cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.26084/ioerfdz-data-de-2024-1
title: Crowd-sourced collected building attributes of the Colouring Dresden project 
title: Data collected in between 06 March 2023 to 31 October 2023

description: The building attribute data was collected by citizens as part of the citizen science project “Colouring Dresden”. Main goal was to collect information about buildings (like building age, usage, number of storeys, roof shape etc.) in an interactive online map. Different action formats (like dialogue series, presentations, mapathons, hackathons, and monthly meetings) were organised to bring citizens into action and discuss building-related topics. Focus was the sustainable construction of buildings and the questions how good current buildings of the city are prepared for natural catastrophes like floods, heavy rain incidents or heat stress. The project period was from October 2022 to September 2023 and the mapping platform was launched in March 2023.

The project is part of the international research network “Colouring Cities Research Programme” (CCRP) and the first local project in Germany. Colouring Dresden is currently coordinating the European Hub.

The project was led by Leibniz Institute of Ecological Urban and Regional Development Dresden, Germany in cooperation with:

-	Sächsische Landesbibliothek - Staats- und Universitätsbibliothek Dresden (SLUB) - Regionalportal Saxorum
-	Bund Deutscher Architektinnen und Architekten (BDA)
-	Zentrum für Baukultur Sachsen (ZfBK)
-	Technische Sammlungen Dresden (TSD)/ DLR_School_Lab TU Dresden
-	Zentralbibliothek der Städtische Bibliotheken Dresden (SBD) 


Data description: 
The data contains several files 
-	building_atributes_geometry_20231001.gpkg: building geometries and building attributes in Geopackage file format
-	building_attributes.csv: building attributes
-	building_verification.csv: building verification data (crowd-sourced)
-	edit_history.csv: edit history of collected building_attributes
-	README.md
DOI: 10.6084/m9.figshare.11888487
title: Additional file 4 of Cell-free DNA analysis reveals POLR1D-mediated resistance to bevacizumab in colorectal cancer

description: Additional file 4: Summary of recurrent focal events in our cohort and TCGA dataset. Our Cohort: Summary of all recurrent focal events with a frequency over 0.01 (Upper) or 0.05 (Bottom) in our CRC cohort. Potential driver genes were identified as in Fig. 1a. TCGA: Summary of all recurrent focal events with a frequency over 0.01 (Upper) or 0.05 (Bottom) in TCGA cohort. Potential driver genes were identified as in Fig. 1a.
DOI: 10.6084/m9.figshare.11888487.v1
title: Additional file 4 of Cell-free DNA analysis reveals POLR1D-mediated resistance to bevacizumab in colorectal cancer

description: Additional file 4: Summary of recurrent focal events in our cohort and TCGA dataset. Our Cohort: Summary of all recurrent focal events with a frequency over 0.01 (Upper) or 0.05 (Bottom) in our CRC cohort. Potential driver genes were identified as in Fig. 1a. TCGA: Summary of all recurrent focal events with a frequency over 0.01 (Upper) or 0.05 (Bottom) in TCGA cohort. Potential driver genes were identified as in Fig. 1a.
DOI: 10.5281/zenodo.10672822
title: IODP Expedition 393 Piece log

description: Dataset includes length data for every whole-round piece: bin length, whole-round piece length (measured by curation staff), and both the archive- and working-half piece lengths (optionally measured by scientists).
DOI: 10.6084/m9.figshare.16607084
title: Additional file 1 of Single-cell exome sequencing reveals multiple subclones in metastatic colorectal carcinoma

description: Additional file 1: Supplementary tables S1~S5
DOI: 10.6084/m9.figshare.16607084.v1
title: Additional file 1 of Single-cell exome sequencing reveals multiple subclones in metastatic colorectal carcinoma

description: Additional file 1: Supplementary tables S1~S5
DOI: 10.6084/m9.figshare.16607090
title: Additional file 3 of Single-cell exome sequencing reveals multiple subclones in metastatic colorectal carcinoma

