cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.11870709
title: Additional file 2 of Assessment of Plasmodium falciparum drug resistance molecular markers from the Blue Nile State, Southeast Sudan

description: Additional file 2. Sequencing data of Pfcrt, Pfmdr1, Pfdhfr, Pfdhps, Pfk13, exonuclease molecular markers of resistance.
DOI: 10.6084/m9.figshare.11870700
title: Additional file 1 of Assessment of Plasmodium falciparum drug resistance molecular markers from the Blue Nile State, Southeast Sudan

description: Additional file 1. European Nucleotide Archive (ENA) accesion numbers of P. falciparum DNA samples successfully sequenced.
DOI: 10.6084/m9.figshare.11870709.v1
title: Additional file 2 of Assessment of Plasmodium falciparum drug resistance molecular markers from the Blue Nile State, Southeast Sudan

description: Additional file 2. Sequencing data of Pfcrt, Pfmdr1, Pfdhfr, Pfdhps, Pfk13, exonuclease molecular markers of resistance.
DOI: 10.6084/m9.figshare.11870700.v1
title: Additional file 1 of Assessment of Plasmodium falciparum drug resistance molecular markers from the Blue Nile State, Southeast Sudan

description: Additional file 1. European Nucleotide Archive (ENA) accesion numbers of P. falciparum DNA samples successfully sequenced.
DOI: 10.6084/m9.figshare.11870634
title: Additional file 3 of Dynamics of toxigenic Clostridium perfringens colonisation in a cohort of prematurely born neonatal infants

description: Additional file 3. Organisms grown in breast milk screening
DOI: 10.6084/m9.figshare.11870631
title: Additional file 1 of Compliance of private pharmacies in Uganda with controlled prescription drugs regulations: a mixed-methods study

description: Additional file 1. Compliance survey dataset Microsoft Excel data set of the questionnaire survey redacted for potential participant identifiers to maximize confidentiality. The following data was deleted completely: type of pharmacy; nationality of dispenser; home region of dispenser; religious background; marital status.
DOI: 10.6084/m9.figshare.11870634.v1
title: Additional file 3 of Dynamics of toxigenic Clostridium perfringens colonisation in a cohort of prematurely born neonatal infants

description: Additional file 3. Organisms grown in breast milk screening
DOI: 10.6084/m9.figshare.11870631.v1
title: Additional file 1 of Compliance of private pharmacies in Uganda with controlled prescription drugs regulations: a mixed-methods study

description: Additional file 1. Compliance survey dataset Microsoft Excel data set of the questionnaire survey redacted for potential participant identifiers to maximize confidentiality. The following data was deleted completely: type of pharmacy; nationality of dispenser; home region of dispenser; religious background; marital status.
DOI: 10.6084/m9.figshare.11870619
title: Additional file 3 of Dietary inclusion of Peptiva, a peptide-based feed additive, can accelerate the maturation of the fecal bacterial microbiome in weaned pigs

description: Additional file 3: Supplementary File 3.P values associated with Table 3 and Table 5. Tables showing the P values obtained from the non-parametric Friedman test and the post hoc Nemenyi test for multiple pairwise comparisons that are presented in Table 3 and Table 5.
DOI: 10.6084/m9.figshare.11870613
title: Additional file 2 of Dietary inclusion of Peptiva, a peptide-based feed additive, can accelerate the maturation of the fecal bacterial microbiome in weaned pigs

description: Additional file 2: Supplementary File 2.. Operational Taxonomic Unit (OTU) table. Relative abundance for each OTU identified in fecal samples collected from nursery pigs fed a control (CON) or Peptiva-supplemented diet (PEP) at two different stages.
DOI: 10.6084/m9.figshare.11870613.v1
title: Additional file 2 of Dietary inclusion of Peptiva, a peptide-based feed additive, can accelerate the maturation of the fecal bacterial microbiome in weaned pigs

description: Additional file 2: Supplementary File 2.. Operational Taxonomic Unit (OTU) table. Relative abundance for each OTU identified in fecal samples collected from nursery pigs fed a control (CON) or Peptiva-supplemented diet (PEP) at two different stages.
DOI: 10.6084/m9.figshare.11870619.v1
title: Additional file 3 of Dietary inclusion of Peptiva, a peptide-based feed additive, can accelerate the maturation of the fecal bacterial microbiome in weaned pigs

