cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.11875584
title: Additional file 2 of Global identification and analysis revealed differentially expressed lncRNAs associated with meiosis and low fertility in autotetraploid rice

description: Additional file 2 Table S1. Characteristics of all lncRNAs identified in this study. Table S2. Conservation of lncRNAs in other plant species. Table S3. Differentially expressed lncRNAs (DEL) in anther and ovary of Taichung 65-4x compared to Taichung 65. Table S4. The lncRNAs selected by aligment assay compared to a previous study. Table S5. Summary of known and predicted miRNAs detected in this study. Table S6. Overview of 21 nt- and 24 nt-phasiRNAs detected in this study. Table S7. LncRNAs corresponding to miRNA precursors. Table S8. LncRNAs corresponding to phasiRNA precursors. Table S9. A list of lncRNAs predicted to be the targets of miRNAs. Table S10. Transposable elements-associated with differentially expressed lncRNAs in autotetraploid rice.
DOI: 10.6084/m9.figshare.11875590
title: Additional file 3 of Global identification and analysis revealed differentially expressed lncRNAs associated with meiosis and low fertility in autotetraploid rice

description: Additional file 3 Table S11. Classification of differentially expressed lncRNAs related to transposable elements (TEs) in autotetraploid rice. Table S12. The potential target genes of differentially expressed lncRNAs detected by cis-regulation. Table S13. The potential target genes of differentially expressed lncRNAs detected by trans-regulation. Table S14. GO (Gene Ontology) analysis of predicted targets of differentially expressed lncRNAs. Table S15. Overall information about the predicted targets of differentially expressed miRNAs (DEM). Table S16. GO (Gene Ontology) analysis of predicted targets of differentially expressed lncRNAs and differentially expressed miRNAs. Table S17. The most important lncRNA-target pairs related to PMC meiosis in autotetraploid rice. Table S18. The important lncRNA-target pairs related to EMC meiosis in autotetraploid rice. Table S19. A list of primers used in the present study. Table S20. The information about ten lncRNAs detected by RACE in the present study.
DOI: 10.6084/m9.figshare.11875584.v2
title: Additional file 2 of Global identification and analysis revealed differentially expressed lncRNAs associated with meiosis and low fertility in autotetraploid rice

description: Additional file 2 Table S1. Characteristics of all lncRNAs identified in this study. Table S2. Conservation of lncRNAs in other plant species. Table S3. Differentially expressed lncRNAs (DEL) in anther and ovary of Taichung 65-4x compared to Taichung 65. Table S4. The lncRNAs selected by aligment assay compared to a previous study. Table S5. Summary of known and predicted miRNAs detected in this study. Table S6. Overview of 21 nt- and 24 nt-phasiRNAs detected in this study. Table S7. LncRNAs corresponding to miRNA precursors. Table S8. LncRNAs corresponding to phasiRNA precursors. Table S9. A list of lncRNAs predicted to be the targets of miRNAs. Table S10. Transposable elements-associated with differentially expressed lncRNAs in autotetraploid rice.
DOI: 10.6084/m9.figshare.11875590.v2
title: Additional file 3 of Global identification and analysis revealed differentially expressed lncRNAs associated with meiosis and low fertility in autotetraploid rice

description: Additional file 3 Table S11. Classification of differentially expressed lncRNAs related to transposable elements (TEs) in autotetraploid rice. Table S12. The potential target genes of differentially expressed lncRNAs detected by cis-regulation. Table S13. The potential target genes of differentially expressed lncRNAs detected by trans-regulation. Table S14. GO (Gene Ontology) analysis of predicted targets of differentially expressed lncRNAs. Table S15. Overall information about the predicted targets of differentially expressed miRNAs (DEM). Table S16. GO (Gene Ontology) analysis of predicted targets of differentially expressed lncRNAs and differentially expressed miRNAs. Table S17. The most important lncRNA-target pairs related to PMC meiosis in autotetraploid rice. Table S18. The important lncRNA-target pairs related to EMC meiosis in autotetraploid rice. Table S19. A list of primers used in the present study. Table S20. The information about ten lncRNAs detected by RACE in the present study.
DOI: 10.6084/m9.figshare.11875605
title: Additional file 2 of A chromosomal connectome for psychiatric and metabolic risk variants in adult dopaminergic neurons

description: Additional file 2. Supplementary Tables.
DOI: 10.6084/m9.figshare.11875647.v1
title: Additional file 4 of A chromosomal connectome for psychiatric and metabolic risk variants in adult dopaminergic neurons

