Corporation, Kanata, Canada) for airflow and snoring, electrodes (Natus Medical Incorporated, Pleasanton, USA) for ECG/EEG/EOG/EMG, and finger-tip pulse oximetry for peripheral blood oxygen saturation (SpO2) in accordance with the American Academy of Sleep Medicine 2014 guidelines. Audio and video data were also recorded and used in order to determine body position and snoring.Code and output - PSG Analysis.docxSupplementary File 3: R Code and output - Feedback AnalysisThis is a stand alone report containing the code and output of an R script, which was generated by the "Compile Report" function in RStudio (R Statistical Software package (version 3.2.4 (2016-03-10))). This code processes the participants' feedback on the PrenaBelt (collected via a questionnaire completed by each participant after each sleep test). It summarizes these data, completes within-participant (paired) comparison of these data ("before/after"), and completes between-participants (unpaired) comparison of these data (bulk test for differences between all PrenaBelt sleep test nights versus all sham-PrenaBelt nights).Code and output - Feedback Analysis.docxSupplementary File 4: R Code and output - Self-Report Accuracy AnalysisThis is a stand alone report containing the code and output of an R script, which was generated by the "Compile Report" function in RStudio (R Statistical Software package (version 3.2.4 (2016-03-10))). This code compares each participant's perception of her sleep behaviours (collected via a questionnaire completed by each participant after each sleep test) to her polysomnography-determined sleep behaviours (collected via audio and video and Embla Sandman Elite sleep diagnostic software (Natus Medical Incorporated, Pleasanton, USA)) in order to determine the ability of participants to accurately recall their sleep onset position, waking position, number of position changes during the night, and percentage of sleep time in each position.Code and output - Self-Report Accuracy Analysis.docx OBJECTIVE: To evaluate whether the percentage of time spent supine during sleep in the third trimester of pregnancy could be reduced using a positional therapy device (PrenaBelt) compared with a sham device. DESIGN: A double-blind, randomized, sham-controlled, crossover pilot trial. SETTING: Conducted between March 2016 and January 2017, at a single, tertiary-level center in Canada. PARTICIPANTS: Twenty-three participants entered the study. Twenty participants completed the study. Participants were low-risk, singleton, third-trimester pregnant women aged 18 years and older with BMI <35 at the first antenatal appointment for the index pregnancy and without known fetal abnormalities, pregnancy complications, or medical conditions complicating sleep. INTERVENTIONS: A two-night, polysomnography study in a sleep laboratory. Participants were randomized by computer-generated, one-to-one, simple randomization to receive either a the PrenaBelt or a sham-PrenaBelt on the 1st night and were crossed over to the alternate device on the 2nd night. Allocation concealment was by unmarked, security-tinted, sealed envelopes. Participants, the recruiter, and personnel involved in setting up, conducting, scoring, and interpreting the polysomnogram were blinded to allocation. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was the percentage of time spent supine during sleep. Secondary outcomes included maternal sleep architecture, respiration, self-reported sleep position, and feedback. RESULTS: The median percentage of sleep time supine was reduced from 16.4% on the sham night to 3.5% on the PrenaBelt night (pseudomedian=5.8, p=0.03). We were unable to demonstrate differences in sleep architecture or respiration. Participants underestimated the time they spent sleeping supine by 7.0%, and six (30%) participants indicated they would make changes to the PrenaBelt. There were no harms in this study. CONCLUSIONS: This study demonstrates that the percentage of sleep time supine during late pregnancy can be significantly reduced via positional therapy. TRIAL REGISTRATION: ClinicalTrials.gov NCT02377817

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    DANS-EASY
    Dataset . 2018
    Data sources: B2FIND
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    DRYAD; ZENODO; NARCIS
    Dataset . 2018
    License: CC 0
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      DANS-EASY
      Dataset . 2018
      Data sources: B2FIND
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      DRYAD; ZENODO; NARCIS
      Dataset . 2018
      License: CC 0
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    Authors: Mielke, Alexander; Preis, Anna; Samuni, Liran; Gogarten, Jan F.; +2 Authors

