cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.5ajr9e
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Elatostema capizense Merr."
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040890-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qbyjap
title: Occurrence Download

description: A dataset containing 252058 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is Uganda"
 ]
}

 The dataset includes 252058 records from 350 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009565-150615163101818/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15169289
title: NFFA-Europe|Pilot proporsal "O2 rich ices: Investigating the catalytic effect of low energy electrons on Solar System relevant ices." PID695

description: IR Spectroscopy, Mass Spectrometry, and XPS data collected during the NEP-PID695 from 11/11/2024 until 14/11/2024.
description: To open '.RAR' files, you can do so using WinRAR softwar, following the steps in the link, or by using the open-source software 7zip, following the steps in the link.
DOI: 10.5281/zenodo.15169288
title: NFFA-Europe|Pilot proporsal "O2 rich ices: Investigating the catalytic effect of low energy electrons on Solar System relevant ices." PID695

description: IR Spectroscopy, Mass Spectrometry, and XPS data collected during the NEP-PID695 from 11/11/2024 until 14/11/2024.
description: To open '.RAR' files, you can do so using WinRAR softwar, following the steps in the link, or by using the open-source software 7zip, following the steps in the link.
DOI: 10.5281/zenodo.15169294
title: Draft genomes of bacterial isolates from Argentina's Museum of Independence

description: This dataset contains draft genome assemblies of eight bacterial isolates recovered from different historical artifacts and architectural surfaces from Argentina’s Museum of Independence. The genomes were sequenced using Illumina technology and assembled using SPAdes. Coverage and metadata are included. These genomes are related to the manuscript submitted to biorxiv: https://doi.org/10.1101/2025.03.28.645971
DOI: 10.5281/zenodo.15169295
title: Draft genomes of bacterial isolates from Argentina's Museum of Independence

description: This dataset contains draft genome assemblies of eight bacterial isolates recovered from different historical artifacts and architectural surfaces from Argentina’s Museum of Independence. The genomes were sequenced using Illumina technology and assembled using SPAdes. Coverage and metadata are included. These genomes are related to the manuscript submitted to biorxiv: https://doi.org/10.1101/2025.03.28.645971
DOI: 10.6084/m9.figshare.28738217
title: Data for <b>Biodiversity and management as central players in the network of relationships underlying forest resilience</b> - Global Change Biology

description: Global change is threatening the integrity of forest ecosystems worldwide, amplifying the need for resilience-based management to ensure their conservation and sustain the services they provide. Yet, current efforts are still limited by the lack of implementation of clear frameworks for operationalizing resilience in decision-making processes. To overcome this limitation, we aim to identify reliable and effective drivers of forest resilience, considering their synergies and trade-offs. From a comprehensive review of 367 scientific articles addressing resilience in forests globally, we identified factors shaping forest resilience. We recognized them into two categories that influence forest responses to disturbances: resilience predictors, which can be modified through management, and codrivers, which are measurable but largely unmanageable (e.g., climate). We then performed network analyses based on predictors and codrivers underlying forest resilience. In total, we recognized 5,332 such relationships linking predictors or codrivers with forest attributes resilience. Our findings support the central role of biodiversity, with mixed, non-planted, or functionally diverse forests promoting resilience across all contexts and biomes. While management also enhanced resilience, the success of specific interventions was highly context-dependent, suggesting that its application requires a careful analysis of trade-offs. Specifically, practices like cutting and prescribed burning generally enhanced resilience in terms of tree growth, plant diversity, landscape vegetation cover, and stand structure. In contrast, pest and herbivore control reduced the resilience of plant taxonomic diversity while offering only minimal gains for other variables. Even long-term restoration projects showed clear trade-offs in the resilience of different forest attributes, highlighting the need for careful consideration of these effects in practical management decisions. Overall, we emphasize that a reduced number of predictors can be used to effectively promote forest resilience across most attributes. Particularly, enhancing biodiversity and implementing targeted management strategies when biodiversity is impoverished emerge as powerful tools to promote forest resilience.
DOI: 10.6084/m9.figshare.24113059
title: Additional file 1 of Copy number variations (CNVs) and karyotyping analysis in males with azoospermia and oligospermia

description: Supplementary Material 1: Excel 1
DOI: 10.6084/m9.figshare.24113062
title: Additional file 2 of Copy number variations (CNVs) and karyotyping analysis in males with azoospermia and oligospermia

