cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.15080239.v1
title: Additional file 5 of A comprehensive approach for microbiota and health monitoring in mouse colonies using metagenomic shotgun sequencing

description: FELASA list of pathogens investigated in the course of the study: comparison between standard vs NGS analyses. Each different line represents the species included in the FELASA list of pathogens. For each species there are 6 columns that describe a short taxonomy (superkingdom, NCBI Taxon ID, species); the last two columns indicates the number of positive mice identified by standard or NGS analyses as described in Matherial and Methods.
DOI: 10.6084/m9.figshare.15080242
title: Additional file 6 of A comprehensive approach for microbiota and health monitoring in mouse colonies using metagenomic shotgun sequencing

description: Raw data form NGS analyses (sample set B). The different lines represent the different species identified with the normalized counts. For each species there are 8 columns that describe the taxonomy (superkingdom, phylum, class, order, family, genus, species, Species ID). The following columns identify the reads of each sample.
DOI: 10.6084/m9.figshare.15080242.v1
title: Additional file 6 of A comprehensive approach for microbiota and health monitoring in mouse colonies using metagenomic shotgun sequencing

description: Raw data form NGS analyses (sample set B). The different lines represent the different species identified with the normalized counts. For each species there are 8 columns that describe the taxonomy (superkingdom, phylum, class, order, family, genus, species, Species ID). The following columns identify the reads of each sample.
DOI: 10.6084/m9.figshare.15080245
title: Additional file 7 of A comprehensive approach for microbiota and health monitoring in mouse colonies using metagenomic shotgun sequencing

description: Differences between SPF and non-SPF mice at phylum and family level. Each line represents phylum (average greater than 100 ppm in at least one of the two groups of samples) or family (average above 100 ppm in both groups of samples, except for Helicobacteraceae which are absent in the SPF mice) identified in SPF and non-SPF samples. Pvalues have been calculated by DSEQ2 in Bioconductor. Families and phyla whose differences were statistically significant show a pvalue&lt; 0,05.
DOI: 10.6084/m9.figshare.15080245.v1
title: Additional file 7 of A comprehensive approach for microbiota and health monitoring in mouse colonies using metagenomic shotgun sequencing

description: Differences between SPF and non-SPF mice at phylum and family level. Each line represents phylum (average greater than 100 ppm in at least one of the two groups of samples) or family (average above 100 ppm in both groups of samples, except for Helicobacteraceae which are absent in the SPF mice) identified in SPF and non-SPF samples. Pvalues have been calculated by DSEQ2 in Bioconductor. Families and phyla whose differences were statistically significant show a pvalue&lt; 0,05.
DOI: 10.6084/m9.figshare.15080251
title: Additional file 9 of A comprehensive approach for microbiota and health monitoring in mouse colonies using metagenomic shotgun sequencing

description: Taxonomic composition of gut microbiota at phylum level: comparison with other studies. Comparison between the present study and four published studies (indicated with author’s name and [ref.]). For each study are indicated: sequencing method; health/ microbiological status of mice; mice strain; type of sample (DNA source); relative abundance of each of the four most represented phyla of the gut microbiota.
DOI: 10.6084/m9.figshare.15080251.v1
title: Additional file 9 of A comprehensive approach for microbiota and health monitoring in mouse colonies using metagenomic shotgun sequencing

description: Taxonomic composition of gut microbiota at phylum level: comparison with other studies. Comparison between the present study and four published studies (indicated with author’s name and [ref.]). For each study are indicated: sequencing method; health/ microbiological status of mice; mice strain; type of sample (DNA source); relative abundance of each of the four most represented phyla of the gut microbiota.
DOI: 10.6084/m9.figshare.15080327
title: Additional file 2 of Genome wide DNA methylation analysis of alveolar capillary dysplasia lung tissue reveals aberrant methylation of genes involved in development including the FOXF1 locus

