cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17028/rd.lboro.21711449.v1
title: The PERUSANO study: Caregivers, health centre and day care centre influences on infant and young child feeding practices: dataset for caregivers

description: Qualitative data from semi-structured in-depth interviews, exit interviews and observations were collected as part of a wider interdisciplinary project (PERUSANO) aimed at addressing multiple forms of malnutrition, particularly stunting, anaemia, and risk of overweight/obesity in peri-urban Peruvian infants and young children (IYC) aged 6-23 months of age. The study took place in two peri-urban areas: Manchay in Lima and Huánuco district in the Andean highlands. <br> Interviews and observations explored drivers of infant and young child complementary feeding (IYCF) practices from the perspective of primary caregivers within the home environment, health professionals involved in CRED care (well-baby checks, nutrition counselling) and staff involved in the CUNAMAS National Programme in day care services. The CUNAMAS is a large-scale early child development programme established by the Ministry of Development and Social Inclusion in 2012. It aims to support the holistic development of children under three living in poverty. <br> Data collection in four health centres and fourteen CUNAMAS day care services took place between October and December 2019. Participants/key informants were purposefully selected to cover the main roles within the health facilities (health professionals involved in CRED care, nutritionists, primary caregivers of children and community health agents), and CUNAMAS day care services (nursery caregivers, district nursery technical managers, mother guides, and primary caregivers of children). <br> Interviews and observations with primary caregivers took place between January and mid-March 2020. A purposive quota sampling was employed to recruit mothers according to the child’s age, maternal working status and nutritional status from participants who had taken part in the quantitative survey of the PERUSANO project. In March 2020, face-to-face interviews stopped due to the COVID-19 pandemic and the remaining interviews with caregivers were conducted by telephone. Observations could no longer be conducted. <br> Transcripts (for primary caregivers) of interviews and observations in Spanish language are available upon request to the UK Principal Investigator Professor Emily Rousham (e.k.rousham@lboro.ac.uk). Detailed sampling information according to interview type, location and stakeholder group can be found in Supplementary material 1. See also the README file attached. <br> The quantitative component of the study has been described elsewhere (Pradeilles et al. 2022). Quantitative survey questionnaires and data can be found at 10.17028/rd.lboro.18750458, 10.17028/rd.lboro.16691455 and 10.17028/rd.lboro.21656348. <br> <br> <br>
DOI: 10.6084/m9.figshare.21723605
title: Phylogenomics of the Mycobacterium tuberculosis Beijing genotype

description: Tuberculosis caused by <em>Mycobacterium tuberculosis</em> complex (MTBC) bacteria is a worldwide public health issue. Among MTBC, phylogenetic lineage 2 (~ Beijing genotype) is one of the most common and is characterized by increased transmissibility and drug resistance. Over time, its classification has undergone a number of changes, from the IS<em>6110</em>-based restriction fragment length polymorphism analysis and large sequence polymorphisms in regions of difference to differentiation based on single nucleotide polymorphisms. Here we have reviewed and correlated the main classifications of lineage 2 at different levels of genome organization. We also introduced a set of genomes and polymorphisms that can be used for further analysis of this lineage. The presented lineage 2 phylogeny can be used for further research on important epidemiological clusters and their ancestors, as well as unclassified strains.
DOI: 10.6084/m9.figshare.21723605.v2
title: Phylogenomics of the Mycobacterium tuberculosis Beijing genotype

description: Tuberculosis caused by <em>Mycobacterium tuberculosis</em> complex (MTBC) bacteria is a worldwide public health issue. Among MTBC, phylogenetic lineage 2 (~ Beijing genotype) is one of the most common and is characterized by increased transmissibility and drug resistance. Over time, its classification has undergone a number of changes, from the IS<em>6110</em>-based restriction fragment length polymorphism analysis and large sequence polymorphisms in regions of difference to differentiation based on single nucleotide polymorphisms. Here we have reviewed and correlated the main classifications of lineage 2 at different levels of genome organization. We also introduced a set of genomes and polymorphisms that can be used for further analysis of this lineage. The presented lineage 2 phylogeny can be used for further research on important epidemiological clusters and their ancestors, as well as unclassified strains.
DOI: 10.6084/m9.figshare.21723605.v1
title: Phylogenomics of the Mycobacterium tuberculosis Beijing genotype

