cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12849719
title: A Nonparametric Nonclassical Measurement Error Approach to Estimating Intergenerational Mobility Elasticities

description: This article provides a framework for estimating intergenerational mobility elasticities (IGEs) of children’s income with respect to parental income. We allow the IGEs to be heterogeneous, by leaving the relationship of parental and child incomes unspecified, while acknowledging and addressing the <i>latent</i> nature of both child and parental <i>permanent</i> incomes and the resulted life-cycle bias. Our framework enables us to test the widely imposed assumption that the intergenerational mobility function is linear. Applying our method to the Panel Studies of Income Dynamics data, we decisively reject the commonly imposed linearity assumption and find substantial heterogeneity in the IGEs across the population. We confirm an important finding that the IGEs with respect to parental income exhibit a U-shape pattern, which is occasionally highlighted in the analysis using transition matrices. Specifically, there is a considerable degree of mobility among the broadly defined middle class, but the children of both high- and low-income parents are more likely to be high- and low-income adults, respectively. This result also provides insights into the (intertemporal) Great Gatsby curve, suggesting that a higher level of inequality within one generation may lead to a higher level of social immobility in the next generation in the United States.
DOI: 10.25403/upresearchdata.25215689.v1
title: Analyses of source water samples from three areas in South Africa for estrogenic activity and oxidative stress

description: These dataset contains concentration–effect curves and oxidative stress response results from the AREc32 reporter gene assay (table 1). Samples were analyzed in replicate through bioassays, and screening for the presence of pharmaceuticals using ultra-high performance liquid chromatography system. During data analysis, the results for each replicate were compared to ensure that the variability did not exceed a pre-determined level. The average of the intra-assay replicates was then used as a single number. The concentration–response curve for all repeats was also evaluated together. The final result was reported as the average of the two closest results.
Estradiol equivalent concentrations (ng/L) in source water from Gauteng (GP), Mpumalanga (MP), and Limpopo (LP) provinces, South Africa, using the yeast estrogen screen (YES) (Table 2). The following equation was applied to correct for turbidity: corrected value = test abs (540 nm) – [test abs (620 nm) – median blank abs (620 nm)]. The detection limit of the yeast assay was calculated as absorbance induced by the solvent control (blank) plus three times the standard deviation. Sample concentrations with absorbance values below the solvent control minus three times the standard deviation were considered cytotoxic concentrations. The estradiol equivalents (EEq) of the samples were interpolated from the estradiol standard curve and corrected with the appropriate dilution factor for each sample. This was calculated for samples with 3 or more points above the detection limit. EEq values were reported as the average ± SD of three independent repeats.
Pharmaceutical compounds were detected using the Dionex Ultimate 3000 UPLC (table 3). Compass Data Analysis 4.3 (Bruker, Germany) software package together with the tools found in the software package such as compass isotope pattern and compound crawler were used in the screening workflow. Accurate mass measurements of each peak from the extracted ion chromatograms were obtained using a sodium formate calibrant solution delivered by a Kd Scientific external pump. The function edit chromatogram was used to obtain the extracted ion chromatogram (EIC) of each compound using their molecular formula. MS/MS spectrum of each compound was then obtained using the find compound spectra function in the data analysis. The compound crawler function in the Data Analysis 4.3 software was used to confirm that the peak represents the suspect compounds in online databases of KEGG (Kyoto Encyclopedia of Genes and Genomes), CHEBI (Chemical Entities of Biological Interest), HMBD (Human Metabolome Data Base), and FOR-IDENT. Parameters used in screening were mass accuracy ≤5 ppm, isotopic fit (mSigma) less than or equal to 100, signal-to-noise ratio of 3, minimum intensity threshold of 500, and presence of a minimum of one production.
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DOI: 10.6084/m9.figshare.7081826
title: Additional file 4: of Comparative proteomic analysis of maize (Zea mays L.) seedlings under rice black-streaked dwarf virus infection

description: Table S4. The detail information of DAPs. (XLSX 40 kb)
DOI: 10.6084/m9.figshare.19664371
title: Additional file 3 of Factors influencing bedtime procrastination in junior college nursing students: a cross-sectional study

