cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.13634475.v1
title: Additional file 5 of Molecular subtypes based on DNA methylation predict prognosis in lung squamous cell carcinoma

description: Additional file 5. Multivariate Cox regression analysis of the 965 methylation sites (965)
DOI: 10.6084/m9.figshare.13634478
title: Additional file 6 of Molecular subtypes based on DNA methylation predict prognosis in lung squamous cell carcinoma

description: Additional file 6. Functional enrichment analysis and the identified 27 enriched pathways
DOI: 10.6084/m9.figshare.13634478.v1
title: Additional file 6 of Molecular subtypes based on DNA methylation predict prognosis in lung squamous cell carcinoma

description: Additional file 6. Functional enrichment analysis and the identified 27 enriched pathways
DOI: 10.6084/m9.figshare.7867316
title: Additional file 3: of Mining, analyzing, and integrating viral signals from metagenomic data

description: Table S3. The number of putative metagenomic phage contigs and non-phage contigs in metagenomic assembled contigs. (XLSX 41â KB) (XLSX 39 kb)
DOI: 10.6084/m9.figshare.13634457
title: Additional file 10 of Molecular subtypes based on DNA methylation predict prognosis in lung squamous cell carcinoma

description: Additional file 10. Genome annotations of the 41 cluster-specific methylation sites
DOI: 10.6084/m9.figshare.7867316.v1
title: Additional file 3: of Mining, analyzing, and integrating viral signals from metagenomic data

description: Table S3. The number of putative metagenomic phage contigs and non-phage contigs in metagenomic assembled contigs. (XLSX 41â KB) (XLSX 39 kb)
DOI: 10.6084/m9.figshare.13634481
title: Additional file 7 of Molecular subtypes based on DNA methylation predict prognosis in lung squamous cell carcinoma

description: Additional file 7. The available expression profile of 965 sites in 266 training set samples
DOI: 10.6084/m9.figshare.13634481.v1
title: Additional file 7 of Molecular subtypes based on DNA methylation predict prognosis in lung squamous cell carcinoma

description: Additional file 7. The available expression profile of 965 sites in 266 training set samples
DOI: 10.6084/m9.figshare.13634464.v1
title: Additional file 1 of The negative charge of the 343 site is essential for maintaining physiological functions of CXCR4

description: Additional file 1: Fig. S1 Ligand-induced internalization of wild type and mutant CXCR4. The mean levels of cell surface CXCR4 at the 40 min post-stimulation with SDF-1was examined by flow cytometry from 3 independent experiments. *p &lt; 0 .05, **p &lt;0 .01, ***p &lt;0 .001 compared to the WT group.
DOI: 10.6084/m9.figshare.7867322
title: Additional file 4: of Mining, analyzing, and integrating viral signals from metagenomic data

description: Table S4. Predictive performance of VirMiner for contigs &gt;â 5â kb based on reads ratio of correctly predicted contigs and the number of correctly predicted contigs. (XLSX 51â KB) (XLSX 50 kb)
DOI: 10.6084/m9.figshare.13634484
title: Additional file 8 of Molecular subtypes based on DNA methylation predict prognosis in lung squamous cell carcinoma

description: Additional file 8. Calculating differences of each methylation sites among 7 clusters
DOI: 10.6084/m9.figshare.13634484.v1
title: Additional file 8 of Molecular subtypes based on DNA methylation predict prognosis in lung squamous cell carcinoma

description: Additional file 8. Calculating differences of each methylation sites among 7 clusters
DOI: 10.6084/m9.figshare.7867322.v1
title: Additional file 4: of Mining, analyzing, and integrating viral signals from metagenomic data

description: Table S4. Predictive performance of VirMiner for contigs &gt;â 5â kb based on reads ratio of correctly predicted contigs and the number of correctly predicted contigs. (XLSX 51â KB) (XLSX 50 kb)
DOI: 10.6084/m9.figshare.12585916
title: Additional file 1 of miR-1323 suppresses bone mesenchymal stromal cell osteogenesis and fracture healing via inhibiting BMP4/SMAD4 signaling