description: Additional file 3: Supplementary File 3.P values associated with Table 3 and Table 5. Tables showing the P values obtained from the non-parametric Friedman test and the post hoc Nemenyi test for multiple pairwise comparisons that are presented in Table 3 and Table 5.
DOI: 10.6084/m9.figshare.11870598
title: Additional file 4 of Evaluation of RNA purification methods by using different blood stabilization tubes: identification of key features for epidemiological studies

description: Additional file 4. Representation of the average Cq value for the RNA obtained by the three methodologies. mRNA genes (18S rRNA, ACTB, and GAPDH) and miRNA (mir-26, mir-30, and mir-16) were tested. Error bars are indicated.
DOI: 10.6084/m9.figshare.11870598.v1
title: Additional file 4 of Evaluation of RNA purification methods by using different blood stabilization tubes: identification of key features for epidemiological studies

description: Additional file 4. Representation of the average Cq value for the RNA obtained by the three methodologies. mRNA genes (18S rRNA, ACTB, and GAPDH) and miRNA (mir-26, mir-30, and mir-16) were tested. Error bars are indicated.
DOI: 10.6084/m9.figshare.11870589
title: Additional file 3 of Evaluation of RNA purification methods by using different blood stabilization tubes: identification of key features for epidemiological studies

description: Additional file 3. Diagram of an RNA electropherogram for six samples purified with Methodology A. Images a–f correspond to the RNA purified by Methodology A, following the manufacturer’s instructions. The images a’–f’ correspond to the same RNA samples after additional treatment with DNase. a and a’: Donor 16 Sample 1, b and b’: Donor 16 Sample 2, c and c’: Donor 17 sample 1, d and d’: Donor 23 Sample 1, e and e’: Donor 23 Sample 2, f and f’: Donor 23 Sample 3. The anomalous peaks of the electropherograms are shaded in the picture.
DOI: 10.6084/m9.figshare.11870583
title: Additional file 2 of Evaluation of RNA purification methods by using different blood stabilization tubes: identification of key features for epidemiological studies

description: Additional file 2: Table A. Summary of the technical characteristics, technical requirements and cost analysis for the three methodologies tested. Table B. Average and standard deviation obtained for RNA yield, A260/A280, A260/A230 and RIN obtained by both technicians with the three methodologies. The average values encompassing the values obtained by both technicians are also indicated. Table C. Robustness of each methodology analysis. Average percentage and standard deviation for variation between methodologies and technicians for variables yield, A260/A280, A260/A230 and RIN.
DOI: 10.6084/m9.figshare.11870583.v1
title: Additional file 2 of Evaluation of RNA purification methods by using different blood stabilization tubes: identification of key features for epidemiological studies

description: Additional file 2: Table A. Summary of the technical characteristics, technical requirements and cost analysis for the three methodologies tested. Table B. Average and standard deviation obtained for RNA yield, A260/A280, A260/A230 and RIN obtained by both technicians with the three methodologies. The average values encompassing the values obtained by both technicians are also indicated. Table C. Robustness of each methodology analysis. Average percentage and standard deviation for variation between methodologies and technicians for variables yield, A260/A280, A260/A230 and RIN.
DOI: 10.6084/m9.figshare.11870589.v1
title: Additional file 3 of Evaluation of RNA purification methods by using different blood stabilization tubes: identification of key features for epidemiological studies

description: Additional file 3. Diagram of an RNA electropherogram for six samples purified with Methodology A. Images a–f correspond to the RNA purified by Methodology A, following the manufacturer’s instructions. The images a’–f’ correspond to the same RNA samples after additional treatment with DNase. a and a’: Donor 16 Sample 1, b and b’: Donor 16 Sample 2, c and c’: Donor 17 sample 1, d and d’: Donor 23 Sample 1, e and e’: Donor 23 Sample 2, f and f’: Donor 23 Sample 3. The anomalous peaks of the electropherograms are shaded in the picture.
DOI: 10.6084/m9.figshare.11870577
title: Additional file 1 of Evaluation of RNA purification methods by using different blood stabilization tubes: identification of key features for epidemiological studies