description: Additional file 3.
DOI: 10.6084/m9.figshare.17043328.v1
title: <i>Ndufa6</i> regulates adipogenic differentiation via <i>Scd1</i>

description: Obesity and associated complications are becoming a pandemic. Inhibiting adipogenesis is an important intervention for the treatment of obesity. Despite intensive investigations, numerous mechanistic aspects of adipogenesis remain unclear, and many potential therapeutic targets have yet to be discovered. Transcriptomics and lipidomics approaches were used to explore the functional genes regulating adipogenic differentiation and the potential mechanism in OP9 cells and adipose-derived stem cells. In this study, we found that NADH:ubiquinone oxidoreductase subunit A6 (<i>Ndufa6</i>) participates in the regulation of adipogenic differentiation. Furthermore, we show that the effect of Ndufa6 is mediated through stearoyl-CoA desaturase 1 (<i>Scd1</i>) and demonstrate the inhibitory effect of a SCD1 inhibitor on adipogenesis. Our study broadens the understanding of adipogenic differentiation and offers NDUFA6-SCD1 as a potential therapeutic target for the treatment of obesity.
DOI: 10.6084/m9.figshare.7081715
title: MOESM1 of Phosphotyrosine profiling of human cerebrospinal fluid

description: Additional file 1: Table S1. A summary of tyrosine phosphopeptides identified in CSF.
DOI: 10.6084/m9.figshare.7081529
title: Additional file 2: of Root exudates drive the soil-borne legacy of aboveground pathogen infection

description: R code and root exudate compounds. (ZIP 360 kb)
DOI: 10.6084/m9.figshare.7081529.v1
title: Additional file 2: of Root exudates drive the soil-borne legacy of aboveground pathogen infection

description: R code and root exudate compounds. (ZIP 360 kb)
DOI: 10.6084/m9.figshare.7081715.v1
title: MOESM1 of Phosphotyrosine profiling of human cerebrospinal fluid

description: Additional file 1: Table S1. A summary of tyrosine phosphopeptides identified in CSF.
DOI: 10.6084/m9.figshare.12324647
title: Additional file 2 of Deciphering the transcriptional regulatory networks that control size, color, and oil content in Brassica rapa seeds

description: Additional file 2: Fig. S1. PCA and coefficient of association analysis. (a) The 2D PCA analysis of SWUK3, The biological replicates of the same period have the same color; (b) Heatmap of all retained samples correlation coefficient of SWUK3. In the upper right corner is the red circle representing relevance, and the bottom left is the correlation coefficient. The higher the value of correlation coefficient, the redder the color; (c) The 2D PCA of SWUK4; (d) Heatmap of all retained samples correlation coefficient of SWUK4. Fig. S2. The process of co-expression network construction. (a) The clustering tree of all 38 samples; (b) The left one displays the relationship between the soft threshold and scale independence with 0.9 red line. The right one displays the relationship between the soft threshold and mean connectivity; (c) The cluster dendrogram; (d) Heatmap of the correlation among the color modules, the higher the correlation, the color more deep. Fig. S3. Module-trait relationships and GO enrichment of interested color modules. (a) Heatmap of the correlation between the 15 color modules and 4 traits, with correlation coefficient and P value; (b) GO enrichment analysis for genes in the MEgreen; (c) GO enrichment analysis for genes in the MEsalmon; (d) GO enrichment analysis for genes in the MEbrown. Only top twenty GO terms were displayed here. Fig. S4. Co-expression network of MEgreen and Bra.A09GRAS. Fig S5. The WGCNA MEbrown module is significantly associated with OC increase. (a) Heatmap of MEbrown module genes in two B. rapa accessions, which was displayed based on log2(FPKM + 1). (b) Primary co-expression network of Bra.A03GRF5. (c) Primary co-expression network of Bra.A09WRI1. (d) Primary co-expression network of Bra.A06FUS3. Square, down arrow, triangle, and disc represent TF, TR, kinase, and other genes, respectively. The edge width represents the weight value between the two nodes: the higher the value of the weight between the nodes, the wider the edge.
DOI: 10.6084/m9.figshare.19664380.v1
title: Additional file 3 of Antibacterial activities and action mode of anti-hyperlipidemic lomitapide against Staphylococcus aureus