description: Additional file 4. Datafile (txt), QTL analysis 1.
DOI: 10.6084/m9.figshare.11875650.v1
title: Additional file 5 of A chromosomal connectome for psychiatric and metabolic risk variants in adult dopaminergic neurons

description: Additional file 5. Datafile (txt), QTL analysis 2.
DOI: 10.6084/m9.figshare.11875590.v1
title: Additional file 3 of Global identification and analysis revealed differentially expressed lncRNAs associated with meiosis and low fertility in autotetraploid rice

description: Additional file 3 Table S11. Classification of differentially expressed lncRNAs related to transposable elements (TEs) in autotetraploid rice. Table S12. The potential target genes of differentially expressed lncRNAs detected by cis-regulation. Table S13. The potential target genes of differentially expressed lncRNAs detected by trans-regulation. Table S14. GO (Gene Ontology) analysis of predicted targets of differentially expressed lncRNAs. Table S15. Overall information about the predicted targets of differentially expressed miRNAs (DEM). Table S16. GO (Gene Ontology) analysis of predicted targets of differentially expressed lncRNAs and differentially expressed miRNAs. Table S17. The most important lncRNA-target pairs related to PMC meiosis in autotetraploid rice. Table S18. The important lncRNA-target pairs related to EMC meiosis in autotetraploid rice. Table S19. A list of primers used in the present study. Table S20. The information about ten lncRNAs detected by RACE in the present study.
DOI: 10.6084/m9.figshare.19738259
title: Additional file 3 of Bi-order multimodal integration of single-cell data

description: Additional file 3: Table S1. Parameter settings used in benchmarking experiments.
DOI: 10.6084/m9.figshare.11875584.v1
title: Additional file 2 of Global identification and analysis revealed differentially expressed lncRNAs associated with meiosis and low fertility in autotetraploid rice

description: Additional file 2 Table S1. Characteristics of all lncRNAs identified in this study. Table S2. Conservation of lncRNAs in other plant species. Table S3. Differentially expressed lncRNAs (DEL) in anther and ovary of Taichung 65-4x compared to Taichung 65. Table S4. The lncRNAs selected by aligment assay compared to a previous study. Table S5. Summary of known and predicted miRNAs detected in this study. Table S6. Overview of 21 nt- and 24 nt-phasiRNAs detected in this study. Table S7. LncRNAs corresponding to miRNA precursors. Table S8. LncRNAs corresponding to phasiRNA precursors. Table S9. A list of lncRNAs predicted to be the targets of miRNAs. Table S10. Transposable elements-associated with differentially expressed lncRNAs in autotetraploid rice.
DOI: 10.6084/m9.figshare.11875605.v1
title: Additional file 2 of A chromosomal connectome for psychiatric and metabolic risk variants in adult dopaminergic neurons

description: Additional file 2. Supplementary Tables.
DOI: 10.6084/m9.figshare.19738259.v1
title: Additional file 3 of Bi-order multimodal integration of single-cell data

description: Additional file 3: Table S1. Parameter settings used in benchmarking experiments.
DOI: 10.6084/m9.figshare.11875647
title: Additional file 4 of A chromosomal connectome for psychiatric and metabolic risk variants in adult dopaminergic neurons

description: Additional file 4. Datafile (txt), QTL analysis 1.
DOI: 10.5281/zenodo.10441304
title: Dataset for Milling cutter fault diagnosis using unsupervised learning on small data: A robust and autonomous framework

description: This is the dataset related to the publication titled: 

Milling cutter fault diagnosis using unsupervised learning on small data: A robust and autonomous frameworkPublished in the journal Eksploatacja i Niezawodność – Maintenance and Reliability DoI: 10.17531/ein/178274

The training and test data have been uploaded in sets of 5000 data points each in form of a structure named cases or A and numbered from 111-117The number and the tool condition are in the table below






111



Normal insert with no defects



TN





112



Wear at flank face



TWFC





113



Wear at nose radius



TWNSR





114



Notch wear



TWNT





115



Crater wear



TWCT





116



Fracture of cutting edge



TFCE





117



Built-up cutting edge



TBUE





 
description: The research was supported by the project "Guided waves based reference-free SHM using fiber Bragg grating sensors (REF-FREE)" (2020/39/D/ST8/00188) granted by National Science Center, Poland.
DOI: 10.5281/zenodo.10441305
title: Dataset for Milling cutter fault diagnosis using unsupervised learning on small data: A robust and autonomous framework

description: This is the dataset related to the publication titled: 