    Living in permanent social groups forces animals to make decisions about when, how and with whom to interact, requiring decisions to be made that integrate multiple sources of information. Changing social environments can influence this decision-making process by constraining choice or altering the likelihood of a positive outcome. Here, we conceptualised grooming as a choice situation where an individual chooses one of a number of potential partners. Studying two wild populations of sympatric primate species, sooty mangabeys (Cercocebus atys atys) and Western chimpanzees (Pan troglodytes verus), we tested what properties of potential partners influenced grooming decisions, including their relative value based on available alternatives and the social relationships of potential partners with bystanders who could observe the outcome of the decision. Across 1,529 decision events, multiple partner attributes (e.g. dominance ranks, social relationship quality, reproductive state, partner sex) influenced choice. Individuals preferred to initiate grooming with partners of similar global rank, but this effect was driven by a bias towards partners with a high rank compared to other locally available options. Individuals also avoided grooming partners who had strong social relationships with at least one bystander. Results indicated flexible decision-making in grooming interactions in both species, based on a partner’s value given the local social environment. Viewing partner choice as a value-based decision-making process allows researchers to compare how different species solve similar social problems. Data Model1Data for Models 1-1 and 1-2Data Model2Data for Models 2-1 and 2-2Script Model 1 and 2Scripts necessary to analyse Models 1 and 2

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    DANS-EASY
    Dataset . 2018
    Data sources: B2FIND
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    ZENODO; DRYAD; NARCIS
    Dataset . 2018
    License: CC 0
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      DANS-EASY
      Dataset . 2018
      Data sources: B2FIND
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      ZENODO; DRYAD; NARCIS
      Dataset . 2018
      License: CC 0
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    Authors: Leger, Michelle M.; Kolisko, Martin; Kamikawa, Ryoma; Stairs, Courtney W.; +13 Authors

    Many anaerobic microbial parasites possess highly modified mitochondria known as mitochondrion-related organelles (MROs). The best-studied of these are the hydrogenosomes of Trichomonas vaginalis and Spironucleus salmonicida, which produce ATP anaerobically through substrate-level phosphorylation with concomitant hydrogen production; and the mitosomes of Giardia intestinalis, which are functionally reduced and lack any role in ATP production. However, to understand the metabolic specializations that these MROs underwent in adaptation to parasitism, data from their free-living relatives are needed. Here, we present a large-scale comparative transcriptomic study of MROs across a major eukaryotic group, Metamonada, examining lineage-specific gain and loss of metabolic functions in the MROs of Trichomonas, Giardia, Spironucleus and their free-living relatives. Our analyses uncover a complex history of ATP production machinery in diplomonads such as Giardia, and their closest relative, Dysnectes; and a correlation between the glycine cleavage machinery and lifestyles. Our data further suggest the existence of a previously undescribed biochemical class of MRO that generates hydrogen but is incapable of ATP synthesis. Protein alignmentsAlignments of organellar proteinsmito_alignments.zipPhylogenomic datasetSingle gene alignments used for phylogenomic analysisPhylogenomic.zipData SourcesFasta files with assembled transcriptomes of Carpediemonas-like organismsAssemblies.zip

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    DANS-EASY
    Dataset . 2017
    Data sources: B2FIND
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      DANS-EASY
      Dataset . 2017
      Data sources: B2FIND
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    Authors: Martin, Allan R.; De Leener, Benjamin; Cohen-Adad, Julien; Cadotte, David W.; +7 Authors

    Objectives: Degenerative cervical myelopathy (DCM) involves extrinsic spinal cord compression causing tissue injury and neurological dysfunction. Asymptomatic spinal cord compression (ASCC) is more common but its significance is poorly defined. This study investigates if: 1) ASCC can be automatically diagnosed using spinal cord shape analysis; 2) multiparametric quantitative MRI can detect similar spinal cord tissue injury as previously observed in DCM. Design: Prospective observational longitudinal cohort study. Setting: Single centre, tertiary care and research institution. Participants: 40 neurologically intact subjects (19 female, 21 male) divided into groups with and without ASCC. Interventions: None. Outcome Measures: Clinical assessments: modified Japanese Orthopedic Association (mJOA) score and physical examination. 3T MRI assessments: automated morphometric analysis compared with consensus ratings of spinal cord compression, and measures of tissue injury: cross-sectional area (CSA), diffusion fractional anisotropy (FA), magnetization transfer ratio (MTR), and T2-weighted imaging white to grey matter signal intensity ratio (T2WI WM/GM) extracted from rostral (C1-3), caudal (C6-7), and maximally compressed levels (MCL). Results: ASCC was present in 20/40 subjects. Diagnosis with automated shape analysis showed area under the curve > 97%. Five MRI metrics showed differences suggestive of tissue injury in ASCC compared with uncompressed subjects (p<0.05), while a composite of all 10 measures (average of z scores) showed highly significant differences (p=0.002). At follow-up (median 21 months), two ASCC subjects developed DCM. Conclusions: ASCC appears to be common and can be accurately and objectively diagnosed with automated morphometric analysis. Quantitative MRI appears to detect subclinical tissue injury in ASCC prior to the onset of neurological symptoms and signs. These findings require further validation, but offer the intriguing possibility of pre-symptomatic diagnosis and treatment of DCM and other spinal pathologies. Registration: Not registered. Demographic, morphometric, and quantitative MRI dataData includes anonymized subject ID, presence of spinal cord compression, age, sex, follow-up mJOA score, spinal cord morphometric parameters of compression ratio, solidity, and relative rotation, measured at C2-3, C3-4, C4-5, C5-6, and C6-7, and quantitative MRI measures of cross sectional area, magnetization transfer ratio, fractional anisotropy, and T2*-weighted white matter to grey matter signal intensity ratio, measured at rostral (C1-3), maximally compressed level, and caudal (C6-7) levels.qMRI_subclinical_tissue_injury_public_data.xlsx