description: Tuberculosis caused by <em>Mycobacterium tuberculosis</em> complex (MTBC) bacteria is a worldwide public health issue. Among MTBC, phylogenetic lineage 2 (~ Beijing genotype) is one of the most common and is characterized by increased transmissibility and drug resistance. Over time, its classification has undergone a number of changes, from the IS<em>6110</em>-based restriction fragment length polymorphism analysis and large sequence polymorphisms in regions of difference to differentiation based on single nucleotide polymorphisms. Here we have reviewed and correlated the main classifications of lineage 2 at different levels of genome organization. We also introduced a set of genomes and polymorphisms that can be used for further analysis of this lineage. The presented lineage 2 phylogeny can be used for further research on important epidemiological clusters and their ancestors, as well as unclassified strains.
DOI: 10.25625/mzjlum
title: Replacing herbicides by mechanical weeding promotes ecosystem multifunctionality and profitability in industrial oil palm plantations

description: Data on Ecosystem functions, Biodiversity and Yield & Profit indicators
DOI: 10.25625/mzjlum/gfnnvu
title: Formaglio, Iddris et al Replacing herbicides by mechanical weeding promotes ecosystem multifunctionality and profitability in industrial oil palm plantations.tab

description: :unav
DOI: 10.6084/m9.figshare.21723740
title: the raw data for manuscript 1118778.xlsx

description: Electroacupuncture (EA) therapy, as a combination of electric stimulation and traditional acupuncture technology, is currently an important mean for treatment of ischemic stroke and post-stroke rehabilitation in China. Because of its remarkable therapeutic effect, it has been widely used in hospitals and clinic, however, the detailed mechanism remains unclear. Previous experimental studies, due to technical limitations, could only focus on a single pathway or mechanism for analysis, and could not comprehensively and systematically summarize mechanisms of EA on treatment of ischemic stroke. In this study, we used middle cerebral artery occlusion (MCAO) in rats to simulate process of cerebral ischemia-reperfusion (I/R), and used RNA-Sequencing (RNA-Seq) to detect transcriptomic changes of various molecules in ischemic hippocampal neurons of rats in Sham, I/R and EA groups. Thus, we detected 18 significantly different genes related to atherosclerosis (AS), including lipid metabolism, thrombosis, monocytes and vascular smooth muscle cells. And, we detected 10 significantly different genes related to oxidative stress and apoptosis and 10 significantly different genes related to calcium overload and excitatory amino acids release. As well as, we detected 19 significantly different genes related to blood-brain barrier (BBB) and 22 significantly different genes related to inflammatory response. In conclusion, EA can play a role in treating ischemic stroke through a variety of mechanisms, including atherosclerosis, oxidative stress, apoptosis, calcium overload, excitatory amino acids release, blood-brain barrier (BBB) and inflammatory response.
DOI: 10.6084/m9.figshare.21723740.v1
title: the raw data for manuscript 1118778.xlsx

description: Electroacupuncture (EA) therapy, as a combination of electric stimulation and traditional acupuncture technology, is currently an important mean for treatment of ischemic stroke and post-stroke rehabilitation in China. Because of its remarkable therapeutic effect, it has been widely used in hospitals and clinic, however, the detailed mechanism remains unclear. Previous experimental studies, due to technical limitations, could only focus on a single pathway or mechanism for analysis, and could not comprehensively and systematically summarize mechanisms of EA on treatment of ischemic stroke. In this study, we used middle cerebral artery occlusion (MCAO) in rats to simulate process of cerebral ischemia-reperfusion (I/R), and used RNA-Sequencing (RNA-Seq) to detect transcriptomic changes of various molecules in ischemic hippocampal neurons of rats in Sham, I/R and EA groups. Thus, we detected 18 significantly different genes related to atherosclerosis (AS), including lipid metabolism, thrombosis, monocytes and vascular smooth muscle cells. And, we detected 10 significantly different genes related to oxidative stress and apoptosis and 10 significantly different genes related to calcium overload and excitatory amino acids release. As well as, we detected 19 significantly different genes related to blood-brain barrier (BBB) and 22 significantly different genes related to inflammatory response. In conclusion, EA can play a role in treating ischemic stroke through a variety of mechanisms, including atherosclerosis, oxidative stress, apoptosis, calcium overload, excitatory amino acids release, blood-brain barrier (BBB) and inflammatory response.
DOI: 10.6084/m9.figshare.21723716
title: ELISA source data for figshare.xlsx

description: source data of ELISA test from three cohorts
DOI: 10.5281/zenodo.7126171
title: Gene expression and splicing counts from the Yepez, Gusic et al study - strand-specific

