cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.8119169
title: Movies and VRML files illustrating Figure 7 (b,c). from Volumetric finite-element modelling of biological growth

description: Differential growth is the driver of tissue morphogenesis in plants, and also plays a fundamental role in animal development. Although the contributions of growth to shape change have been captured through modelling tissue sheets or isotropic volumes, a framework for modelling both isotropic and anisotropic volumetric growth in three dimensions over large changes in size and shape has been lacking. Here, we describe an approach based on finite-element modelling of continuous volumetric structures, and apply it to a range of forms and growth patterns, providing mathematical validation, for examples, that admit analytic solution. We show that a major difference between sheet and bulk tissues is that the growth of bulk tissue is more constrained, reducing the possibility of tissue conflict resolution through deformations such as buckling. Tissue sheets or cylinders may be generated from bulk shapes through anisotropic specified growth, oriented by a polarity field. A second polarity field, orthogonal to the first, allows sheets with varying lengths and widths to be generated, as illustrated by the wide range of leaf shapes observed in nature. The framework we describe thus provides a key tool for developing hypotheses for plant morphogenesis and is also applicable to other tissues that deform through differential growth or contraction.
DOI: 10.6084/m9.figshare.8119169.v1
title: Movies and VRML files illustrating Figure 7 (b,c). from Volumetric finite-element modelling of biological growth

description: Differential growth is the driver of tissue morphogenesis in plants, and also plays a fundamental role in animal development. Although the contributions of growth to shape change have been captured through modelling tissue sheets or isotropic volumes, a framework for modelling both isotropic and anisotropic volumetric growth in three dimensions over large changes in size and shape has been lacking. Here, we describe an approach based on finite-element modelling of continuous volumetric structures, and apply it to a range of forms and growth patterns, providing mathematical validation, for examples, that admit analytic solution. We show that a major difference between sheet and bulk tissues is that the growth of bulk tissue is more constrained, reducing the possibility of tissue conflict resolution through deformations such as buckling. Tissue sheets or cylinders may be generated from bulk shapes through anisotropic specified growth, oriented by a polarity field. A second polarity field, orthogonal to the first, allows sheets with varying lengths and widths to be generated, as illustrated by the wide range of leaf shapes observed in nature. The framework we describe thus provides a key tool for developing hypotheses for plant morphogenesis and is also applicable to other tissues that deform through differential growth or contraction.
DOI: 10.6084/m9.figshare.8119058
title: Mapping human microbiome drug metabolism by gut bacteria and their genes

description: Data sets for analysis and visualization pipelines for screening the capacity of common gut bacteria to metabolize oral drugs.############################################################Analysis schemes are provided in AnalysisSchemes subfolder.Subfolders Input and Output contain tables and figure files to reproduce tables and figures from the corresponding study. See analysis schemes and the project code readme files for further details. <br>############################################################The project code is deposited on GitHub (https://github.com/mszimmermann/drug-bacteria-gene_mapping) and consists of four pipelines:1) Drug Screen AnalysisData are in Raw_DrugScreenAnalysis subfolder. <br>Perform differential analysis and hierarchical clustering of the metabolism patterns of 271 oral drugs by 76 diverse human gut bacteria (and four pH controls).<br><br>2) Drug Metabolism Products AnalysisData files are in Raw_DrugMetabolismProducts subfolder. <br>Perform differential analysis of metabolites co-occuring with specific drugs measured by untargeted mass-spectrometry.<br>3) Drug-metabolizing Gene Products AnalysisData files are in Raw_DrugMetabolizingGeneProducts subfolder. <br>Perform protein identity analysis for the identified bacterial gene products.<br>4) Gain-of-Function Screen AnalysisData files are in Raw_GainOfFunction subfolder. <br>Reproduce other manuscript figures (including gain-of-function bacterial gene identification screen). <br><br>############################################################ This project is part of the work by Michael Zimmermann, Maria Zimmermann-Kogadeeva, Rebekka Wegmann and Andrew L. Goodman.
DOI: 10.6084/m9.figshare.8119058.v1
title: Mapping human microbiome drug metabolism by gut bacteria and their genes