Milling cutter fault diagnosis using unsupervised learning on small data: A robust and autonomous frameworkPublished in the journal Eksploatacja i Niezawodność – Maintenance and Reliability DoI: 10.17531/ein/178274

The training and test data have been uploaded in sets of 5000 data points each in form of a structure named cases or A and numbered from 111-117The number and the tool condition are in the table below






111



Normal insert with no defects



TN





112



Wear at flank face



TWFC





113



Wear at nose radius



TWNSR





114



Notch wear



TWNT





115



Crater wear



TWCT





116



Fracture of cutting edge



TFCE





117



Built-up cutting edge



TBUE





 
description: The research was supported by the project "Guided waves based reference-free SHM using fiber Bragg grating sensors (REF-FREE)" (2020/39/D/ST8/00188) granted by National Science Center, Poland.
DOI: 10.6084/m9.figshare.8207597
title: Additional file 9: of Novel secretome-to-transcriptome integrated or secreto-transcriptomic approach to reveal liquid biopsy biomarkers for predicting individualized prognosis of breast cancer patients

description: Table S1. All proteins LFQR2. (XLSX 644 kb)
DOI: 10.6084/m9.figshare.11875650
title: Additional file 5 of A chromosomal connectome for psychiatric and metabolic risk variants in adult dopaminergic neurons

description: Additional file 5. Datafile (txt), QTL analysis 2.
DOI: 10.6084/m9.figshare.8207597.v1
title: Additional file 9: of Novel secretome-to-transcriptome integrated or secreto-transcriptomic approach to reveal liquid biopsy biomarkers for predicting individualized prognosis of breast cancer patients

description: Table S1. All proteins LFQR2. (XLSX 644 kb)
DOI: 10.6084/m9.figshare.6632993
title: First-trimester metabolomic prediction of stillbirth

description: <b>Background:</b> Stillbirth remains a major problem in both developing and developed countries. Omics evaluation of stillbirth has been highlighted as a top research priority. <b>Objective:</b> To identify new putative first-trimester biomarkers in maternal serum for stillbirth prediction using metabolomics-based approach. <b>Methods:</b> Targeted, nuclear magnetic resonance (NMR) and mass spectrometry (MS), and untargeted liquid chromatography-MS (LC-MS) metabolomic analyses were performed on first-trimester maternal serum obtained from 60 cases that subsequently had a stillbirth and 120 matched controls. Metabolites by themselves or in combination with clinical factors were used to develop logistic regression models for stillbirth prediction. Prediction of stillbirths overall, early (&lt;28 weeks and &lt;32 weeks), those related to growth restriction/placental disorder, and unexplained stillbirths were evaluated. <b>Results:</b> Targeted metabolites including glycine, acetic acid, L-carnitine, creatine, lysoPCaC18:1, PCaeC34:3, and PCaeC44:4 predicted stillbirth overall with an area under the curve [AUC, 95% confidence interval (CI)] = 0.707 (0.628–0.785). When combined with clinical predictors the AUC value increased to 0.740 (0.667–0.812). First-trimester targeted metabolites also significantly predicted early, unexplained, and placental-related stillbirths. Untargeted LC-MS features combined with other clinical predictors achieved an AUC (95%CI) = 0.860 (0.793–0.927) for the prediction of stillbirths overall. We found novel preliminary evidence that, verruculotoxin, a toxin produced by common household molds, might be linked to stillbirth. <b>Conclusions:</b> We have identified novel biomarkers for stillbirth using metabolomics and demonstrated the feasibility of first-trimester prediction.
DOI: 10.6084/m9.figshare.11875926
title: Additional file 12 of Comparative genomics and association analysis identifies virulence genes of Cercospora sojina in soybean

description: Additional file 12: Table S12. Results of genomic association analysis of SNP and virulence values.
DOI: 10.6084/m9.figshare.11875938
title: Additional file 14 of Comparative genomics and association analysis identifies virulence genes of Cercospora sojina in soybean

description: Additional file 14: Table S14. Four virulence-related genes including at least one associated SNP.
DOI: 10.6084/m9.figshare.19738535
title: Additional file 4 of Comparative transcriptome analysis of resistant and susceptible wheat in response to Rhizoctonia cerealis

description: Additional file 4: Table S4.
DOI: 10.6084/m9.figshare.11875974.v1
title: Additional file 5 of Comparative genomics and association analysis identifies virulence genes of Cercospora sojina in soybean