description: Supplementary Material 2: Excel 2
DOI: 10.6084/m9.figshare.24113062.v1
title: Additional file 2 of Copy number variations (CNVs) and karyotyping analysis in males with azoospermia and oligospermia

description: Supplementary Material 2: Excel 2
DOI: 10.6084/m9.figshare.24113065
title: Additional file 3 of Copy number variations (CNVs) and karyotyping analysis in males with azoospermia and oligospermia

description: Supplementary Material 3: Excel 3
DOI: 10.6084/m9.figshare.24113065.v1
title: Additional file 3 of Copy number variations (CNVs) and karyotyping analysis in males with azoospermia and oligospermia

description: Supplementary Material 3: Excel 3
DOI: 10.15468/dl.rtvbnd
title: Occurrence Download

description: A dataset containing 57 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((148.699634 -33.849214, 148.699634 -33.853706, 148.695143 -33.853706, 148.695143 -33.855952, 148.697388 -33.855952, 148.697388 -33.860443, 148.704126 -33.860443, 148.704126 -33.855952, 148.710863 -33.855952, 148.710863 -33.849214, 148.722092 -33.849214, 148.722092 -33.844723, 148.726584 -33.844723, 148.726584 -33.846969, 148.72883 -33.846969, 148.72883 -33.837985, 148.719846 -33.837985, 148.719846 -33.840231, 148.717601 -33.840231, 148.717601 -33.844723, 148.706372 -33.844723, 148.706372 -33.849214, 148.699634 -33.849214)), ((148.699634 -33.849214, 148.699634 -33.846969, 148.697388 -33.846969, 148.697388 -33.849214, 148.699634 -33.849214)), ((148.72883 -33.846969, 148.72883 -33.849214, 148.733321 -33.849214, 148.733321 -33.853706, 148.742304 -33.853706, 148.742304 -33.849214, 148.735567 -33.849214, 148.735567 -33.846969, 148.72883 -33.846969)), ((148.733321 -33.853706, 148.72883 -33.853706, 148.72883 -33.855952, 148.733321 -33.855952, 148.733321 -33.853706)))"
 ]
}

 The dataset includes 57 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069818-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.24112975
title: Additional file 4 of Integrated bioinformatics analysis of dendritic cells hub genes reveal potential early tuberculosis diagnostic markers

description: Supplementary Material 4: Table S2 GO analysis for genes.Table S3 KEGG analysis for genes.
DOI: 10.6084/m9.figshare.24112975.v1
title: Additional file 4 of Integrated bioinformatics analysis of dendritic cells hub genes reveal potential early tuberculosis diagnostic markers

description: Supplementary Material 4: Table S2 GO analysis for genes.Table S3 KEGG analysis for genes.
DOI: 10.6084/m9.figshare.24113102
title: Additional file 1 of Genetic diversity and wing geometric morphometrics among four populations of Aedes aegypti (Diptera: Culicidae) from Benin

description: Additional file 1. Table S1: Sampling data and landmark coordinates.
DOI: 10.6084/m9.figshare.24113102.v1
title: Additional file 1 of Genetic diversity and wing geometric morphometrics among four populations of Aedes aegypti (Diptera: Culicidae) from Benin

description: Additional file 1. Table S1: Sampling data and landmark coordinates.
DOI: 10.6084/m9.figshare.24115070
title: Additional file 1 of New mechanisms and biomarkers of lymph node metastasis in cervical cancer: reflections from plasma proteomics

description: Additional file 1: Figure S1. The top nine DEPs with a significant difference between every two groups. Figure S2. Subcellular localization and domain enrichment analysis of DEPs between the LNM and NC groups. Figure S3. GO and KEGG pathway analysis of DEPs between the LNM and NC groups. Figure S4. Subcellular localization and domain enrichment analysis of DEPs between the LVSI and NC groups. Figure S5. GO and KEGG pathway analysis of DEPs between the LVSI and NC groups. Figure S6. Subcellular localization and domain enrichment analysis of DEPs between the LNM and LVSI groups. Figure S7. GO and KEGG pathway analysis of DEPs between the LNM and LVSI groups.
DOI: 10.6084/m9.figshare.24115070.v1
title: Additional file 1 of New mechanisms and biomarkers of lymph node metastasis in cervical cancer: reflections from plasma proteomics