description: Additional file 3.
DOI: 10.25387/g3.7607060.v1
title: Supplemental Material for Xu et al., 2019

description: Supplemental Tables S1, S2, S3; <br>Supplemental Figures S1, S2;Supplemental Files S1, S2
DOI: 10.6084/m9.figshare.7081781.v1
title: Additional file 1: of Comparative proteomic analysis of maize (Zea mays L.) seedlings under rice black-streaked dwarf virus infection

description: Table S1. The primer sequences for qRT-PCR. (XLSX 8 kb)
DOI: 10.25387/g3.7607060.v2
title: Supplemental Material for Xu et al., 2019

description: Supplemental Tables S1, S2, S3; <br>Supplemental Figures S1, S2;Supplemental Files S1, S2
DOI: 10.6084/m9.figshare.7081781
title: Additional file 1: of Comparative proteomic analysis of maize (Zea mays L.) seedlings under rice black-streaked dwarf virus infection

description: Table S1. The primer sequences for qRT-PCR. (XLSX 8 kb)
DOI: 10.6084/m9.figshare.7081790.v1
title: Additional file 2: of Comparative analysis of circular RNAs between soybean cytoplasmic male-sterile line NJCMS1A and its maintainer NJCMS1B by high-throughput sequencing

description: Table S2. The circRNAs identified in NJCMS1A and NJCMS1B. (XLSX 254 kb)
DOI: 10.6084/m9.figshare.7081814
title: Additional file 3: of Comparative proteomic analysis of maize (Zea mays L.) seedlings under rice black-streaked dwarf virus infection

description: Table S3. The annotation information of all identified proteins. (XLSX 1598 kb)
DOI: 10.6084/m9.figshare.7081814.v1
title: Additional file 3: of Comparative proteomic analysis of maize (Zea mays L.) seedlings under rice black-streaked dwarf virus infection

description: Table S3. The annotation information of all identified proteins. (XLSX 1598 kb)
DOI: 10.6084/m9.figshare.7081829
title: Additional file 5: of Comparative analysis of circular RNAs between soybean cytoplasmic male-sterile line NJCMS1A and its maintainer NJCMS1B by high-throughput sequencing

description: Table S4â 1. The up-expressed circRNAs identified in NJCMS1A and NJCMS1B; Table S4â 2. The down-expressed circRNAs identified in NJCMS1A and NJCMS1B. (XLSX 106 kb)
DOI: 10.6084/m9.figshare.7081829.v1
title: Additional file 5: of Comparative analysis of circular RNAs between soybean cytoplasmic male-sterile line NJCMS1A and its maintainer NJCMS1B by high-throughput sequencing

description: Table S4â 1. The up-expressed circRNAs identified in NJCMS1A and NJCMS1B; Table S4â 2. The down-expressed circRNAs identified in NJCMS1A and NJCMS1B. (XLSX 106 kb)
DOI: 10.6084/m9.figshare.7081763
title: Additional file 10: of Comparative analysis of circular RNAs between soybean cytoplasmic male-sterile line NJCMS1A and its maintainer NJCMS1B by high-throughput sequencing

description: Table S8. Conserved domains of the predicted protein-coding products. (XLSX 72 kb)
DOI: 10.6084/m9.figshare.7081826.v1
title: Additional file 4: of Comparative proteomic analysis of maize (Zea mays L.) seedlings under rice black-streaked dwarf virus infection

description: Table S4. The detail information of DAPs. (XLSX 40 kb)
DOI: 10.6084/m9.figshare.12324647.v1
title: Additional file 2 of Deciphering the transcriptional regulatory networks that control size, color, and oil content in Brassica rapa seeds