description: Additional file 3: Supplementary table S6
DOI: 10.6084/m9.figshare.16607093
title: Additional file 4 of Single-cell exome sequencing reveals multiple subclones in metastatic colorectal carcinoma

description: Additional file 4:. Source data for Fig. 5
DOI: 10.6084/m9.figshare.16607093.v1
title: Additional file 4 of Single-cell exome sequencing reveals multiple subclones in metastatic colorectal carcinoma

description: Additional file 4:. Source data for Fig. 5
DOI: 10.6084/m9.figshare.16607090.v1
title: Additional file 3 of Single-cell exome sequencing reveals multiple subclones in metastatic colorectal carcinoma

description: Additional file 3: Supplementary table S6
DOI: 10.6084/m9.figshare.16607102.v1
title: Additional file 1 of Platelet transcriptome profiles provide potential therapeutic targets for elderly acute myelocytic leukemia patients

description: Additional file 1. Quality control details of platelet RNA-seq.
DOI: 10.6084/m9.figshare.16607105
title: Additional file 2 of Platelet transcriptome profiles provide potential therapeutic targets for elderly acute myelocytic leukemia patients

description: Additional file 2. Differential transcript levels of genes in platelets between young and elderly AML patients.
DOI: 10.6084/m9.figshare.16607105.v1
title: Additional file 2 of Platelet transcriptome profiles provide potential therapeutic targets for elderly acute myelocytic leukemia patients

description: Additional file 2. Differential transcript levels of genes in platelets between young and elderly AML patients.
DOI: 10.6084/m9.figshare.16607108
title: Additional file 3 of Platelet transcriptome profiles provide potential therapeutic targets for elderly acute myelocytic leukemia patients

description: Additional file 3. KEGG pathway enrichment analysis results.
DOI: 10.6084/m9.figshare.16607108.v1
title: Additional file 3 of Platelet transcriptome profiles provide potential therapeutic targets for elderly acute myelocytic leukemia patients

description: Additional file 3. KEGG pathway enrichment analysis results.
DOI: 10.6084/m9.figshare.16607111.v1
title: Additional file 4 of Platelet transcriptome profiles provide potential therapeutic targets for elderly acute myelocytic leukemia patients

description: Additional file 4. GO enrichment analysis results of genes with downward transcript levels.
DOI: 10.6084/m9.figshare.16607114.v1
title: Additional file 5 of Platelet transcriptome profiles provide potential therapeutic targets for elderly acute myelocytic leukemia patients

description: Additional file 5. GSEA enrichment analysis results.
DOI: 10.6084/m9.figshare.16607102
title: Additional file 1 of Platelet transcriptome profiles provide potential therapeutic targets for elderly acute myelocytic leukemia patients

description: Additional file 1. Quality control details of platelet RNA-seq.
DOI: 10.6084/m9.figshare.16607111
title: Additional file 4 of Platelet transcriptome profiles provide potential therapeutic targets for elderly acute myelocytic leukemia patients

description: Additional file 4. GO enrichment analysis results of genes with downward transcript levels.
DOI: 10.6084/m9.figshare.16607114
title: Additional file 5 of Platelet transcriptome profiles provide potential therapeutic targets for elderly acute myelocytic leukemia patients

description: Additional file 5. GSEA enrichment analysis results.
DOI: 10.6084/m9.figshare.12937112
title: Associations of genetic polymorphisms within <i>MALAT1</i>, <i>UCA1</i>, <i>FAM211A-AS1</i> and <i>AC000111.6</i> with genetic susceptibility to rheumatoid arthritis