description: Additional file 1: Figure S1. The top nine DEPs with a significant difference between every two groups. Figure S2. Subcellular localization and domain enrichment analysis of DEPs between the LNM and NC groups. Figure S3. GO and KEGG pathway analysis of DEPs between the LNM and NC groups. Figure S4. Subcellular localization and domain enrichment analysis of DEPs between the LVSI and NC groups. Figure S5. GO and KEGG pathway analysis of DEPs between the LVSI and NC groups. Figure S6. Subcellular localization and domain enrichment analysis of DEPs between the LNM and LVSI groups. Figure S7. GO and KEGG pathway analysis of DEPs between the LNM and LVSI groups.
DOI: 10.6084/m9.figshare.24115004
title: Additional file 1 of Maternal COVID-19 causing intrauterine foetal demise with microthrombotic placental insufficiency: a case report

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.24115004.v1
title: Additional file 1 of Maternal COVID-19 causing intrauterine foetal demise with microthrombotic placental insufficiency: a case report

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.24115068
title: Additional file 2 of Genomic characterization of colistin-resistant Klebsiella pneumoniae isolated from intensive care unit patients in Egypt

description: Additional file 2: Table S1. Demographic data of collected colistin-resistant K. pneumoniae isolates. Table S2. MIC Distribution of colistin determined by broth microdilution. Table S3. Assembly statistics of the 17 colistin-resistant K. pneumoniae draft genomes. Table S4. Plasmid replicon types and genetic determinants of virulence, heavy metal resistance and antimicrobial resistance of the colistin-resistant K. pneumoniae isolates. Table S5. Phenotypic and genotypic profiles of  antimicrobial resistance for K. pneumoniae isolates.
DOI: 10.6084/m9.figshare.24115068.v1
title: Additional file 2 of Genomic characterization of colistin-resistant Klebsiella pneumoniae isolated from intensive care unit patients in Egypt

description: Additional file 2: Table S1. Demographic data of collected colistin-resistant K. pneumoniae isolates. Table S2. MIC Distribution of colistin determined by broth microdilution. Table S3. Assembly statistics of the 17 colistin-resistant K. pneumoniae draft genomes. Table S4. Plasmid replicon types and genetic determinants of virulence, heavy metal resistance and antimicrobial resistance of the colistin-resistant K. pneumoniae isolates. Table S5. Phenotypic and genotypic profiles of  antimicrobial resistance for K. pneumoniae isolates.
DOI: 10.6084/m9.figshare.24115095
title: Additional file 1 of Breastfeeding in primiparous women – expectations and reality: a prospective questionnaire survey

description: Additional file 1.
DOI: 10.6084/m9.figshare.24115095.v1
title: Additional file 1 of Breastfeeding in primiparous women – expectations and reality: a prospective questionnaire survey

description: Additional file 1.
DOI: 10.6084/m9.figshare.24116530
title: Additional file 2 of Purifying selection leads to low protein diversity of the mitochondrial cyt b gene in avian malaria parasites

description: Additional file 2.
DOI: 10.6084/m9.figshare.24116530.v1
title: Additional file 2 of Purifying selection leads to low protein diversity of the mitochondrial cyt b gene in avian malaria parasites

description: Additional file 2.
DOI: 10.6084/m9.figshare.24123771
title: Additional file 1 of Sulfur-cycling chemolithoautotrophic microbial community dominates a cold, anoxic, hypersaline Arctic spring

