cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.11897151
title: Supplementary Material for: Employment in Myasthenia Gravis: A Systematic Literature Review and Meta-Analysis

description: <b><i>Introduction:</i></b> Myasthenia gravis (MG) is an autoimmune disease whose period of typical onset is around 20–40 years (i.e., early onset), thus in the peak of working age, or around 60–80 years (i.e., late onset). However, the information on work-related issues and employment status are sparse and not systematically reported. Therefore, we performed a systematic literature review with meta-analysis to address the employment status of MG patients. <b><i>Methods:</i></b> We searched for papers reporting employment status on participants with MG published between January 2000 and May 2019. Information on employment was extracted. Random-effects models were used to produce meta-analytic estimates for the proportion of employed patients. <b><i>Results:</i></b> In total, 1,045 records were retrieved, of which 19 fitted the inclusion criteria. In total, 3,600 participants (average age 47.5, range 35–60) were included in the studies and 1,579 of them were employed. The proportion of employed patients varied from 28 to 82%, with an extreme heterogeneity between studies. Overall, the pooled proportion of workers was 50% (95% CI 41–60%). Subgroup analyses suggested a possible, although not significant, higher proportion of workers among women, younger participants, those with a higher level of education, shorter MG duration, and less frequently thymectomized, whereas a lower proportion was observed among those with generalized, bulbar, and respiratory symptoms. <b><i>Conclusions:</i></b> The results of our meta-analysis show that the percentage of employment is considerably low if we take into account that the mean age of MG patients involved in the included studies was around 48 years, thus in peak of working life. Therefore, it is important to understand what kind of influence MG exerts on work dynamics.
DOI: 10.6084/m9.figshare.11897151.v1
title: Supplementary Material for: Employment in Myasthenia Gravis: A Systematic Literature Review and Meta-Analysis

description: <b><i>Introduction:</i></b> Myasthenia gravis (MG) is an autoimmune disease whose period of typical onset is around 20–40 years (i.e., early onset), thus in the peak of working age, or around 60–80 years (i.e., late onset). However, the information on work-related issues and employment status are sparse and not systematically reported. Therefore, we performed a systematic literature review with meta-analysis to address the employment status of MG patients. <b><i>Methods:</i></b> We searched for papers reporting employment status on participants with MG published between January 2000 and May 2019. Information on employment was extracted. Random-effects models were used to produce meta-analytic estimates for the proportion of employed patients. <b><i>Results:</i></b> In total, 1,045 records were retrieved, of which 19 fitted the inclusion criteria. In total, 3,600 participants (average age 47.5, range 35–60) were included in the studies and 1,579 of them were employed. The proportion of employed patients varied from 28 to 82%, with an extreme heterogeneity between studies. Overall, the pooled proportion of workers was 50% (95% CI 41–60%). Subgroup analyses suggested a possible, although not significant, higher proportion of workers among women, younger participants, those with a higher level of education, shorter MG duration, and less frequently thymectomized, whereas a lower proportion was observed among those with generalized, bulbar, and respiratory symptoms. <b><i>Conclusions:</i></b> The results of our meta-analysis show that the percentage of employment is considerably low if we take into account that the mean age of MG patients involved in the included studies was around 48 years, thus in peak of working life. Therefore, it is important to understand what kind of influence MG exerts on work dynamics.
DOI: 10.6084/m9.figshare.11897112
title: Coral Habitat Orthomosaics to Obtain Structural Complexity

description: Dataset used for structural complexity analysis of coral habitats. Orthomosaics were used to produce Ruggedness Index rasters and evaluate differences. Benthic cover quantification raw values and shape files are provided.<br>
DOI: 10.6084/m9.figshare.11897112.v1
title: Coral Habitat Orthomosaics to Obtain Structural Complexity