description: Additional file 1: Table S1. Sequences of oligonucleotides used in this study.
DOI: 10.6084/m9.figshare.13634464
title: Additional file 1 of The negative charge of the 343 site is essential for maintaining physiological functions of CXCR4

description: Additional file 1: Fig. S1 Ligand-induced internalization of wild type and mutant CXCR4. The mean levels of cell surface CXCR4 at the 40 min post-stimulation with SDF-1was examined by flow cytometry from 3 independent experiments. *p &lt; 0 .05, **p &lt;0 .01, ***p &lt;0 .001 compared to the WT group.
DOI: 10.6084/m9.figshare.12585916.v1
title: Additional file 1 of miR-1323 suppresses bone mesenchymal stromal cell osteogenesis and fracture healing via inhibiting BMP4/SMAD4 signaling

description: Additional file 1: Table S1. Sequences of oligonucleotides used in this study.
DOI: 10.6084/m9.figshare.7867325
title: Additional file 5: of Mining, analyzing, and integrating viral signals from metagenomic data

description: Table S5. Predictive performance of VirMiner for contigs &gt;â 3â kb based on reads ratio of correctly predicted contigs and the number of correctly predicted contigs. (XLSX 50â KB) (XLSX 48 kb)
DOI: 10.6084/m9.figshare.7867325.v1
title: Additional file 5: of Mining, analyzing, and integrating viral signals from metagenomic data

description: Table S5. Predictive performance of VirMiner for contigs &gt;â 3â kb based on reads ratio of correctly predicted contigs and the number of correctly predicted contigs. (XLSX 50â KB) (XLSX 48 kb)
DOI: 10.6084/m9.figshare.12585919
title: Additional file 2 of miR-1323 suppresses bone mesenchymal stromal cell osteogenesis and fracture healing via inhibiting BMP4/SMAD4 signaling

description: Additional file 2: Table S2. Primers used in qRT-PCR experiments.
DOI: 10.6084/m9.figshare.12585919.v1
title: Additional file 2 of miR-1323 suppresses bone mesenchymal stromal cell osteogenesis and fracture healing via inhibiting BMP4/SMAD4 signaling

description: Additional file 2: Table S2. Primers used in qRT-PCR experiments.
DOI: 10.6084/m9.figshare.12585922
title: Additional file 3 of miR-1323 suppresses bone mesenchymal stromal cell osteogenesis and fracture healing via inhibiting BMP4/SMAD4 signaling

description: Additional file 3: Table S3. Clinicodemographic characteristics of tibial fracture enrollees (n = 10).
DOI: 10.6084/m9.figshare.12585922.v1
title: Additional file 3 of miR-1323 suppresses bone mesenchymal stromal cell osteogenesis and fracture healing via inhibiting BMP4/SMAD4 signaling

description: Additional file 3: Table S3. Clinicodemographic characteristics of tibial fracture enrollees (n = 10).
DOI: 10.6084/m9.figshare.7867334
title: Additional file 6: of Mining, analyzing, and integrating viral signals from metagenomic data

description: Table S6. Predictive performance of VirMiner for contigs &gt;â 1â kb based on reads ratio of correctly predicted contigs and the number of correctly predicted contigs. (XLSX 50â KB) (XLSX 48 kb)
DOI: 10.6084/m9.figshare.7867334.v1
title: Additional file 6: of Mining, analyzing, and integrating viral signals from metagenomic data

description: Table S6. Predictive performance of VirMiner for contigs &gt;â 1â kb based on reads ratio of correctly predicted contigs and the number of correctly predicted contigs. (XLSX 50â KB) (XLSX 48 kb)
DOI: 10.6084/m9.figshare.7867343
title: Additional file 7: of Mining, analyzing, and integrating viral signals from metagenomic data

