cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.23273358.v1
title: Additional file 1 of Causality of genetically determined metabolites and metabolic pathways on osteoarthritis: a two-sample mendelian randomization study

description: Additional file 1 Table S1: Information of the instrumental variables an SNPs identified by Mendelian randomization estimates. Table S2: Raw data of the results from IVW analysis between metabolites and 8 osteoarthritis phenotypes. Table S3: The results of MR analysis for 10 causal associations with multiple test correction significance. Table S4: Raw data of the results of sensitivity analysis between all metabolites and osteoarthritis phenotypes. Table S5: Raw data of the results for the metabolic pathway analysis.
DOI: 10.6084/m9.figshare.7546286
title: Additional file 9: of Transcriptomic profiling reveals molecular regulation of seasonal reproduction in Tibetan highland fish, Gymnocypris przewalskii

description: Table S8. Gene interactions in the darkgreen module. (XLSX 279 kb)
DOI: 10.6084/m9.figshare.7546283
title: Additional file 8: of Transcriptomic profiling reveals molecular regulation of seasonal reproduction in Tibetan highland fish, Gymnocypris przewalskii

description: Table S9. Correlation coefficients between modules and sample groups with corresponding p-values. (XLSX 51 kb)
DOI: 10.6084/m9.figshare.7546118.v1
title: Additional file 3: of Dual RNA-seq analysis provides new insights into interactions between Norway spruce and necrotrophic pathogen Heterobasidion annosum s.l.

description: Table S3. List of Norway spruce genes showing higher transcript abundance in asymptomatic trees. (XLSX 25 kb)
DOI: 10.6084/m9.figshare.23273316
title: Additional file 1 of Constructing ferroptosis-related competing endogenous RNA networks and exploring potential biomarkers correlated with immune infiltration cells in asthma using combinative bioinformatics strategy

description: Additional file 1: Table S1. List of ferroptosis-related genes.
DOI: 10.6084/m9.figshare.14361510
title: Additional file 2 of Integrated analysis of lncRNA, miRNA and mRNA profiles reveals potential lncRNA functions during early HIV infection

description: Additional file 2: Table S2. LncRNA expression profiling.
DOI: 10.6084/m9.figshare.9119237
title: Additional file 1: of Meta-analysis of the effects of overexpression of WRKY transcription factors on plant responses to drought stress

description: The data of original studies on WRKY-overexpression. Details on the WRKY-overexpression studies used in the meta-analyses, including each of the moderators used for categorical analyses, the transgenic and WT means (X), sample sizes (N) and standard deviation (SD). (XLSX 106 kb)
DOI: 10.6084/m9.figshare.12788683
title: Additional file 11 of Genome-wide pQTL analysis of protein expression regulatory networks in the human liver

description: Additional file 11: Data file S5. Interactions among pQTL variants, proteins, and traits. The pQTL variant-protein interactions were discovered by pQTL analysis. The variant-trait interactions were obtained from the GWAS Catalog, ClinVar and PharmGKB databases. The protein-trait interactions were discovered by the integrated pQTL and trait-variants analysis.
DOI: 10.6084/m9.figshare.7550192
title: A novel location-routing problem in electric vehicle transportation with stochastic demands

description: This is the experimental data of the manuscript entitled "A novel location-routing problem in electric vehicle transportation with stochastic demands". All data are saved in the file with txt format. <br>
DOI: 10.6084/m9.figshare.9119237.v1
title: Additional file 1: of Meta-analysis of the effects of overexpression of WRKY transcription factors on plant responses to drought stress

description: The data of original studies on WRKY-overexpression. Details on the WRKY-overexpression studies used in the meta-analyses, including each of the moderators used for categorical analyses, the transgenic and WT means (X), sample sizes (N) and standard deviation (SD). (XLSX 106 kb)
DOI: 10.6084/m9.figshare.12788692
title: Additional file 2 of Genome-wide pQTL analysis of protein expression regulatory networks in the human liver

description: Additional file 2: Data file S1. Protein concentrations in the 287 human liver samples.
DOI: 10.6084/m9.figshare.12788683.v1
title: Additional file 11 of Genome-wide pQTL analysis of protein expression regulatory networks in the human liver

description: Additional file 11: Data file S5. Interactions among pQTL variants, proteins, and traits. The pQTL variant-protein interactions were discovered by pQTL analysis. The variant-trait interactions were obtained from the GWAS Catalog, ClinVar and PharmGKB databases. The protein-trait interactions were discovered by the integrated pQTL and trait-variants analysis.
DOI: 10.6084/m9.figshare.7546118
title: Additional file 3: of Dual RNA-seq analysis provides new insights into interactions between Norway spruce and necrotrophic pathogen Heterobasidion annosum s.l.