description: Data sets for analysis and visualization pipelines for screening the capacity of common gut bacteria to metabolize oral drugs.############################################################Analysis schemes are provided in AnalysisSchemes subfolder.Subfolders Input and Output contain tables and figure files to reproduce tables and figures from the corresponding study. See analysis schemes and the project code readme files for further details. <br>############################################################The project code is deposited on GitHub (https://github.com/mszimmermann/drug-bacteria-gene_mapping) and consists of four pipelines:1) Drug Screen AnalysisData are in Raw_DrugScreenAnalysis subfolder. <br>Perform differential analysis and hierarchical clustering of the metabolism patterns of 271 oral drugs by 76 diverse human gut bacteria (and four pH controls).<br><br>2) Drug Metabolism Products AnalysisData files are in Raw_DrugMetabolismProducts subfolder. <br>Perform differential analysis of metabolites co-occuring with specific drugs measured by untargeted mass-spectrometry.<br>3) Drug-metabolizing Gene Products AnalysisData files are in Raw_DrugMetabolizingGeneProducts subfolder. <br>Perform protein identity analysis for the identified bacterial gene products.<br>4) Gain-of-Function Screen AnalysisData files are in Raw_GainIfFunction subfolder. <br>Reproduce other manuscript figures (including gain-of-function bacterial gene identification screen). <br><br>############################################################ This project is part of the work by Michael Zimmermann, Maria Zimmermann-Kogadeeva, Rebekka Wegmann and Andrew L. Goodman.
DOI: 10.6084/m9.figshare.8119058.v2
title: Mapping human microbiome drug metabolism by gut bacteria and their genes

description: Data sets for analysis and visualization pipelines for screening the capacity of common gut bacteria to metabolize oral drugs.############################################################Analysis schemes are provided in AnalysisSchemes subfolder.Subfolders Input and Output contain tables and figure files to reproduce tables and figures from the corresponding study. See analysis schemes and the project code readme files for further details. <br>############################################################The project code is deposited on GitHub (https://github.com/mszimmermann/drug-bacteria-gene_mapping) and consists of four pipelines:1) Drug Screen AnalysisData are in Raw_DrugScreenAnalysis subfolder. <br>Perform differential analysis and hierarchical clustering of the metabolism patterns of 271 oral drugs by 76 diverse human gut bacteria (and four pH controls).<br><br>2) Drug Metabolism Products AnalysisData files are in Raw_DrugMetabolismProducts subfolder. <br>Perform differential analysis of metabolites co-occuring with specific drugs measured by untargeted mass-spectrometry.<br>3) Drug-metabolizing Gene Products AnalysisData files are in Raw_DrugMetabolizingGeneProducts subfolder. <br>Perform protein identity analysis for the identified bacterial gene products.<br>4) Gain-of-Function Screen AnalysisData files are in Raw_GainIfFunction subfolder. <br>Reproduce other manuscript figures (including gain-of-function bacterial gene identification screen). <br><br>############################################################ This project is part of the work by Michael Zimmermann, Maria Zimmermann-Kogadeeva, Rebekka Wegmann and Andrew L. Goodman.
DOI: 10.6084/m9.figshare.8118992
title: GADO genes 01-02-2018

description: Data used to run GADO command line: https://github.com/molgenis/systemsgenetics/wiki/GADO-Command-line
DOI: 10.6084/m9.figshare.8118992.v1
title: GADO genes 01-02-2018

description: Data used to run GADO command line: https://github.com/molgenis/systemsgenetics/wiki/GADO-Command-line
DOI: 10.6084/m9.figshare.8118980
title: Paramedic-Identified Enablers of and Barriers to Pediatric Seizure Management: A Multicenter, Qualitative Study