description: Dataset used for structural complexity analysis of coral habitats. Orthomosaics were used to produce Ruggedness Index rasters and evaluate differences. Benthic cover quantification raw values and shape files are provided.<br>
DOI: 10.6084/m9.figshare.11896914
title: Patient Metadata

description: This file contains a description of the metadata for each of the serum samples that were evaluated in the project.
DOI: 10.6084/m9.figshare.11896944
title: Tables 1-6 csv

description: Curculionid beetles associated with willow (<em>Salix</em> spp.) were surveyed at 42 sites across Europe, from Greece (lat. 38.8 °N) to arctic Norway (lat. 69.7 °N). DNA sequence data provide additional verification of identifications and geographic clustering.
DOI: 10.6084/m9.figshare.11896914.v1
title: Patient Metadata

description: This file contains a description of the metadata for each of the serum samples that were evaluated in the project.
DOI: 10.6084/m9.figshare.11896851
title: Selected trajectories

description: Trajectories for the est results obtained from docking pesticides cataloged by the WHO on the beta-lactoglobulin from Bos taurus.Simulations carried out using FF14SB with TIP4P water. The trajectories shared here contain <b>only</b> the protein complexed with is ligand.To use these files a <i>prmtop</i> and a <i>mdcrd</i> are requiered. <br>For example,<br>Paraquat.prmtop and Paraquat.mdcrd<br>
DOI: 10.6084/m9.figshare.11896851.v1
title: Selected trajectories

description: Trajectories for the est results obtained from docking pesticides cataloged by the WHO on the beta-lactoglobulin from Bos taurus.Simulations carried out using FF14SB with TIP4P water. The trajectories shared here contain <b>only</b> the protein complexed with is ligand.To use these files a <i>prmtop</i> and a <i>mdcrd</i> are requiered. <br>For example,<br>Paraquat.prmtop and Paraquat.mdcrd<br>
DOI: 10.6084/m9.figshare.11896542
title: Additional file 13 of Entomopathogenic nematode-associated microbiota: from monoxenic paradigm to pathobiome

description: Additional file 13. a. List of OTUs obtained with the V3V4 marker. b. List of OTUs obtained with rpoB marker. c. Venn diagram table detailing compositions of core and non-core OTUs of Figure 2a. d. List and frequency of OTUs associated with the S. carpocapsae IJs obtained with the V3V4 marker for which abundance in the whole dataset exceeded 0.1% (plotted in Figure 5.b). e. List and frequency of OTUs associated with S. carpocapsae IJs obtained with the rpoB marker for which abundance in the whole dataset exceeded 0.1% (plotted in Figure 5.a).
DOI: 10.6084/m9.figshare.11896542.v1
title: Additional file 13 of Entomopathogenic nematode-associated microbiota: from monoxenic paradigm to pathobiome

description: Additional file 13. a. List of OTUs obtained with the V3V4 marker. b. List of OTUs obtained with rpoB marker. c. Venn diagram table detailing compositions of core and non-core OTUs of Figure 2a. d. List and frequency of OTUs associated with the S. carpocapsae IJs obtained with the V3V4 marker for which abundance in the whole dataset exceeded 0.1% (plotted in Figure 5.b). e. List and frequency of OTUs associated with S. carpocapsae IJs obtained with the rpoB marker for which abundance in the whole dataset exceeded 0.1% (plotted in Figure 5.a).
DOI: 10.6084/m9.figshare.11896377
title: Additional file 4 of Prediction of new associations between ncRNAs and diseases exploiting multi-type hierarchical clustering

description: Additional file 4 Detailed list of associations involving the acquired immunodeficiency syndrome and similar disease terms in three hierarchical levels extracted by lP-HCLUS.
DOI: 10.6084/m9.figshare.11896380
title: Additional file 5 of Prediction of new associations between ncRNAs and diseases exploiting multi-type hierarchical clustering