description: Table S7. Comparison with VirMiner, VirSorter, and VirFinder for contigs &gt;â 5â kb based on reads ratio of correctly predicted contigs and the number of correctly predicted contigs. (XLSX 47â KB) (XLSX 48 kb)
DOI: 10.6084/m9.figshare.7867346
title: Additional file 8: of Mining, analyzing, and integrating viral signals from metagenomic data

description: Table S8. Comparison with VirMiner, VirSorter, and VirFinder for contigs &gt;â 3â kb based on reads ratio of correctly predicted contigs and the number of correctly predicted contigs. (XLSX 53â KB) (XLSX 49 kb)
DOI: 10.6084/m9.figshare.7867346.v1
title: Additional file 8: of Mining, analyzing, and integrating viral signals from metagenomic data

description: Table S8. Comparison with VirMiner, VirSorter, and VirFinder for contigs &gt;â 3â kb based on reads ratio of correctly predicted contigs and the number of correctly predicted contigs. (XLSX 53â KB) (XLSX 49 kb)
DOI: 10.6084/m9.figshare.7867352
title: Additional file 9: of Mining, analyzing, and integrating viral signals from metagenomic data

description: Table S9. Comparison with VirMiner, VirSorter, and VirFinder for contigs &gt;â 1â kb based on reads ratio of correctly predicted contigs and the number of correctly predicted contigs. (XLSX 55â KB) (XLSX 50 kb)
DOI: 10.6084/m9.figshare.7867352.v1
title: Additional file 9: of Mining, analyzing, and integrating viral signals from metagenomic data

description: Table S9. Comparison with VirMiner, VirSorter, and VirFinder for contigs &gt;â 1â kb based on reads ratio of correctly predicted contigs and the number of correctly predicted contigs. (XLSX 55â KB) (XLSX 50 kb)
DOI: 10.6084/m9.figshare.19401714
title: Additional file 1 of Metabolome and transcriptome analyses identify the plant immunity systems that facilitate sesquiterpene and lignan biosynthesis in Syringa pinnatifolia Hemsl.

description: Additional file 1.
DOI: 10.6084/m9.figshare.19401714.v1
title: Additional file 1 of Metabolome and transcriptome analyses identify the plant immunity systems that facilitate sesquiterpene and lignan biosynthesis in Syringa pinnatifolia Hemsl.

description: Additional file 1.
DOI: 10.6084/m9.figshare.13634499
title: Additional file 2 of Time-course single-cell RNA sequencing reveals transcriptional dynamics and heterogeneity of limbal stem cells derived from human pluripotent stem cells

description: Additional file 2: Table S1. List of DEGs between cluster 8 and cluster 0. Table S2. List of DEGs between cluster 7 and cluster 0. Table S3. List of DEGs between cluster 6 and cluster 0. Table S4. List of DEGs between cluster 5 and cluster 0. Table S5. List of DEGs between cluster 7 and cluster 6. Table S6. List of DEGs between cluster 6 and cluster 8. Table S7. List of DEGs between cluster 5 and cluster 8. Table S8. List of DEGs between cluster 6 and cluster 7. Table S9. List of DEGs between cluster 5 and cluster 7. Table S10. List of DEGs between cluster 6 and cluster 5.
DOI: 10.6084/m9.figshare.13634499.v1
title: Additional file 2 of Time-course single-cell RNA sequencing reveals transcriptional dynamics and heterogeneity of limbal stem cells derived from human pluripotent stem cells

description: Additional file 2: Table S1. List of DEGs between cluster 8 and cluster 0. Table S2. List of DEGs between cluster 7 and cluster 0. Table S3. List of DEGs between cluster 6 and cluster 0. Table S4. List of DEGs between cluster 5 and cluster 0. Table S5. List of DEGs between cluster 7 and cluster 6. Table S6. List of DEGs between cluster 6 and cluster 8. Table S7. List of DEGs between cluster 5 and cluster 8. Table S8. List of DEGs between cluster 6 and cluster 7. Table S9. List of DEGs between cluster 5 and cluster 7. Table S10. List of DEGs between cluster 6 and cluster 5.
DOI: 10.6084/m9.figshare.13110290
title: Nonparametric Copula Estimation for Mixed Insurance Claim Data