description: Table S3. List of Norway spruce genes showing higher transcript abundance in asymptomatic trees. (XLSX 25 kb)
DOI: 10.6084/m9.figshare.14361525
title: Additional file 7 of Integrated analysis of lncRNA, miRNA and mRNA profiles reveals potential lncRNA functions during early HIV infection

description: Additional file 7: Table S7. Enrichment analyses of target mRNAs in ceRNA neworks.
DOI: 10.6084/m9.figshare.12788692.v1
title: Additional file 2 of Genome-wide pQTL analysis of protein expression regulatory networks in the human liver

description: Additional file 2: Data file S1. Protein concentrations in the 287 human liver samples.
DOI: 10.6084/m9.figshare.14361513
title: Additional file 3 of Integrated analysis of lncRNA, miRNA and mRNA profiles reveals potential lncRNA functions during early HIV infection

description: Additional file 3: Table S3. mRNA expression profiling.
DOI: 10.6084/m9.figshare.7546685.v1
title: Dominant inflammatory profile of the placenta in a preterm labor mouse model

description: <b>Objective:</b> Despite a growing association between inflammation and preterm labor, the underlying mechanisms explaining the development of preterm labor after infection are still poorly understood. Here, we use RNA-sequencing to characterize the transcriptome changes of placenta tissue in a preterm labor mouse model. <b>Materials and methods:</b> On day 15.5 of gestation, BALB/c mice received intrauterine injection of LPS to mimic preterm labor. A comprehensive catalog of genes was obtained using RNA-sequences and followed by bioinformatics analysis. The NOD-like receptor signaling pathway (Nod2, Cxcl1, Cxcl2, and IL-1β) and two downregulated genes (Ctsg and Snca) were selected for validating the results using qPCR analysis. <b>Results:</b> We identified 155 differentially expressed genes (DEGs), 84 biological processes and 45 pathways in the placenta using RNA-seq. Fifty-four biological processes could be categorized as immune-related processes and 33 pathways were mainly related to immune disease and infections. All genes were consistent between the RNA-seq and qPCR analyses. <b>Conclusions:</b> The dominant role for inflammatory biological processes and pathways in placenta can lead to preterm labor.
DOI: 10.6084/m9.figshare.14361513.v1
title: Additional file 3 of Integrated analysis of lncRNA, miRNA and mRNA profiles reveals potential lncRNA functions during early HIV infection

description: Additional file 3: Table S3. mRNA expression profiling.
DOI: 10.6084/m9.figshare.12788710.v1
title: Additional file 8 of Genome-wide pQTL analysis of protein expression regulatory networks in the human liver

description: Additional file 8: Data file S3. Genome hotspots for p/eQTL identified in the human livers.
DOI: 10.6084/m9.figshare.14361881.v1
title: Additional file 1 of IPCARF: improving lncRNA-disease association prediction using incremental principal component analysis feature selection and a random forest classifier

description: Additional file 1. LncRNA name, Disease name, Dysfunction type.
DOI: 10.6084/m9.figshare.7546244
title: Additional file 2: of Transcriptomic profiling reveals molecular regulation of seasonal reproduction in Tibetan highland fish, Gymnocypris przewalskii

description: Table S3. KEGG annotation of the G. przewalskii reference transcriptome. (XLSX 180 kb)
DOI: 10.6084/m9.figshare.7546106
title: Additional file 1: of Dual RNA-seq analysis provides new insights into interactions between Norway spruce and necrotrophic pathogen Heterobasidion annosum s.l.

description: Table S1. List of Heterobasidion genes expressed during colonization of Norway spruce trees. (XLSX 74 kb)
DOI: 10.6084/m9.figshare.7546253
title: Additional file 3: of Transcriptomic profiling reveals molecular regulation of seasonal reproduction in Tibetan highland fish, Gymnocypris przewalskii

description: Table S4. DEGs in female brain. (XLSX 384 kb)
DOI: 10.6084/m9.figshare.23273455
title: Additional file 2 of Risk prediction for dermatomyositis-associated hepatocellular carcinoma

description: Additional file 2. Original data of HCC.xlsx.
DOI: 10.6084/m9.figshare.7546106.v1
title: Additional file 1: of Dual RNA-seq analysis provides new insights into interactions between Norway spruce and necrotrophic pathogen Heterobasidion annosum s.l.