description: Additional file 5 Comparative analysis of the ranking produced by lP-HCLUS and its competitors with respect to the new validated relationships in hMDD v3.2.
DOI: 10.6084/m9.figshare.11896377.v1
title: Additional file 4 of Prediction of new associations between ncRNAs and diseases exploiting multi-type hierarchical clustering

description: Additional file 4 Detailed list of associations involving the acquired immunodeficiency syndrome and similar disease terms in three hierarchical levels extracted by lP-HCLUS.
DOI: 10.6084/m9.figshare.11896380.v1
title: Additional file 5 of Prediction of new associations between ncRNAs and diseases exploiting multi-type hierarchical clustering

description: Additional file 5 Comparative analysis of the ranking produced by lP-HCLUS and its competitors with respect to the new validated relationships in hMDD v3.2.
DOI: 10.6084/m9.figshare.11896368
title: Additional file 3 of Prediction of new associations between ncRNAs and diseases exploiting multi-type hierarchical clustering

description: Additional file 3 Complete results of the comparative analysis between the predictions returned by lP-HCLUS from hMDD v3.0 and the new validated relationships in hMDD v3.2.
DOI: 10.6084/m9.figshare.11896368.v1
title: Additional file 3 of Prediction of new associations between ncRNAs and diseases exploiting multi-type hierarchical clustering

description: Additional file 3 Complete results of the comparative analysis between the predictions returned by lP-HCLUS from hMDD v3.0 and the new validated relationships in hMDD v3.2.
DOI: 10.6084/m9.figshare.11896305
title: Additional file 2 of GenEpi: gene-based epistasis discovery using machine learning

description: Additional file 2. The R script to draw a heatmap for GTEx dataset.
DOI: 10.6084/m9.figshare.11896305.v1
title: Additional file 2 of GenEpi: gene-based epistasis discovery using machine learning

description: Additional file 2. The R script to draw a heatmap for GTEx dataset.
DOI: 10.6084/m9.figshare.11896296
title: Additional file 1 of Benzodiazepines in the oral fluid of Spanish drivers

description: Additional file 1: Figure S1. Distribution of the percentage of tests positive for any drug and tests positive for benzodiazepines, by age. Figure S2. Distribution of medians and interquartile ranges for oral fluid nordiazepam concentrations, by age, for nordiazepam-positive cases. Figure S3. Distribution of medians and interquartile ranges for oral fluid alprazolam concentrations, by age, for alprazolam-positive cases. Table S1. Oral fluid drug testing devices used between 2011 and 2016: substances detected and cut-offs. Table S2. Roadside drug tests performed between 2011 and 2016 and the gender distribution of the Spanish population and the Spanish driving population. Table S3. Logistic regression analysis: for driver who tested positive for benzodiazepines and drivers who tested positive for benzodiazepines in conjunction with other drugs. Table S4. Benzodiazepine concentration deciles for all confirmed benzodiazepine-positive tests between 2011 and 2016.
DOI: 10.6084/m9.figshare.11896296.v1
title: Additional file 1 of Benzodiazepines in the oral fluid of Spanish drivers

description: Additional file 1: Figure S1. Distribution of the percentage of tests positive for any drug and tests positive for benzodiazepines, by age. Figure S2. Distribution of medians and interquartile ranges for oral fluid nordiazepam concentrations, by age, for nordiazepam-positive cases. Figure S3. Distribution of medians and interquartile ranges for oral fluid alprazolam concentrations, by age, for alprazolam-positive cases. Table S1. Oral fluid drug testing devices used between 2011 and 2016: substances detected and cut-offs. Table S2. Roadside drug tests performed between 2011 and 2016 and the gender distribution of the Spanish population and the Spanish driving population. Table S3. Logistic regression analysis: for driver who tested positive for benzodiazepines and drivers who tested positive for benzodiazepines in conjunction with other drugs. Table S4. Benzodiazepine concentration deciles for all confirmed benzodiazepine-positive tests between 2011 and 2016.
DOI: 10.6084/m9.figshare.11896269
title: Additional file 1 of Identification of DNA N6-methyladenine sites by integration of sequence features

