cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.2mj3bh
title: Occurrence Download

description: A dataset containing 133 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mermis nigrescens Dujardin, 1842"
 ]
}

 The dataset includes 133 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010133-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nx9a7c
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is one of (Ursus arctos)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "Elevation is greater than 200m",
 "Country is Spain",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1990"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0245111-200613084148143/datasets/export for details.
DOI: 10.15468/dl.tqcu2b
title: Occurrence Download

description: A dataset containing 2847 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carphophis amoenus (Say, 1825)",
 "HasCoordinate is True",
 "Country is United States of America",
 "Year is greater than or equal to 1960",
 "Year is less than or equal to 2020",
 "Month is greater than or equal to January",
 "Month is less than or equal to December",
 "HasGeospatialIssue is False",
 "DecimalLatitude is greater than or equal to 24.5",
 "DecimalLatitude is less than or equal to 49.5",
 "DecimalLongitude is greater than or equal to -125.0",
 "DecimalLongitude is less than or equal to -66.5"
 ]
}

 The dataset includes 2847 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0107152-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wlxqty
title: Occurrence Download

description: A dataset containing 10994 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Herpetofauna del Estado de Veracruz"
 ]
}

 The dataset includes 10994 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007155-180730143533302/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8ds348
title: Occurrence Download

description: A dataset containing 327 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Pseudoplatystoma fasciatum (Linnaeus, 1766)",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 327 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010140-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dhvkvr
title: Occurrence Download

description: A dataset containing 765 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-74.8877 -48.14454,-44.12598 -48.14454,-44.12598 -18.45703,-74.8877 -18.45703,-74.8877 -48.14454))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Sagittaria Ruppius ex L."
 ]
}

 The dataset includes 765 records from 72 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0287714-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8j8bwk
title: Occurrence Download

description: A dataset containing 3191734 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae",
 "Year 1991-1996"
 ]
}

 The dataset includes 3191734 records from 88 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0242326-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2qhfz4
title: Occurrence Download

description: A dataset containing 2416 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cenchrus incertus M.A.Curtis"
 ]
}

 The dataset includes 2416 records from 154 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050077-200613084148143/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.19234510.v1
title: Additional file 22 of DrABC: deep learning accurately predicts germline pathogenic mutation status in breast cancer patients based on phenotype data

description: Additional file 22. Pathogenic variants and variants of uncertain significance in this study.
DOI: 10.6084/m9.figshare.20282206
title: Additional file 9 of Genome-wide identification, phylogenetic analysis, and expression profiles of trihelix transcription factor family genes in quinoa (Chenopodium quinoa Willd.) under abiotic stress conditions

description: Additional file 9: Table S6. Relative expression data and ANOVA results for 10 selected CqTH genes.
DOI: 10.6084/m9.figshare.13466709
title: Additional file 10 of Weighted Gene Co-Expression Network Coupled with a Critical-Time-Point Analysis during Pathogenesis for Predicting the Molecular Mechanism Underlying Blast Resistance in Rice

description: Additional file 10 : Table S6. The genes information in brown module.
DOI: 10.6084/m9.figshare.13466715.v1
title: Additional file 13 of Weighted Gene Co-Expression Network Coupled with a Critical-Time-Point Analysis during Pathogenesis for Predicting the Molecular Mechanism Underlying Blast Resistance in Rice

description: Additional file 13 : Table S9. The genes information in red module.
DOI: 10.6084/m9.figshare.6651515.v1
title: Additional file 11: of Landscape of transcription and long non-coding RNAs reveals new insights into the inflammatory and fibrotic response following ventilator-induced lung injury

description: Table S6. The entire list of significant dysregulated GO terms of target genesÂ in the comparisons of each pair. (XLSX 2312 kb)
DOI: 10.6084/m9.figshare.19234465
title: Additional file 11 of DrABC: deep learning accurately predicts germline pathogenic mutation status in breast cancer patients based on phenotype data