description: Multivariate claim data are common in insurance applications, for example, claims of each policyholder from different types of insurance coverages. Understanding the dependencies among such multivariate risks is critical to the solvency and profitability of insurers. Effectively modeling insurance claim data is challenging due to their special complexities. At the policyholder level, claim outcomes usually follow a two-part mixed distribution: a probability mass at zero corresponding to no claim and an otherwise positive claim from a skewed and long-tailed distribution. To simultaneously accommodate the complex features of the marginal distributions while flexibly quantifying the dependencies among multivariate claims, copula models are commonly used. Although a substantial body of literature focusing on copulas with continuous outcomes has emerged, some key steps do not carry over to mixed data. In particular, existing nonparametric copula estimators are not consistent for mixed data, and thus copula specification and diagnostics for mixed outcomes have been a problem. However, insurance is a closely regulated industry in which model validation is particularly important, and it is essential to develop a baseline nonparametric copula estimator to identify the underlying dependence structure. In this article, we fill in this gap by developing a nonparametric copula estimator for mixed data. We show the uniform convergence of the proposed nonparametric copula estimator. Through simulation studies, we demonstrate that the proportion of zeros plays a key role in the finite sample performance of the proposed estimator. Using the claim data from the Wisconsin Local Government Property Insurance Fund, we illustrate that our nonparametric copula estimator can assist analysts in identifying important features of the underlying dependence structure, revealing how different claims or risks are related to one another.
DOI: 10.6084/m9.figshare.13110290.v2
title: Nonparametric Copula Estimation for Mixed Insurance Claim Data

description: Multivariate claim data are common in insurance applications, for example, claims of each policyholder from different types of insurance coverages. Understanding the dependencies among such multivariate risks is critical to the solvency and profitability of insurers. Effectively modeling insurance claim data is challenging due to their special complexities. At the policyholder level, claim outcomes usually follow a two-part mixed distribution: a probability mass at zero corresponding to no claim and an otherwise positive claim from a skewed and long-tailed distribution. To simultaneously accommodate the complex features of the marginal distributions while flexibly quantifying the dependencies among multivariate claims, copula models are commonly used. Although a substantial body of literature focusing on copulas with continuous outcomes has emerged, some key steps do not carry over to mixed data. In particular, existing nonparametric copula estimators are not consistent for mixed data, and thus copula specification and diagnostics for mixed outcomes have been a problem. However, insurance is a closely regulated industry in which model validation is particularly important, and it is essential to develop a baseline nonparametric copula estimator to identify the underlying dependence structure. In this article, we fill in this gap by developing a nonparametric copula estimator for mixed data. We show the uniform convergence of the proposed nonparametric copula estimator. Through simulation studies, we demonstrate that the proportion of zeros plays a key role in the finite sample performance of the proposed estimator. Using the claim data from the Wisconsin Local Government Property Insurance Fund, we illustrate that our nonparametric copula estimator can assist analysts in identifying important features of the underlying dependence structure, revealing how different claims or risks are related to one another.
DOI: 10.6084/m9.figshare.7867433
title: Additional file 6: of Exogenous 2-(3,4-Dichlorophenoxy) triethylamine ameliorates the soil drought effect on nitrogen metabolism in maize during the pre-female inflorescence emergence stage

description: Research data. (XLSX 99 kb)
DOI: 10.6084/m9.figshare.7867433.v1
title: Additional file 6: of Exogenous 2-(3,4-Dichlorophenoxy) triethylamine ameliorates the soil drought effect on nitrogen metabolism in maize during the pre-female inflorescence emergence stage