description: Additional file 2. Table S 2. Results of gene ontology enrichment analysis using Metascape (26).
DOI: 10.6084/m9.figshare.15080327.v1
title: Additional file 2 of Genome wide DNA methylation analysis of alveolar capillary dysplasia lung tissue reveals aberrant methylation of genes involved in development including the FOXF1 locus

description: Additional file 2. Table S 2. Results of gene ontology enrichment analysis using Metascape (26).
DOI: 10.5281/zenodo.5142664
title: MetaMIDI Dataset

description: We introduce the MetaMIDI Dataset (MMD) a large scale collection of 436,631 MIDI files and metadata. MMD contains artist and title metadata for 221,504 MIDI files, and genre metadata for 143,868 MIDI files, collected during the web-scraping process. MIDI files in MMD were matched against a collection of 32,000,000 30-second audio clips retrieved from Spotify, resulting in over 10,796,557 audio-MIDI matches. In addition, we linked 600,142 Spotify tracks with 1,094,901 MusicBrainz recordings to produce a set of 168,032 MIDI files that are matched to the MusicBrainz database. We also provide a set of 53,496 MIDI files using audio-MIDI matches where the derived metadata on Spotify is a fuzzy match to the web-scraped metadata. These links augment many files in the dataset with the extensive metadata available via the Spotify API and the MusicBrainz database. We anticipate that this collection of data will be of great use to MIR researchers addressing a variety of research topics.
DOI: 10.5281/zenodo.5147546
title: DICOMRT04

description: Test files for OnkoDICOM
DOI: 10.5281/zenodo.5142621
title: MetaMIDI Dataset

description: We introduce the MetaMIDI Dataset (MMD) a large scale collection of 436,631 MIDI files and metadata. MMD contains artist and title metadata for 221,504 MIDI files, and genre metadata for 143,868 MIDI files, collected during the web-scraping process. MIDI files in MMD were matched against a collection of 32,000,000 30-second audio clips retrieved from Spotify, resulting in over 10,796,557 audio-MIDI matches. In addition, we linked 600,142 Spotify tracks with 1,094,901 MusicBrainz recordings to produce a set of 168,032 MIDI files that are matched to the MusicBrainz database. We also provide a set of 53,496 MIDI files using audio-MIDI matches where the derived metadata on Spotify is a fuzzy match to the web-scraped metadata. These links augment many files in the dataset with the extensive metadata available via the Spotify API and the MusicBrainz database. We anticipate that this collection of data will be of great use to MIR researchers addressing a variety of research topics.
DOI: 10.5281/zenodo.5147545
title: DICOMRT04

description: Test files for OnkoDICOM
DOI: 10.6084/m9.figshare.15080499.v1
title: An active control study of the rubber hand illusion

description: Trial-by-trial data for our active control study of mindfulness meditation in the rubber-hand illusion. <br><br>Each csv file contains the data that supported our analysis of subjective experience surveys (rhi_experience_long.csv), proprioceptive drift (drift_longform.csv), and galvanic skin conductance response (mm-rhi-subset.csv).<br><br>Included is the R code used to analyse each dataset
DOI: 10.5281/zenodo.5144656
title: sVerify experiment result

description: The experiment result for a supplement for paper sVerify.
DOI: 10.5281/zenodo.5144655
title: sVerify experiment result

description: The experiment result for a supplement for paper sVerify.
DOI: 10.48342/nyyn-y551
title: ISSAI Kazakh Speech Corpus v1.1

description: The version 1.1 of Kazakh speech corpus (KSC). Different from the previous version 1.0, the corrupted utterances have been removed from the training, validation and test sets. The KSC version 1.1 contains around 332 hours of transcribed audio comprising over 154,000 utterances spoken by participants from different regions, age groups, and gender. It was carefully inspected by native Kazakh speakers to ensure high quality. The KSC is the largest publicly available database developed to advance various Kazakh speech and language processing applications such as speech recognition, speech synthesis, and speaker recognition. The KSC database is available for public and commercial use upon request under Creative Commons Attribution 4.0 International License.
DOI: 10.48342/gkg9-gn84
title: ISSAI Kazakh Speech Corpus v1.0