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    DANS-EASY
    Dataset . 2018
    Data sources: B2FIND
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    DRYAD; ZENODO; NARCIS
    Dataset . 2018
    License: CC 0
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      DANS-EASY
      Dataset . 2018
      Data sources: B2FIND
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      DRYAD; ZENODO; NARCIS
      Dataset . 2018
      License: CC 0
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    Authors: Parra, Esteban J.; Mazurek, Andrew; Gignoux, Christopher R.; Sockell, Alexandra; +8 Authors

    We carried out an admixture mapping study of lipid traits in two samples from Mexico City. Native American locus ancestry was significantly associated with triglyceride levels in a broad region of chromosome 11 overlapping the BUD13, ZNF259 and APOA5 genes. In our fine-mapping analysis of this region using dense genome-wide data, rs964184 is the only marker included in the 99% credible set of SNPs, providing strong support for rs964184 as the causal variant within this region. The frequency of the allele associated with increased triglyceride concentrations (rs964184-G) is between 30-40% higher in Native American populations from Mexico than in European populations. The evidence currently available for this variant indicates that it may be exerting its effect through three potential mechanisms: 1) modification of enhancer activity, 2) regulation of the expression of several genes in cis and/or trans, or 3) modification of the methylation patterns of the promoter of the APOA5 gene. MC-sample1-HDL-AMAdmixture Mapping results for HDL-cholesterol: Mexico City sample 1MC-sample1-LDL-AMAdmixture Mapping results for LDL-cholesterol: Mexico City sample 1MC-sample1-TCHOL-AMAdmixture Mapping results for Total-cholesterol: Mexico City sample 1MC-sample1-TG-AMAdmixture Mapping results for triglycerides: Mexico City sample 1MC-sample2-HDL-AMAdmixture Mapping results for HDL-cholesterol: Mexico City sample 2MC-sample2-LDL-AMAdmixture Mapping results for LDL-cholesterol: Mexico City sample 2MC-sample2-TCHOL-AMAdmixture Mapping results for Total-cholesterol: Mexico City sample 2MC-sample2-TG-AMAdmixture Mapping results for triglycerides: Mexico City sample 2Mexico-City-AM-signalsAdmixture Mapping signals identified in both Mexico City samples for all the lipid traits.

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    DANS-EASY
    Dataset . 2017
    Data sources: B2FIND
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      DANS-EASY
      Dataset . 2017
      Data sources: B2FIND
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    Authors: Lively, Starlee; Schlichter, Lyanne C.;