description: Additional file 1: Tables S1, S2. Summary of performances of 4 predictors onÂ benchmark dataset and A. thaliana dataset.
DOI: 10.6084/m9.figshare.11896269.v1
title: Additional file 1 of Identification of DNA N6-methyladenine sites by integration of sequence features

description: Additional file 1: Tables S1, S2. Summary of performances of 4 predictors onÂ benchmark dataset and A. thaliana dataset.
DOI: 10.6084/m9.figshare.11896203
title: Additional file 3 of Combining feature selection and shape analysis uncovers precise rules for miRNA regulation in Huntington’s disease mice

description: Additional file 3: Table S3. Surface-matched miRNA-target pairs for which there is evidence for a binding site. This table shows the miR-target pairs for which (i) the Spearman’s score for plane matching is positive and has a p-value
DOI: 10.6084/m9.figshare.11896203.v1
title: Additional file 3 of Combining feature selection and shape analysis uncovers precise rules for miRNA regulation in Huntington’s disease mice

description: Additional file 3: Table S3. Surface-matched miRNA-target pairs for which there is evidence for a binding site. This table shows the miR-target pairs for which (i) the Spearman’s score for plane matching is positive and has a p-value
DOI: 10.6084/m9.figshare.11896200
title: Additional file 2 of Combining feature selection and shape analysis uncovers precise rules for miRNA regulation in Huntington’s disease mice

description: Additional file 2: Table S2. miRNA-target pairs retained by RF analysis. The p-values are the ones provided by the Altmann’s RF algorithm [27]. This table shows the Spearman’s score for surface matching (see Methods) and LFC values on the targets for all miRNA-target pairs.
DOI: 10.6084/m9.figshare.11896197
title: Additional file 1 of Combining feature selection and shape analysis uncovers precise rules for miRNA regulation in Huntington’s disease mice

description: Additional file 1: Table S1. Lists of nodes in miRNA and mRNA WGCNA modules. Module membership is indicated for mRNAs and miRNAs. NA, not applicable.
DOI: 10.6084/m9.figshare.11896200.v1
title: Additional file 2 of Combining feature selection and shape analysis uncovers precise rules for miRNA regulation in Huntington’s disease mice

description: Additional file 2: Table S2. miRNA-target pairs retained by RF analysis. The p-values are the ones provided by the Altmann’s RF algorithm [27]. This table shows the Spearman’s score for surface matching (see Methods) and LFC values on the targets for all miRNA-target pairs.
DOI: 10.6084/m9.figshare.11896197.v1
title: Additional file 1 of Combining feature selection and shape analysis uncovers precise rules for miRNA regulation in Huntington’s disease mice

description: Additional file 1: Table S1. Lists of nodes in miRNA and mRNA WGCNA modules. Module membership is indicated for mRNAs and miRNAs. NA, not applicable.
DOI: 10.6084/m9.figshare.11896005
title: Additional file 2 of A diet based on cured acorn-fed ham with oleic acid content promotes anti-inflammatory gut microbiota and prevents ulcerative colitis in an animal model

description: Additional file 2. Raw data table.
DOI: 10.6084/m9.figshare.11896005.v1
title: Additional file 2 of A diet based on cured acorn-fed ham with oleic acid content promotes anti-inflammatory gut microbiota and prevents ulcerative colitis in an animal model

description: Additional file 2. Raw data table.
DOI: 10.6084/m9.figshare.11895831
title: In situ data.xlsx

description: Dataset of the article titled"The distribution of aerosols and their impacts on the chlorophyll-<i>a </i>distribution in the South China Sea".The part includes the data used for generating the figures 6 & 9b. Column 1 is date of observation, Columns 2-4 are concentrations of the total nitrogen (TN), Nitrate (NO3-), Ammonium(NH4+) and total suspended particulates (TSP) in Yongxing Island, respectively.
DOI: 10.6084/m9.figshare.11895831.v1
title: In situ data.xlsx