description: Recently, several long non-coding RNAs (lncRNAs) including MALAT1, UCA1, ENST00000483588, and ENST00000456270 have been implicated in the pathogenesis of rheumatoid arthritis (RA), and we hypothesized that polymorphisms within these lncRNA genes might be genetic modifiers for the development of RA. A total of 10 potentially functional single-nucleotide polymorphisms (SNPs) were selected and genotyped in 1198 participants, including 594 RA patients and 604 healthy controls. Significant associations of <i>FAM211A-AS1</i> rs2882581 (G vs. A, OR = 1.31, 95%CI 1.07–1.62, <i>p</i> = .01; G/G + A/G vs. A/A, OR = 1.40, 95%CI 1.08–1.83, <i>p</i> = .01), rs3744281 (T vs. A, OR = 1.25, 95%CI 1.02–1.54, <i>p</i> = .03; T/T vs. A/T + A/A, OR = 1.69, 95%CI 1.01–2.82, <i>p</i> = 4.59 × 10<sup>−2</sup>), and rs3760235 (A vs. G, OR = 1.32, 95%CI 1.04–1.68, <i>p</i> = .02; A/A vs. A/G + G/G, OR = 1.32, 95%CI 1.00–1.74, <i>p</i> = 4.89 × 10<sup>−2</sup>) with RF-positive RA were found. Functional annotation results indicated that these identified polymorphisms might regulate the expression of FAM211A-AS1 and nearby genes <i>via</i> impacting on transcription factor binding. Taken together, our results indicated that <i>FAM211A-AS1</i> rs2882581, rs3744281, and rs3760235 were involved in the genetic background of RF-positive RA.
DOI: 10.6084/m9.figshare.12937112.v1
title: Associations of genetic polymorphisms within <i>MALAT1</i>, <i>UCA1</i>, <i>FAM211A-AS1</i> and <i>AC000111.6</i> with genetic susceptibility to rheumatoid arthritis

description: Recently, several long non-coding RNAs (lncRNAs) including MALAT1, UCA1, ENST00000483588, and ENST00000456270 have been implicated in the pathogenesis of rheumatoid arthritis (RA), and we hypothesized that polymorphisms within these lncRNA genes might be genetic modifiers for the development of RA. A total of 10 potentially functional single-nucleotide polymorphisms (SNPs) were selected and genotyped in 1198 participants, including 594 RA patients and 604 healthy controls. Significant associations of <i>FAM211A-AS1</i> rs2882581 (G vs. A, OR = 1.31, 95%CI 1.07–1.62, <i>p</i> = .01; G/G + A/G vs. A/A, OR = 1.40, 95%CI 1.08–1.83, <i>p</i> = .01), rs3744281 (T vs. A, OR = 1.25, 95%CI 1.02–1.54, <i>p</i> = .03; T/T vs. A/T + A/A, OR = 1.69, 95%CI 1.01–2.82, <i>p</i> = 4.59 × 10<sup>−2</sup>), and rs3760235 (A vs. G, OR = 1.32, 95%CI 1.04–1.68, <i>p</i> = .02; A/A vs. A/G + G/G, OR = 1.32, 95%CI 1.00–1.74, <i>p</i> = 4.89 × 10<sup>−2</sup>) with RF-positive RA were found. Functional annotation results indicated that these identified polymorphisms might regulate the expression of FAM211A-AS1 and nearby genes <i>via</i> impacting on transcription factor binding. Taken together, our results indicated that <i>FAM211A-AS1</i> rs2882581, rs3744281, and rs3760235 were involved in the genetic background of RF-positive RA.
DOI: 10.6084/m9.figshare.11888535
title: Additional file 1 of MicroRNA expression profiling of peripheral blood mononuclear cells associated with syphilis

description: Additional file 1. Information on target genes of differential miRNAs.
DOI: 10.6084/m9.figshare.11888535.v1
title: Additional file 1 of MicroRNA expression profiling of peripheral blood mononuclear cells associated with syphilis

description: Additional file 1. Information on target genes of differential miRNAs.
DOI: 10.6084/m9.figshare.14509924
title: Additional file 1 of Shared genetic etiology and causality between body fat percentage and cardiovascular diseases: a large-scale genome-wide cross-trait analysis

