cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12674189.v1
title: Bracon brevicornis genome assembly

description: Presented here is the <i>Bracon brevicornis</i> genome assembly (fasta file). Also available via the ENA (BioProject PRJEB35412), presented here as an additional file resource. Briefly, this is a 10X Genomics linked-read assembly, where <i>B. brevicornis</i> females of a fairly inbred lab strain were used in the DNA extraction. This DNA isolation was used in concert with DNA from a known specimen of an unrelated (plant) species where the other DNA was carrier DNA to ensure that the 10X Genomics reaction succeeded. More is explained in the forthcoming preprint (NB: to be added after it is preprinted).<br>
DOI: 10.6084/m9.figshare.12674045
title: JVASP-68900 to JVASP-69751

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12674063.v1
title: Supplementary Material for: Remote Ischemic Preconditioning Reduces the Risk of Contrast-Induced Nephropathy in Patients with Moderate Renal Impairment Undergoing Percutaneous Coronary Angiography: A Meta-Analysis

description: <b><i>Background/Aims:</i></b> This meta-analysis evaluated the effects of remote ischemic preconditioning (RIPC) on the risk of contrast-induced nephropathy (CIN) in patients undergoing percutaneous coronary intervention/coronary angiography (PCI/CA). <b><i>Methods:</i></b> PubMed, Embase, and the Cochrane Central Register of Controlled Trials databases were searched for randomized controlled trials (RCTs) that assessed the effect of RIPC on CIN in patients undergoing PCI/CA. The main outcomes of interest were the incidence of CIN 48–72 h after CA, the levels of serum creatinine, cystatin C, neutrophil gelatinase-associated lipocalin, and estimated glomerular filtration rate (eGFR), mortality, and requirement of hemodialysis and rehospitalization. The analysis was conducted using the random-effect model due to the expected heterogeneity among different studies. <b><i>Results:</i></b> In total, 16 trials covering 2,048 patients were identified. By assessing the methodological quality of the included studies through the Coch­rane risk of bias, we found that of the 16 RCTs, 3 had a low risk of bias, 6 a high, and 7 an unclear risk. The application of RIPC decreased the incidence of CIN (relative risk, RR, 0.50, 95% confidence interval, CI, 0.39–0.65; <i>p</i> &lt; 0.001). Subgroup analyses showed that RIPC decreased the incidence of CIN in patients with eGFR &lt;60 mL/min/1.73 m<sup>2</sup> (RR 0.53, 95% CI 0.38–0.75; <i>p</i> &lt; 0.001) but not in patients with eGRF ≥60 mL/min/1.73 m<sup>2</sup> (RR 0.82, 95% CI 0.35–1.94; <i>p</i> = 0.66) at baseline. Furthermore, the increase in serum creatinine was significantly lower in patients with RIPC compared to control patients (standardized mean difference –1.41, 95% CI –2.46 to –0.35; <i>p</i> = 0.009). <b><i>Conclusions:</i></b> Based on 16 RCTs, this meta-analysis shows that RIPC can reduce the risk of CIN in patients with moderate renal impairment undergoing PCI/CA. However, this needs to be confirmed by further high-quality evidence.
DOI: 10.6084/m9.figshare.12674042
title: JVASP-67902 to JVASP-68896

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12674045.v1
title: JVASP-68900 to JVASP-69751

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12674039
title: JVASP-66938 to JVASP-67901

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12674042.v1
title: JVASP-67902 to JVASP-68896

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12674036
title: JVASP-66154 to JVASP-66937

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12674036.v1
title: JVASP-66154 to JVASP-66937

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12674039.v1
title: JVASP-66938 to JVASP-67901

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12674024
title: Lancet_DTB.sav

description: Lancet Dataset
DOI: 10.6084/m9.figshare.12673988
title: JVASP-65230 to JVASP-66152

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12673982
title: JVASP-63112 to JVASP-64401

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12673985
title: JVASP-64402 to JVASP-65229

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12673988.v1
title: JVASP-65230 to JVASP-66152

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12673982.v1
title: JVASP-63112 to JVASP-64401