description: Additional file 1. (i) Reversotranscription, (ii) mRNA and miRNA real time PCR conditions, (iii) and oligo sequences details.
DOI: 10.6084/m9.figshare.11870577.v1
title: Additional file 1 of Evaluation of RNA purification methods by using different blood stabilization tubes: identification of key features for epidemiological studies

description: Additional file 1. (i) Reversotranscription, (ii) mRNA and miRNA real time PCR conditions, (iii) and oligo sequences details.
DOI: 10.6084/m9.figshare.11870475
title: Additional file 8 of Comprehensive pharmacogenomic characterization of gastric cancer

description: Additional file 8: Table S7. Pharmacogenomic interactions using integrative analysis of drug sensitivity results (AUC) and genomic alterations. The statistical significance was calculated using Wilcoxon rank-sum test.
DOI: 10.6084/m9.figshare.11870463
title: Additional file 7 of Comprehensive pharmacogenomic characterization of gastric cancer

description: Additional file 7: Table S6. Tumor type-specific drug associations. Wilcoxon rank-sum test was applied to determine the relative difference of drug sensitivity between individual tumor type and the rest.
DOI: 10.6084/m9.figshare.11870475.v1
title: Additional file 8 of Comprehensive pharmacogenomic characterization of gastric cancer

description: Additional file 8: Table S7. Pharmacogenomic interactions using integrative analysis of drug sensitivity results (AUC) and genomic alterations. The statistical significance was calculated using Wilcoxon rank-sum test.
DOI: 10.6084/m9.figshare.11870463.v1
title: Additional file 7 of Comprehensive pharmacogenomic characterization of gastric cancer

description: Additional file 7: Table S6. Tumor type-specific drug associations. Wilcoxon rank-sum test was applied to determine the relative difference of drug sensitivity between individual tumor type and the rest.
DOI: 10.6084/m9.figshare.11870451
title: Additional file 6 of Comprehensive pharmacogenomic characterization of gastric cancer

description: Additional file 6: Table S5. Area Under the Curve (AUC) values for 60 drugs in 129 PDCs.
DOI: 10.6084/m9.figshare.11870451.v1
title: Additional file 6 of Comprehensive pharmacogenomic characterization of gastric cancer

description: Additional file 6: Table S5. Area Under the Curve (AUC) values for 60 drugs in 129 PDCs.
DOI: 10.6084/m9.figshare.11870436
title: Additional file 4 of Comprehensive pharmacogenomic characterization of gastric cancer

description: Additional file 4: Table S4. Mutational landscape of gastric cancer.
DOI: 10.6084/m9.figshare.11870436.v1
title: Additional file 4 of Comprehensive pharmacogenomic characterization of gastric cancer

description: Additional file 4: Table S4. Mutational landscape of gastric cancer.
DOI: 10.6084/m9.figshare.11870427
title: Additional file 3 of Comprehensive pharmacogenomic characterization of gastric cancer

description: Additional file 3: Table S3. List of major cancer-driver genes and sequencing library information for CancerSCAN.
DOI: 10.6084/m9.figshare.11870427.v1
title: Additional file 3 of Comprehensive pharmacogenomic characterization of gastric cancer

description: Additional file 3: Table S3. List of major cancer-driver genes and sequencing library information for CancerSCAN.
DOI: 10.6084/m9.figshare.11870415
title: Additional file 2 of Comprehensive pharmacogenomic characterization of gastric cancer

description: Additional file 2: Table S2. Clinical annotations of 131 gastric cancers used in the drug screening and/or genomic characterization.
DOI: 10.6084/m9.figshare.11870415.v1
title: Additional file 2 of Comprehensive pharmacogenomic characterization of gastric cancer

description: Additional file 2: Table S2. Clinical annotations of 131 gastric cancers used in the drug screening and/or genomic characterization.
DOI: 10.6084/m9.figshare.11870409
title: Additional file 1 of Comprehensive pharmacogenomic characterization of gastric cancer

description: Additional file 1: Table S1. List of 60 drugs that were used in the drug sensitivity analysis. Drugs have been annotated based on their chemical and/or generic name, target molecule and clinical phase.
DOI: 10.6084/m9.figshare.11870409.v1
title: Additional file 1 of Comprehensive pharmacogenomic characterization of gastric cancer