description: Additional file 11: Table S3. The Performance of DrABC versus Previous Models in Multi-Center Validation Cohort.
DOI: 10.6084/m9.figshare.19234516
title: Additional file 3 of DrABC: deep learning accurately predicts germline pathogenic mutation status in breast cancer patients based on phenotype data

description: Additional file 3: Table S1. Summary of Pathogenic Variants and Variants of Uncertain Significance.
DOI: 10.6084/m9.figshare.6651602.v1
title: Additional file 2: of Landscape of transcription and long non-coding RNAs reveals new insights into the inflammatory and fibrotic response following ventilator-induced lung injury

description: Table S1. The entire list of differentially expressed transcripts (DETs) in the pairwiseÂ comparisons among the sham and VILI groups on day 0 and day 7. (XLSX 266 kb)
DOI: 10.6084/m9.figshare.6651665.v1
title: Additional file 6: of Landscape of transcription and long non-coding RNAs reveals new insights into the inflammatory and fibrotic response following ventilator-induced lung injury

description: Table S3. The entire list of significant dysregulated GO terms of DE mRNAs in the comparisons of each pair. (XLSX 1870 kb)
DOI: 10.6084/m9.figshare.13466713
title: Additional file 12 of Weighted Gene Co-Expression Network Coupled with a Critical-Time-Point Analysis during Pathogenesis for Predicting the Molecular Mechanism Underlying Blast Resistance in Rice

description: Additional file 12 : Table S8. The genes information in magenta module.
DOI: 10.6084/m9.figshare.13466715
title: Additional file 13 of Weighted Gene Co-Expression Network Coupled with a Critical-Time-Point Analysis during Pathogenesis for Predicting the Molecular Mechanism Underlying Blast Resistance in Rice

description: Additional file 13 : Table S9. The genes information in red module.
DOI: 10.6084/m9.figshare.19234483.v1
title: Additional file 16 of DrABC: deep learning accurately predicts germline pathogenic mutation status in breast cancer patients based on phenotype data

description: Additional file 16: Table S5. The Algorithms and Variables Incorporated in the Risk Prediction Models.
DOI: 10.6084/m9.figshare.19234573.v1
title: Additional file 2 of Predictive role of ferroptosis-related long non-coding RNAs in bladder cancer and their association with immune microenvironment and immunotherapy response

description: Additional file 2: Table S1. The expression matrix of TCGA cohort. Table S2. The downloaded clinical files of TCGA cohort. Table S3. The expression matrix of GEO cohort. Table S4. The downloaded clinical files of GEO cohort. Table S5. The Genome Reference file discriminating lncRNAs and mRNAs. Table S6. The expression matrix of lncRNAs during TCGA cohort. Table S7. The expression matrix of mRNAs during TCGA cohort. Table S8. The expression matrix of lncRNAs during GEO cohort. Table S9. The expression matrix of mRNAs during GEO cohort. Table S10. The detailed list of ferroptosis-related genes. Table S11. The expression matrix of ferroptosis-related genes during TCGA cohort. Table S12. The co-expression analysis results between lncRNAs and mRNAs. Table S13. The expression matrix of ferroptosis lncRNAs. Table S14. Detailed list of 59 differentially expressed ferroptosis genes between bladder cancer and normal tissues. Table S15. Detailed list of 538 differentially expressed ferroptosis lncRNAs between bladder cancer and normal tissues. Table S16. Detailed expression matrix of differentially expressed ferroptosis genes between bladder cancer and normal tissues. Table S17. Detailed expression matrix of differentially expressed ferroptosis lncRNAs between bladder cancer and normal tissues. Table S18. The merged document including both ferroptosis lncRNA expression and clinical information. Table S19. Detailed expression matrix of prognostic ferroptosis lncRNAs. Table S20. Detailed ferroptosis lncRNAs included in risk signature. Table S21. Detailed risk results depending on lncRNA risk signature in TCGA cohort. Table S22. Detailed risk results depending on lncRNA risk signature in GEO cohort. Table S23. The significantly enriched biological activities during high risk group. Table S24. The significantly enriched biological activities during low risk group. Table 25. The infiltration levels of various immune cells from http://timer.comp-genomics.org . Table S26. The detailed list of immune checkpoints-related genes. Table S27. The immunotherapy scoring information for TCGA cohort.
DOI: 10.6084/m9.figshare.19234492.v1
title: Additional file 18 of DrABC: deep learning accurately predicts germline pathogenic mutation status in breast cancer patients based on phenotype data