    Microglia respond to CNS injuries and diseases with complex reactions, often called “activation.” A pro-inflammatory phenotype (also called classical or M1 activation) lies at one extreme of the reactivity spectrum. There were several motivations for this study. First, bacterial endotoxin (lipopolysaccharide, LPS) is the most commonly used pro-inflammatory stimulus for microglia, both in vitro and in vivo; however, pro-inflammatory cytokines (e.g., IFNγ, TNFα) rather than LPS will be encountered with sterile CNS damage and disease. We lack direct comparisons of responses between LPS and such cytokines. Second, while transcriptional profiling is providing substantial data on microglial responses to LPS, these studies mainly use mouse cells and models, and there is increasing evidence that responses of rat microglia can differ. Third, the cytokine milieu is dynamic after acute CNS damage, and an important question in microglial biology is: How malleable are their responses? There are very few studies of effects of resolving cytokines, particularly for rat microglia, and much of the work has focused on pro-inflammatory outcomes. Here, we first exposed primary rat microglia to LPS or to IFNγ+TNFα (I+T) and compared hallmark functional (nitric oxide production, migration) and molecular responses (almost 100 genes), including surface receptors that can be considered part of the sensome. Protein changes for exemplary molecules were also quantified: ARG1, CD206/MRC1, COX-2, iNOS, and PYK2. Despite some similarities, there were notable differences in responses to LPS and I+T. For instance, LPS often evoked higher pro-inflammatory gene expression and also increased several anti-inflammatory genes. Second, we compared the ability of two anti-inflammatory, resolving cytokines (IL-4, IL-10), to counteract responses to LPS and I+T. IL-4 was more effective after I+T than after LPS, and IL-10 was surprisingly ineffective after either stimulus. These results should prove useful in modeling microglial reactivity in vitro; and comparing transcriptional responses to sterile CNS inflammation in vivo. Lively & Schlichter_6h_24h NanoString count dataNormalized mRNA counts

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    DANS-EASY
    Dataset . 2018
    Data sources: B2FIND
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      DANS-EASY
      Dataset . 2018
      Data sources: B2FIND
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    Authors: McTavish, Jill R.; Kimber, Melissa; Devries, Karen; Colombini, Manuela; +4 Authors

    Objective: To systematically search for research about the effectiveness of mandatory reporting of child maltreatment and to synthesize qualitative research that explores mandated reporters’ (MRs) experiences with reporting. Design: As no studies assessing the effectiveness of mandatory reporting were retrieved from our systematic search, we conducted a meta-synthesis of retrieved qualitative research. Searches in Medline (OVID), Embase, PsycINFO, CINAHL, Sociological Abstracts, ERIC, Criminal Justice Abstracts, and Cochrane Library yielded over 6000 citations, which were deduplicated and then screened by two independent reviewers. English-language, primary qualitative studies that investigated MRs’ experiences with reporting of child maltreatment were included. Critical appraisal involved a modified checklist from the Critical Appraisal Skills Programme (CASP) and qualitative meta-synthesis was used to combine results from the primary studies. Setting: All healthcare and social-service settings implicated by mandatory reporting laws were included. Included studies crossed nine high-income countries (United States, Australia, Sweden, Taiwan, Canada, Norway, Finland, Israel and Cyprus) and three middle-income countries (South Africa, Brazil, and El Salvador). Participants: The studies represent the views of 1088 MRs. Outcomes: Factors that influence MRs’ decision to report and MRs’ views towards and experiences with mandatory reporting of child maltreatment. Results: Forty-four articles reporting 42 studies were included. Findings indicate that MRs struggle to identify and respond to less overt forms of child maltreatment. While some articles (14%) described positive experiences MRs had with the reporting process, negative experiences were reported in 73% of articles and included accounts of harm to therapeutic relationships and child death following removal from their family of origin. Conclusions: The findings of this meta-synthesis suggest that there are many potentially harmful experiences associated with mandatory reporting and that research on the effectiveness of this process is urgently needed. Mandatory Reporting Meta-Synthesis - Extracted Data CodedAll data extracted and coded data for this meta-synthesis is found in this excel file.