description: Additional file 1: Figure S1.a. Photograph of GH-4 primary outlet and downstream channels (July 2019). A fine layer of gypsum coats the area around the springs. b. Location of the Gypsum Hill springs on Axel Heiberg Island, Nunavut, Canada (indicated with red dot). Map generated in QGIS with the Natural Earth dataset. c. Photograph of the Gypsum Hill springs area in which GH-4 is located. Photos: E. Magnuson. Figure S2. Phylogenetic tree of DsrAB sequences. Figure S3. Phylogenetic tree of DsrA sequences. Figure S4. Phylogenetic tree of DsrB sequences. Figure S5. Phylogenetic trees of DsrA and DsrB sequences. Figure S6. Relative abundance of reads in the metagenome and metatranscriptome classified by Kaiju using the NCBI non-redundant database (nr_euk). Relative abundance was averaged between replicates for both the metagenome and metatranscriptome. Figure S7. Level of taxonomic novelty of ASVs (2,885 ASVs in total). Figure S8. Spearman’s rank correlation of the top 50 most abundant taxa in the subset of thirteen 16S rRNA gene sequencing data sets with environmental parameters. Metadata for this plot is located in Table S4. Figure S9. NMDS plot with Bray Curtis dissimilarity matrix for 16S rRNA gene amplicon sequences from GH and comparable environments. Metadata for this plot is located in Table S4. Table S1. Physical and chemical parameters in GH-4. Table S2. Sequencing library statistics. Table S3. Metagenome co-assembly statistics. Table S4. Metadata for amplicon metagenome libraries used in beta diversity analysis. Table S5. Taxonomic count table used for beta diversity analysis. Table S6. List of contigs in each MAG. Table S7. MAG supplemental information. Table S8. Taxonomic classification of genes of interest with mapped transcripts. Table S9. Gene content of MAGs. Table S10. Relative expression of genes of interest in MAGs. Table S11. Total tpm per genome feature product ID. Table S12. Gene counts and relative expression of genes of interest in the metagenome. Table S13. Complete BLAST output of elemental sulfur reduction proteins queried against Desulfuromusa sp. GH17. Table S14. Relative expression of all genes.
DOI: 10.6084/m9.figshare.24123771.v1
title: Additional file 1 of Sulfur-cycling chemolithoautotrophic microbial community dominates a cold, anoxic, hypersaline Arctic spring

description: Additional file 1: Figure S1.a. Photograph of GH-4 primary outlet and downstream channels (July 2019). A fine layer of gypsum coats the area around the springs. b. Location of the Gypsum Hill springs on Axel Heiberg Island, Nunavut, Canada (indicated with red dot). Map generated in QGIS with the Natural Earth dataset. c. Photograph of the Gypsum Hill springs area in which GH-4 is located. Photos: E. Magnuson. Figure S2. Phylogenetic tree of DsrAB sequences. Figure S3. Phylogenetic tree of DsrA sequences. Figure S4. Phylogenetic tree of DsrB sequences. Figure S5. Phylogenetic trees of DsrA and DsrB sequences. Figure S6. Relative abundance of reads in the metagenome and metatranscriptome classified by Kaiju using the NCBI non-redundant database (nr_euk). Relative abundance was averaged between replicates for both the metagenome and metatranscriptome. Figure S7. Level of taxonomic novelty of ASVs (2,885 ASVs in total). Figure S8. Spearman’s rank correlation of the top 50 most abundant taxa in the subset of thirteen 16S rRNA gene sequencing data sets with environmental parameters. Metadata for this plot is located in Table S4. Figure S9. NMDS plot with Bray Curtis dissimilarity matrix for 16S rRNA gene amplicon sequences from GH and comparable environments. Metadata for this plot is located in Table S4. Table S1. Physical and chemical parameters in GH-4. Table S2. Sequencing library statistics. Table S3. Metagenome co-assembly statistics. Table S4. Metadata for amplicon metagenome libraries used in beta diversity analysis. Table S5. Taxonomic count table used for beta diversity analysis. Table S6. List of contigs in each MAG. Table S7. MAG supplemental information. Table S8. Taxonomic classification of genes of interest with mapped transcripts. Table S9. Gene content of MAGs. Table S10. Relative expression of genes of interest in MAGs. Table S11. Total tpm per genome feature product ID. Table S12. Gene counts and relative expression of genes of interest in the metagenome. Table S13. Complete BLAST output of elemental sulfur reduction proteins queried against Desulfuromusa sp. GH17. Table S14. Relative expression of all genes.
DOI: 10.15468/dl.5pxdby
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.753533 -33.858198, 148.753533 -33.860443, 148.755779 -33.860443, 148.755779 -33.858198, 148.753533 -33.858198))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069820-240626123714530/datasets/export for details.
DOI: 10.6084/m9.figshare.26628415.v1
title: Additional file 1 of Determinants of life satisfaction among migrants in South Africa: an analysis of the GCRO’s quality of life survey (2009–2021)

