cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.22757254
title: Additional file 1 of Characterization of gut microbiota associated with metabolic syndrome and type-2 diabetes mellitus in Mexican pediatric subjects

description: Additional file 1: Table S1. Cardiometabolic risk factors in subjects with T2DM, MetS and controls. Table S2. Medical treatments taken by studied subjects with T2DM, MetS and controls. Table S3. Sequencing statistics of samples used in the study. Table S4. Operational taxonomic units (OTUs) from the studied groups. Table S5. Operational taxonomic units (OTUs) at phylum level. Table S6. Operational taxonomic units (OTUs) at family level. Table S7. Operational taxonomic units (OTUs) at genus level. Table S8. Read relative abundance of bacterial communities at genus level &gt; 1% within each studied group. Table S9. Linear discriminant analysis of relevant microorganisms at family level. Table S10. Linear discriminant analysis of relevant microorganisms at genus level.
DOI: 10.6084/m9.figshare.22757254.v1
title: Additional file 1 of Characterization of gut microbiota associated with metabolic syndrome and type-2 diabetes mellitus in Mexican pediatric subjects

description: Additional file 1: Table S1. Cardiometabolic risk factors in subjects with T2DM, MetS and controls. Table S2. Medical treatments taken by studied subjects with T2DM, MetS and controls. Table S3. Sequencing statistics of samples used in the study. Table S4. Operational taxonomic units (OTUs) from the studied groups. Table S5. Operational taxonomic units (OTUs) at phylum level. Table S6. Operational taxonomic units (OTUs) at family level. Table S7. Operational taxonomic units (OTUs) at genus level. Table S8. Read relative abundance of bacterial communities at genus level &gt; 1% within each studied group. Table S9. Linear discriminant analysis of relevant microorganisms at family level. Table S10. Linear discriminant analysis of relevant microorganisms at genus level.
DOI: 10.5517/ccdc.csd.cc2fg0pm
title: CCDC 2247800: Experimental Crystal Structure Determination

description: Related Article: Alessandra Logallo, Eva Hevia|2023|Chem.Commun.|59|5383|doi:10.1039/D3CC01216F
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fg0qn
title: CCDC 2247801: Experimental Crystal Structure Determination

description: Related Article: Alessandra Logallo, Eva Hevia|2023|Chem.Commun.|59|5383|doi:10.1039/D3CC01216F
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc1p4pdx
title: CCDC 1553639: Experimental Crystal Structure Determination

description: Related Article: Jiyuan Du, Shilong Wei, Zhijie Jiang, Hongshan Ke, Lin Sun, Yiquan Zhang, Sanping Chen|2023|Phys.Chem.Chem.Phys.(PCCP)|25|11717|doi:10.1039/D2CP06074D
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.22757280
title: Additional file 1 of Genome-wide assessment and mapping of inbreeding depression identifies candidate genes associated with semen traits in Holstein bulls

description: Additional file 1: Table S1. Genome-wide association with inbreeding depression of sperm concentration.
DOI: 10.6084/m9.figshare.22757280.v1
title: Additional file 1 of Genome-wide assessment and mapping of inbreeding depression identifies candidate genes associated with semen traits in Holstein bulls

description: Additional file 1: Table S1. Genome-wide association with inbreeding depression of sperm concentration.
DOI: 10.6084/m9.figshare.22757283
title: Additional file 2 of Genome-wide assessment and mapping of inbreeding depression identifies candidate genes associated with semen traits in Holstein bulls

description: Additional file 2: Table S2. Genome-wide association with inbreeding depression of sperm motility.
DOI: 10.6084/m9.figshare.22757283.v1
title: Additional file 2 of Genome-wide assessment and mapping of inbreeding depression identifies candidate genes associated with semen traits in Holstein bulls

description: Additional file 2: Table S2. Genome-wide association with inbreeding depression of sperm motility.
DOI: 10.6084/m9.figshare.22757286
title: Additional file 3 of Genome-wide assessment and mapping of inbreeding depression identifies candidate genes associated with semen traits in Holstein bulls

description: Additional file 3: Table S3. Genes associated with inbreeding depression of sperm motility trait.
DOI: 10.6084/m9.figshare.22757286.v1
title: Additional file 3 of Genome-wide assessment and mapping of inbreeding depression identifies candidate genes associated with semen traits in Holstein bulls