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    NARCIS; DRYAD; ZENODO
    Dataset . 2017
    License: CC 0
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    DANS-EASY
    Dataset . 2017
    Data sources: B2FIND
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      NARCIS; DRYAD; ZENODO
      Dataset . 2017
      License: CC 0
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      DANS-EASY
      Dataset . 2017
      Data sources: B2FIND
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    OV2295 Tables ov2295_breakpoint_counts.csv.gz: Table of breakpoint counts per cell prediction_id: identifier for the breakpoint cell_id: identifier for the cell read_count: number of reads library_id: identifier for the DNA library sample_id: identifier for the sequenced sample chromosome_1: chromosome of breakend 1 strand_1: orientation of break end 1 position_1: position of break end 1 chromosome_2: chromosome of breakend 2 strand_2: orientation of break end 2 position_2: position of break end 2 ov2295_cell_cn.csv.gz: Table of cell specific copy number cell_id: identifier for the cell sample_id: identifier for the sequenced sample library_id: identifier for the DNA library chr: chromosome of bin start: start of bin end: end of bin reads: number of reads copy: raw normalized copy number state: copy number state gc: percent gc of the bin map: average mappability of the bin ov2295_cell_metrics.csv.gz: Table of cell metrics cell_id: identifier of the cell unpaired_mapped_reads: number of unpaired mapped reads paired_mapped_reads: number of mapped reads that were properly paired unpaired_duplicate_reads: number of unpaired duplicated reads paired_duplicate_reads: number of paired reads that were also marked as duplicate unmapped_reads: number of unmapped reads percent_duplicate_reads: percentage of duplicate reads estimated_library_size: scaled total number of mapped reads total_reads: total number of reads, regardless of mapping status total_mapped_reads: total number of mapped reads total_duplicate_reads: number of duplicate reads total_properly_paired: number of properly paired reads coverage_breadth: percentage of genome covered by some read coverage_depth: average reads per nucleotide position in the genome median_insert_size: median insert size between paired reads mean_insert_size: mean insert size between paired reads standard_deviation_insert_size: standard deviation of the insert size between paired reads index_sequence: index sequence of the adaptor sequence column: column of the cell on the nanowell chip img_col: column of the cell from the perspective of the microscope index_i5: id of the i5 index adapter sequence sample_type: type of the sample primer_i7: id of the i5 index primer sequence experimental_condition: experimental treatment of the cell, includes controls index_i7: id of the i7 index adapter sequence cell_call: living/dead classification of the cell based on staining usually, C1 == living, C2 == dead sample_id: name of the sample primer_i5: id of the i5 index primer sequence row: row of the cell on the nanowell chip library_id: identifier for the DNA library index: ignored multiplier: during parameter searching, the set [1..6] that was chosen MSRSI_non_integerness: median of segment residuals from segment integer copy number states MBRSI_dispersion_non_integerness: median of bin residuals from segment integer copy number states MBRSM_dispersion: median of bin residuals from segment median copy number values autocorrelation_hmmcopy: hmmcopy copy autocorrelation cv_hmmcopy: ignored empty_bins_hmmcopy: number of empty bins in hmmcopy mad_hmmcopy: median absolute deviation of hmmcopy copy mean_hmmcopy_reads_per_bin: mean reads per hmmcopy bin median_hmmcopy_reads_per_bin: median reads per hmmcopy bin std_hmmcopy_reads_per_bin: standard deviation value of reads in hmmcopy bins total_halfiness: summed halfiness penality score of the cell total_mapped_reads_hmmcopy: total mapped reads in all hmmcopy bins scaled_halfiness: summed scaled halfiness penalty score of the cell mean_state_mads: mean value for all median absolute deviation scores for each state mean_state_vars: variance value for all median absolute deviation scores for each state mad_neutral_state: median absolute deviation score of the neutral 2 copy state breakpoints: number of breakpoints, as indicated by state changes not at the ends of chromosomes mean_copy: mean hmmcopy copy value state_mode: the most commonly occuring state log_likelihood: hmmcopy log likelihood for the cell true_multiplier: the exact decimal value used to scale the copy number for segmentation order: order of the cell in the hierarchical clustering tree quality: random forest classifier proability score that cell is good ov2295_clone_alleles.csv.gz: Table of clone specific allele data chr: chromosome of bin start: start of bin end: end of bin hap_label: haplotype block identifier clone_id: clone identifier allele_1_sum: number of reads for allele 1 of the haplotype block allele_2_sum: number of reads for allele 2 of the haplotype block total_counts_sum: total reads for the haplotype block ov2295_clone_breakpoints.csv.gz: Table of breakpoints per clone for OV2295 samples. Columns: prediction_id: identifier for the breakpoint chromosome_1: chromosome of breakend 1 strand_1: orientation of break end 1 position_1: position of break end 1 chromosome_2: chromosome of breakend 2 strand_2: orientation of break end 2 position_2: position of break end 2 clone_id: clone identifier read_count: number of reads is_present: presence=1, absent=0 ov2295_clone_clusters.csv.gz: Table of cell clusters as putative clones cell_id: identifier for the cell clone_id: clone identifier ov2295_clone_cn.csv.gz: Table of allele specific copy number per clone for OV2295 samples. Columns: chr: chromosome of bin start: start of bin end: end of bin total_cn: HMMCopy predicted total copy number minor_cn: HMM predicted minor copy number major_cn: HMM predicted major copy number clone_id: clone identifier ov2295_clone_snvs.csv.gz: Table of SNVs per clone for OV2295 samples. Columns: chrom: chromosome coord: genome position ref: reference nucleotide alt: alternate nucleotide clone_id: clone identifier ref_counts: number of reads at this position matching the reference nucleotide alt_counts: number of reads at this position matching the alternate nucleotide total_counts: total number of reads at this position is_present: presence=0, absent=1 is_het: is heterozygous is_hom: is homozygous for the alternate ov2295_nodes.csv.gz: Table of phylogenetic information for SNV evolution variant_id: identifier for the SNV as chrom:coord:ref:alt node: node in the phylogenetic tree loss: probability the SNV was lost at this node origin: probability the SNV originated at this node presence: probability the SNV is present at this node ml_origin: binary indicator the SNV originated at this node ml_presence: binary indicator the SNV is present at this node ml_loss: binary indicator the SNV was lost at this node ov2295_snv_counts.csv.gz: Table of SNV counts chrom: chromosome coord: genome position ref: reference nucleotide alt: alternate nucleotide ref_counts: number of reads at this position matching the reference nucleotide alt_counts: number of reads at this position matching the alternate nucleotide cell_id: identifier for the cell total_counts: total number of reads at this position sample_id: identifier for the sequenced sample ov2295_tree.pickle: Phylogenetic tree in python pickle format. Requires installation of the stochastic dollo code at: https://bitbucket.org/dranew/dollo, version 0.4.2. Note the following sample mapping: ���SA922���: ���OV2295(R2)���, ���SA921���: ���TOV2295(R)���, ���SA1090���: ���OV2295���, Plots ov_supp_clone_allele_cn.png: Clone allele ratios for each OV2295 sample. ov_supp_clone_total_cn.png: Clone copy number for each OV2295 sample. ov_supp_sample_total_cn.png: Bulk copy number for each OV2295 sample. ov_supp_sample_allele_cn.png: Bulk allele ratios for each OV2295 sample.