description: Additional file 2: Fig. S1. PCA and coefficient of association analysis. (a) The 2D PCA analysis of SWUK3, The biological replicates of the same period have the same color; (b) Heatmap of all retained samples correlation coefficient of SWUK3. In the upper right corner is the red circle representing relevance, and the bottom left is the correlation coefficient. The higher the value of correlation coefficient, the redder the color; (c) The 2D PCA of SWUK4; (d) Heatmap of all retained samples correlation coefficient of SWUK4. Fig. S2. The process of co-expression network construction. (a) The clustering tree of all 38 samples; (b) The left one displays the relationship between the soft threshold and scale independence with 0.9 red line. The right one displays the relationship between the soft threshold and mean connectivity; (c) The cluster dendrogram; (d) Heatmap of the correlation among the color modules, the higher the correlation, the color more deep. Fig. S3. Module-trait relationships and GO enrichment of interested color modules. (a) Heatmap of the correlation between the 15 color modules and 4 traits, with correlation coefficient and P value; (b) GO enrichment analysis for genes in the MEgreen; (c) GO enrichment analysis for genes in the MEsalmon; (d) GO enrichment analysis for genes in the MEbrown. Only top twenty GO terms were displayed here. Fig. S4. Co-expression network of MEgreen and Bra.A09GRAS. Fig S5. The WGCNA MEbrown module is significantly associated with OC increase. (a) Heatmap of MEbrown module genes in two B. rapa accessions, which was displayed based on log2(FPKM + 1). (b) Primary co-expression network of Bra.A03GRF5. (c) Primary co-expression network of Bra.A09WRI1. (d) Primary co-expression network of Bra.A06FUS3. Square, down arrow, triangle, and disc represent TF, TR, kinase, and other genes, respectively. The edge width represents the weight value between the two nodes: the higher the value of the weight between the nodes, the wider the edge.
DOI: 10.6084/m9.figshare.17043328
title: <i>Ndufa6</i> regulates adipogenic differentiation via <i>Scd1</i>

description: Obesity and associated complications are becoming a pandemic. Inhibiting adipogenesis is an important intervention for the treatment of obesity. Despite intensive investigations, numerous mechanistic aspects of adipogenesis remain unclear, and many potential therapeutic targets have yet to be discovered. Transcriptomics and lipidomics approaches were used to explore the functional genes regulating adipogenic differentiation and the potential mechanism in OP9 cells and adipose-derived stem cells. In this study, we found that NADH:ubiquinone oxidoreductase subunit A6 (<i>Ndufa6</i>) participates in the regulation of adipogenic differentiation. Furthermore, we show that the effect of Ndufa6 is mediated through stearoyl-CoA desaturase 1 (<i>Scd1</i>) and demonstrate the inhibitory effect of a SCD1 inhibitor on adipogenesis. Our study broadens the understanding of adipogenic differentiation and offers NDUFA6-SCD1 as a potential therapeutic target for the treatment of obesity.
DOI: 10.6084/m9.figshare.7081877
title: Additional file 8: of Comparative analysis of circular RNAs between soybean cytoplasmic male-sterile line NJCMS1A and its maintainer NJCMS1B by high-throughput sequencing

description: Table S6. Predicted circRNA-miRNA-mRNA connection for differentially expressed circRNAs in NJCMS1A and NJCMS1B. (XLSX 48 kb)
DOI: 10.6084/m9.figshare.7082021
title: Additional file 9: of Comparative transcriptome analysis reveals that tricarboxylic acid cycle-related genes are associated with maize CMS-C fertility restoration

description: Two hundred forty-two significantly enriched GO terms obtained by Fisher’s test (Q ≤ 0.05). (XLSX 20 kb)
DOI: 10.5281/zenodo.10663512
title: Export der Ergebnisse der OstData-Online-Umfrage zur Bedarfsermittlung in den Bereichen Datenmanagement, Beratung, Publikation von Forschungsdaten und Community-Building

description: Das Projekt OstData baut einen Forschungsdatenservice für die ost-, ostmittel- und südosteuropäische Forschung auf und umfasst ein breites Spektrum an Beratungs- und Informationsdienstleistungen zu Themen des Forschungsdatenmanagements (FDM). Um den entstehenden Forschungsdatenservice an die Bedürfnisse und Wünsche der wissenschaftlichen Community anzupassen, hat das Projektteam verschiedene Community-Building-Maßnahmen ergriffen. Eine davon war die Online-Befragung zur Ermittlung der Bedürfnisse in den Bereichen Beratungsformate, Erwerbungsstrategien und Informationsmaterialien.