description: The Kazakh Speech Corpus (KSC) contains around 335 hours of transcribed audio comprising over 154,000 utterances spoken by participants from different regions, age groups, and gender. It was carefully inspected by native Kazakh speakers to ensure high quality. The KSC is the largest publicly available database developed to advance various Kazakh speech and language processing applications such as speech recognition, speech synthesis, and speaker recognition. The KSC database is available for public and commercial use upon request under Creative Commons Attribution 4.0 International License.
DOI: 10.6084/m9.figshare.15079293
title: results_with-amur

description: The file is the raw data of CTRL case, output of the model COCO.<br>
DOI: 10.6084/m9.figshare.15079293.v1
title: results_with-amur

description: The file is the raw data of CTRL case, output of the model COCO.<br>
DOI: 10.5517/ccdc.csd.cc23xh1l
title: CCDC 1963789: Experimental Crystal Structure Determination

description: Related Article: Bedadyuti Vedvyas Pati, Prateep Singh Sagara, Asit Ghosh, Gopal Krushna Das Adhikari, Ponneri Chandrababu Ravikumar|2021|J.Org.Chem.|86|9428|doi:10.1021/acs.joc.1c00759
DOI: 10.5517/ccdc.csd.cc23xh3n
title: CCDC 1963791: Experimental Crystal Structure Determination

description: Related Article: Bedadyuti Vedvyas Pati, Prateep Singh Sagara, Asit Ghosh, Gopal Krushna Das Adhikari, Ponneri Chandrababu Ravikumar|2021|J.Org.Chem.|86|9428|doi:10.1021/acs.joc.1c00759
DOI: 10.5517/ccdc.csd.cc23xh4p
title: CCDC 1963792: Experimental Crystal Structure Determination

description: Related Article: Bedadyuti Vedvyas Pati, Prateep Singh Sagara, Asit Ghosh, Gopal Krushna Das Adhikari, Ponneri Chandrababu Ravikumar|2021|J.Org.Chem.|86|9428|doi:10.1021/acs.joc.1c00759
DOI: 10.5517/ccdc.csd.cc2665rc
title: CCDC 2031732: Experimental Crystal Structure Determination

description: Related Article: Tiantian Li, Jianjun Wang, Xinhao Zhu, Xin Zhou, Shaozi Sun, Peng Wang, Hongzhi Cao, Guangli Yu, Ming Li|2021|J.Am.Chem.Soc.|143|11171|doi:10.1021/jacs.1c05048
DOI: 10.5517/ccdc.csd.cc26pb19
title: CCDC 2046280: Experimental Crystal Structure Determination

description: Related Article: Qingzhao Xing, Zhe Hao, Jing Hou, Gaoqiang Li, Ziwei Gao, Jing Gou, Chaoqun Li, Binxun Yu|2021|J.Org.Chem.|86|9563|doi:10.1021/acs.joc.1c00858
DOI: 10.5517/ccdc.csd.cc26pb2b
title: CCDC 2046281: Experimental Crystal Structure Determination

description: Related Article: Qingzhao Xing, Zhe Hao, Jing Hou, Gaoqiang Li, Ziwei Gao, Jing Gou, Chaoqun Li, Binxun Yu|2021|J.Org.Chem.|86|9563|doi:10.1021/acs.joc.1c00858
DOI: 10.6084/m9.figshare.15080505
title: result_noriver_case

description: The raw data of No-river case
DOI: 10.6084/m9.figshare.15080505.v1
title: result_noriver_case

description: The raw data of No-river case
DOI: 10.5281/zenodo.5147737
title: DICOMRT Sets

description: Test files for OnkoDICOM
DOI: 10.5281/zenodo.5147736
title: DICOMRT Sets

description: Test files for OnkoDICOM
DOI: 10.5281/zenodo.5140612
title: Associated data for D-SCRIPT, Cell Systems