description: Additional file 3: Table S3. Genes associated with inbreeding depression of sperm motility trait.
DOI: 10.6084/m9.figshare.22757344
title: Additional file 1 of Biosensor-guided rapid screening for improved recombinant protein secretion in Pichia pastoris

description: Additional file 1: Fig. 1. Optical density of biosensor expressing strains. Absorbance at 600 nm of biosensor strains expressing phytase, laccase, β-casein and β-lactoglobulin. Table 1. Data aquation parameters for liquid chromatography-multiple reaction monitoring-mass spectrometry (LC-MRM-MS).
DOI: 10.6084/m9.figshare.22757344.v1
title: Additional file 1 of Biosensor-guided rapid screening for improved recombinant protein secretion in Pichia pastoris

description: Additional file 1: Fig. 1. Optical density of biosensor expressing strains. Absorbance at 600 nm of biosensor strains expressing phytase, laccase, β-casein and β-lactoglobulin. Table 1. Data aquation parameters for liquid chromatography-multiple reaction monitoring-mass spectrometry (LC-MRM-MS).
DOI: 10.6084/m9.figshare.22757371
title: Additional file 1 of Unraveling transcriptomics of sorghum grain carotenoids: a step forward for biofortification

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.22757371.v1
title: Additional file 1 of Unraveling transcriptomics of sorghum grain carotenoids: a step forward for biofortification

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.22757394
title: Additional file 1 of MBECS: Microbiome Batch Effects Correction Suite

description: Additional file 1. Vignette.
DOI: 10.6084/m9.figshare.22757394.v1
title: Additional file 1 of MBECS: Microbiome Batch Effects Correction Suite

description: Additional file 1. Vignette.
DOI: 10.6084/m9.figshare.22757397
title: Additional file 2 of MBECS: Microbiome Batch Effects Correction Suite

description: Additional file 2. Preliminary report.
DOI: 10.6084/m9.figshare.22757397.v1
title: Additional file 2 of MBECS: Microbiome Batch Effects Correction Suite

description: Additional file 2. Preliminary report.
DOI: 10.6084/m9.figshare.22757400
title: Additional file 3 of MBECS: Microbiome Batch Effects Correction Suite

description: Additional file 3. Post-correction report.
DOI: 10.6084/m9.figshare.22757400.v1
title: Additional file 3 of MBECS: Microbiome Batch Effects Correction Suite

description: Additional file 3. Post-correction report.
DOI: 10.25909/645325e040207
title: Sparse spike trains and the limitation of rate codes underlying rapid behaviours - data

description: Raw data from the paper "Sparse spike trains and the limitation of rate codes underlying rapid behaviours" by Joseph Fabian et al.
DOI: 10.3886/e190781
title: Long Life-Long Learning English as a Foreign Language Education

description: Specifically in English as a Foreign Language Education, the "Long Life-Long Learning English as a Foreign Language Education" notion highlights the significance of lifelong language learning. The method acknowledges that learning a language is a continuous process that calls for consistent time and attention throughout one's life. It also recognizes that a learner's requirements and goals for language acquisition may change over time and that, as a result, they should have access to flexible learning options. Learners are given the tools they need to become more fluent, self-assured, and successful communicators in English via the Long Life-Long Learning method's advocacy of a flexible, individualized, and learner-centred approach to language instruction.
DOI: 10.5519/qd.20eddy2e
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (205 records)
DOI: 10.5281/zenodo.7894414
title: A numerical exploration of hyporheic zone solute transport behavior estimated from electrical resistivity inversions

description: 1). We run the Comsol model (ER3D_cs300ws6ds20_Zxl1.m) with an electrical push-pull loop, and then the voltage at every electrode of each time is printed to model_name.out and resistivity to model_name.ro. 2). superposition.m is used to create final voltage results for later use in R2 inversions. 3). postproc_c_dual.m is used to create the pixel breakthrough curves of the simulated results. 4). plot_c_comsol.m read the resistivity result from step (1), convert the resistivity to bulk EC, and plot the bulk EC contour map. 5). protocal_pc.m is used to take the voltages, add some random noise, and make the input files and batch scripts for R2. 6). runr2.bat and runr2_TL.bat are used to generate inverted bulk EC. 7). plot_C_r2_dual.m is used to plot the inversed bulk EC.
DOI: 10.5281/zenodo.7894413
title: A numerical exploration of hyporheic zone solute transport behavior estimated from electrical resistivity inversions

