cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.26652144
title: Additional file 2 of Research on the targeted improvement of the yield of a new VB12-producing strain, Ensifer adhaerens S305, based on genomic and transcriptomic analysis

description: Additional file 2: Table S1. Comparison of genomic basic information between S305 and Casida A, Ensifer adhaerens Corn53 strains. Table S2. Ensifer adhaerens S305 genome sequencing genes and protein association annotations of VB12 synthesis related genes. Table S3. Similarity of amino acid sequences of the protein encoding the VB12 synthesis pathway gene between S305 and Casida A strain. Table S4. Quality control data statistics. Table S5. Significant expression of genes in the VB12 synthesis pathway of S305 and Casida A strain. Table S6. List of the strains and plasmids used in this study. Table S7. Primers used in this study.
DOI: 10.6084/m9.figshare.26652144.v1
title: Additional file 2 of Research on the targeted improvement of the yield of a new VB12-producing strain, Ensifer adhaerens S305, based on genomic and transcriptomic analysis

description: Additional file 2: Table S1. Comparison of genomic basic information between S305 and Casida A, Ensifer adhaerens Corn53 strains. Table S2. Ensifer adhaerens S305 genome sequencing genes and protein association annotations of VB12 synthesis related genes. Table S3. Similarity of amino acid sequences of the protein encoding the VB12 synthesis pathway gene between S305 and Casida A strain. Table S4. Quality control data statistics. Table S5. Significant expression of genes in the VB12 synthesis pathway of S305 and Casida A strain. Table S6. List of the strains and plasmids used in this study. Table S7. Primers used in this study.
DOI: 10.15468/dl.pdzk3c
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.047733 -32.342283, 149.047733 -32.344529, 149.052225 -32.344529, 149.052225 -32.342283, 149.047733 -32.342283))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065988-240626123714530/datasets/export for details.
DOI: 10.5281/zenodo.13318908
title: New Insights into the Correlation between Bone Mineral Density at Various Sites and Dental Caries: Highlighting the Role of Head Bone Mineral Density

description:  Investigate the relationship between bone mineral density (BMD) at various body sites and dental caries.Materials and methods: Based on the National Health and Nutrition Examination Survey (NHANES) database from 2011-2016, the correlation between BMD at various body sites and the DMFS index among 7044 adults aged 20-59 years was analyzed. Multiple linear regression, restricted cubic splines (RCS), piecewise linear regression, logistic regression, weighted quantile sum regression (WQS) and mediation effects analysis were integrated to explore the relationship between BMD and dental caries.Results: Under the linear assumption, except for arm BMD, the BMDs of all other sites are negatively correlated with the DMFS index of dental caries. RCS analysis indicates a U-shaped relationship between head BMD and the DMFS index (p for nonlinear < 0.0001). WQS analysis indicates that mixed BMD is significantly negatively correlated with the DMFS index for dental caries (estimate, −0.023; 95% CI, −0.025 ~ −0.020), and head BMD has the most significant impact on the DMFS index (weight = 91.4%). Simple mediation analysis of the effect of dental caries on BMD levels mediated by inflammation levels showed negative results, suggesting that dental caries may not influence BMD through inflammation levels.Conclusion: Monitoring BMD should be combined with appropriate oral healthcare and caries management strategies to effectively address these interconnected health issues, and particular attention should be paid to the monitoring of head BMD.
DOI: 10.5281/zenodo.13318909
title: New Insights into the Correlation between Bone Mineral Density at Various Sites and Dental Caries: Highlighting the Role of Head Bone Mineral Density

description:  Investigate the relationship between bone mineral density (BMD) at various body sites and dental caries.Materials and methods: Based on the National Health and Nutrition Examination Survey (NHANES) database from 2011-2016, the correlation between BMD at various body sites and the DMFS index among 7044 adults aged 20-59 years was analyzed. Multiple linear regression, restricted cubic splines (RCS), piecewise linear regression, logistic regression, weighted quantile sum regression (WQS) and mediation effects analysis were integrated to explore the relationship between BMD and dental caries.Results: Under the linear assumption, except for arm BMD, the BMDs of all other sites are negatively correlated with the DMFS index of dental caries. RCS analysis indicates a U-shaped relationship between head BMD and the DMFS index (p for nonlinear < 0.0001). WQS analysis indicates that mixed BMD is significantly negatively correlated with the DMFS index for dental caries (estimate, −0.023; 95% CI, −0.025 ~ −0.020), and head BMD has the most significant impact on the DMFS index (weight = 91.4%). Simple mediation analysis of the effect of dental caries on BMD levels mediated by inflammation levels showed negative results, suggesting that dental caries may not influence BMD through inflammation levels.Conclusion: Monitoring BMD should be combined with appropriate oral healthcare and caries management strategies to effectively address these interconnected health issues, and particular attention should be paid to the monitoring of head BMD.
DOI: 10.15468/dl.nzz3z7
title: Occurrence Download

description: A dataset containing 265 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Nassella trichotoma (Nees) Hack. & Arechav.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1900",
 "BasisOfRecord is one of (Specimen)",
 "Country is one of (Australia)",
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than or equal to 20000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 265 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065990-240626123714530/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.26591765
title: Additional file 4 of scMEB: a fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data

description: Additional file 4.
DOI: 10.15468/dl.p62qc2
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((144.486515 -36.705871, 144.486515 -36.712608, 144.488761 -36.712608, 144.488761 -36.714854, 144.495499 -36.714854, 144.495499 -36.712608, 144.497744 -36.712608, 144.497744 -36.708117, 144.493253 -36.708117, 144.493253 -36.705871, 144.486515 -36.705871))"
 ]
}