Ziel der Online-Umfrage war es, zielgruppenspezifische Besonderheiten für die FDM-Beratung in der Ost-, Ostmittel- und Südosteuropaforschung zu eruieren, um im Rahmen von OstData entsprechende Beratungsangebote für die wissenschaftliche Community anbieten zu können. Die Befragung lief vom 24.08.2021 bis 30.09.2021 über die Software LimeSurvey und war vollständig anonym. Für die Teilnahme an der Befragung gab es keine Zugangsvoraussetzungen. Interessierte Teilnehmende erreichten den Fragebogen über einen Link, der über einschlägige Kanäle im Bereich der Ost-, Ostmittel- und Südosteuropastudien sowie über Mailinglisten im Bereich des FDM beworben wurde.

Am Ende des Erhebungszeitraums lagen 60 vollständig ausgefüllte Fragebögen vor. Ab der zweiten Frage bietet die Umfrage drei verschiedene Antwortpfade für drei Gruppen von Teilnehmenden. Jeder Pfad führt die Teilnehmenden durch vier Bereiche der Umfrage - Bereich A: Datenmanagement, Bereich B: Beratung und Materialien zum FDM, Bereich C: Publikation von Forschungsdaten, Bereich D: Fragen, Angebote und Community-Vernetzung.

Die Fragestruktur bestand hauptsächlich aus Pflichtangaben in Form von Listen mit Multiple-Choice-Optionen, Listen mit Single-Choice-Optionen und Matrixfragen mit Bewertungsmöglichkeit auf einer Skala. Der Datensatz enthält die Fragecodes sowie die Fragentexte und Antworten der Teilnehmenden (in .csv). Der Umfrage liegt ein geisteswissenschaftliches Forschungsinteresse zugrunde.
DOI: 10.5281/zenodo.10663513
title: Export der Ergebnisse der OstData-Online-Umfrage zur Bedarfsermittlung in den Bereichen Datenmanagement, Beratung, Publikation von Forschungsdaten und Community-Building

description: Das Projekt OstData baut einen Forschungsdatenservice für die ost-, ostmittel- und südosteuropäische Forschung auf und umfasst ein breites Spektrum an Beratungs- und Informationsdienstleistungen zu Themen des Forschungsdatenmanagements (FDM). Um den entstehenden Forschungsdatenservice an die Bedürfnisse und Wünsche der wissenschaftlichen Community anzupassen, hat das Projektteam verschiedene Community-Building-Maßnahmen ergriffen. Eine davon war die Online-Befragung zur Ermittlung der Bedürfnisse in den Bereichen Beratungsformate, Erwerbungsstrategien und Informationsmaterialien.

Ziel der Online-Umfrage war es, zielgruppenspezifische Besonderheiten für die FDM-Beratung in der Ost-, Ostmittel- und Südosteuropaforschung zu eruieren, um im Rahmen von OstData entsprechende Beratungsangebote für die wissenschaftliche Community anbieten zu können. Die Befragung lief vom 24.08.2021 bis 30.09.2021 über die Software LimeSurvey und war vollständig anonym. Für die Teilnahme an der Befragung gab es keine Zugangsvoraussetzungen. Interessierte Teilnehmende erreichten den Fragebogen über einen Link, der über einschlägige Kanäle im Bereich der Ost-, Ostmittel- und Südosteuropastudien sowie über Mailinglisten im Bereich des FDM beworben wurde.

Am Ende des Erhebungszeitraums lagen 60 vollständig ausgefüllte Fragebögen vor. Ab der zweiten Frage bietet die Umfrage drei verschiedene Antwortpfade für drei Gruppen von Teilnehmenden. Jeder Pfad führt die Teilnehmenden durch vier Bereiche der Umfrage - Bereich A: Datenmanagement, Bereich B: Beratung und Materialien zum FDM, Bereich C: Publikation von Forschungsdaten, Bereich D: Fragen, Angebote und Community-Vernetzung.