description: <b>Background:</b> Seizures have the potential to cause significant morbidity and mortality, and are a common reason emergency medical services (EMS) are requested for a child. An evidence-based guideline (EBG) for pediatric prehospital seizures was published and has been implemented as protocol in multiple EMS systems. Knowledge translation and protocol adherence in medicine can be incomplete. In EMS, systems-based factors and providers’ attitudes and beliefs may contribute to incomplete knowledge translation and protocol implementation. <b>Objective:</b> The purpose of this study was to identify paramedic attitudes and beliefs regarding pediatric seizure management and regarding potential barriers to and enablers of adherence to evidence-based pediatric seizure protocols in multiple EMS systems. <b>Methods:</b> This was a qualitative study utilizing semi-structured interviews of paramedics who recently transported actively seizing 0–17 year-old patients in 3 different urban EMS systems. Interviewers explored the providers’ decision-making during their recent case and regarding seizures in general. Interview questions explored barriers to and enablers of protocol adherence. Two investigators used the grounded theory approach and constant comparison to independently analyze transcribed interview recordings until thematic saturation was reached. Findings were validated with follow-up member-checking interviews. <b>Results:</b> Several themes emerged from the 66 interviewed paramedics. Enablers of protocol adherence included point-of-care references, the availability of different routes for midazolam and availability of online medical control. Systems-level barriers included equipment availability, controlled substance management, infrequent pediatric training, and protocol ambiguity. Provider-level barriers included concerns about respiratory depression, provider fatigue, preferences for specific routes, febrile seizure perceptions, and inaccurate methods of weight estimation. Paramedics suggested system improvements to address dose standardization, protocol clarity, simplified controlled substance logistics, and equipment availability. <b>Conclusions:</b> Paramedics identified enablers of and barriers to adherence to evidence-based pediatric seizure protocols. The identified barriers existed at both the provider and systems levels. Paramedics identified multiple potential solutions to overcome several barriers to protocol adherence. Future research should focus on using the findings of this study to revise seizure protocols and to deploy measures to improve protocol implementation. Future research should also analyze process and outcome measures before and after the implementation of revised seizure protocols informed by the findings of this study.
DOI: 10.6084/m9.figshare.8118980.v2
title: Paramedic-Identified Enablers of and Barriers to Pediatric Seizure Management: A Multicenter, Qualitative Study

description: <b>Background:</b> Seizures have the potential to cause significant morbidity and mortality, and are a common reason emergency medical services (EMS) are requested for a child. An evidence-based guideline (EBG) for pediatric prehospital seizures was published and has been implemented as protocol in multiple EMS systems. Knowledge translation and protocol adherence in medicine can be incomplete. In EMS, systems-based factors and providers’ attitudes and beliefs may contribute to incomplete knowledge translation and protocol implementation. <b>Objective:</b> The purpose of this study was to identify paramedic attitudes and beliefs regarding pediatric seizure management and regarding potential barriers to and enablers of adherence to evidence-based pediatric seizure protocols in multiple EMS systems. <b>Methods:</b> This was a qualitative study utilizing semi-structured interviews of paramedics who recently transported actively seizing 0–17 year-old patients in 3 different urban EMS systems. Interviewers explored the providers’ decision-making during their recent case and regarding seizures in general. Interview questions explored barriers to and enablers of protocol adherence. Two investigators used the grounded theory approach and constant comparison to independently analyze transcribed interview recordings until thematic saturation was reached. Findings were validated with follow-up member-checking interviews. <b>Results:</b> Several themes emerged from the 66 interviewed paramedics. Enablers of protocol adherence included point-of-care references, the availability of different routes for midazolam and availability of online medical control. Systems-level barriers included equipment availability, controlled substance management, infrequent pediatric training, and protocol ambiguity. Provider-level barriers included concerns about respiratory depression, provider fatigue, preferences for specific routes, febrile seizure perceptions, and inaccurate methods of weight estimation. Paramedics suggested system improvements to address dose standardization, protocol clarity, simplified controlled substance logistics, and equipment availability. <b>Conclusions:</b> Paramedics identified enablers of and barriers to adherence to evidence-based pediatric seizure protocols. The identified barriers existed at both the provider and systems levels. Paramedics identified multiple potential solutions to overcome several barriers to protocol adherence. Future research should focus on using the findings of this study to revise seizure protocols and to deploy measures to improve protocol implementation. Future research should also analyze process and outcome measures before and after the implementation of revised seizure protocols informed by the findings of this study.
DOI: 10.6084/m9.figshare.8118980.v1
title: Paramedic-Identified Enablers of and Barriers to Pediatric Seizure Management: A Multicenter, Qualitative Study