description: Trained models, processed sequence and PPI training data, and new predictions described in "<strong>D-SCRIPT translates genome to phenome with sequence-based, structure-aware, genome-scale predictions of protein-protein interactions"</strong>, by Sledzieski, Singh, Cowen, and Berger
DOI: 10.5281/zenodo.5140611
title: Associated data for D-SCRIPT, Cell Systems

description: Trained models, processed sequence and PPI training data, and new predictions described in "<strong>D-SCRIPT translates genome to phenome with sequence-based, structure-aware, genome-scale predictions of protein-protein interactions"</strong>, by Sledzieski, Singh, Cowen, and Berger
DOI: 10.5281/zenodo.5147747
title: IES-R MEDITATORS DATA

description: 801 Rajyoga meditators data
DOI: 10.5281/zenodo.5147746
title: IES-R MEDITATORS DATA

description: 801 Rajyoga meditators data
DOI: 10.5281/zenodo.5101271
title: PCMDB_all_data

description: PCMDB contains three different types of cell markers for six model plants (Arabidopsis, rice, maize, soybean, tomato and tobacco), including experimentally validated marker genes, differentially expressed marker genes based on transcriptomic data, and differentially expressed genes across specific cells identified by single cell RNA sequencing. 3119 experimentally validated marker genes were collected by manually curating over 1676 literatures. Meanwhile, information including tissue type, sub-tissue type and cell type were also recorded. 0 marker genes were identified based on differential expression analysis using bulk RNA-Seq data. Moreover, 0 marker genes were collected from single-cell RNA sequencing studies. PCMDB provides a user-friendly interface for browsing, searching and downloading markers of various cell types from different tissues. Different analysis tools, including cell type prediction and cell marker prediction, are also provided to facilitate different purpose of users.
DOI: 10.5281/zenodo.5101270
title: PCMDB_all_data

description: PCMDB contains three different types of cell markers for six model plants (Arabidopsis, rice, maize, soybean, tomato and tobacco), including experimentally validated marker genes, differentially expressed marker genes based on transcriptomic data, and differentially expressed genes across specific cells identified by single cell RNA sequencing. 3119 experimentally validated marker genes were collected by manually curating over 1676 literatures. Meanwhile, information including tissue type, sub-tissue type and cell type were also recorded. 0 marker genes were identified based on differential expression analysis using bulk RNA-Seq data. Moreover, 0 marker genes were collected from single-cell RNA sequencing studies. PCMDB provides a user-friendly interface for browsing, searching and downloading markers of various cell types from different tissues. Different analysis tools, including cell type prediction and cell marker prediction, are also provided to facilitate different purpose of users.
DOI: 10.6084/m9.figshare.15079434
title: data of Direct determination of the soil and bark components around a battery industrial park by LA-SPAMS

description: This is all the raw data of Direct determination of the soil and bark components around a battery industrial park by LA-SPAMS
DOI: 10.6084/m9.figshare.15079434.v1
title: data of Direct determination of the soil and bark components around a battery industrial park by LA-SPAMS

description: This is all the raw data of Direct determination of the soil and bark components around a battery industrial park by LA-SPAMS
DOI: 10.6084/m9.figshare.14761641
title: Supplementary Material for: High sensitivity of circadian clock in the hippocampal dentate gyrus to glucocorticoid- and GSK3beta-dependent signals

description: Medicine
DOI: 10.6084/m9.figshare.14761641.v1
title: Supplementary Material for: High sensitivity of circadian clock in the hippocampal dentate gyrus to glucocorticoid- and GSK3beta-dependent signals

description: Medicine
DOI: 10.5281/zenodo.5145654
title: Seven Cucurbitaceae Leaves Morphometric Data

description: Here, we apply MorphoLeaf in generating a morphometric dataset from 140 leaf specimens of seven Cucurbitaceae species via landmark extraction, reparametrization of leaf contours, data quantification, and analysis. The data is also available on GitHub at https://github.com/osooluwatobia/cucurbitaceae-morpholeaf, and the paper from it titled "<strong>Digital Morphometrics: Application of MorphoLeaf in Shape Visualization and Species Delimitation, using Cucurbitaceae Leaves as a Model"</strong> is currently under review at Applications in Botany Journal.
DOI: 10.5281/zenodo.5145653
title: Seven Cucurbitaceae Leaves Morphometric Data