description: Dataset of the article titled"The distribution of aerosols and their impacts on the chlorophyll-<i>a </i>distribution in the South China Sea".The part includes the data used for generating the figures 6 & 9b. Column 1 is date of observation, Columns 2-4 are concentrations of the total nitrogen (TN), Nitrate (NO3-), Ammonium(NH4+) and total suspended particulates (TSP) in Yongxing Island, respectively.
DOI: 10.6084/m9.figshare.11895798
title: Additional file 4 of Linked optical and gene expression profiling of single cells at high-throughput

description: Additional file 4. Python scripts for processing data.
DOI: 10.6084/m9.figshare.11895798.v1
title: Additional file 4 of Linked optical and gene expression profiling of single cells at high-throughput

description: Additional file 4. Python scripts for processing data.
DOI: 10.6084/m9.figshare.11895738
title: Additional file 5 of Macroevolutionary bursts and constraints generate a rainbow in a clade of tropical birds

description: Additional file 5: Table S3. Modularity Maximum Likelihoods. Maximum likelihood results of EMMLi model selection.
DOI: 10.6084/m9.figshare.11895741
title: Additional file 6 of Macroevolutionary bursts and constraints generate a rainbow in a clade of tropical birds

description: Additional file 6: Table S4. Sampling Table. Table of AMNH specimens from which color data were collected.
DOI: 10.6084/m9.figshare.11895732
title: Additional file 4 of Macroevolutionary bursts and constraints generate a rainbow in a clade of tropical birds

description: Additional file 4: Table S2. Model Fit Parameters. Statistics for each of the four relative fit models (Brownian Motion, OU, Delta), phylogenetic signal, and overall variance for each patch and each color PC.
DOI: 10.6084/m9.figshare.11895738.v1
title: Additional file 5 of Macroevolutionary bursts and constraints generate a rainbow in a clade of tropical birds

description: Additional file 5: Table S3. Modularity Maximum Likelihoods. Maximum likelihood results of EMMLi model selection.
DOI: 10.6084/m9.figshare.11895732.v1
title: Additional file 4 of Macroevolutionary bursts and constraints generate a rainbow in a clade of tropical birds

description: Additional file 4: Table S2. Model Fit Parameters. Statistics for each of the four relative fit models (Brownian Motion, OU, Delta), phylogenetic signal, and overall variance for each patch and each color PC.
DOI: 10.6084/m9.figshare.11895741.v1
title: Additional file 6 of Macroevolutionary bursts and constraints generate a rainbow in a clade of tropical birds

description: Additional file 6: Table S4. Sampling Table. Table of AMNH specimens from which color data were collected.
DOI: 10.6084/m9.figshare.11895723
title: Additional file 3 of Macroevolutionary bursts and constraints generate a rainbow in a clade of tropical birds

description: Additional file 3: Table S1. Arbutus Statistics By Patch. Absolute fit for each of the six statistics calculated by arbutus. If the value is for a given statistic is below p
DOI: 10.6084/m9.figshare.11895723.v1
title: Additional file 3 of Macroevolutionary bursts and constraints generate a rainbow in a clade of tropical birds

description: Additional file 3: Table S1. Arbutus Statistics By Patch. Absolute fit for each of the six statistics calculated by arbutus. If the value is for a given statistic is below p
DOI: 10.6084/m9.figshare.11895552
title: Additional file 6 of Transcriptional insights into the CD8+ T cell response in mono-HIV and HCV infection

description: Additional file 6.IFIT3- and STAT5A-targeting miRNAs
DOI: 10.6084/m9.figshare.11895552.v1
title: Additional file 6 of Transcriptional insights into the CD8+ T cell response in mono-HIV and HCV infection