description: <strong>File description:</strong> geneCounts: gene-level counts k_j: split counts spanning from one exon to another. k_theta: non-split counts covering a splice site n_psi3: total split counts from a given acceptor site n_psi5: total split counts from a given donor site n_theta: total split and non-split counts for a given splice site Sample annotation describing each sample from the dataset Description file with global information from the dataset The gene counts were originated using the GTF file from release 34 of GENCODE https://www.gencodegenes.org/human/release_34, and the split and non-split counts contain only the annotated junctions from the same release. <strong>Use: </strong>The count matrices are intended to help researchers that are interested in using RNA-Seq data with the purpose of diagnostics. Researchers can merge their own dataset with the downloaded ones, provided the tissue, genome build, strand, and paired-end specifications match. Afterwards, DROP can be used to compute expression and splicing outliers (https://github.com/gagneurlab/drop). <strong>Number of samples: </strong>269<br> <strong>Tissue:</strong> Fibroblast<br> <strong>Organism:</strong> Homo sapiens<br> <strong>Genome assembly:</strong> hg19<br> <strong>Gene annotation:</strong> gencode34<br> <strong>Disease (ICD-10: N):</strong> E72: 4, E75: 2, E77: 1, E88: 199, F82: 1, F89: 7, G31: 14, G40: 2, G71: 3, G82: 1, G93: 2, I42: 1, K72: 4, NONE: 18, P94: 2, Q02: 1, Q78: 1, R16: 2, R27: 3, R29: 1<br> <strong>Strand specific: </strong>TRUE<br> <strong>Paired end: </strong>TRUE<br> <strong>Protocol: </strong>poly(A) enrichment<br> <strong>Dataset contact: </strong>Vicente Yepez, yepez@in.tum.de; Julien Gagneur, gagneur@in.tum.de; Holger Prokisch, prokisch@helmholtz-muenchen.de <strong>Citation:</strong> Cite both the resource using Zenodo's citation and the publication under References
description: {"references": ["Y\u00e9pez, V. A., Gusic, M., Kopajtich, R., Mertes, C., et al. (2022). Clinical implementation of RNA sequencing for Mendelian disease diagnostics. Genome Med 14, 38. doi: 10.1186/s13073-022-01019-9."]}
DOI: 10.5281/zenodo.4646826
title: Gene expression and splicing counts from the Yepez, Gusic et al study - strand-specific

description: <strong>File description:</strong> geneCounts: gene-level counts k_j: split counts spanning from one exon to another. k_theta: non-split counts covering a splice site n_psi3: total split counts from a given acceptor site n_psi5: total split counts from a given donor site n_theta: total split and non-split counts for a given splice site Sample annotation describing each sample from the dataset Description file with global information from the dataset The gene counts were originated using the GTF file from release 34 of GENCODE https://www.gencodegenes.org/human/release_34, and the split and non-split counts contain only the annotated junctions from the same release. <strong>Use: </strong>The count matrices are intended to help researchers that are interested in using RNA-Seq data with the purpose of diagnostics. Researchers can merge their own dataset with the downloaded ones, provided the tissue, genome build, strand, and paired-end specifications match. Afterwards, DROP can be used to compute expression and splicing outliers (https://github.com/gagneurlab/drop). <strong>Number of samples: </strong>269<br> <strong>Tissue:</strong> Fibroblast<br> <strong>Organism:</strong> Homo sapiens<br> <strong>Genome assembly:</strong> hg19<br> <strong>Gene annotation:</strong> gencode34<br> <strong>Disease (ICD-10: N):</strong> E72: 4, E75: 2, E77: 1, E88: 199, F82: 1, F89: 7, G31: 14, G40: 2, G71: 3, G82: 1, G93: 2, I42: 1, K72: 4, NONE: 18, P94: 2, Q02: 1, Q78: 1, R16: 2, R27: 3, R29: 1<br> <strong>Strand specific: </strong>TRUE<br> <strong>Paired end: </strong>TRUE<br> <strong>Protocol: </strong>poly(A) enrichment<br> <strong>Dataset contact: </strong>Vicente Yepez, yepez@in.tum.de; Julien Gagneur, gagneur@in.tum.de; Holger Prokisch, prokisch@helmholtz-muenchen.de <strong>Citation:</strong> Cite both the resource using Zenodo's citation and the publication under References
description: {"references": ["Y\u00e9pez, V. A., Gusic, M., Kopajtich, R., Mertes, C., et al. (2022). Clinical implementation of RNA sequencing for Mendelian disease diagnostics. Genome Med 14, 38. doi: 10.1186/s13073-022-01019-9."]}
DOI: 10.5281/zenodo.7022794
title: Fastball pitching performance only slightly decreases after mobility impediment of the pelvis and trunk – Do (catch-up) compensation strategies come into play? (Dataset)