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.24123863
title: Additional file 1 of Arabic version of the Extended Nordic Musculoskeletal Questionnaire, cross-cultural adaptation and psychometric testing

description: Additional file 1. Raw Data.
DOI: 10.6084/m9.figshare.24123863.v1
title: Additional file 1 of Arabic version of the Extended Nordic Musculoskeletal Questionnaire, cross-cultural adaptation and psychometric testing

description: Additional file 1. Raw Data.
DOI: 10.6084/m9.figshare.26627818.v1
title: Additional file 1 of A novel deep learning-based algorithm combining histopathological features with tissue areas to predict colorectal cancer survival from whole-slide images

description: Additional file 1: Table S1. The performance of different combinations of histopathological tissue.
DOI: 10.6084/m9.figshare.24123890
title: Additional file 8 of Combination of RUNX1 inhibitor and gemcitabine mitigates chemo‐resistance in pancreatic ductal adenocarcinoma by modulating BiP/PERK/eIF2α-axis-mediated endoplasmic reticulum stress

description: Additional file 8. Clinical drug file of patients for PDAC from TCGA dataset.
DOI: 10.6084/m9.figshare.24123890.v1
title: Additional file 8 of Combination of RUNX1 inhibitor and gemcitabine mitigates chemo‐resistance in pancreatic ductal adenocarcinoma by modulating BiP/PERK/eIF2α-axis-mediated endoplasmic reticulum stress

description: Additional file 8. Clinical drug file of patients for PDAC from TCGA dataset.
DOI: 10.6084/m9.figshare.24123776
title: Additional file 2 of Multiomics comparative analysis of the maize large grain mutant tc19 identified pathways related to kernel development

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.24123776.v1
title: Additional file 2 of Multiomics comparative analysis of the maize large grain mutant tc19 identified pathways related to kernel development

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.24123779
title: Additional file 3 of Multiomics comparative analysis of the maize large grain mutant tc19 identified pathways related to kernel development

description: Supplementary Material 3
DOI: 10.6084/m9.figshare.24123779.v1
title: Additional file 3 of Multiomics comparative analysis of the maize large grain mutant tc19 identified pathways related to kernel development

description: Supplementary Material 3
DOI: 10.6084/m9.figshare.24123708
title: Additional file 3 of Radiomic features from multiparametric magnetic resonance imaging predict molecular subgroups of pediatric low-grade gliomas

description: Supplementary Material 3
DOI: 10.6084/m9.figshare.24123708.v1
title: Additional file 3 of Radiomic features from multiparametric magnetic resonance imaging predict molecular subgroups of pediatric low-grade gliomas

description: Supplementary Material 3
DOI: 10.6084/m9.figshare.24123738.v1
title: Additional file 2 of Degradation of methylation signals in cryopreserved DNA

description: Additional file2: Table S1. Results for the robust linear regression for mean global methylation, repeated using methylation beta-values. Table S2. Mean AIC and BIC for the discovery cohort for different models testing differential methylation in association with duration in storage as DNA. Table S3. Mean AIC and BIC for the validation cohort for different models testing differential methylation in association with duration in storage as DNA. Table S4. CpGs hypomethylated in both the discovery (q &lt; 0.05) and validation (p &lt; 0.05) cohorts.
DOI: 10.6084/m9.figshare.24123738
title: Additional file 2 of Degradation of methylation signals in cryopreserved DNA

description: Additional file2: Table S1. Results for the robust linear regression for mean global methylation, repeated using methylation beta-values. Table S2. Mean AIC and BIC for the discovery cohort for different models testing differential methylation in association with duration in storage as DNA. Table S3. Mean AIC and BIC for the validation cohort for different models testing differential methylation in association with duration in storage as DNA. Table S4. CpGs hypomethylated in both the discovery (q &lt; 0.05) and validation (p &lt; 0.05) cohorts.
DOI: 10.6084/m9.figshare.24123899.v1
title: Additional file 1 of Analysis of DNA methylation at birth and in childhood reveals changes associated with season of birth and latitude

description: Additional file 1. Table S1: “Summary of the studies in the meta-analysis for the association between Season of Birth and DNA methylation at birth and in children (age: 1 to 11 years)”. Baseline summary of participants from each of the individual cohorts.
DOI: 10.6084/m9.figshare.24123899
title: Additional file 1 of Analysis of DNA methylation at birth and in childhood reveals changes associated with season of birth and latitude

description: Additional file 1. Table S1: “Summary of the studies in the meta-analysis for the association between Season of Birth and DNA methylation at birth and in children (age: 1 to 11 years)”. Baseline summary of participants from each of the individual cohorts.
DOI: 10.6084/m9.figshare.24123920
title: Additional file 5 of Analysis of DNA methylation at birth and in childhood reveals changes associated with season of birth and latitude

description: Additional file 5. Table S4: “Direction of differential methylation of CpGs in DMRs of the at-birth and childhood analyses (preliminary analysis”).