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12673830
title: Additional file 7 of Candidate methylation sites associated with endocrine therapy resistance in ER+/HER2- breast cancer

description: Additional file 7. Multi-locus survival analysis. Results of multi-locus survival analysis on ER+/HER2-, TAM and AI cohorts. For each CpG the results of the correlation analysis and of the differential methylation analysis of month 7 versus WT in the T47D RA experiment are also included.
DOI: 10.6084/m9.figshare.12673833
title: Additional file 8 of Candidate methylation sites associated with endocrine therapy resistance in ER+/HER2- breast cancer

description: Additional file 8. Survival analysis using risk score. Results of survival analysis of the multi-locus signature using the risk score corrected for selected clinical variables in ER+/HER2-, TAM and AI cohorts.
DOI: 10.6084/m9.figshare.12673833.v1
title: Additional file 8 of Candidate methylation sites associated with endocrine therapy resistance in ER+/HER2- breast cancer

description: Additional file 8. Survival analysis using risk score. Results of survival analysis of the multi-locus signature using the risk score corrected for selected clinical variables in ER+/HER2-, TAM and AI cohorts.
DOI: 10.6084/m9.figshare.12673830.v1
title: Additional file 7 of Candidate methylation sites associated with endocrine therapy resistance in ER+/HER2- breast cancer

description: Additional file 7. Multi-locus survival analysis. Results of multi-locus survival analysis on ER+/HER2-, TAM and AI cohorts. For each CpG the results of the correlation analysis and of the differential methylation analysis of month 7 versus WT in the T47D RA experiment are also included.
DOI: 10.6084/m9.figshare.12673818
title: Additional file 3 of Candidate methylation sites associated with endocrine therapy resistance in ER+/HER2- breast cancer

description: Additional file 3. Sample annotation. Sample annotation for the 552 patients in the ER+/HER2- cohort. The first sheet provides a short definition of the variables included in the second sheet.
DOI: 10.6084/m9.figshare.12673821
title: Additional file 4 of Candidate methylation sites associated with endocrine therapy resistance in ER+/HER2- breast cancer

description: Additional file 4. Single-locus survival analysis. Results of single-locus survival analysis on ER+/HER2-, TAM and AI cohorts. For each CpG the results of the correlation analysis and of the differential methylation analysis of month 7 versus WT in the T47D RA experiment are also included.
DOI: 10.6084/m9.figshare.12673812
title: Additional file 1 of Candidate methylation sites associated with endocrine therapy resistance in ER+/HER2- breast cancer

description: Additional file 1. Mapping to generic drug names. Overview of synonyms and spelling variants for drug names used in TCGA BRCA and their mapping to a generic drug name used in our study.
DOI: 10.6084/m9.figshare.12673815
title: Additional file 2 of Candidate methylation sites associated with endocrine therapy resistance in ER+/HER2- breast cancer

description: Additional file 2. Molecular subtypes. Overview of the molecular subtype frequency as determined by immunohistochemistry of ER and HER2 and as predicted by the SCMOD2 model (R package genefu) using TGCA BRCA primary tumour gene expression data. Subtypes are listed for the 1095 patients for whom gene expression data is available (Fig. 1).
DOI: 10.6084/m9.figshare.12673818.v1
title: Additional file 3 of Candidate methylation sites associated with endocrine therapy resistance in ER+/HER2- breast cancer

description: Additional file 3. Sample annotation. Sample annotation for the 552 patients in the ER+/HER2- cohort. The first sheet provides a short definition of the variables included in the second sheet.
DOI: 10.6084/m9.figshare.12673821.v1
title: Additional file 4 of Candidate methylation sites associated with endocrine therapy resistance in ER+/HER2- breast cancer

description: Additional file 4. Single-locus survival analysis. Results of single-locus survival analysis on ER+/HER2-, TAM and AI cohorts. For each CpG the results of the correlation analysis and of the differential methylation analysis of month 7 versus WT in the T47D RA experiment are also included.
DOI: 10.6084/m9.figshare.12673812.v1
title: Additional file 1 of Candidate methylation sites associated with endocrine therapy resistance in ER+/HER2- breast cancer

description: Additional file 1. Mapping to generic drug names. Overview of synonyms and spelling variants for drug names used in TCGA BRCA and their mapping to a generic drug name used in our study.
DOI: 10.6084/m9.figshare.12673803
title: Additional file 13 of Candidate methylation sites associated with endocrine therapy resistance in ER+/HER2- breast cancer

description: Additional file 13. Survival analyses including luminal status. Reanalysis when also including luminal status in the (i) multivariable survival analysis, (ii) single-locus survival analysis, and (iii) risk score for the multi-locus signature.
DOI: 10.6084/m9.figshare.12673806
title: Additional file 14 of Candidate methylation sites associated with endocrine therapy resistance in ER+/HER2- breast cancer