description: 1). We run the Comsol model (ER3D_cs300ws6ds20_Zxl1.m) with an electrical push-pull loop, and then the voltage at every electrode of each time is printed to model_name.out and resistivity to model_name.ro. 2). superposition.m is used to create final voltage results for later use in R2 inversions. 3). postproc_c_dual.m is used to create the pixel breakthrough curves of the simulated results. 4). plot_c_comsol.m read the resistivity result from step (1), convert the resistivity to bulk EC, and plot the bulk EC contour map. 5). protocal_pc.m is used to take the voltages, add some random noise, and make the input files and batch scripts for R2. 6). runr2.bat and runr2_TL.bat are used to generate inverted bulk EC. 7). plot_C_r2_dual.m is used to plot the inversed bulk EC.
DOI: 10.6084/m9.figshare.22757663
title: Half-monthly in-situ SM measurements at 10cm depth

description: Half-monthly in-situ SM measurements at 10cm depth reprocessed from Wang and Shi (2019). Including 732 in-situ SM measurements over China, in MatLab data format (.mat). <br> Reference: Wang, A., Shi, X., 2019. A Multilayer Soil Moisture Dataset Based on the Gravimetric Method in China and Its Characteristics. Journal of Hydrometeorology 20, 1721–1736. https://doi.org/10.1175/JHM-D-19-0035.1
DOI: 10.6084/m9.figshare.22757663.v1
title: Half-monthly in-situ SM measurements at 10cm depth

description: Half-monthly in-situ SM measurements at 10cm depth reprocessed from Wang and Shi (2019). Including 732 in-situ SM measurements over China, in MatLab data format (.mat). <br> Reference: Wang, A., Shi, X., 2019. A Multilayer Soil Moisture Dataset Based on the Gravimetric Method in China and Its Characteristics. Journal of Hydrometeorology 20, 1721–1736. https://doi.org/10.1175/JHM-D-19-0035.1
DOI: 10.6084/m9.figshare.22730780
title: <strong>Machine learning enabled rational design for dynamic thermal emitters with phase-change materials</strong>

description: It is about 5000 groups of structural parameters that are randomly generated, and their spectral responses at both metallic and insulator states are calculated by using the full-wave method, which is performed using the finite element solver in conjunction with Python.
DOI: 10.6084/m9.figshare.22730780.v1
title: <strong>Machine learning enabled rational design for dynamic thermal emitters with phase-change materials</strong>

description: It is about 5000 groups of structural parameters that are randomly generated, and their spectral responses at both metallic and insulator states are calculated by using the full-wave method, which is performed using the finite element solver in conjunction with Python.
DOI: 10.6084/m9.figshare.22757963
title: VenomSeq on 9 purified teretoxin peptides

description: # DESCRIPTION OF CONTENTS <br> This directory contains one CSV file for each of 13 expression signatures (9 experimental samples and 3 controls) used to evaluate the VenomSeq technology platform against isolated, purified venom components. <br> <br> # OTHER EXPERIMENTAL INFORMATION <br> The human cell line used for perturbational differential expression analysis is IMR-32. <br> <br> # OTHER INCLUDED FILES <br> Original raw data is provided in the data/ subdirectory. <br> Also included is an R-Markdown file used to perform the differential expression analysis. <br> <br> # EXPLANATION OF DIFFERENTIAL EXPRESSION SIGNATURES <br> An empty CSV file indicates that no genes were significantly differentially expressed on exposure to the peptide in question. <br> Two positive controls are included: <br> - Cy3crotamine.csv; Fluorescent version of crotamine, a major peptide from the venom of Crotalus durissus terrificus known to inhibit the growth of several cancer cell types via the inhibition of voltage-gated potassium ion channels such as Kv1.3. Since crotamine is known to have strong effects on human neuronal cell lines (such as IMR-32), we expected to see a robust differential expression signature in the form of multiple up- and down-regulated genes. This is confirmed by Crotamine yielding the largest expression signature. <br> - Cimperialis.csv; Conus imperialis - the magician cone snail - is a venomous marine snail with a complex venom consisting of several hundred distinct components. Crude C. imperialis venom was used in the inital run of VenomSeq on venoms from 25 diverse species. The resulting expression signature in this VenomSeq run is consistent with the signature produced in the original run. <br> One negative control is included: <br> - GsMTx4.csv; GsMTx-4 is a neurotoxic venom component from Grammostola spatulata, which reduces sensation by inhibiting mechanosensitive channels such as PIEZO1 and TRPC6. This is a negative control, because these inhibitory effects are not expected to result in significant changes to gene expression. This is confirmed by the signature being empty. <br> <br> Expression signatures for 9 teretoxins selected from an in-house terebrid venom component library are included: <br> - Tba1.1 - Tv1 - Tan9.10 - Tfu6.8 - Ts14.1 - Mki8.7 - Tan22.12 - Tsu1.1 - ArgT5 <br> Mki8.7 is the teretoxin yielding the most robust differential expression signature, with 13 down-regulated and 12 up-regulated genes. <br> 5 teretoxins yielded empty expression signatures. <br>
DOI: 10.6084/m9.figshare.22757963.v1
title: VenomSeq on 9 purified teretoxin peptides