description: Additional file 1: Table S1. List of 60 drugs that were used in the drug sensitivity analysis. Drugs have been annotated based on their chemical and/or generic name, target molecule and clinical phase.
DOI: 10.6084/m9.figshare.11870364
title: Additional file 4 of Developing an experimental necrotic enteritis model in turkeys - the impact of Clostridium perfringens, Eimeria meleagrimitis and host age on frequency of severe intestinal lesions

description: Additional file 4. Data supporting conclusions on the ability to differentiate statistically between levels of study variables when using three different outcome variables.
DOI: 10.6084/m9.figshare.11870364.v1
title: Additional file 4 of Developing an experimental necrotic enteritis model in turkeys - the impact of Clostridium perfringens, Eimeria meleagrimitis and host age on frequency of severe intestinal lesions

description: Additional file 4. Data supporting conclusions on the ability to differentiate statistically between levels of study variables when using three different outcome variables.
DOI: 10.6084/m9.figshare.11870355
title: Additional file 3 of Developing an experimental necrotic enteritis model in turkeys - the impact of Clostridium perfringens, Eimeria meleagrimitis and host age on frequency of severe intestinal lesions

description: Additional file 3. Data supporting conclusions regarding impact of study variables on OPG counts.
DOI: 10.6084/m9.figshare.11870349
title: Additional file 2 of Developing an experimental necrotic enteritis model in turkeys - the impact of Clostridium perfringens, Eimeria meleagrimitis and host age on frequency of severe intestinal lesions

description: Additional file 2. Data supporting conclusions regarding impact of study variables on frequency of turkeys with severe intestinal lesions.
DOI: 10.6084/m9.figshare.11870355.v1
title: Additional file 3 of Developing an experimental necrotic enteritis model in turkeys - the impact of Clostridium perfringens, Eimeria meleagrimitis and host age on frequency of severe intestinal lesions

description: Additional file 3. Data supporting conclusions regarding impact of study variables on OPG counts.
DOI: 10.6084/m9.figshare.11870349.v1
title: Additional file 2 of Developing an experimental necrotic enteritis model in turkeys - the impact of Clostridium perfringens, Eimeria meleagrimitis and host age on frequency of severe intestinal lesions

description: Additional file 2. Data supporting conclusions regarding impact of study variables on frequency of turkeys with severe intestinal lesions.
DOI: 10.6084/m9.figshare.11870337
title: Additional file 1 of Developing an experimental necrotic enteritis model in turkeys - the impact of Clostridium perfringens, Eimeria meleagrimitis and host age on frequency of severe intestinal lesions

description: Additional file 1. Additional photos of intestinal lesions. Folder with 47 additional photos in JPG format illustrating turkeys with intestinal lesions that were assigned to scores 0, 1, 2 or 3.
DOI: 10.6084/m9.figshare.11870265
title: Additional file 1 of Spatial clustering of suicide mortality and associated community characteristics in Kanagawa prefecture, Japan, 2011â€“2017

description: Additional file 1. Supplementary material 1. The proportion of suicides according to specific motivations during the 2011 to 2017 by year. Supplementary material 2. Indices for standardized mortality. Supplementary material 3. Regional code of Kanagawa prefecture. Supplementary material 4. SMR for male suicide by year (each year standardization) in Kanagawa prefecture. Supplementary material 5. SMR for female suicide by year (each year standardization) in Kanagawa prefecture. Supplementary material 6. EBSMR for male suicide by year (total year standardization) in Kanagawa prefecture. Supplementary material 7. EBSMR for female suicide by year (total year standardization) in Kanagawa prefecture.
DOI: 10.6084/m9.figshare.11870259
title: Additional file 1 of Prospective isolation of chondroprogenitors from human iPSCs based on cell surface markers identified using a CRISPR-Cas9-generated reporter