description: Additional file 14. CpGs with concordant significant changes in the survival and resistance acquisition signatures and with significant correlation between paired DNA methylation and gene expression profiles. CpGs in single-locus (Additional File 4) and multi-locus (Additional File 7) survival signatures were selected according to three additional criteria: (i) CpG DNA methylation is significantly (adjusted p-value
DOI: 10.6084/m9.figshare.12673815.v1
title: Additional file 2 of Candidate methylation sites associated with endocrine therapy resistance in ER+/HER2- breast cancer

description: Additional file 2. Molecular subtypes. Overview of the molecular subtype frequency as determined by immunohistochemistry of ER and HER2 and as predicted by the SCMOD2 model (R package genefu) using TGCA BRCA primary tumour gene expression data. Subtypes are listed for the 1095 patients for whom gene expression data is available (Fig. 1).
DOI: 10.6084/m9.figshare.12673803.v1
title: Additional file 13 of Candidate methylation sites associated with endocrine therapy resistance in ER+/HER2- breast cancer

description: Additional file 13. Survival analyses including luminal status. Reanalysis when also including luminal status in the (i) multivariable survival analysis, (ii) single-locus survival analysis, and (iii) risk score for the multi-locus signature.
DOI: 10.6084/m9.figshare.12673806.v1
title: Additional file 14 of Candidate methylation sites associated with endocrine therapy resistance in ER+/HER2- breast cancer

description: Additional file 14. CpGs with concordant significant changes in the survival and resistance acquisition signatures and with significant correlation between paired DNA methylation and gene expression profiles. CpGs in single-locus (Additional File 4) and multi-locus (Additional File 7) survival signatures were selected according to three additional criteria: (i) CpG DNA methylation is significantly (adjusted p-value
DOI: 10.6084/m9.figshare.12673794
title: Additional file 10 of Candidate methylation sites associated with endocrine therapy resistance in ER+/HER2- breast cancer

description: Additional file 10. Stability of multi-locus signatures. Results of Fisher’s exact test to determine the significance of the overlap between the original multi-locus signature and the stability signature.
DOI: 10.6084/m9.figshare.12673794.v1
title: Additional file 10 of Candidate methylation sites associated with endocrine therapy resistance in ER+/HER2- breast cancer

description: Additional file 10. Stability of multi-locus signatures. Results of Fisher’s exact test to determine the significance of the overlap between the original multi-locus signature and the stability signature.
DOI: 10.6084/m9.figshare.12673724
title: New martian dust simulant JMDS-1 and applied it to the laboratory thermal conductivity measurements

description: JMDS-1 data
DOI: 10.6084/m9.figshare.12673766
title: Tree demography @ Eden Burning Exp (Watson et al. FEM)

description: The data contained in this repository are measures of eucalypt mortality, growth rate and ingrowth over approximately 3 decades at the Eden Burning Study Experiment (EBSA) in south-eastern New South Wales, Australia. The data was used in a paper published in Forest Ecology and Management (add publication details when available). <br>Details of the study design and historic data collection at the EBSA can be found here: https://www.dpi.nsw.gov.au/content/research/areas/resources-research/forest-resources/pubs/Ecological-Impacts-and-Sustainability-of-Timber-Harvesting-and-Burning-in-Coastal-Forests-on-the-Eden-Area-Establishment-and-Progress-of-the-Eden-Burning-Study.pdf
DOI: 10.6084/m9.figshare.12673712
title: Gene database of Neurospora crassa OR74A

description: <i>Neurospora crassa</i> is a fungus belonging to the phylum Ascomycota. Commonly known as the red bread mold, its haploid genome architecture affords its ready use in the deciphering of recessive traits arising from genetic mutations. Genome sequencing efforts have elucidated the genetic complement of all 7 chromosomes of this species, and its repertoire of about 10000 genes is a rich resource for understanding varied mechanisms that pertains to epigenetics, cell polarity, cell fusion and gene silencing. This resource hopes to provide the genetic repertoire of <i>N. crassa</i> OR74A whose annotated genome sequence was downloaded from Genbank. Parsed using an in-house MATLAB software, the resulting gene database contains gene name, gene function and gene sequence of all genes in the genome of <i>N. crassa</i> OR74A. which could inform varied aspects of biotechnology and fundamental biology research.
DOI: 10.6084/m9.figshare.12673709
title: soil 16S ASV otu.xlsx

description: soil bacterial ASVs
DOI: 10.6084/m9.figshare.12673709.v1
title: soil 16S ASV otu.xlsx