description: Here, we apply MorphoLeaf in generating a morphometric dataset from 140 leaf specimens of seven Cucurbitaceae species via landmark extraction, reparametrization of leaf contours, data quantification, and analysis. The data is also available on GitHub at https://github.com/osooluwatobia/cucurbitaceae-morpholeaf, and the paper from it titled "<strong>Digital Morphometrics: Application of MorphoLeaf in Shape Visualization and Species Delimitation, using Cucurbitaceae Leaves as a Model"</strong> is currently under review at Applications in Botany Journal.
DOI: 10.6084/m9.figshare.15081390
title: Supplementary Material for: Metabolic Response to Submaximal and Maximal Exercise in People with Severe Obesity, Prediabetes, and Diabetes

description: <b><i>Introduction:</i></b> Metabolic adaptations to maximal physical exercise in people with obesity (PwO) are scarcely described. This cross-sectional study evaluates the metabolic response to exercise via the respiratory exchange ratio (RER) in PwO and different degrees of glycemic control. <b><i>Methods:</i></b> Eighty-five PwO (body mass index 46.0 [39.0–54.0] kg/m<sup>2</sup>), that is, 32 normoglycemic (Ob-N), 25 prediabetic (Ob-preDM), and 28 diabetic (Ob-T2DM) subjects and 18 healthy subjects performed an incremental, maximal cardiopulmonary exercise test. The RER was measured at rest (RERrest) and at peak exercise (RERpeak). <b><i>Results:</i></b> RERpeak was significantly higher in healthy subjects than that in PwO. Among those, RERpeak was significantly higher in Ob-N than that in Ob-preDM and Ob-T2DM (1.20 [1.15–1.27] vs. 1.18 [1.10–1.22] <i>p</i> = 0.04 and vs. 1.14 [1.10–1.18] <i>p</i> &lt; 0.001, respectively). Accordingly, ΔRER (RERpeak-RERrest) was lower in Ob-preDM and Ob-T2DM than that in Ob-N (0.32 [0.26–0.39] <i>p</i> = 0.04 and 0.29 [0.24–0.36] <i>p</i> &lt; 0.001 vs. 0.38 [0.32–0.43], respectively), while no significant difference was found in ΔRER between Ob-preDM and Ob-T2DM and not even between Ob-N and healthy subjects. Moreover, ΔRER in PwO correlated with glucose area under curve (<i>p</i> = 0.002). <b><i>Conclusions:</i></b> PwO demonstrate restricted metabolic response during maximal exercise. Particularly, those with prediabetes already show metabolic inflexibility during exercise, similarly to those with type 2 diabetes. These findings also suggest a potential role of cardiopulmonary exercise testing in detecting early metabolic alterations in PwO.
DOI: 10.6084/m9.figshare.15081390.v1
title: Supplementary Material for: Metabolic Response to Submaximal and Maximal Exercise in People with Severe Obesity, Prediabetes, and Diabetes