description: Additional file 5: Table S5. Genes from Race15 annotated in PHI.
DOI: 10.6084/m9.figshare.11875938.v1
title: Additional file 14 of Comparative genomics and association analysis identifies virulence genes of Cercospora sojina in soybean

description: Additional file 14: Table S14. Four virulence-related genes including at least one associated SNP.
DOI: 10.6084/m9.figshare.11875926.v1
title: Additional file 12 of Comparative genomics and association analysis identifies virulence genes of Cercospora sojina in soybean

description: Additional file 12: Table S12. Results of genomic association analysis of SNP and virulence values.
DOI: 10.6084/m9.figshare.11875989.v1
title: Additional file 8 of Comparative genomics and association analysis identifies virulence genes of Cercospora sojina in soybean

description: Additional file 8: Table S8. Genes of Race15 annotated in different databases.
DOI: 10.6084/m9.figshare.11875875.v1
title: Additional file 4 of Mitochondrial 8-hydroxy-2′-deoxyguanosine and coronary artery disease in patients with type 2 diabetes mellitus

description: Additional file 4: Data S1. Original data of all 1920 participants analyzed in this study.
DOI: 10.6084/m9.figshare.11875941.v1
title: Additional file 15 of Comparative genomics and association analysis identifies virulence genes of Cercospora sojina in soybean

description: Additional file 15: Table S15. Four virulence -related genes with the more than 50 non-synonymous SNPs.
DOI: 10.6084/m9.figshare.9254579
title: Additional file 10: of Hybrid sequencing of the Gynostemma pentaphyllum transcriptome provides new insights into gypenoside biosynthesis

description: Table S4. The primers used for real-time PCR. (XLSX 14 kb)
DOI: 10.6084/m9.figshare.9254657
title: Additional file 8: of Hybrid sequencing of the Gynostemma pentaphyllum transcriptome provides new insights into gypenoside biosynthesis

description: Table S3 The distribution of GpbHLHs from G. pentaphyllum. (XLSX 12 kb)
DOI: 10.6084/m9.figshare.11875920.v1
title: Additional file 11 of Comparative genomics and association analysis identifies virulence genes of Cercospora sojina in soybean

description: Additional file 11: Table S11. 31,812 SNP sites of the 32 isolates.
DOI: 10.6084/m9.figshare.6632993.v1
title: First-trimester metabolomic prediction of stillbirth

description: <b>Background:</b> Stillbirth remains a major problem in both developing and developed countries. Omics evaluation of stillbirth has been highlighted as a top research priority. <b>Objective:</b> To identify new putative first-trimester biomarkers in maternal serum for stillbirth prediction using metabolomics-based approach. <b>Methods:</b> Targeted, nuclear magnetic resonance (NMR) and mass spectrometry (MS), and untargeted liquid chromatography-MS (LC-MS) metabolomic analyses were performed on first-trimester maternal serum obtained from 60 cases that subsequently had a stillbirth and 120 matched controls. Metabolites by themselves or in combination with clinical factors were used to develop logistic regression models for stillbirth prediction. Prediction of stillbirths overall, early (&lt;28 weeks and &lt;32 weeks), those related to growth restriction/placental disorder, and unexplained stillbirths were evaluated. <b>Results:</b> Targeted metabolites including glycine, acetic acid, L-carnitine, creatine, lysoPCaC18:1, PCaeC34:3, and PCaeC44:4 predicted stillbirth overall with an area under the curve [AUC, 95% confidence interval (CI)] = 0.707 (0.628–0.785). When combined with clinical predictors the AUC value increased to 0.740 (0.667–0.812). First-trimester targeted metabolites also significantly predicted early, unexplained, and placental-related stillbirths. Untargeted LC-MS features combined with other clinical predictors achieved an AUC (95%CI) = 0.860 (0.793–0.927) for the prediction of stillbirths overall. We found novel preliminary evidence that, verruculotoxin, a toxin produced by common household molds, might be linked to stillbirth. <b>Conclusions:</b> We have identified novel biomarkers for stillbirth using metabolomics and demonstrated the feasibility of first-trimester prediction.
DOI: 10.6084/m9.figshare.11875875
title: Additional file 4 of Mitochondrial 8-hydroxy-2′-deoxyguanosine and coronary artery disease in patients with type 2 diabetes mellitus

description: Additional file 4: Data S1. Original data of all 1920 participants analyzed in this study.
DOI: 10.6084/m9.figshare.6632933
title: Foley catheter with simultaneous oxytocin on labor induction: a meta-analysis of randomized controlled trials