description: Additional file 1: Table S1. Summary of GWAS data. Table S2. SNP based heritability estimated by LDSC. Table S3. Partitioned genetic correlation between BF% and 2 cardiac traits. Table S4. Novel loci in MTAG for single trait compared with GWAS. Table S5. GO biological process pathway analysis for BF% and HF. Table S6. GO biological process pathway analysis for BF% and CAD. Table S7. Reactome pathways analysis for BF% and HF. Table S8. Reactome pathways analysis for BF% and CAD. Table S9. List of credible set SNPs in each locus from fine mapping. For each of the 5 BF% and HF shared loci, the table lists all SNPs within 500 kb in the 99% credible sets that were calculated. Table S10. List of credible set SNPs in each locus from fine mapping. For each of the 16 BF% and CAD shared loci, the table lists all SNPs within 500 kb in the 99% credible sets that were calculated. Table S11. Genome-wide significant loci by cross-trait meta-analysis at sentinel SNPs associated with BF% and HF with directional effect (Pmeta &lt; 5×10-8; single trait P &lt; 0.05). Table S12. Genome-wide significant loci by cross-trait meta-analysis at sentinel SNPs associated with BF% and CAD with directional effect (Pmeta &lt; 5×10-8; single trait P &lt; 0.05). Table S13. Specific characteristics of genetic instruments of MR analysis of BF% levels upon CVD traits. Table S14. Specific characteristics of genetic instruments of MR analysis of CVDs upon BF% levels. Table S15. MR analysis between BF% and cardiac traits in a leave one out approach. Table S16. MR analysis between BF% and cardiac traits for a single snp. Table S17. Significant overlap transcriptome-wide association analysis results between BF% and CVDs. (FDR&lt;0.05). Table S18. Significant single-tissue eQTL from GTEx for 3 representative gene between BF% and HF. Table S19. Significant single-tissue eQTL from GTEx for 8 representative gene between BF% and CAD.
DOI: 10.6084/m9.figshare.14509924.v1
title: Additional file 1 of Shared genetic etiology and causality between body fat percentage and cardiovascular diseases: a large-scale genome-wide cross-trait analysis

description: Additional file 1: Table S1. Summary of GWAS data. Table S2. SNP based heritability estimated by LDSC. Table S3. Partitioned genetic correlation between BF% and 2 cardiac traits. Table S4. Novel loci in MTAG for single trait compared with GWAS. Table S5. GO biological process pathway analysis for BF% and HF. Table S6. GO biological process pathway analysis for BF% and CAD. Table S7. Reactome pathways analysis for BF% and HF. Table S8. Reactome pathways analysis for BF% and CAD. Table S9. List of credible set SNPs in each locus from fine mapping. For each of the 5 BF% and HF shared loci, the table lists all SNPs within 500 kb in the 99% credible sets that were calculated. Table S10. List of credible set SNPs in each locus from fine mapping. For each of the 16 BF% and CAD shared loci, the table lists all SNPs within 500 kb in the 99% credible sets that were calculated. Table S11. Genome-wide significant loci by cross-trait meta-analysis at sentinel SNPs associated with BF% and HF with directional effect (Pmeta &lt; 5×10-8; single trait P &lt; 0.05). Table S12. Genome-wide significant loci by cross-trait meta-analysis at sentinel SNPs associated with BF% and CAD with directional effect (Pmeta &lt; 5×10-8; single trait P &lt; 0.05). Table S13. Specific characteristics of genetic instruments of MR analysis of BF% levels upon CVD traits. Table S14. Specific characteristics of genetic instruments of MR analysis of CVDs upon BF% levels. Table S15. MR analysis between BF% and cardiac traits in a leave one out approach. Table S16. MR analysis between BF% and cardiac traits for a single snp. Table S17. Significant overlap transcriptome-wide association analysis results between BF% and CVDs. (FDR&lt;0.05). Table S18. Significant single-tissue eQTL from GTEx for 3 representative gene between BF% and HF. Table S19. Significant single-tissue eQTL from GTEx for 8 representative gene between BF% and CAD.
DOI: 10.6084/m9.figshare.7169960
title: Proteomics investigation of the changes in serum proteins after high- and low-flux hemodialysis