description: <b><i>Introduction:</i></b> Metabolic adaptations to maximal physical exercise in people with obesity (PwO) are scarcely described. This cross-sectional study evaluates the metabolic response to exercise via the respiratory exchange ratio (RER) in PwO and different degrees of glycemic control. <b><i>Methods:</i></b> Eighty-five PwO (body mass index 46.0 [39.0–54.0] kg/m<sup>2</sup>), that is, 32 normoglycemic (Ob-N), 25 prediabetic (Ob-preDM), and 28 diabetic (Ob-T2DM) subjects and 18 healthy subjects performed an incremental, maximal cardiopulmonary exercise test. The RER was measured at rest (RERrest) and at peak exercise (RERpeak). <b><i>Results:</i></b> RERpeak was significantly higher in healthy subjects than that in PwO. Among those, RERpeak was significantly higher in Ob-N than that in Ob-preDM and Ob-T2DM (1.20 [1.15–1.27] vs. 1.18 [1.10–1.22] <i>p</i> = 0.04 and vs. 1.14 [1.10–1.18] <i>p</i> &lt; 0.001, respectively). Accordingly, ΔRER (RERpeak-RERrest) was lower in Ob-preDM and Ob-T2DM than that in Ob-N (0.32 [0.26–0.39] <i>p</i> = 0.04 and 0.29 [0.24–0.36] <i>p</i> &lt; 0.001 vs. 0.38 [0.32–0.43], respectively), while no significant difference was found in ΔRER between Ob-preDM and Ob-T2DM and not even between Ob-N and healthy subjects. Moreover, ΔRER in PwO correlated with glucose area under curve (<i>p</i> = 0.002). <b><i>Conclusions:</i></b> PwO demonstrate restricted metabolic response during maximal exercise. Particularly, those with prediabetes already show metabolic inflexibility during exercise, similarly to those with type 2 diabetes. These findings also suggest a potential role of cardiopulmonary exercise testing in detecting early metabolic alterations in PwO.
DOI: 10.6084/m9.figshare.15081462
title: Supplementary Material for: Performance of the Rowland Universal Dementia Assessment Scale in Screening Mild Cognitive Impairment at an Outpatient Setting

description: <b><i>Introduction:</i></b> Mild cognitive impairment (MCI) is defined as the symptomatic pre-dementia phase on the continuum of cognitive decline. Early recognition and application of potential interventions could prevent or delay the progression to dementia. The Rowland Universal Dementia Assessment Scale (RUDAS) shows good performance in the screening of dementia but has limited data regarding its diagnostic properties in the screening of MCI. The objectives of this study were to assess the psychometric properties of the Thai version of the RUDAS (RUDAS-Thai) in the screening of MCI, identify associated factors for the RUDAS performance, and determine the optimal cutoff point in detecting MCI. <b><i>Methods:</i></b> This was a cross-sectional study conducted from January 2020 to March 2021. Older patients at the outpatient clinic of an internal medicine department at a tertiary care hospital in Thailand were examined. Baseline data were collected, and the RUDAS-Thai was administered to each patient. Afterward, a geriatrician assessed each patient for MCI. <b><i>Results:</i></b> A total of 150 patients were included, of whom 42 cases (28%) had MCI. The overall performance of the test using an area under the receiver operating characteristic curve (AUC) was 0.82 (95% confidence interval 0.75–0.89). At the optimal cutoff point of 25/30, the AUC was 0.76 with sensitivity and specificity of 76.2 and 75%, respectively. The educational level affected the test performance according to regression analysis. For patients with years of education ≤6 and &gt;6, the optimal cutoff points were 25/30 and 26/30, respectively. <b><i>Conclusion:</i></b> The RUDAS-Thai performed well in differentiating patients with MCI from normal cognition; however, it was affected by educational level. A score of 25/30 or lower for persons with ≤6 years of education or 26/30 or lower for persons with higher than 6 years of education is the optimal cutoff point for indication of developing MCI.
DOI: 10.5517/ccdc.csd.cc27wdr9
title: CCDC 2081921: Experimental Crystal Structure Determination

description: Related Article: Gauthier Lefebvre, Olivier Charron, Janine Cossy, Christophe Meyer|2021|Org.Lett.|23|5491|doi:10.1021/acs.orglett.1c01840
DOI: 10.5517/ccdc.csd.cc27wdsb
title: CCDC 2081922: Experimental Crystal Structure Determination

description: Related Article: Gauthier Lefebvre, Olivier Charron, Janine Cossy, Christophe Meyer|2021|Org.Lett.|23|5491|doi:10.1021/acs.orglett.1c01840
DOI: 10.5517/ccdc.csd.cc27wgcz
title: CCDC 2081971: Experimental Crystal Structure Determination

description: Related Article: Katarina L. Keel, Jetze J. Tepe|2021|Org.Lett.|23|5368|doi:10.1021/acs.orglett.1c01681