description: Table S1. List of Heterobasidion genes expressed during colonization of Norway spruce trees. (XLSX 74 kb)
DOI: 10.6084/m9.figshare.7546253.v1
title: Additional file 3: of Transcriptomic profiling reveals molecular regulation of seasonal reproduction in Tibetan highland fish, Gymnocypris przewalskii

description: Table S4. DEGs in female brain. (XLSX 384 kb)
DOI: 10.6084/m9.figshare.7546274.v1
title: Additional file 6: of Transcriptomic profiling reveals molecular regulation of seasonal reproduction in Tibetan highland fish, Gymnocypris przewalskii

description: Table S7. DEGs in male gonad. (XLSX 2574 kb)
DOI: 10.6084/m9.figshare.7546286.v1
title: Additional file 9: of Transcriptomic profiling reveals molecular regulation of seasonal reproduction in Tibetan highland fish, Gymnocypris przewalskii

description: Table S8. Gene interactions in the darkgreen module. (XLSX 279 kb)
DOI: 10.6084/m9.figshare.16460317
title: An investigation of pharmacovigilance and reporting of adverse drug reactions in hospitals: a cross-sectional study in China

description: Pharmacovigilance is a science that plays a significant role in reducing ADRs and helps predict adverse reactions to drugs in community. To safely use drugs in treatment and prevention of disease, adverse drug reaction has been paid more attention. To evaluate the future needs of existing systems, the paper investigated the current state of pharmacovigilance and the reporting of ADR in Chinese hospitals. This cross-sectional, questionnaire-based study involved 10,063 pharmacists, doctors, and nurses from primary, secondary, and tertiary hospitals in all 31 provinces of China. It was commissioned by the National Centre for ADR Monitoring of China and conducted in March 2020. Three areas were assessed: sociodemographic characteristics of participants, awareness of the pharmacovigilance system, and the current state of hospitals’ reporting of ADRs. Chi-square tests were used to calculate P values. Health care professionals had heard the term “pharmacovigilance” previously (89.40%) and knew the reporting object (68.47%), content (65.94%), and range (64.83%) of pharmacovigilance. Most hospitals dispatched responsible professionals (87.64%) and departments (86.25%) to monitor ADR reporting. A total of 58.66% of tertiary medical, 45.25% of secondary, and 38.90% of primary hospitals extracted ADRs from a hospital information system. Moreover, 53.09% of tertiary medical, 38.93% of secondary, and 23.89% of primary hospitals had established a prescription automatic screening system to warn about risks for ADRs. Health care professionals’ reports (99.92%) and patient feedback (77.99%) were included in most hospitals’ ADR reporting. Chinese health care professionals generally have good awareness of pharmacovigilance, and pharmacovigilance is relatively more advanced in China compared to other developing countries.
DOI: 10.6084/m9.figshare.21701698.v1
title: Depletion of circPDSS1 inhibits ITGA11 production to confer cisplatin sensitivity through miR-515-5p in gastric cancer

description: Chemoresistance limits cisplatin (DDP)-mediated treatment for gastric cancer (GC). Circular RNA (circRNA) acts an important role in chemoresistance. However, the underlying mechanism of circPDSS1 regulating DDP sensitivity in GC remains unclear. The expression patterns of circPDSS1, miR-515-5p and integrin subunit alpha 11 (ITGA11) were analyzed by qRT-PCR. Protein expression was checked by Western blotting analysis. Cell viability was investigated by 3-(4,5-dimethylthazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Cell proliferation was evaluated by colony formation assay and 5-ethynyl-2′-deoxyuridine (EdU) assay. The analysis of cell apoptosis, migration and invasion was performed by flow cytometry analysis and transwell assays. Dual-luciferase reporter assay and RNA immunoprecipitation assay were conducted to identify the associations among circPDSS1, miR-515-5p and ITGA11. <i>In vivo</i> assay was implemented using a xenograft mouse model assay. CircPDSS1 and ITGA11 expression were significantly upregulated, whereas miR-515-5p was downregulated in DDP-resistant GC tissues and cells in comparison with controls. CircPDSS1 depletion reduced DDP resistance, cell proliferation, migration and invasion but induced cell apoptosis in DDP-resistant GC cells. CircPDSS1 directly bound to miR-515-5p. CircPDSS1-mediated actions were dependent on the regulation of miR-515-5p. Besides, miR-515-5p was associated with ITGA11, and circPDSS1 regulated ITGA11 expression by binding to miR-515-5p. Overexpression of miR-515-5p improved DDP sensitivity owing to the downregulation of ITGA11. Further, circPDSS1 mediated DDP sensitivity by regulating miR-515-5p and ITGA11 <i>in vivo</i>. CircPDSS1 conferred DDP resistance through the miR-515-5p/ITGA11 axis in GC cells.
DOI: 10.6084/m9.figshare.12264524.v2
title: Spectral Inference under Complex Temporal Dynamics

