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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/

    Additional file7: Table S18. DNAmeQTL analysis for the loci significantly associated with DNAme-based XCI status calls. See additional files. These loci were independently tested as DNAmeQTLs in females and males, with some columns color coded based on sex (pink female, light blue male). There are also columns with the median and mean DNAme value at the gene’s island for samples with the reference or alternate allele at that loci; these columns are color coded based on whether the allele is in the range to escape from XCI (DNAme<0.01, blue) or in the range to be subject to XCI (DNAme>0.15, orange). There are mean and median columns for both males and females, but only the female columns are color coded based on XCI status. There are boxes around the genes with female median values with one allele in the range to escape XCI and the other allele in the range to be subject to XCI.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ figsharearrow_drop_down
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    Dataset . 2022
    License: CC BY
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    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ figsharearrow_drop_down
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      Dataset . 2022
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Dataset . 2022
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      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Lalonde, Simon; Valérie-Anne Codina-Fauteux; Bellefon, Sébastian; Leblanc, Francis; +7 Authors

    Biological pathways that are enriched for transcription factors that bind within ATACseq peaks profiled in NT and TNFα treated teloHAEC. (XLSX 14 kb)

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    Dataset . 2019
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Dataset . 2019
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    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ figsharearrow_drop_down
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      Dataset . 2019
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Dataset . 2019
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      Data sources: Datacite
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    Authors: Liu, Feng; Cai, Ping; Imir Metushi; Jinze Li; +3 Authors

    Amodiaquine (AQ) is associated with a relatively high incidence of idiosyncratic drug-induced liver injury (IDILI) and agranulocytosis. A previous study reported that a combination of high dose AQ and glutathione (GSH) depletion led to liver injury. However, the characteristics of this toxicity were very different from AQ-induced liver injury in humans. We developed a model of AQ-induced liver injury with characteristics similar to the injury in humans by treating mice with lower doses of AQ for several weeks. In this study we found that not only did GSH depletion not increase AQ covalent binding to hepatic proteins at this lower dose, but also it paradoxically prevented the liver injury. We extended the model to rats and found AQ treatment led to a mild delayed onset liver injury that resolved despite continued treatment with AQ. Immunohistochemistry indicated the presence of Kupffer cell activation, apoptosis and hepatocyte proliferation in the liver. There was also an increase in serum IL-2, IL-5, IL-9, IL-12, MCP-1 and TGFβ, but a decrease in leptin. Coincident with the elevated serum ALT, the number of liver CD4+ T-cells, IL-17 secreting cells and TH17/Treg cells increased at Week 3 and decreased during continued treatment. Increases in NK1.1+ cells and activated M2 macrophages were also observed during liver injury. These results suggest that the outcome of the liver injury was determined by the balance between effector and regulatory cells. Co-treatment with cyclosporin prevented AQ-induced liver injury, which supports an immune mechanism. Retinoic acid (RA), which has been reported to enhance natural killer (NK) cell activity, exacerbated AQ-induced liver injury. These results suggest that AQ-induced IDILI is immune mediated and the subsequent adaptation appears to represent immune tolerance.

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    Dataset . 2016
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    Dataset . 2016
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      Dataset . 2016
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      Dataset . 2016
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    Authors: Mealey, Nicole E.; O���Sullivan, Dylan E.; Peters, Cheryl E.; Heng, Daniel Y. C.; +1 Authors

    Additional file 6: Table S1. Comparison of COSMIC mutational signature contributions to non-seminomatous (n = 56) and seminomatous (n = 44) testicular tumors. Entries are number (proportion) of cases with a signature present above a threshold of 6% in each histologic group. P-values were calculated adjusting for age of onset * indicates statistical significance at a 0.05 level.

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    Dataset . 2021
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    Dataset . 2021
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      Dataset . 2021
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      Dataset . 2021
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    Pairwise t-test results for sampsize intra-parameter groups for the combined NSCLC validation data. All p-values were adjusted using a Benjamini-Hochberg procedure. Significant differences were observed between large and small sampsize values, in particular, sampsize 26 from sampsize 102 − 255; sampsize 51 from sampsize 128 − 255; sampsize 77 from sampsize 128 − 255, etc. (TXT 1 kb)

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    Dataset . 2016
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    Dataset . 2016
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      Dataset . 2016
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      Dataset . 2016
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    Authors: Corkum, Christopher; Ings, Danielle; Burgess, Christopher; Karwowska, Sylwia; +2 Authors

    Comparison of gene expression of CD4+ T cells separated from PBMC isolated using CPT and Ficoll. A two-group comparison with permutation analysis for differential expression was performed, as described in Methods, on microarray data to identify differentially expressed genes between CD4+ T cells separated from CPT- and Ficoll-isolated PBMC. Probsets are ranked according to the FDR value. (CSV 26355 kb)

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    Dataset . 2015
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    Dataset . 2015
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      Dataset . 2015
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      Dataset . 2015
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    Authors: Akhabir, Loubna; Stringer, Randa; Desai, Dipika; Mandhane, Piush J; +6 Authors

    Additional file 6. Meta-analysis association of Gestational age with methylation in CHILD and START. Results of meta-analysis association analysis of Gestational age in CHILD and START with methylation in sites identified in the literature.