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    ZENODO
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2019
    License: CC BY
    Data sources: ZENODO
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    ZENODO
    Dataset . 2019
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2019
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2019
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2019
      License: CC BY
      Data sources: ZENODO
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2019
      License: CC BY
      Data sources: Datacite
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      ZENODO
      Dataset . 2019
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/

    Funding: This work was supported by CIHR Foundation grant FDN 143312 (DWA), CIHR grant PJT 156167 (LZP), the European Union's Seventh Framework Programme (FP7/2008–2013) under Grant Agreement 627951 (Marie Curie IOF to PM), the German Academic Exchange Service (DAAD) with funds from the German Federal Ministry of Education and Research (57212163 to PM), and in part by the Bundesministerium für Bildung und Forschung, Germany (BMBF, grant no. 16GW0191 to PM). JMP is recipient of the Queen Elizabeth II graduate scholarship in science and technology. PM has been supported by the BIH‐Charité Clinical Scientist Program funded by the Charité – Universitätsmedizin Berlin and the Berlin Institute of Health. DWA holds a Tier 1 Canada Research Chair (CRC) in Membrane Biogenesis. LZP holds a Tier 1 CRC in Molecular Oncology. 3D confocal image stacks of primary cortical neurons under different treatment conditions to test the functionality of Phindr3D. Explanatory .txt file contained in the ZIP file. Please see the manuscript for details and on how to access the full data set: Rapid 3D phenotypic analysis of neurons and organoids using data-driven cell segmentation-free machine learning Philipp Mergenthaler*, Santosh Hariharan*, James M. Pemberton, Corey Lourenco, Linda Z. Penn, David W. Andrews PLOS Computational Biology, DOI: 10.1371/journal.pcbi.1008630 Phindr3D is available on GitHub: GitHub - DWALab/Phindr3D

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Bernhardt, Boris C.; Fadaie, Fatemeh; Liu, Min; Caldairou, Benoit; +6 Authors