description: We develop a unified theory and methodology for the inference of evolutionary Fourier power spectra for a general class of locally stationary and possibly nonlinear processes. In particular, simultaneous confidence regions (SCR) with asymptotically correct coverage rates are constructed for the evolutionary spectral densities on a nearly optimally dense grid of the joint time-frequency domain. A simulation based bootstrap method is proposed to implement the SCR. The SCR enables researchers and practitioners to visually evaluate the magnitude and pattern of the evolutionary power spectra with asymptotically accurate statistical guarantee. The SCR also serves as a unified tool for a wide range of statistical inference problems in time-frequency analysis ranging from tests for white noise, stationarity and time-frequency separability to the validation for non-stationary linear models.
DOI: 10.6084/m9.figshare.14361638
title: Additional file 3 of Feedback activation of NF-KB signaling leads to adaptive resistance to EZH2 inhibitors in prostate cancer cells

description: Additional file 3. List of 709 down-regulated genes in SOX9 silenced prostate cancer cells.
DOI: 10.6084/m9.figshare.21176068
title: Additional file 1 of Population transcriptomic analysis identifies the comprehensive lncRNAs landscape of spike in wheat (Triticum aestivum L.)

description: Additional file 1: Table S1. Summary of all lncRNAs. Table S2. Summary of all lncRNA-mRNA pairs. Table S3. GO and KEGG enrichment of all target mRNAs. Table S4. Homologous lncRNAs between wheat and other species. Table S5. Sequence conservation of wheat lncRNAs based on results of whole-genome alignment. Table S6. Message of samples in population analysis. Table S7. Nucleotide diversity in each group. Table S8. Detail information of haplotype in lncRNA or target mRNA. (Yellow annotation indicates that gene has different haplotypes in different populations). Table S9. Interrelationship of ceRNA network between lncRNA, miRNA and mRNA. Table S10. Overlap between lncRNA or target mRNA and GWAS signals. Table S11. Overlap between lncRNA or target mRNA and known QTLs. Table S12. Overlap between lncRNA or target mRNA and introgression regions. Table S13. Information of 93 wheat lines. Table S14. Primers used for qRT-PCR analysis.
DOI: 10.5281/zenodo.10036211
title: Zonal Statistics of Climate Indicators from ERA5-Land for Brazilian Municipalities, 1950-2022

description: Climate indicators are used in several statistical models for many research areas and are specially important for modelling Climate Sensitive Diseases (CSD) incidence. Those models usually adopts a lattice structure, where its data is aggregated at administrative boundaries (e.g. disease incidence), but climate indicators are usually presented in a continuous regular grid format.
To make climate indicators compatible with lattice structures, zonal statistics may be adopted. Zonal statistics are descriptive statistics calculated using a set of cells that spatially intersects a given spatial boundary. For each boundary in a map, statistics like average, maximum value, minimum value, standard deviation, and sum are obtained to represent the cell's values that intersect the boundary.
This dataset present zonal statistic of climate indicators computed from Copernicus ERA5-Land daily aggregates for the Brazilian municipalities, from 1950 to 2022.
DOI: 10.5281/zenodo.10036212
title: Zonal Statistics of Climate Indicators from ERA5-Land for Brazilian Municipalities, 1950-2022

description: Climate indicators are used in several statistical models for many research areas and are specially important for modelling Climate Sensitive Diseases (CSD) incidence. Those models usually adopts a lattice structure, where its data is aggregated at administrative boundaries (e.g. disease incidence), but climate indicators are usually presented in a continuous regular grid format.
To make climate indicators compatible with lattice structures, zonal statistics may be adopted. Zonal statistics are descriptive statistics calculated using a set of cells that spatially intersects a given spatial boundary. For each boundary in a map, statistics like average, maximum value, minimum value, standard deviation, and sum are obtained to represent the cell's values that intersect the boundary.
This dataset present zonal statistic of climate indicators computed from Copernicus ERA5-Land daily aggregates for the Brazilian municipalities, from 1950 to 2022.
DOI: 10.6084/m9.figshare.14361638.v1
title: Additional file 3 of Feedback activation of NF-KB signaling leads to adaptive resistance to EZH2 inhibitors in prostate cancer cells