description: soil bacterial ASVs
DOI: 10.6084/m9.figshare.12673766.v2
title: Tree demography @ Eden Burning Exp (Watson et al. FEM)

description: The data contained in this repository are measures of eucalypt mortality, growth rate and ingrowth over approximately 3 decades at the Eden Burning Experiment in south-eastern New South Wales, Australia. The data was used in a paper published in Forest Ecology and Management (add publication details when available)
DOI: 10.6084/m9.figshare.12673766.v1
title: Tree demography @ Eden Burning Exp (Watson et al. FEM)

description: The data contained in this repository are measures of eucalypt mortality, growth rate and ingrowth over approximately 3 decades at the Eden Burning Experiment in south-eastern New South Wales, Australia. The data was used in a paper published in Forest Ecology and Management (add publication details when available)
DOI: 10.6084/m9.figshare.12673616
title: JVASP-59627 to JVASP-63111

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12673613
title: JVASP-57834 to JVASP-59625

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12673610
title: JVASP-56857 to JVASP-57833

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12673613.v1
title: JVASP-57834 to JVASP-59625

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12673580
title: Fossil pollen record in North America in 20-0 ka

description: This is the dataset of fossil pollen record in North America after 20 ka. The related plant biome information is constructed by the modern analog technique (Williams and Shuman 2008) and biomization method (Williams et al. 2001). The related age information is by Bacon age model (Wang et al. 2019). The fossil pollen records are collected from Neotoma (Williams et al. 2018).
DOI: 10.6084/m9.figshare.12673610.v1
title: JVASP-56857 to JVASP-57833

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12673580.v1
title: Fossil pollen record in North America in 20-0 ka

description: This is the dataset of fossil pollen record in North America after 20 ka. The related plant biome information is constructed by the modern analog technique (Williams and Shuman 2008) and biomization method (Williams et al. 2001). The related age information is by Bacon age model (Wang et al. 2019). The fossil pollen records are collected from Neotoma (Williams et al. 2018).
DOI: 10.6084/m9.figshare.12673553
title: JVASP-50915 to JVASP-51768

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12673550
title: JVASP-51779 to JVASP-53413

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12673553.v1
title: JVASP-50915 to JVASP-51768

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12673547
title: JVASP-53414 to JVASP-55274

description: JARVIS-DFT
DOI: 10.5519/qd.dya5rbxw
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.6084/m9.figshare.12673547.v1
title: JVASP-53414 to JVASP-55274

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12673550.v1
title: JVASP-51779 to JVASP-53413

description: JARVIS-DFT
DOI: 10.25375/uct.12673358
title: Embedding Aspen Custom Modeller for bioethanol fermentation in Aspen Plus flowsheet simulator

description: Aspen Custom Modeller file for integration into Aspen Plus for bioethanol production.
DOI: 10.6084/m9.figshare.12673361
title: JVASP-55275 to JVASP-56856

description: JARVIS-DFT
DOI: 10.25375/uct.12673358.v1
title: Embedding Aspen Custom Modeller for bioethanol fermentation in Aspen Plus flowsheet simulator

description: Aspen Custom Modeller file for integration into Aspen Plus for bioethanol production.
DOI: 10.6084/m9.figshare.12673361.v1
title: JVASP-55275 to JVASP-56856

description: JARVIS-DFT
DOI: 10.6084/m9.figshare.12673250
title: VCF files of industrial yeasts

description: Results of GATK genome analysis, used for allele frequency plots.<br>Newly generated FASTQ sequencing files along with those obtained from SRA were trimmed and filtered using fastp (Chen et al., 2018), and mapped to the S288C reference genome (R64.2.1.) downloaded from the SGD database (yeastgenome.org) and the reference genomes of the other Saccharomyces species (Scannell et al., 2011), using bwa 0.7.17. (Li and Durbin, 2009). Sorted BAM files were obtained using samtools 1.7. (Li et al., 2009) and Picard-tools 1.124. (http://picard.sourceforge.net) was used to mark duplicated reads. Local realignment around indels and joint variant calling and filtering for the six samples were performed with GATK 4.1.6.0 (Auwera et al., 2013; Poplin et al., 2018) with regions annotated in the SGD database as simple repeats, centromeric regions, telomeric regions, or LTRs excluded. First, genomic VCF files were obtained, joint calling was applied, and in the resulting VCF files, only SNPs were selected. SNPs were filtered according to the parameters used by (Fay et al., 2019): QD &lt; 5.0; QUAL &lt; 30.0; SOR &gt; 3.0; FS &gt; 60.0; MQ &lt; 40.0; MQRankSum &lt; -12.5; ReadPosRankSum &lt; -8.0; --set-filtered-genotype-to-no-call true.<br>
DOI: 10.6084/m9.figshare.12673256
title: Clonal heterogeneity test