description: <b>Background:</b> Seizures have the potential to cause significant morbidity and mortality, and are a common reason emergency medical services (EMS) are requested for a child. An evidence-based guideline (EBG) for pediatric prehospital seizures was published and has been implemented as protocol in multiple EMS systems. Knowledge translation and protocol adherence in medicine can be incomplete. In EMS, systems-based factors and providers’ attitudes and beliefs may contribute to incomplete knowledge translation and protocol implementation. <b>Objective:</b> The purpose of this study was to identify paramedic attitudes and beliefs regarding pediatric seizure management and regarding potential barriers to and enablers of adherence to evidence-based pediatric seizure protocols in multiple EMS systems. <b>Methods:</b> This was a qualitative study utilizing semi-structured interviews of paramedics who recently transported actively seizing 0–17 year-old patients in 3 different urban EMS systems. Interviewers explored the providers’ decision-making during their recent case and regarding seizures in general. Interview questions explored barriers to and enablers of protocol adherence. Two investigators used the grounded theory approach and constant comparison to independently analyze transcribed interview recordings until thematic saturation was reached. Findings were validated with follow-up member-checking interviews. <b>Results:</b> Several themes emerged from the 66 interviewed paramedics. Enablers of protocol adherence included point-of-care references, the availability of different routes for midazolam and availability of online medical control. Systems-level barriers included equipment availability, controlled substance management, infrequent pediatric training, and protocol ambiguity. Provider-level barriers included concerns about respiratory depression, provider fatigue, preferences for specific routes, febrile seizure perceptions, and inaccurate methods of weight estimation. Paramedics suggested system improvements to address dose standardization, protocol clarity, simplified controlled substance logistics, and equipment availability. <b>Conclusions:</b> Paramedics identified enablers of and barriers to adherence to evidence-based pediatric seizure protocols. The identified barriers existed at both the provider and systems levels. Paramedics identified multiple potential solutions to overcome several barriers to protocol adherence. Future research should focus on using the findings of this study to revise seizure protocols and to deploy measures to improve protocol implementation. Future research should also analyze process and outcome measures before and after the implementation of revised seizure protocols informed by the findings of this study.
DOI: 10.21954/ou.rd.8118947
title: Transcripts from 3 Focus Groups

description: These transcripts were collected from:<br>2 focus groups conducted in Pontefract, West Yorkshire1 focus group conducted in the Mumbles, Swansea, Wales<br>
DOI: 10.21954/ou.rd.8118947.v1
title: Transcripts from 3 Focus Groups

description: These transcripts were collected from:<br>2 focus groups conducted in Pontefract, West Yorkshire1 focus group conducted in the Mumbles, Swansea, Wales<br>
DOI: 10.6084/m9.figshare.8118926
title: HPO build 135

description: HPO obo made by the: Human Phenotype Ontology<br>
DOI: 10.6084/m9.figshare.8118914
title: GADO HPO Prediction info 01-02-2018

description: Data used to run GADO command line: https://github.com/molgenis/systemsgenetics/wiki/GADO-Command-line
DOI: 10.6084/m9.figshare.8118914.v2
title: GADO HPO Prediction info 01-02-2018

description: Data used to run GADO command line: https://github.com/molgenis/systemsgenetics/wiki/GADO-Command-line
DOI: 10.6084/m9.figshare.8118914.v1
title: GADO HPO Prediction info 01-02-2018

description: Data used to run GADO command line: https://github.com/molgenis/systemsgenetics/wiki/GADO-Command-line
DOI: 10.6084/m9.figshare.8118710
title: Datasets(Original, Mean, Median, Most Frequent).zip

description: The dataset is transformed into Matlab format. They are designed to be in cell formats. Each cell is a matrix which consists of a column representing the gene and row for the subject.Each dataset is organized in a separate directory. The directory contains four versions: <br>a) Original dataset, <br>b) Imputed dataset by MEAN,<br>c) Imputed dataset by MEDIAN,d) Imputed dataset by Most Frequent,
DOI: 10.6084/m9.figshare.8118710.v1
title: Datasets(Original, Mean, Median, Most Frequent).zip