description: Additional file 3. List of 709 down-regulated genes in SOX9 silenced prostate cancer cells.
DOI: 10.6084/m9.figshare.7545947
title: Additional file 1: of Global status of 47 major wheat loci controlling yield, quality, adaptation and stress resistance selected over the last century

description: Table S1. Detailed information on materials and their allelic variations of 47 genes used in this study. Table S2. Basic information including allelic variations and primer sequences for the 52 KASP assays. Table S3. Basic descriptive statistics in Chinese landraces (CL) and modern Chinese cultivars (MCC) for eleven traits using BLUP values. Table S4. Putative selective genes during wheat improvement based on the BLUP values of phenotypic traits. Table S5. Genome-wide association signals of 47 genes controlling adaptation and yield-related traits. (XLS 1118 kb)
DOI: 10.6084/m9.figshare.8074505
title: Exploration of prognosis-related microRNA and transcription factor co-regulatory networks across cancer types

description: The study of cancer prognosis serves as an important part of cancer research. Large-scale cancer studies have identified numerous genes and microRNAs (miRNAs) associated with prognosis. These informative genes and miRNAs represent potential biomarkers to predict survival and to elucidate the molecular mechanism of tumour progression. MiRNAs and transcription factors (TFs) can work cooperatively as essential mediators of gene expression, and their dysregulation affects cancer prognosis. A panoramic view of cancer prognosis at the system level, considering the co-regulation roles of miRNA and TF, remains elusive. Here, we establish 12 prognosis-related miRNA-TF co-regulatory networks. The characteristics of prognostic target genes and their regulators in the network are depicted. Although the target genes and co-regulatory patterns exhibit cancer-specific properties, some miRNAs and TFs are highly conserved across cancers. We illustrate and interpret the roles of these conserved regulators by building a model associated with cancer hallmarks, functional enrichment analysis, network community detection, and exhaustive literature research. The elaborated system-level prognostic miRNA-TF co-regulation landscape, including the highlighted roles of conserved regulators, provides a novel and powerful insights into further biological and medical discoveries.
DOI: 10.6084/m9.figshare.8074505.v1
title: Exploration of prognosis-related microRNA and transcription factor co-regulatory networks across cancer types

description: The study of cancer prognosis serves as an important part of cancer research. Large-scale cancer studies have identified numerous genes and microRNAs (miRNAs) associated with prognosis. These informative genes and miRNAs represent potential biomarkers to predict survival and to elucidate the molecular mechanism of tumour progression. MiRNAs and transcription factors (TFs) can work cooperatively as essential mediators of gene expression, and their dysregulation affects cancer prognosis. A panoramic view of cancer prognosis at the system level, considering the co-regulation roles of miRNA and TF, remains elusive. Here, we establish 12 prognosis-related miRNA-TF co-regulatory networks. The characteristics of prognostic target genes and their regulators in the network are depicted. Although the target genes and co-regulatory patterns exhibit cancer-specific properties, some miRNAs and TFs are highly conserved across cancers. We illustrate and interpret the roles of these conserved regulators by building a model associated with cancer hallmarks, functional enrichment analysis, network community detection, and exhaustive literature research. The elaborated system-level prognostic miRNA-TF co-regulation landscape, including the highlighted roles of conserved regulators, provides a novel and powerful insights into further biological and medical discoveries.
DOI: 10.6084/m9.figshare.21176069.v1
title: Additional file 3 of DNA methylation underpins the epigenomic landscape regulating genome transcription in Arabidopsis

description: Additional file 3: Table S2. List of upregulated Tes with gain of active marks in ddcc, met1, and mddcc mutants.
DOI: 10.6084/m9.figshare.7547657.v1
title: MOESM6 of Comprehensive evaluation of fuel properties and complex regulation of intracellular transporters for high oil production in developing seeds of Prunus sibirica for woody biodiesel

description: Additional file 6: Table S6. Genes annotated for other transport proteins for FA/lipid transport in developing P. sibirica seeds. They mainly included ATP-binding cassette (ABC) proteins, acyl-CoA-binding proteins (ACBPs), lipid transfer proteins (LTPs) and trigalactosyldiacylglycerol 1 (TGD1) protein.