description: # DESCRIPTION OF CONTENTS <br> This directory contains one CSV file for each of 13 expression signatures (9 experimental samples and 3 controls) used to evaluate the VenomSeq technology platform against isolated, purified venom components. <br> <br> # OTHER EXPERIMENTAL INFORMATION <br> The human cell line used for perturbational differential expression analysis is IMR-32. <br> <br> # OTHER INCLUDED FILES <br> Original raw data is provided in the data/ subdirectory. <br> Also included is an R-Markdown file used to perform the differential expression analysis. <br> <br> # EXPLANATION OF DIFFERENTIAL EXPRESSION SIGNATURES <br> An empty CSV file indicates that no genes were significantly differentially expressed on exposure to the peptide in question. <br> Two positive controls are included: <br> - Cy3crotamine.csv; Fluorescent version of crotamine, a major peptide from the venom of Crotalus durissus terrificus known to inhibit the growth of several cancer cell types via the inhibition of voltage-gated potassium ion channels such as Kv1.3. Since crotamine is known to have strong effects on human neuronal cell lines (such as IMR-32), we expected to see a robust differential expression signature in the form of multiple up- and down-regulated genes. This is confirmed by Crotamine yielding the largest expression signature. <br> - Cimperialis.csv; Conus imperialis - the magician cone snail - is a venomous marine snail with a complex venom consisting of several hundred distinct components. Crude C. imperialis venom was used in the inital run of VenomSeq on venoms from 25 diverse species. The resulting expression signature in this VenomSeq run is consistent with the signature produced in the original run. <br> One negative control is included: <br> - GsMTx4.csv; GsMTx-4 is a neurotoxic venom component from Grammostola spatulata, which reduces sensation by inhibiting mechanosensitive channels such as PIEZO1 and TRPC6. This is a negative control, because these inhibitory effects are not expected to result in significant changes to gene expression. This is confirmed by the signature being empty. <br> <br> Expression signatures for 9 teretoxins selected from an in-house terebrid venom component library are included: <br> - Tba1.1 - Tv1 - Tan9.10 - Tfu6.8 - Ts14.1 - Mki8.7 - Tan22.12 - Tsu1.1 - ArgT5 <br> Mki8.7 is the teretoxin yielding the most robust differential expression signature, with 13 down-regulated and 12 up-regulated genes. <br> 5 teretoxins yielded empty expression signatures. <br>
DOI: 10.25901/427v-dd41
title: Warra Tall Eucalypt Site, Long-Term Monitoring of Beetle Succession in Decaying Eucalyptus obliqua Logs, 1999-2009
DOI: 10.25912/rdf_1683174974223
title: Prebiotic supplement use, the gut microbiome and behaviour change in children with autism spectrum disorder (ASD).
DOI: 10.6084/m9.figshare.22758134
title: Phylogenetic placement of Scaphopoda

description: Phylogenetic placement of Scaphopoda
DOI: 10.6084/m9.figshare.22732451
title: Summary.xlsx