description: Additional file 1: Figure S1. related to Figure 2 and 3. GO enrichment analysis of unsorted and sorted cells. (A) Top 10 GO terms (biological process) that were associated with each population in unsorted cells. (B) CD47 was highly expressed in SOX2/TTR+ cells. (C) Top 10 GO terms (biological process) that were associated with each population in sorted cells. Figure S2. related to Figure 2 and 3. Overall gene expression of sorted and unsorted chondroprogenitors. RT-qPCR reveals differences between sorted and unsorted chondroprogenitor cells in overall expression of (A) neurogenic, (B) mesenchymal, and (C) chondrogenic genes. Gene expression in reference to undifferentiated hiPSCs with housekeeping gene TBP. * p &lt; 0.05. *** p &lt; 0.001. Data represented as mean ± SEM. n = 4 samples/group. Figure S3 related to Figure 2 and 3. Expression profiles of pro-chondrogenic genes in sorted and unsorted chondroprogenitor cells. scRNA-seq reveals that sorted and unsorted cells had distinct gene expression patterns of several markers that were proposed to be pro-chondrogenic identified by previous studies. Figure S4 related to Fig. 5. Histology for matrix proteins. Safranin-O staining for sGAG showing pellets derived from sorted chondroprogenitor cells had more robust staining and homogenous cell morphology compared to pellets derived from unsorted cells in two individual experimental replicates. Scale bar = 200 μm. Inset scale bar = 400 μm. Figure S5 related to Figure 5. IHC labeling for COL6A1. There was more distributed labeling for COL6A1 in unsorted chondroprogenitor pellets compared to the localization around cells in sorted chondroprogenitor pellets. Scale bar = 200 μm. Inset scale bar = 400 μm. Figure S6 related to Figure 6. Alternative analysis of gene expression. Expression of chondrogenic genes ACAN, SOX9, and COL2A1, fibrocartilage and bone matrix marker COL1A1, and hypertrophic cartilage marker COL10A1 was significantly increased with sorting. CT value of gene of interest was normalized to CT value of housekeeping gene TBP for each sample. ** p &lt; 0.01. *** p &lt; 0.001. **** p &lt; 0.0001. Data represented as mean ± SEM. n = 6-7 per group: 2 experimental replicates, 3-4 technical replicates (pellets). Figure S7. Histology of pellets derived from in vitro expanded unsorted and sorted chondroprogenitors. Chondrogenic capacity was maintained after one passage of both unsorted and sorted chondroprogenitor cells as shown by staining for sGAG. There was more robust staining in pellets derived from sorted cells. Safranin-O staining for sGAG showed similar loss of chondrogenic capacity for both unsorted and sorted chondroprogenitor cells through four passages. Table S1. Antibodies used for flow cytometry and sorting. Table S2. Human primer sequences. Primers were used for RT-qPCR and are listed as 5’ to 3’.
DOI: 10.6084/m9.figshare.11870265.v1
title: Additional file 1 of Spatial clustering of suicide mortality and associated community characteristics in Kanagawa prefecture, Japan, 2011â€“2017

description: Additional file 1. Supplementary material 1. The proportion of suicides according to specific motivations during the 2011 to 2017 by year. Supplementary material 2. Indices for standardized mortality. Supplementary material 3. Regional code of Kanagawa prefecture. Supplementary material 4. SMR for male suicide by year (each year standardization) in Kanagawa prefecture. Supplementary material 5. SMR for female suicide by year (each year standardization) in Kanagawa prefecture. Supplementary material 6. EBSMR for male suicide by year (total year standardization) in Kanagawa prefecture. Supplementary material 7. EBSMR for female suicide by year (total year standardization) in Kanagawa prefecture.
DOI: 10.6084/m9.figshare.11870253
title: Additional file 3 of Unveiling synapse pathology in spinal bulbar muscular atrophy by genome-wide transcriptome analysis of purified motor neurons derived from disease specific iPSCs

description: Additional file 3: Table S1. DEGs in heatmap (NT). Related to Fig. 5C. Table S2. DEGs in heatmap (HPF). Related to Fig. 5D. Table S3. Profiles of GSEA. Table S4. Gene ontology terms (down in NT). List of GO terms negatively enriched in SBMA-MNs of NT (FDR 2-fold) expression levels in SBMA-MNs than in control-MNs. Table S9. Primer sequences and cycling conditions for quantitative RT-PCR. Table S10. Antibodies for immunocytochemistry.