description: Additional file 18: Table S6. The Performance of Reconstructed Previous Models Which Were Trained in the Discovery Cohort and Tested in the Validation Cohort.
DOI: 10.6084/m9.figshare.19234366
title: Additional file 2 of MR-guided radiotherapy in node-positive non-small cell lung cancer and severely limited pulmonary reserve: a report proposing a new clinical pathway for the management of high-risk patients

description: Additional file 2: Box-plot of the primary tumour motion in posterior-anterior and inferior-superior directions for fractions 2-16.
DOI: 10.6084/m9.figshare.19234516.v1
title: Additional file 3 of DrABC: deep learning accurately predicts germline pathogenic mutation status in breast cancer patients based on phenotype data

description: Additional file 3: Table S1. Summary of Pathogenic Variants and Variants of Uncertain Significance.
DOI: 10.6084/m9.figshare.19234537.v1
title: Additional file 8 of DrABC: deep learning accurately predicts germline pathogenic mutation status in breast cancer patients based on phenotype data

description: Additional file 8: Table S2. The Neurons in the Input Layer of the DrABC Model.
DOI: 10.6084/m9.figshare.19234366.v1
title: Additional file 2 of MR-guided radiotherapy in node-positive non-small cell lung cancer and severely limited pulmonary reserve: a report proposing a new clinical pathway for the management of high-risk patients

description: Additional file 2: Box-plot of the primary tumour motion in posterior-anterior and inferior-superior directions for fractions 2-16.
DOI: 10.6084/m9.figshare.13466845
title: Additional file 8 of CircCDKN2B-AS1 interacts with IMP3 to stabilize hexokinase 2 mRNA and facilitate cervical squamous cell carcinoma aerobic glycolysis progression

description: Additional file 8: Table S4. All proteins verified by mass spectrometry analysis.
DOI: 10.6084/m9.figshare.6651695.v1
title: Additional file 8: of Landscape of transcription and long non-coding RNAs reveals new insights into the inflammatory and fibrotic response following ventilator-induced lung injury

description: Table S4. The entire list of dysregulated functional pathways of DE mRNAs in the comparisons of each pair. (XLSX 94 kb)
DOI: 10.6084/m9.figshare.19234537
title: Additional file 8 of DrABC: deep learning accurately predicts germline pathogenic mutation status in breast cancer patients based on phenotype data

description: Additional file 8: Table S2. The Neurons in the Input Layer of the DrABC Model.
DOI: 10.6084/m9.figshare.6651707
title: Additional file 9: of Landscape of transcription and long non-coding RNAs reveals new insights into the inflammatory and fibrotic response following ventilator-induced lung injury

description: Table S5. The entire list of DE lncRNAsÂ in the comparisons of each pair. (XLSX 100 kb)
DOI: 10.6084/m9.figshare.13466973.v1
title: Additional file 1 of Mutation screening of the UBE3A gene in Chinese Han population with autism

description: Additional file 1: Table S1. The allele and genotype distributions of rs71127053 and rs150331504 in ASD patients and healthy controls.
DOI: 10.6084/m9.figshare.6651635.v1
title: Additional file 4: of Landscape of transcription and long non-coding RNAs reveals new insights into the inflammatory and fibrotic response following ventilator-induced lung injury

description: Table S2. The entire list of dysregulated transcription factors (TFs) in the comparisons of each pair. (XLSX 62 kb)
DOI: 10.6084/m9.figshare.6651695
title: Additional file 8: of Landscape of transcription and long non-coding RNAs reveals new insights into the inflammatory and fibrotic response following ventilator-induced lung injury