 The dataset includes 24 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065991-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/bbzr6tcsz9.1
title: Validation of Social Science Theories Using Machine Learning Models: A Methodological Perspective

description: this data was use in In validating Social Trust Theory, Political Participation Theory, and Happiness and Well-being Theory,leverages machine learning models—Random Forest (RF) and Support Vector Machine (SVM)— from 1972 to 2023 across six diverse countries.
DOI: 10.6084/m9.figshare.26591762.v1
title: Additional file 3 of scMEB: a fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data

description: Additional file 3.
DOI: 10.6084/m9.figshare.26591768
title: Additional file 5 of scMEB: a fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data

description: Additional file 5.
DOI: 10.6084/m9.figshare.26591771
title: Additional file 6 of scMEB: a fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data

description: Additional file 6.
DOI: 10.6084/m9.figshare.26565669.v1
title: Additional file 8 of Insights into the susceptibility of Pseudomonas putida to industrially relevant aromatic hydrocarbons that it can synthesize from sugars

description: Additional file 8: Table S5. Proteins induced 1.5-fold or more in response to styrene supplied through the gas phase (Styrene (g)), trans-cinnamic acid (tCA) or both compounds (Styrene (g) + tCA).
DOI: 10.6084/m9.figshare.26591768.v1
title: Additional file 5 of scMEB: a fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data

description: Additional file 5.
DOI: 10.15468/dl.w5mb8p
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.148794 -32.342283, 149.148794 -32.346775, 149.15104 -32.346775, 149.15104 -32.353512, 149.160023 -32.353512, 149.160023 -32.346775, 149.155531 -32.346775, 149.155531 -32.344529, 149.15104 -32.344529, 149.15104 -32.342283, 149.148794 -32.342283))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065992-240626123714530/datasets/export for details.
DOI: 10.5281/zenodo.13319047
title: CLDF dataset derived from Lieberherr and Bodt's "Comparative Wordlists of Kho-Bwa" from 2017

description: Cite the source of the dataset as:




Lieberherr, Ismail and Bodt, Timotheus Adrianus (2017): Sub-grouping Kho-Bwa based on shared core vocabulary. Himalayan Linguistics 16(2). 26-63. URL: https://escholarship.org/uc/item/4t27h5fg
DOI: 10.6084/m9.figshare.26652258
title: Additional file 8 of Caprin-1 influences autophagy-induced tumor growth and immune modulation in pancreatic cancer

description: Additional file 8: Intersection of gene signatures between early vs. late stage tumors and long-term vs. short survival patients.
DOI: 10.6084/m9.figshare.26652258.v1
title: Additional file 8 of Caprin-1 influences autophagy-induced tumor growth and immune modulation in pancreatic cancer

description: Additional file 8: Intersection of gene signatures between early vs. late stage tumors and long-term vs. short survival patients.
DOI: 10.6084/m9.figshare.26565723.v1
title: Additional file 4 of Semi-field evaluation of the space spray efficacy of Fludora Co-Max EW against wild insecticide-resistant Aedes aegypti and Culex quinquefasciatus mosquito populations from Abidjan, Côte d’Ivoire

description: Additional file 4: Figure S2. Different methods used for the semi-field evaluation of the efficacy of Fludora Co-Max EW and K-Othrine against Aedes aegypti and Culex quinquefasciatus Abidjan strain mosquitoes in Agboville, Côte d’Ivoire. a outdoor ULV, b outdoor TF, c indoor ULV, and d indoor TF. ULV, Ultra-low volume; TF, thermal fogging.
DOI: 10.6084/m9.figshare.26565669
title: Additional file 8 of Insights into the susceptibility of Pseudomonas putida to industrially relevant aromatic hydrocarbons that it can synthesize from sugars

description: Additional file 8: Table S5. Proteins induced 1.5-fold or more in response to styrene supplied through the gas phase (Styrene (g)), trans-cinnamic acid (tCA) or both compounds (Styrene (g) + tCA).
DOI: 10.17632/34368brxcr.1
title: Sample2

description: Sample2 data
DOI: 10.6084/m9.figshare.26591651
title: Additional file 4 of Molecular drivers of insecticide resistance in the Sahelo-Sudanian populations of a major malaria vector Anopheles coluzzii

description: Additional file 4: Population genetics analyses. Sheet 1: Tajima’s per gene. Sheet 2: FST per gene.
DOI: 10.15156/bio/sh0185247.10fu
title: SH0185247.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0185248.10fu
title: SH0185248.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0185249.10fu
title: SH0185249.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0185250.10fu
title: SH0185250.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0185251.10fu
title: SH0185251.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0185252.10fu
title: SH0185252.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0185253.10fu
title: SH0185253.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0185254.10fu
title: SH0185254.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0185255.10fu
title: SH0185255.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0185256.10fu
title: SH0185256.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.