    OBJECTIVE. To assess whether HS severity is mirrored at the level of large-scale networks. METHODS. We studied preoperative high-resolution anatomical and diffusion-weighted MRI of 44 TLE patients with histopathological diagnosis of HS (n=25; TLE-HS) and isolated gliosis (n=19; TLE-G), and 25 healthy controls. Hippocampal measurements included surface-based subfield mapping of atrophy and T2 hyperintensity indexing cell loss and gliosis, respectively. Whole-brain connectomes were generated via diffusion tractography and examined using graph theory along with a novel network control theory paradigm which simulates functional dynamics from structural network data. RESULTS. Compared to controls, we observed markedly increased path length and decreased clustering in TLE-HS compared to controls, indicating lower global and local network efficiency, while TLE-G showed only subtle alterations. Similarly, network controllability was lower in TLE-HS only, suggesting limited range of functional dynamics. Hippocampal imaging markers were positively associated with macroscale network alterations, particularly in ipsilateral CA1-3. Systematic assessment across several networks revealed maximal changes in the hippocampal circuity. Findings were consistent when correcting for cortical thickness, suggesting independence from grey matter atrophy. CONCLUSIONS. Severe HS is associated with marked remodeling of connectome topology and structurally-governed functional dynamics in TLE, as opposed to isolated gliosis which has negligible effects. Cell loss, particularly in CA1-3, may exert a cascading effect on brain-wide connectomes, underlining coupled disease processes across multiple scales. Data_phen_conn_dryadPhenotypic information and mean connectome feature data for Bernhardt et al. (2019) Temporal lobe epilepsy: hippocampal pathology modulates white matter connectome topology and controllability. Neurology

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ DANS-EASYarrow_drop_down
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    DANS-EASY
    Dataset . 2019
    Data sources: B2FIND
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    NARCIS; ZENODO; DRYAD
    Dataset . 2019
    License: CC 0
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ DANS-EASYarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      DANS-EASY
      Dataset . 2019
      Data sources: B2FIND
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      NARCIS; ZENODO; DRYAD
      Dataset . 2019
      License: CC 0
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Kember, Allan J.; Scott, Heather M.; O'Brien, Louise M.; Borazjani, Ali; +6 Authors

    Supplementary File 1: R Code and output - Demographic AnalysisThis is a stand alone report containing the code and output of an R script, which was generated by the "Compile Report" function in RStudio (R Statistical Software package (version 3.2.4 (2016-03-10))). This code summarizes the demographic, obstetric, and sleep behaviour of the participants (collected via a questionnaire completed by each participant on her first sleep test) and compares these data between all participants whose first sleep test was PrenaBelt (followed by sham-PrenaBelt on the second sleep test) versus all participants whose first sleep test was sham-PrenaBelt (followed by PrenaBelt on the second sleep test).Code and output - Demographic Analysis.docxSupplementary File 2: R Code and output - PSG AnalysisThis is a stand alone report containing the code and output of an R script, which was generated by the "Compile Report" function in RStudio (R Statistical Software package (version 3.2.4 (2016-03-10))). This code processes the polysomnography (PSG) sleep reports in full, making within-participant (paired) comparisons and between-participant (unpaired) comparisons. The sleep reports were generated by Embla Sandman Elite sleep diagnostic software (Natus Medical Incorporated, Pleasanton, USA). The data in the PSG sleep reports was collected via Pro-Tech zRIP Durabelts (Philips Respironics, Murrysville, USA) for respiration, PT1 pressure transducers (BRAEBON Medical Corporation, Kanata, Canada) for airflow and snoring, electrodes (Natus Medical Incorporated, Pleasanton, USA) for ECG/EEG/EOG/EMG, and finger-tip pulse oximetry for peripheral blood oxygen saturation (SpO2) in accordance with the American Academy of Sleep Medicine 2014 guidelines. Audio and video data were also recorded and used in order to determine body position and snoring.Code and output - PSG Analysis.docxSupplementary File 3: R Code and output - Feedback AnalysisThis is a stand alone report containing the code and output of an R script, which was generated by the "Compile Report" function in RStudio (R Statistical Software package (version 3.2.4 (2016-03-10))). This code processes the participants' feedback on the PrenaBelt (collected via a questionnaire completed by each participant after each sleep test). It summarizes these data, completes within-participant (paired) comparison of these data ("before/after"), and completes between-participants (unpaired) comparison of these data (bulk test for differences between all PrenaBelt sleep test nights versus all sham-PrenaBelt nights).Code and output - Feedback Analysis.docxSupplementary File 4: R Code and output - Self-Report Accuracy AnalysisThis is a stand alone report containing the code and output of an R script, which was generated by the "Compile Report" function in RStudio (R Statistical Software package (version 3.2.4 (2016-03-10))). This code compares each participant's perception of her sleep behaviours (collected via a questionnaire completed by each participant after each sleep test) to her polysomnography-determined sleep behaviours (collected via audio and video and Embla Sandman Elite sleep diagnostic software (Natus Medical Incorporated, Pleasanton, USA)) in order to determine the ability of participants to accurately recall their sleep onset position, waking position, number of position changes during the night, and percentage of sleep time in each position.Code and output - Self-Report Accuracy Analysis.docx OBJECTIVE: To evaluate whether the percentage of time spent supine during sleep in the third trimester of pregnancy could be reduced using a positional therapy device (PrenaBelt) compared with a sham device. DESIGN: A double-blind, randomized, sham-controlled, crossover pilot trial. SETTING: Conducted between March 2016 and January 2017, at a single, tertiary-level center in Canada. PARTICIPANTS: Twenty-three participants entered the study. Twenty participants completed the study. Participants were low-risk, singleton, third-trimester pregnant women aged 18 years and older with BMI <35 at the first antenatal appointment for the index pregnancy and without known fetal abnormalities, pregnancy complications, or medical conditions complicating sleep. INTERVENTIONS: A two-night, polysomnography study in a sleep laboratory. Participants were randomized by computer-generated, one-to-one, simple randomization to receive either a the PrenaBelt or a sham-PrenaBelt on the 1st night and were crossed over to the alternate device on the 2nd night. Allocation concealment was by unmarked, security-tinted, sealed envelopes. Participants, the recruiter, and personnel involved in setting up, conducting, scoring, and interpreting the polysomnogram were blinded to allocation. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was the percentage of time spent supine during sleep. Secondary outcomes included maternal sleep architecture, respiration, self-reported sleep position, and feedback. RESULTS: The median percentage of sleep time supine was reduced from 16.4% on the sham night to 3.5% on the PrenaBelt night (pseudomedian=5.8, p=0.03). We were unable to demonstrate differences in sleep architecture or respiration. Participants underestimated the time they spent sleeping supine by 7.0%, and six (30%) participants indicated they would make changes to the PrenaBelt. There were no harms in this study. CONCLUSIONS: This study demonstrates that the percentage of sleep time supine during late pregnancy can be significantly reduced via positional therapy. TRIAL REGISTRATION: ClinicalTrials.gov NCT02377817