description: <b>Purpose:</b> This study aimed to use proteomics methods to investigate the changes in serum protein levels after high- and low-flux hemodialysis (HD). <b>Methods:</b> Before and after HD, serum samples were obtained from two selected patients who were treated with a Polyflux 140 H high-flux dialyzer and a Polyflux 14 L low-flux dialyzer during two continuous therapy sessions. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was performed to identify the proteins. <b>Results:</b> A total of 212 and 203 serum proteins were identified after high-flux and low-flux HD, respectively. After high-flux HD, 21 proteins increased, and 132 proteins decreased. After low-flux HD, 87 proteins increased, and 45 proteins decreased. High-flux HD led to a significantly greater reduction in protein levels than low-flux HD (0.73 ± 0.13 vs. 0.84 ± 0.18, <i>p</i> = .00). Among the increased and decreased proteins, the isoelectric point (pI) values mainly ranged from 5 to 7, and the molecular weights (Mws) were mostly smaller than 30 kDa. The serum proteins showed no difference in pI or Mw for high- and low-flux HD. Gene ontology (GO) analysis showed that the detected proteins were related to immune system processes and complement activation. <b>Conclusions:</b> Serum protein levels differentially changed after high- and low-flux HD. Long-term effects should be observed in future studies.
DOI: 10.6084/m9.figshare.7169960.v1
title: Proteomics investigation of the changes in serum proteins after high- and low-flux hemodialysis

description: <b>Purpose:</b> This study aimed to use proteomics methods to investigate the changes in serum protein levels after high- and low-flux hemodialysis (HD). <b>Methods:</b> Before and after HD, serum samples were obtained from two selected patients who were treated with a Polyflux 140 H high-flux dialyzer and a Polyflux 14 L low-flux dialyzer during two continuous therapy sessions. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was performed to identify the proteins. <b>Results:</b> A total of 212 and 203 serum proteins were identified after high-flux and low-flux HD, respectively. After high-flux HD, 21 proteins increased, and 132 proteins decreased. After low-flux HD, 87 proteins increased, and 45 proteins decreased. High-flux HD led to a significantly greater reduction in protein levels than low-flux HD (0.73 ± 0.13 vs. 0.84 ± 0.18, <i>p</i> = .00). Among the increased and decreased proteins, the isoelectric point (pI) values mainly ranged from 5 to 7, and the molecular weights (Mws) were mostly smaller than 30 kDa. The serum proteins showed no difference in pI or Mw for high- and low-flux HD. Gene ontology (GO) analysis showed that the detected proteins were related to immune system processes and complement activation. <b>Conclusions:</b> Serum protein levels differentially changed after high- and low-flux HD. Long-term effects should be observed in future studies.
DOI: 10.6084/m9.figshare.19752879
title: The polymorphisms in <i>cGAS-STING</i> pathway are associated with mitochondrial DNA copy number in coke oven workers

description: To evaluate the interaction effects of Polycyclic aromatic hydrocarbons (PAHs) exposure and variants in <i>cGAS-STING</i> genes on mitochondrial DNA copy number (mtDNAcn) in workers. The mtDNAcn was determined by real-time quantitative polymerase-chain reaction in 544 PAHs-exposed workers and 238 office workers. The polymorphisms were detected by flight mass spectrometry. The mtDNAcn in PAHs exposure group was significantly lower than non-occupational exposure population (<i>P</i> &lt; 0.00). The cGAS rs610913 CA+AA had significant interaction effects with STING rs11554776 GG+GA (<i>P</i> = 0.035), rs7380824 CC+CT (<i>P</i> = 0.026), and rs78233829 GC+CC (<i>P</i> = 0.034) on mtDNAcn. The generalized linear model results showed that the influencing factors of mtDNAcn include PAHs exposure (<i>P</i> &lt; 0.001) and the interaction of PAHs exposure and <i>cGAS rs</i> 311678 AA+AG (<i>P</i> = 0.047). The influencing factors of mtDNAcn include PAHs exposure and the interaction of PAHs exposure and <i>cGAS rs</i> 311678 AA+AG.
DOI: 10.6084/m9.figshare.19752879.v1
title: The polymorphisms in <i>cGAS-STING</i> pathway are associated with mitochondrial DNA copy number in coke oven workers