description: Kinematic data (position data) of eleven baseball pitchers who performed 25 fastballs recorded with a VICON motion capture system. The pickle-files (version 4.0) contain the position data of a static anatomical reference posture ('STATIC') and a fastball pitch motion ('PITCH') the landmarks attached to our subjects according to the modified plug-in-gait model<sup>1</sup>. The anatomical landmarks of the static posture and pitch motion are organised in Python dictionaries containing pandas DataFrames (version 1.1.0) with the X, Y and Z coordinates. For more information about the data read the original paper<sup>2</sup> and/or send an e-mail to corresponding author of the article: a.j.r.leenen@vu.nl. <strong>References</strong><br> 1. Vicon R©. Plug-in-Gait Modelling Instructions (2010)<br> 2. Leenen A, Trigt B van, Hoozemans M, Veeger H. Fastball pitching performance only slightly decreases after mobility impediment of the pelvis and trunk—Do (catch-up) compensation strategies come into play? Sports Act Living (2022) doi: 10.3389/fspor.2022.1044616
description: {"references": ["Leenen A, Trigt B van, Hoozemans M, Veeger H. Fastball pitching performance only slightly decreases after mobility impediment of the pelvis and trunk\u2014Do (catch-up) compensation strategies come into play? Sports Act Living (2022) doi: 10.3389/fspor.2022.1044616"]}
DOI: 10.5281/zenodo.7022793
title: Fastball pitching performance only slightly decreases after mobility impediment of the pelvis and trunk – Do (catch-up) compensation strategies come into play? (Dataset)

description: Kinematic data (position data) of eleven baseball pitchers who performed 25 fastballs recorded with a VICON motion capture system. The pickle-files (version 4.0) contain the position data of a static anatomical reference posture ('STATIC') and a fastball pitch motion ('PITCH') the landmarks attached to our subjects according to the modified plug-in-gait model<sup>1</sup>. The anatomical landmarks of the static posture and pitch motion are organised in Python dictionaries containing pandas DataFrames (version 1.1.0) with the X, Y and Z coordinates. For more information about the data read the original paper<sup>2</sup> and/or send an e-mail to corresponding author of the article: a.j.r.leenen@vu.nl. <strong>References</strong><br> 1. Vicon R©. Plug-in-Gait Modelling Instructions (2010)<br> 2. Leenen A, Trigt B van, Hoozemans M, Veeger H. Fastball pitching performance only slightly decreases after mobility impediment of the pelvis and trunk—Do (catch-up) compensation strategies come into play? Sports Act Living (2022) doi: 10.3389/fspor.2022.1044616
description: {"references": ["Leenen A, Trigt B van, Hoozemans M, Veeger H. Fastball pitching performance only slightly decreases after mobility impediment of the pelvis and trunk\u2014Do (catch-up) compensation strategies come into play? Sports Act Living (2022) doi: 10.3389/fspor.2022.1044616"]}
DOI: 10.5281/zenodo.7126296
title: Gene expression and splicing counts from the Yepez, Gusic et al study - non strand-specific