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    DANS-EASY
    Dataset . 2018
    Data sources: B2FIND
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    DRYAD; ZENODO; NARCIS
    Dataset . 2018
    License: CC 0
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      DANS-EASY
      Dataset . 2018
      Data sources: B2FIND
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      DRYAD; ZENODO; NARCIS
      Dataset . 2018
      License: CC 0
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Mielke, Alexander; Preis, Anna; Samuni, Liran; Gogarten, Jan F.; +2 Authors

    Living in permanent social groups forces animals to make decisions about when, how and with whom to interact, requiring decisions to be made that integrate multiple sources of information. Changing social environments can influence this decision-making process by constraining choice or altering the likelihood of a positive outcome. Here, we conceptualised grooming as a choice situation where an individual chooses one of a number of potential partners. Studying two wild populations of sympatric primate species, sooty mangabeys (Cercocebus atys atys) and Western chimpanzees (Pan troglodytes verus), we tested what properties of potential partners influenced grooming decisions, including their relative value based on available alternatives and the social relationships of potential partners with bystanders who could observe the outcome of the decision. Across 1,529 decision events, multiple partner attributes (e.g. dominance ranks, social relationship quality, reproductive state, partner sex) influenced choice. Individuals preferred to initiate grooming with partners of similar global rank, but this effect was driven by a bias towards partners with a high rank compared to other locally available options. Individuals also avoided grooming partners who had strong social relationships with at least one bystander. Results indicated flexible decision-making in grooming interactions in both species, based on a partner’s value given the local social environment. Viewing partner choice as a value-based decision-making process allows researchers to compare how different species solve similar social problems. Data Model1Data for Models 1-1 and 1-2Data Model2Data for Models 2-1 and 2-2Script Model 1 and 2Scripts necessary to analyse Models 1 and 2

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    DANS-EASY
    Dataset . 2018
    Data sources: B2FIND
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO; DRYAD; NARCIS
    Dataset . 2018
    License: CC 0
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      DANS-EASY
      Dataset . 2018
      Data sources: B2FIND
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO; DRYAD; NARCIS
      Dataset . 2018
      License: CC 0
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/