description: Table S4. The entire list of dysregulated functional pathways of DE mRNAs in the comparisons of each pair. (XLSX 94 kb)
DOI: 10.6084/m9.figshare.19234573
title: Additional file 2 of Predictive role of ferroptosis-related long non-coding RNAs in bladder cancer and their association with immune microenvironment and immunotherapy response

description: Additional file 2: Table S1. The expression matrix of TCGA cohort. Table S2. The downloaded clinical files of TCGA cohort. Table S3. The expression matrix of GEO cohort. Table S4. The downloaded clinical files of GEO cohort. Table S5. The Genome Reference file discriminating lncRNAs and mRNAs. Table S6. The expression matrix of lncRNAs during TCGA cohort. Table S7. The expression matrix of mRNAs during TCGA cohort. Table S8. The expression matrix of lncRNAs during GEO cohort. Table S9. The expression matrix of mRNAs during GEO cohort. Table S10. The detailed list of ferroptosis-related genes. Table S11. The expression matrix of ferroptosis-related genes during TCGA cohort. Table S12. The co-expression analysis results between lncRNAs and mRNAs. Table S13. The expression matrix of ferroptosis lncRNAs. Table S14. Detailed list of 59 differentially expressed ferroptosis genes between bladder cancer and normal tissues. Table S15. Detailed list of 538 differentially expressed ferroptosis lncRNAs between bladder cancer and normal tissues. Table S16. Detailed expression matrix of differentially expressed ferroptosis genes between bladder cancer and normal tissues. Table S17. Detailed expression matrix of differentially expressed ferroptosis lncRNAs between bladder cancer and normal tissues. Table S18. The merged document including both ferroptosis lncRNA expression and clinical information. Table S19. Detailed expression matrix of prognostic ferroptosis lncRNAs. Table S20. Detailed ferroptosis lncRNAs included in risk signature. Table S21. Detailed risk results depending on lncRNA risk signature in TCGA cohort. Table S22. Detailed risk results depending on lncRNA risk signature in GEO cohort. Table S23. The significantly enriched biological activities during high risk group. Table S24. The significantly enriched biological activities during low risk group. Table 25. The infiltration levels of various immune cells from http://timer.comp-genomics.org . Table S26. The detailed list of immune checkpoints-related genes. Table S27. The immunotherapy scoring information for TCGA cohort.
DOI: 10.6084/m9.figshare.6651665
title: Additional file 6: of Landscape of transcription and long non-coding RNAs reveals new insights into the inflammatory and fibrotic response following ventilator-induced lung injury

description: Table S3. The entire list of significant dysregulated GO terms of DE mRNAs in the comparisons of each pair. (XLSX 1870 kb)
DOI: 10.6084/m9.figshare.13466833
title: Additional file 2 of CircCDKN2B-AS1 interacts with IMP3 to stabilize hexokinase 2 mRNA and facilitate cervical squamous cell carcinoma aerobic glycolysis progression

description: Additional file 2: Table S2. Sequences of primers, probes, siRNAs and peptides.
DOI: 10.6084/m9.figshare.19234610
title: Additional file 1 of Transcriptome analysis revealed growth phase-associated changes of a centenarian-originated probiotic Bifidobacterium animalis subsp. lactis A6

description: Additional file 1.
DOI: 10.6084/m9.figshare.13466847
title: Additional file 9 of CircCDKN2B-AS1 interacts with IMP3 to stabilize hexokinase 2 mRNA and facilitate cervical squamous cell carcinoma aerobic glycolysis progression

description: Additional file 9: Table S5. All proteins predicted by RBPmap.
DOI: 10.6084/m9.figshare.19234610.v1
title: Additional file 1 of Transcriptome analysis revealed growth phase-associated changes of a centenarian-originated probiotic Bifidobacterium animalis subsp. lactis A6

description: Additional file 1.
DOI: 10.6084/m9.figshare.16613759
title: Identification of downstream targets and signaling pathways of long non-coding RNA NR_002794 in human trophoblast cells