description: This study was performed in the frame of a more extensive study dedicated to the integrated analysis of the single-cell transcriptome and chromatin accessibility datasets of peripheral blood mononuclear cells (PBMCs) with a large-scale GWAS of 45 complex traits in Chinese Holstein cattle. Lipopolysaccharide (LPS) is a crucial mediator of chronic inflammation to modulate immune responses. PBMCs include primary T and B cells, natural killer (NK) cells, monocytes (Mono), and dendritic cells (DC). How LPS stimulates PBMCs at the single-cell level in dairy cattle remains largely unknown. We sequenced 30,756 single cells with approximately 62,254 reads per cell for four whole-blood treatments (no, 2 h, 4 h, and 8 h LPS) by single-cell RNA sequencing (scRNA-seq) and single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq). Finally, 7,107 (no), 9,174 (2 h), 6,741 (4 h), and 3,119 (8 h) cells were generated with ~ 15,000 total genes in the whole population. Therefore, the single-cell transcriptome and chromatin accessibility datasets in this study enable a further understanding of the cell types and functions of PBMCs and their responses to LPS stimulation <em>in vitro</em>.
DOI: 10.6084/m9.figshare.22732451.v7
title: Summary.xlsx

description: This study was performed in the frame of a more extensive study dedicated to the integrated analysis of the single-cell transcriptome and chromatin accessibility datasets of peripheral blood mononuclear cells (PBMCs) with a large-scale GWAS of 45 complex traits in Chinese Holstein cattle. Lipopolysaccharide (LPS) is a crucial mediator of chronic inflammation to modulate immune responses. PBMCs include primary T and B cells, natural killer (NK) cells, monocytes (Mono), and dendritic cells (DC). How LPS stimulates PBMCs at the single-cell level in dairy cattle remains largely unknown. We sequenced 30,756 single cells with approximately 62,254 reads per cell for four whole-blood treatments (no, 2 h, 4 h, and 8 h LPS) by single-cell RNA sequencing (scRNA-seq) and single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq). Finally, 7,107 (no), 9,174 (2 h), 6,741 (4 h), and 3,119 (8 h) cells were generated with ~ 15,000 total genes in the whole population. Therefore, the single-cell transcriptome and chromatin accessibility datasets in this study enable a further understanding of the cell types and functions of PBMCs and their responses to LPS stimulation <em>in vitro</em>.
DOI: 10.6084/m9.figshare.22732451.v6
title: Summary.xlsx

description: This study was performed in the frame of a more extensive study dedicated to the integrated analysis of the single-cell transcriptome and chromatin accessibility datasets of peripheral blood mononuclear cells (PBMCs) with a large-scale GWAS of 45 complex traits in Chinese Holstein cattle. Lipopolysaccharide (LPS) is a crucial mediator of chronic inflammation to modulate immune responses. PBMCs include primary T and B cells, natural killer (NK) cells, monocytes (Mono), and dendritic cells (DC). How LPS stimulates PBMCs at the single-cell level in dairy cattle remains largely unknown. We sequenced 30,756 single cells with approximately 62,254 reads per cell for four whole-blood treatments (no, 2 h, 4 h, and 8 h LPS) by single-cell RNA sequencing (scRNA-seq) and single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq). Finally, 7,107 (no), 9,174 (2 h), 6,741 (4 h), and 3,119 (8 h) cells were generated with ~ 15,000 total genes in the whole population. Therefore, the single-cell transcriptome and chromatin accessibility datasets in this study enable a further understanding of the cell types and functions of PBMCs and their responses to LPS stimulation <em>in vitro</em>.
DOI: 10.6084/m9.figshare.21821253
title: Source data file

description: This source data includes dynamics of community composition, detected metabolites in metabolomics, differentially expressed genes in transcriptomic data, abundances of different genotypes in co-culture and concentrations of AAs.
DOI: 10.6084/m9.figshare.21821253.v3
title: Source data file

description: This source data includes dynamics of community composition, detected metabolites in metabolomics, differentially expressed genes in transcriptomic data, abundances of different genotypes in co-culture and concentrations of AAs.
DOI: 10.5281/zenodo.7892405
title: Interface Adsorption versus Bulk Micellization of Surfactants: Insights from Molecular Simulations

description: Essential files for Gromacs used in the study "Interface Adsorption versus Bulk Micellization of Surfactants: Insights from Molecular Simulations," JCTC to simulate C12EO6 surfactants in bulk water (as micelles) and at a decane/water interface (monolayer).
DOI: 10.5281/zenodo.7892404
title: Interface Adsorption versus Bulk Micellization of Surfactants: Insights from Molecular Simulations

description: Essential files for Gromacs used in the study "Interface Adsorption versus Bulk Micellization of Surfactants: Insights from Molecular Simulations," JCTC to simulate C12EO6 surfactants in bulk water (as micelles) and at a decane/water interface (monolayer).