description: Research data. (XLSX 99 kb)
DOI: 10.6084/m9.figshare.13634523
title: Additional file 1 of Quality of online self-management resources for adults living with primary brain cancer, and their carers: a systematic environmental scan

description: Additional file 1. Quality and readability analysis of online resources for people living with brain cancer and their carers. A list of all resources captured, including country of origin; type and name of developing organisation; and quality and readability scores.
DOI: 10.6084/m9.figshare.13634523.v1
title: Additional file 1 of Quality of online self-management resources for adults living with primary brain cancer, and their carers: a systematic environmental scan

description: Additional file 1. Quality and readability analysis of online resources for people living with brain cancer and their carers. A list of all resources captured, including country of origin; type and name of developing organisation; and quality and readability scores.
DOI: 10.6084/m9.figshare.13110331
title: Network during light-induced cotyledons opening and greening in <i>Astragalus membranaceus</i>

description: Opening and greening are main characteristics of morphogenesis of cotyledons. For revealing interrelationship between metabolism and morphogenesis, metabolic shifts were analyzed in cotyledon of <i>A. membranaceus</i> seedlings with different stages in light and in darkness. Light induced 69 metabolites (MA), related to cotyledon greening; additional 89 metabolites (MB), related to cotyledon opening, were identified by WGCNA. The screening of metabolites shared in both MA and MB obtained 37 specific metabolites (MC) related to both opening and greening. In this context, main changes in MC occurred during A3, the stage in which cotyledons fully opened and greened. Within MC, few sugars, including L-(-)-sorbose, mannose, glucose and its derivatives, markedly decreased, while other sugars, amino acids, and unsaturated fatty acids increased. Most isoflavones and flavonols including ononin, caycosin-7-glucosides, quercetin, genistein, and catechin increased 5.3, 5.5, 13.4, 6.4 and 1.8 times, respectively. Thus, accumulated flavonoids play an important role during this developmental stage.
DOI: 10.6084/m9.figshare.13110331.v1
title: Network during light-induced cotyledons opening and greening in <i>Astragalus membranaceus</i>

description: Opening and greening are main characteristics of morphogenesis of cotyledons. For revealing interrelationship between metabolism and morphogenesis, metabolic shifts were analyzed in cotyledon of <i>A. membranaceus</i> seedlings with different stages in light and in darkness. Light induced 69 metabolites (MA), related to cotyledon greening; additional 89 metabolites (MB), related to cotyledon opening, were identified by WGCNA. The screening of metabolites shared in both MA and MB obtained 37 specific metabolites (MC) related to both opening and greening. In this context, main changes in MC occurred during A3, the stage in which cotyledons fully opened and greened. Within MC, few sugars, including L-(-)-sorbose, mannose, glucose and its derivatives, markedly decreased, while other sugars, amino acids, and unsaturated fatty acids increased. Most isoflavones and flavonols including ononin, caycosin-7-glucosides, quercetin, genistein, and catechin increased 5.3, 5.5, 13.4, 6.4 and 1.8 times, respectively. Thus, accumulated flavonoids play an important role during this developmental stage.
DOI: 10.6084/m9.figshare.7867469
title: Additional file 3: of Identifying and exploiting gene-pathway interactions from RNA-seq data for binary phenotype

description: The enriched GO pathways from both GSEA and DAVID. (XLSX 13 kb)
DOI: 10.6084/m9.figshare.7867469.v1
title: Additional file 3: of Identifying and exploiting gene-pathway interactions from RNA-seq data for binary phenotype

description: The enriched GO pathways from both GSEA and DAVID. (XLSX 13 kb)
DOI: 10.6084/m9.figshare.12586064
title: Additional file 1 of Exosomal miR-200c-3p negatively regulates the migration and invasion of lipopolysaccharide (LPS)-stimulated colorectal cancer (CRC)