description: <b>Objective:</b> It is unclear that whether Foley catheter with simultaneous oxytocin could improve the efficacy of induction outcome. <b>Method:</b> To conduct a meta-analysis of randomized controlled trial (RCT) studies to evaluate the effect of Foley catheter with simultaneous oxytocin on labor induction. PubMed, Embase, and other databases were searched from their inception to July 2017. We included all RCTs comparing Foley catheter with simultaneous oxytocin (i.e. intervention group) with Foley catheter followed by oxytocin (i.e. control group) in the three kinds of women (nulliparas and multiparas/only nulliparas/only multiparas). We estimate summarized relative risk (RR) and 95% confidence intervals (CIs) for dichotomous outcomes, standard mean difference for continuous outcomes. Fixed- and random-effects models were used, depending on heterogeneity. <b>Results:</b> After application of our inclusion and exclusion criteria, six RCTs with a total of 1133 participants were identified. We found that only nulliparas had significant RR of delivery within 24 h (RR = 1.32, 95% CI: 1.12, 1.55, <i>I</i><sup>2</sup> = 46.5%). Meanwhile, there was no statistically significant difference between intervention and control groups in vaginal delivery in 24 h, cesarean delivery, time to delivery, and Apgar score at 5 min less than 7. Foley catheter with simultaneous oxytocin did not increase the risk of side effects, included chorioamnionitis, postpartum hemorrhage, uterine hyperstimulation, and neonatal intensive care unit admission. <b>Conclusion:</b> The results seem to support the use of oxytocin to a Foley catheter at the initiation of labor induction, as it might lead to increases the rate of delivery within 24 h in nulliparas.
DOI: 10.6084/m9.figshare.11875932.v1
title: Additional file 13 of Comparative genomics and association analysis identifies virulence genes of Cercospora sojina in soybean

description: Additional file 13: Table S13. Genes including at least one SNP.
DOI: 10.6084/m9.figshare.11875941
title: Additional file 15 of Comparative genomics and association analysis identifies virulence genes of Cercospora sojina in soybean

description: Additional file 15: Table S15. Four virulence -related genes with the more than 50 non-synonymous SNPs.
DOI: 10.6084/m9.figshare.11875932
title: Additional file 13 of Comparative genomics and association analysis identifies virulence genes of Cercospora sojina in soybean

description: Additional file 13: Table S13. Genes including at least one SNP.
DOI: 10.6084/m9.figshare.12924504
title: Wilms’ tumor 1 (<i>WT1</i>) promotes ovarian cancer progression by regulating E-cadherin and ERK1/2 signaling

description: Wilms’ tumor 1 (<i>WT1</i>) is reported to play an important role in tumor invasion and metastasis, two hallmarks of ovarian cancer (OC) that influence treatment efficacy and prognosis. However, the specific roles and underlying mechanisms of <i>WT1</i> in OC have not been fully understood. Here, we investigated the potential function and signaling pathways of <i>WT1</i> in OC cells. We showed that WT1 was significantly upregulated in human OC tissues and closely associated with OC type, grade and FIGO stage. In cultured cells and xenograft mouse models, <i>WT1</i> depletion significantly inhibited cell migration and invasion, reversed epithelial–mesenchymal transition (EMT), and prevented metastasis of OC cells. We further demonstrated that <i>WT1</i> inhibited E-cadherin expression via targeting <i>E-cadherin</i> gene promoter by chromatin immunoprecipitation and luciferase reporter assay. Moreover, ERK1/2 activation was suppressed upon <i>WT1</i> silencing. Inhibiting ERK1/2 phosphorylation increased E-cadherin expression and suppressed WT1-induced OC cell migration and invasion. Taken together, our study reveals <i>WT1</i> exerts a tumor-promoting role in OC, enhancing EMT through negative modulation of E-cadherin expression via ERK1/2 signaling. <i>WT1</i> may represent a novel therapeutic target that may improve the prognosis of OC.
DOI: 10.6084/m9.figshare.9254585.v1
title: Additional file 1: of Hybrid sequencing of the Gynostemma pentaphyllum transcriptome provides new insights into gypenoside biosynthesis

description: Table S1. The libraries for PacBio and Illumina sequencing. A total of 13 sequencing libraries. PacBio sequencing includes three libraries. The fragment length was 0.8–2 kb, 2–3 kb, and 3–6 kb. Illumina sequencing libraries were constructed with the root, stem and leaves from G. pentaphyllum with three replicates. MeJA-treated leaves at different times (0 h, 6 h, 12 h, 24 h) were collected to construct Illumina sequencing libraries. (XLSX 9 kb)