description: Preeclampsia (PE) is a huge threat to pregnant women. Our previous study demonstrated that long non-coding RNA (lncRNA) NR_002794 was highly expressed in placentas of PE patients and could regulate the phenotypes of trophoblast cells. However, the downstream regulatory mechanisms of NR_002794 remain unknown. In this text, some potential downstream targets or signaling pathways of NR_002794 were identified through RNA sequencing (RNA-seq) and bioinformatics analysis in SWAN71 trophoblast cells. Western blot assay demonstrated that NR_002794 inactivated protein kinase B (AKT) and extracellular signal-regulated kinase 1/2 (ERK1/2) pathways and activated cell apoptotic signaling in SWAN71 cells. Both RNA-seq and reverse transcription-quantitative PCR (RT-qPCR) outcomes showed that NR_002794 up-regulation could notably inhibit the expression of C-C motif chemokine ligand 4 like 2 (CCL4L2), interleukin 15 receptor subunit alpha (IL15RA), interleukin 32 (IL32), and tyrosine kinase with immunoglobulin-like and EGF-like domains 1 (TIE1), while NR_002794 knockdown induced these gene expressions in SWAN71 cells. CCK-8, BrdU, Transwell, wound healing, and flow cytometry analyses showed that NR_002794 inhibited cell proliferation and migration and induced cell apoptosis through down-regulating TIE1 in SWAN71 cells. In conclusion, lncRNA NR_002794 could exert its functions by regulating AKT and ERK1/2 pathways and TIE1 expression in human trophoblast cells.
DOI: 10.6084/m9.figshare.16613759.v2
title: Identification of downstream targets and signaling pathways of long non-coding RNA NR_002794 in human trophoblast cells

description: Preeclampsia (PE) is a huge threat to pregnant women. Our previous study demonstrated that long non-coding RNA (lncRNA) NR_002794 was highly expressed in placentas of PE patients and could regulate the phenotypes of trophoblast cells. However, the downstream regulatory mechanisms of NR_002794 remain unknown. In this text, some potential downstream targets or signaling pathways of NR_002794 were identified through RNA sequencing (RNA-seq) and bioinformatics analysis in SWAN71 trophoblast cells. Western blot assay demonstrated that NR_002794 inactivated protein kinase B (AKT) and extracellular signal-regulated kinase 1/2 (ERK1/2) pathways and activated cell apoptotic signaling in SWAN71 cells. Both RNA-seq and reverse transcription-quantitative PCR (RT-qPCR) outcomes showed that NR_002794 up-regulation could notably inhibit the expression of C-C motif chemokine ligand 4 like 2 (CCL4L2), interleukin 15 receptor subunit alpha (IL15RA), interleukin 32 (IL32), and tyrosine kinase with immunoglobulin-like and EGF-like domains 1 (TIE1), while NR_002794 knockdown induced these gene expressions in SWAN71 cells. CCK-8, BrdU, Transwell, wound healing, and flow cytometry analyses showed that NR_002794 inhibited cell proliferation and migration and induced cell apoptosis through down-regulating TIE1 in SWAN71 cells. In conclusion, lncRNA NR_002794 could exert its functions by regulating AKT and ERK1/2 pathways and TIE1 expression in human trophoblast cells.
DOI: 10.6084/m9.figshare.21856131
title: Effect of preparation methods on tosufloxacin tosylate/ hydroxypropyl-β-cyclodextrin inclusion complex

description: Abstract The main purpose of this work was to compare the effects of the four preparation methods on the TFLX/HP-β-CD inclusion complex. The effects of different preparation methods on the inclusion complex were investigated by SEM, DSC, PXRD, FT-IR and 1H NMR. All the characterization information indicated that the four preparation methods could cause interaction between TFLX and HP-β-CD, but the inclusion complex prepared by solvent evaporation has more reaction sites. Phase solubility experiments demonstrated that the inclusion reaction was spontaneous. In vitro dissolution experiments showed that the dissolution of the inclusion complex in water was: solvent evaporation method (64.39%) &gt; grinding method (42.37%) &gt; ultrasonic method (40.00%) &gt; freezing method (36.08%), and all higher than pure TFLX and physical mixture. These results suggest that the solvent evaporation is the most suitable method for preparing TFLX/HP-β-CD inclusion complexes.