description: <strong>File description:</strong> geneCounts: gene-level counts k_j: split counts spanning from one exon to another. k_theta: non-split counts covering a splice site n_psi3: total split counts from a given acceptor site n_psi5: total split counts from a given donor site n_theta: total split and non-split counts for a given splice site Sample annotation describing each sample from the dataset Description file with global information from the dataset The gene counts were originated using the GTF file from release 34 of GENCODE https://www.gencodegenes.org/human/release_34, and the split and non-split counts contain only the annotated junctions from the same release. <strong>Use: </strong>The count matrices are intended to help researchers that are interested in using RNA-Seq data with the purpose of diagnostics. Researchers can merge their own dataset with the downloaded ones, provided the tissue, genome build, strand, and paired-end specifications match. Afterwards, the DROP can be used to compute expression and splicing outliers (https://github.com/gagneurlab/drop). <strong>Number of samples: </strong>154<br> <strong>Tissue:</strong> Fibroblast<br> <strong>Organism:</strong> Homo sapiens<br> <strong>Genome assembly:</strong> hg19<br> <strong>Gene annotation:</strong> gencode34<br> <strong>Disease (ICD-10: N):</strong> E75: 1, E79: 13, E88: 118, G31: 9, K72: 3, NONE: 10<br> <strong>Strand specific: </strong>FALSE<br> <strong>Paired end: </strong>TRUE<br> <strong>Protocol: </strong>poly(A) enrichment<br> <strong>Dataset contact: </strong>Vicente Yepez, yepez@in.tum.de; Julien Gagneur, gagneur@in.tum.de; Holger Prokisch, prokisch@helmholtz-muenchen.de <strong>Citation:</strong> Cite both the resource using Zenodo's citation and the publication under References
description: {"references": ["Y\u00e9pez, V. A., Gusic, M., Kopajtich, R., Mertes, C., et al. (2022). Clinical implementation of RNA sequencing for Mendelian disease diagnostics. Genome Med 14, 38. doi: 10.1186/s13073-022-01019-9."]}
DOI: 10.5281/zenodo.4646822
title: Gene expression and splicing counts from the Yepez, Gusic et al study - non strand-specific

description: <strong>File description:</strong> geneCounts: gene-level counts k_j: split counts spanning from one exon to another. k_theta: non-split counts covering a splice site n_psi3: total split counts from a given acceptor site n_psi5: total split counts from a given donor site n_theta: total split and non-split counts for a given splice site Sample annotation describing each sample from the dataset Description file with global information from the dataset The gene counts were originated using the GTF file from release 34 of GENCODE https://www.gencodegenes.org/human/release_34, and the split and non-split counts contain only the annotated junctions from the same release. <strong>Use: </strong>The count matrices are intended to help researchers that are interested in using RNA-Seq data with the purpose of diagnostics. Researchers can merge their own dataset with the downloaded ones, provided the tissue, genome build, strand, and paired-end specifications match. Afterwards, the DROP can be used to compute expression and splicing outliers (https://github.com/gagneurlab/drop). <strong>Number of samples: </strong>154<br> <strong>Tissue:</strong> Fibroblast<br> <strong>Organism:</strong> Homo sapiens<br> <strong>Genome assembly:</strong> hg19<br> <strong>Gene annotation:</strong> gencode34<br> <strong>Disease (ICD-10: N):</strong> E75: 1, E79: 13, E88: 118, G31: 9, K72: 3, NONE: 10<br> <strong>Strand specific: </strong>FALSE<br> <strong>Paired end: </strong>TRUE<br> <strong>Protocol: </strong>poly(A) enrichment<br> <strong>Dataset contact: </strong>Vicente Yepez, yepez@in.tum.de; Julien Gagneur, gagneur@in.tum.de; Holger Prokisch, prokisch@helmholtz-muenchen.de <strong>Citation:</strong> Cite both the resource using Zenodo's citation and the publication under References
description: {"references": ["Y\u00e9pez, V. A., Gusic, M., Kopajtich, R., Mertes, C., et al. (2022). Clinical implementation of RNA sequencing for Mendelian disease diagnostics. Genome Med 14, 38. doi: 10.1186/s13073-022-01019-9."]}
DOI: 10.4121/18318644
title: Data underlying the publication: Mucosal expression of Ca and P transporters and claudins in the small intestine of broilers is altered by dietary Ca:P in a limestone particle size dependent manner.

description: Effect of limestone particle size and inclusion level on duodenal and jejunal mucosal expression of Ca and P transporters and claudins in broilers was tested in a 2 × 3 factorial arrangement. Two limestone sources, coarse (mean particle size 1062 µm) vs. fine (mean particle size 160 µm), were separated from the same limestone limestone products via sieving. These two limestone sources were then added to a basal diet at three inclusion levels, resulting in Ca/P ratio 0.50, 1.00 and 1.75 in the experimental diets (dietary P content was fixed at 5.5 g/kg in the basal diet). Experimental diets were provided on day 14 onwards, and on day 20 and 21 three birds per replicate pen were randomly selected for collection of duodenal and jejunal mucosa. mRNA expression of Ca- and P-related transporters and claudins in the duodenal and jejunal mucosa were determined on individual bird level using RT-PCR. <br>For more details about the experimental design, please see the paper “Mucosal expression of Ca and P transporters and claudins in the small intestine of broilers is altered by dietary Ca:P in a limestone particle size dependent manner”.<br>