Die Fragestruktur bestand hauptsächlich aus Pflichtangaben in Form von Listen mit Multiple-Choice-Optionen, Listen mit Single-Choice-Optionen und Matrixfragen mit Bewertungsmöglichkeit auf einer Skala. Der Datensatz enthält die Fragecodes sowie die Fragentexte und Antworten der Teilnehmenden (in .csv). Der Umfrage liegt ein geisteswissenschaftliches Forschungsinteresse zugrunde.
DOI: 10.6084/m9.figshare.12324644.v1
title: Additional file 1 of Deciphering the transcriptional regulatory networks that control size, color, and oil content in Brassica rapa seeds

description: Additional file 1: Table S1. Phenotypic traits of two B. rapa accessions. Table S2. Overview of transcriptomic data and mapping efficiency. Table S3. Classification and overview of DEGs. Table S4. Identification of classification of all TF, TR and kinase genes in B. rapa. Table S5. GO enrichment analysis of DEGs obtained by comparison two accessions at the seven stages. Table S6. GO enrichment analysis of DEGs obtained by comparison the adjacent stages in each one accession. Table S7. Homologous cell cycle genes in Arabidopsis and B. rapa. Table S8. GO enrichment analysis of color modules in WGCNA. Table S9. Expression values of flavonoid pathway genes in two B. rapa accessions at seven seed developmental stages. Table S10. Expression values of genes involved in fatty acid metabolism in two B. rapa accessions at seven seed developmental stages. Table S11. Primers used in qRT-PCR.
DOI: 10.6084/m9.figshare.7081799.v1
title: Additional file 3: of Comparative analysis of circular RNAs between soybean cytoplasmic male-sterile line NJCMS1A and its maintainer NJCMS1B by high-throughput sequencing

description: Table S3. The homologous circRNAs identified in this study vs. previous study of Zhao et al. (XLSX 3455 kb)
DOI: 10.6084/m9.figshare.7081898.v1
title: Additional file 1: of Comparative transcriptome analysis reveals that tricarboxylic acid cycle-related genes are associated with maize CMS-C fertility restoration

description: List of primers used for qPCR in this study. 18S RNA was used as an internal control. (XLSX 12 kb)
DOI: 10.6084/m9.figshare.7081931
title: Additional file 3: of Comparative transcriptome analysis reveals that tricarboxylic acid cycle-related genes are associated with maize CMS-C fertility restoration

description: Fertility segregations of the BC4 and BC5 populations. A chi-squared test was used to evaluate the fertility segregation ratios. (XLSX 11 kb)
DOI: 10.6084/m9.figshare.7082096.v1
title: Additional file 11: of LGR5, a novel functional glioma stem cell marker, promotes EMT by activating the Wnt/Î˛-catenin pathway and predicts poor survival of glioma patients

description: Table S4. Univariate analysis of factors associated with prognosis in the LGG group. (XLS 12 kb)
DOI: 10.6084/m9.figshare.7081919.v1
title: Additional file 10: of Identification and expression analysis of genes with pathogen-inducible cis-regulatory elements in the promoter regions in Oryza sativa

description: Table S8. Differentially expressed genes without the PICEs in the promoters identified from the rice microarray data analysis. (XLSX 16 kb)
DOI: 10.6084/m9.figshare.7081964.v1
title: Additional file 1: of Identification and expression analysis of genes with pathogen-inducible cis-regulatory elements in the promoter regions in Oryza sativa

description: Table S1. Chromosomal distribution of the rice genes controlled by putative PIPs. (XLSX 21 kb)
DOI: 10.6084/m9.figshare.7081970
title: Additional file 6: of Comparative transcriptome analysis reveals that tricarboxylic acid cycle-related genes are associated with maize CMS-C fertility restoration

description: Coding sequences of novel genes. (TXT 1323 kb)