description: Heterogeneity in colony morphologies (colony phenotype switch) and frequency of petite mitochondrial mutants in packed products were assessed by plating samples directly after the first pre-culturing (as described above) onto YPD agar plates (for colony morphologies) and onto GlyYP (glycerol yeast extract peptone) + 0.1% glucose agar plates with cell densities of approx. 200/plate (after cell counting in a haemocytometer). Plates were incubated for 10 days at 30°C (with agar surface facing down) and were visually scored for various phenotypes on YPD (rough, wrinkled, sectored, stalk-like, and very small colonies) and for potential petite mutants on GlyYP. Presumed petites were transferred to YPD and after overnight culturing, were inoculated onto GlyYP plates without glucose. Subclones unable to grow on glucose-free GlyYP were scored as petites. Finally, YPD colonies were washed under tap water to determine the frequency of invasivitiy into agar. At least 1,000 subclone colonies were counted for each strain and for each assay.<br><br>Clonal heterogeneity ins tress tolerance was assessed by using the same stress conditions as in the spot plate assays, supplemented with assays on SD and YPD media. Freshly grown cells (as described for spot plates) were counted in a haemocytometer and spread to land about 200 cells/plate. Plates were incubated at 30°C for 2 days (YPD and SD media), or for 2, 3, 4, and 6 days (stress media) as colonies reached sizes that were visible but not yet close to each other. For each condition, three replicate plates were used for each sample. Photographs were taken 4 and 6 days after inoculation with a DSLR camera. Data on colony area was gathered by using the Fiji software package CountPHICS (Brzozowska et al., 2019) with circularity set to 0.8. Pixel to mm ratios were measured and area calculations were randomly verified by manual measurment in ImageJ for altogether ten colonies (Rueden et al., 2017). Plate photographs and all colony area values were uploaded to FigShare.
DOI: 10.6084/m9.figshare.12673253
title: Spot plate assay

description: Tolerance to various stress factors with a focus on industrially relevant stresses (Gibson et al., 2007; Qiu et al., 2019) and growth on rich and minimal media were assessed using the spot-plate method for all strains and all subclones of the strains. The following stress media based on SD (synthetic defined, 2% glucose, 0.67% yeast nitrogen base without amino acids) were used: ethanol and high sugar osmotic stress (Bioethanol, Ale, Lager, Wine yeasts), NaCl and high sugar osmotic stress (ADY_Baker), and salt and oxidative stress (H2O2) media for the Probiotic yeast. In preliminary experiments, we determined the optimal concentrations of stressors that may enable differentiating between subclone lineages (Table S1.). Samples grown overnight (30°C) on YPD plates were washed in ddH2O, prepared in equal cell concentrations after cell counting with a haemocytometer, and spotted in 10 µl drops in a series of approx. 50,000; 5,000; 500; 50; and 5 cells to the various plates. The samples originating from the initial isolations were briefly stored at 4°C, single-cell bottlenecks were avoided as described above. Plates were incubated at 30°C for 2 days before photographing them using a DSLR camera. Growth was evaluated visually.
DOI: 10.6084/m9.figshare.12673253.v1
title: Spot plate assay

description: Tolerance to various stress factors with a focus on industrially relevant stresses (Gibson et al., 2007; Qiu et al., 2019) and growth on rich and minimal media were assessed using the spot-plate method for all strains and all subclones of the strains. The following stress media based on SD (synthetic defined, 2% glucose, 0.67% yeast nitrogen base without amino acids) were used: ethanol and high sugar osmotic stress (Bioethanol, Ale, Lager, Wine yeasts), NaCl and high sugar osmotic stress (ADY_Baker), and salt and oxidative stress (H2O2) media for the Probiotic yeast. In preliminary experiments, we determined the optimal concentrations of stressors that may enable differentiating between subclone lineages (Table S1.). Samples grown overnight (30°C) on YPD plates were washed in ddH2O, prepared in equal cell concentrations after cell counting with a haemocytometer, and spotted in 10 µl drops in a series of approx. 50,000; 5,000; 500; 50; and 5 cells to the various plates. The samples originating from the initial isolations were briefly stored at 4°C, single-cell bottlenecks were avoided as described above. Plates were incubated at 30°C for 2 days before photographing them using a DSLR camera. Growth was evaluated visually.