description: Additional file 1: Table S1. Full list of differentially expressed exosomal miRNAs after LPS stimulation in HCT-116 cells.
DOI: 10.6084/m9.figshare.12586064.v1
title: Additional file 1 of Exosomal miR-200c-3p negatively regulates the migration and invasion of lipopolysaccharide (LPS)-stimulated colorectal cancer (CRC)

description: Additional file 1: Table S1. Full list of differentially expressed exosomal miRNAs after LPS stimulation in HCT-116 cells.
DOI: 10.6084/m9.figshare.12586055
title: Additional file 1 of Model of genetic and environmental factors associated with type 2 diabetes mellitus in a Chinese Han population

description: Additional file 1. The following are available online at www.mdpi.com/xxx/s1 , Table S1. The information of 107 SNPs. Table S2. Elastic net regularisation feature selection for gene-score and lifestyles.
DOI: 10.6084/m9.figshare.12586055.v1
title: Additional file 1 of Model of genetic and environmental factors associated with type 2 diabetes mellitus in a Chinese Han population

description: Additional file 1. The following are available online at www.mdpi.com/xxx/s1 , Table S1. The information of 107 SNPs. Table S2. Elastic net regularisation feature selection for gene-score and lifestyles.
DOI: 10.6084/m9.figshare.16780399
title: FLT4/VEGFR3 activates AMPK to coordinate glycometabolic reprogramming with autophagy and inflammasome activation for bacterial elimination

description: Macrophages rapidly undergo glycolytic reprogramming in response to macroautophagy/autophagy, inflammasome activation and pyroptosis for the clearance of bacteria. Identification the key molecules involved in these three events will provide critical potential therapeutic applications. Upon <i>S. typhimurium</i> infection, FLT4/VEGFR3 and its ligand VEGFC were inducibly expressed in macrophages, and FLT4 signaling inhibited CASP1 (caspase 1)-dependent inflammasome activation and pyroptosis but enhanced MAP1LC3/LC3 activation for elimination of the bacteria. Consistently, FLT4 mutants lacking the extracellular ligand-binding domain increased production of the proinflammatory metabolites such as succinate and lactate, and reduced antimicrobial metabolites including citrate and NAD(P)H in macrophages and liver upon infection. Mechanistically, FLT4 recruited AMP-activated protein kinase (AMPK) and phosphorylated Y247 and Y441/442 in the PRKAA/alpha subunit for AMPK activation. The AMPK agonist AICAR could rescue glycolytic reprogramming and inflammasome activation in macrophages expressing the mutant FLT4, which has potential translational application in patients carrying <i>Flt4</i> mutations to prevent recurrent infections. Collectively, we have elucidated that the FLT4-AMPK module in macrophages coordinates glycolytic reprogramming, autophagy, inflammasome activation and pyroptosis to eliminate invading bacteria. <b>Abbreviations:</b> 3-MA: 3-methyladenine; AICAR: 5-aminoimidazole-4-carboxamide1-β-D-ribofuranoside; AMP: adenosine monophosphate; AMPK: AMP-activated protein kinase; ATP: adenosine triphosphate; BMDM: bone marrow-derived macrophage; CASP1: caspase 1; CFUs: colony-forming units; FLT4/VEGFR3: FMS-like tyrosine kinase 4; GFP: green fluorescent protein; LDH: lactate dehydrogenase; LPS: lipopolysaccharide; MAP1LC3/LC3: microtubule-associated protein 1 light chain 3; PEM: peritoneal exudate macrophage; PRKAA1/AMPKα1: protein kinase, AMP-activated, alpha 1 catalytic subunit; PYCARD/ASC: PYD and CARD domain containing; ROS: reactive oxygen species; SQSTM1/p62: sequestosome 1; TLR4: toll-like receptor 4; ULK1: unc-51 like autophagy activating kinase 1; VEGFC: vascular endothelial growth factor C; WT: wild type