description: Additional file 6.IFIT3- and STAT5A-targeting miRNAs
DOI: 10.6084/m9.figshare.11895543
title: Additional file 5 of Transcriptional insights into the CD8+ T cell response in mono-HIV and HCV infection

description: Additional file 5. CD8+ T cell DEGs from HCV resolvers compared with chronic progressors
DOI: 10.6084/m9.figshare.11895534
title: Additional file 4 of Transcriptional insights into the CD8+ T cell response in mono-HIV and HCV infection

description: Additional file 4.CD8+ T cell DEGs from HIV non-progressors compared with chronic progressors
DOI: 10.6084/m9.figshare.11895534.v1
title: Additional file 4 of Transcriptional insights into the CD8+ T cell response in mono-HIV and HCV infection

description: Additional file 4.CD8+ T cell DEGs from HIV non-progressors compared with chronic progressors
DOI: 10.6084/m9.figshare.11895543.v1
title: Additional file 5 of Transcriptional insights into the CD8+ T cell response in mono-HIV and HCV infection

description: Additional file 5. CD8+ T cell DEGs from HCV resolvers compared with chronic progressors
DOI: 10.6084/m9.figshare.11895525
title: Additional file 3 of Transcriptional insights into the CD8+ T cell response in mono-HIV and HCV infection

description: Additional file 3. CD8+ T cell DEGs from HCV chronic progressors compared with healthy donors
DOI: 10.6084/m9.figshare.11895525.v1
title: Additional file 3 of Transcriptional insights into the CD8+ T cell response in mono-HIV and HCV infection

description: Additional file 3. CD8+ T cell DEGs from HCV chronic progressors compared with healthy donors
DOI: 10.6084/m9.figshare.11895516
title: Additional file 2 of Transcriptional insights into the CD8+ T cell response in mono-HIV and HCV infection

description: Additional file 2. CD8+ T cell DEGs from HIV chronic progressors compared with healthy donors
DOI: 10.6084/m9.figshare.11895516.v1
title: Additional file 2 of Transcriptional insights into the CD8+ T cell response in mono-HIV and HCV infection

description: Additional file 2. CD8+ T cell DEGs from HIV chronic progressors compared with healthy donors
DOI: 10.6084/m9.figshare.11895450
title: Additional file 1 of How resource limitations and household economics mayÂ compromise efforts to safeguard children during outbreaks

description: Additional file 1. Supplemental File 1: Model implementations in the Wolfram language.
DOI: 10.6084/m9.figshare.11895450.v1
title: Additional file 1 of How resource limitations and household economics mayÂ compromise efforts to safeguard children during outbreaks

description: Additional file 1. Supplemental File 1: Model implementations in the Wolfram language.
DOI: 10.6084/m9.figshare.11895054
title: Selected docking results

description: Best results obtained from docking pesticides cataloged by the WHO on the beta-lactoglobulin from Bos taurus.
DOI: 10.6084/m9.figshare.11894682
title: A novel outlier-adapted multi-stage ensemble model with feature transformation for credit scoring

description: Three datasets are chosen from the UCI machine learning repository in this study, which have been extensively adopted in data-driven researches, including Australian and Japanese datasets (Asuncion & Newman, 2007), and Polish bankruptcy dataset (Zięba et al., 2016). The three datasets contain different numbers of samples and features. Each sample in a credit dataset can be classified into good credit or bad credit. The size of Australian credit dataset is 690, with 307 samples in good credit and 383 in bad, and its feature dimension is 14, with 6 numerical and 8 categorical features. The size of Japanese credit dataset is 690, with 307 samples in good credit and 383 in bad, and its feature dimension is 15, with 6 numerical and 9 categorical features. Similarly, there are 7027 samples in Polish bankruptcy dataset, with 6756 samples in good credit and 271 in bad, and its 64 input features are numerical. All the dimensions of the input features of the three datasets listed in Table 1 do not include the class labels.<br>