description: To evaluate the interaction effects of Polycyclic aromatic hydrocarbons (PAHs) exposure and variants in <i>cGAS-STING</i> genes on mitochondrial DNA copy number (mtDNAcn) in workers. The mtDNAcn was determined by real-time quantitative polymerase-chain reaction in 544 PAHs-exposed workers and 238 office workers. The polymorphisms were detected by flight mass spectrometry. The mtDNAcn in PAHs exposure group was significantly lower than non-occupational exposure population (<i>P</i> &lt; 0.00). The cGAS rs610913 CA+AA had significant interaction effects with STING rs11554776 GG+GA (<i>P</i> = 0.035), rs7380824 CC+CT (<i>P</i> = 0.026), and rs78233829 GC+CC (<i>P</i> = 0.034) on mtDNAcn. The generalized linear model results showed that the influencing factors of mtDNAcn include PAHs exposure (<i>P</i> &lt; 0.001) and the interaction of PAHs exposure and <i>cGAS rs</i> 311678 AA+AG (<i>P</i> = 0.047). The influencing factors of mtDNAcn include PAHs exposure and the interaction of PAHs exposure and <i>cGAS rs</i> 311678 AA+AG.
DOI: 10.6084/m9.figshare.16607127
title: Additional file 2 of Genome-wide association study and transcriptome analysis reveal key genes affecting root growth dynamics in rapeseed

description: Additional file 2: Table S1 Trait statistics collected at the five stages of each repetition. Table S2 Correlations in each captured trait among replication at five stages. Table S3 Summary of SNPs and LD decay on 19 chromosomes of B. napus. Table S4 Detailed information on trait-related significant SNPs identified by GWAS. Table S5 Detailed information on 48 valid QTL clusters. Table S6 Correlations among root-related traits at each examined stage. Table S7 RNA-Seq statistics of four growth types against B. napus reference genome. Table S8 FPKM of persistent DEGs. Table S9 GO enrichment results of persistent DEGs. Table S10 FPKM of stage-specific DEGs. Table S11 GO enrichment results of stage-specific expressed genes. Table S12 FPKM of genes located in haplotype blocks on 48 QTL clusters. Table S13 Information on peak SNPs overlapped with SNPs reported by Wang et al. (2017). Table S14 Primers used in this study.
DOI: 10.6084/m9.figshare.12937205
title: Effects of vitamin D supplementation on metabolic parameters of women with polycystic ovary syndrome: a meta-analysis of randomized controlled trials

description: The purpose of this meta-analysis was to evaluate the effects of vitamin D supplementation on metabolic parameters of women with polycystic ovary syndrome (PCOS). We performed a literature search of databases and identified randomized controlled trials (RCTs) published prior to December 2019. A meta-analysis was conducted using RevMan 5.3 and Stata 12.0 software. We compared the effects of vitamin D supplementation alone to the administration of placebos on metabolic parameters of PCOS women with vitamin D deficiency. Ten articles of RCTs were included and analyzed in this meta-analysis, which included a total of 520 PCOS women. Our meta-analysis results showed no significant effects of vitamin D supplementation on BMI (<i>p</i> = .43), systolic blood pressure (<i>p</i> = .05), diastolic blood pressure (<i>p</i> = .87), fasting insulin concentration (<i>p</i> = .86), HOMA-IR (<i>p</i> = .47), HDL-C (<i>p</i> = .76), LDL-C (<i>p</i> = .23) and triglyceride (<i>p</i> = .77). Both low dose vitamin D supplementation (&lt;4000 IU/day) and high dose vitamin D supplementation (≥4000 IU/day) were found to significantly decreased the fasting glucose concentration (<i>p</i> = .01, <i>p</i> = .001, respectively). Vitamin D supplementation significantly decreased total cholesterol concentration (<i>p</i> = .03). The results of this meta-analysis suggested that vitamin D supplementation decreases fasting glucose concentration and total cholesterol concentration in PCOS women with vitamin D deficiency.