description: The dataset is transformed into Matlab format. They are designed to be in cell formats. Each cell is a matrix which consists of a column representing the gene and row for the subject.Each dataset is organized in a separate directory. The directory contains four versions: <br>a) Original dataset, <br>b) Imputed dataset by MEAN,<br>c) Imputed dataset by MEDIAN,d) Imputed dataset by Most Frequent,
DOI: 10.6084/m9.figshare.8118704.v1
title: Differential Impact of Mitral Valve Repair on Outcome of Coronary Artery Bypass Grafting With or Without Surgical Ventricular Reconstruction in the Surgical Treatment for Ischemic Heart Failure (STICH) Trial

description: <b><i>Background</i></b>: This study examined the impact of mitral valve repair (MVRe) on survival of patients with moderate or severe (≥2+) MR and ischemic cardiomyopathy randomized to coronary artery bypass grafting (CABG) versus CABG+surgical ventricular reconstruction (SVR) in the STICH trial. Methods: Among patients with moderate or severe MR and ischemic cardiomyopathy undergoing CABG or CABG+SVR, the impact of MVRe on mortality between the two treatment arms was compared. Results: Among 867 patients with assessment of baseline MR severity, 211 had moderate or severe MR. After excluding 7 patients who underwent mitral valve replacement, 50, 44, 62, and 48 patients underwent CABG, CABG+MVRe, CABG+SVR, and CABG+SVR+MVRe, respectively. Four-year mortality rates were lower following CABG+MVRe than CABG alone (16% vs. 55%; adjusted hazard ratio [HR] 0.30; 95% CI 0.13-0.71). In contrast, the CABG+SVR+MVRe and CABG+SVR groups had similar 4-year mortality of 39% vs. 39% (adjusted HR 0.88; 95% CI 0.46-1.70). MVRe had a more favorable effect on survival in patients undergoing CABG alone compared to CABG+SVR (<i>p</i>=0.013). Baseline MR severity was similar between patients that received CABG+MVRe and those that underwent CABG+SVR+MVRe. A larger proportion of patients demonstrated a reduction in MR between 4 and 24 months after CABG+MVRe compared to CABG+SVR+MVRe (50.0% versus 25.0%, <i>p</i>=0.023). <b><i>Conclusion</i></b>: In patients with moderate or severe MR and ischemic cardiomyopathy undergoing CABG, MVRe appears to have a favorable effect on survival. The addition of SVR to CABG may attenuate the anticipated benefits of MVRe by limiting the long-term reduction of MR with MVRe.
DOI: 10.6084/m9.figshare.8118692
title: Metabolite BridgeDb ID Mapping Database (20190509)

description: BridgeDb ID mapping database for metabolites, using HMDB 4.0 (Release of 16 Jan. 2019), ChEBI 175 (Release of 01 May 2019), and Wikidata (09 May 2019) as data sources.<br>Quality control was performed with BridgeDb (2.3.1.1), with updated DrugBank identifiers (including DBSALT, see the QC report 20190509_against_20190509). Furthermore, we have over 1600 more EPA CompTox, 5000 Wikidata, 4500 PubChem compound and almost 400 new LipidMaps identifiers supported. See our QC report (20190509_against_20190207).<br><i>This work was funded by ELIXIR, the research infrastructure for life-science data.</i>
DOI: 10.6084/m9.figshare.8118692.v1
title: Metabolite BridgeDb ID Mapping Database (20190509)

description: BridgeDb ID mapping database for metabolites, using HMDB 4.0 (Release of 16 Jan. 2019), ChEBI 175 (Release of 01 May 2019), and Wikidata (09 May 2019) as data sources.<br>Quality control was performed with BridgeDb (2.3.1.1), with updated DrugBank identifiers (including DBSALT, see the QC report 20190509_against_20190509). Furthermore, we have over 1600 more EPA CompTox, 5000 Wikidata, 4500 PubChem compound and almost 400 new LipidMaps identifiers supported. See our QC report (20190509_against_20190207).<br><i>This work was funded by ELIXIR, the research infrastructure for life-science data.</i>