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    Dataset . 2022
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    Dataset . 2022
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    Authors: Villandré, Luc; Labbe, Aurélie; Brenner, Bluma; Roger, Michel; +1 Authors

    This file contains an R object giving the results for the scenario in the simulation study where the concentration parameter prior is assumed to have mean 10 and we use the MAP topology. The file is compressed in gzip format. (GZ 8365 kb)

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    Authors: Faheem, Muhammad; Deneault, Eric; Alexandrova, Roumiana; Rodrigues, Deivid C.; +12 Authors

    Additional file 1. Supplementary tables.

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    Authors: Visser, Pieter Jelle; Reus, Lianne M.; Gobom, Johan; Jansen, Iris; +25 Authors

    Additional file 1: Data S1. Participant characteristics. S1a: Characteristics of individuals with CSF Aβ1-42 and tau measurements available; S1b: Characteristics of individuals with CSF proteomic data. Data S2. Protein annotation and statistics of group comparisons of protein levels. Data S3a. Full list of GO biological processes associated with proteins that differ according to group and clinical stage. Data S3b. SynGO enriched synaptic cellular components and biological processes that differ according to group. Data S4a. Estimated marginal means of AD GWAS-based polygenic risk scores in controls, AD individuals with increased t-tau and AD individuals with normal t-tau. Data S4b. Top 1000 SNPS from GWAS on AD individuals with increased t-tau and normal t-tau in pooled ADNI and EMIF-AD MBD cohorts. Data S4c. Difference in MAGMA gene score between AD individuals with increased t-tau and normal t-tau based on t-tau GWAS in pooled ADNI and EMIF-AD MBD cohorts. Data S4d. Difference in GO biological process MAGMA geneset score between AD individuals with increased t-tau and normal t-tau based on t-tau GWAS in pooled ADNI and EMIF-AD MBD cohorts. Data S5a. Correlation between genetic risk score and CSF protein level in individuals with abnormal Aβ1-42. Data S5b. Association of the number of GMNC rs9877502-A risk alleles and number of APOE-e4 alleles with CSF protein concentrations in a linear model in individuals with AD. Data S5c. GO-BP processes enriched for proteins that have a positive or negative association with the number of rs9877502-A risk alleles in an additive model. Data S6. Annual change in imaging measures.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/

    Additional file7: Table S18. DNAmeQTL analysis for the loci significantly associated with DNAme-based XCI status calls. See additional files. These loci were independently tested as DNAmeQTLs in females and males, with some columns color coded based on sex (pink female, light blue male). There are also columns with the median and mean DNAme value at the gene’s island for samples with the reference or alternate allele at that loci; these columns are color coded based on whether the allele is in the range to escape from XCI (DNAme<0.01, blue) or in the range to be subject to XCI (DNAme>0.15, orange). There are mean and median columns for both males and females, but only the female columns are color coded based on XCI status. There are boxes around the genes with female median values with one allele in the range to escape XCI and the other allele in the range to be subject to XCI.

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    Authors: Lalonde, Simon; Valérie-Anne Codina-Fauteux; Bellefon, Sébastian; Leblanc, Francis; +7 Authors

    Biological pathways that are enriched for transcription factors that bind within ATACseq peaks profiled in NT and TNFα treated teloHAEC. (XLSX 14 kb)

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    Authors: Liu, Feng; Cai, Ping; Imir Metushi; Jinze Li; +3 Authors

    Amodiaquine (AQ) is associated with a relatively high incidence of idiosyncratic drug-induced liver injury (IDILI) and agranulocytosis. A previous study reported that a combination of high dose AQ and glutathione (GSH) depletion led to liver injury. However, the characteristics of this toxicity were very different from AQ-induced liver injury in humans. We developed a model of AQ-induced liver injury with characteristics similar to the injury in humans by treating mice with lower doses of AQ for several weeks. In this study we found that not only did GSH depletion not increase AQ covalent binding to hepatic proteins at this lower dose, but also it paradoxically prevented the liver injury. We extended the model to rats and found AQ treatment led to a mild delayed onset liver injury that resolved despite continued treatment with AQ. Immunohistochemistry indicated the presence of Kupffer cell activation, apoptosis and hepatocyte proliferation in the liver. There was also an increase in serum IL-2, IL-5, IL-9, IL-12, MCP-1 and TGFβ, but a decrease in leptin. Coincident with the elevated serum ALT, the number of liver CD4+ T-cells, IL-17 secreting cells and TH17/Treg cells increased at Week 3 and decreased during continued treatment. Increases in NK1.1+ cells and activated M2 macrophages were also observed during liver injury. These results suggest that the outcome of the liver injury was determined by the balance between effector and regulatory cells. Co-treatment with cyclosporin prevented AQ-induced liver injury, which supports an immune mechanism. Retinoic acid (RA), which has been reported to enhance natural killer (NK) cell activity, exacerbated AQ-induced liver injury. These results suggest that AQ-induced IDILI is immune mediated and the subsequent adaptation appears to represent immune tolerance.

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    Dataset . 2016
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    Authors: Mealey, Nicole E.; O���Sullivan, Dylan E.; Peters, Cheryl E.; Heng, Daniel Y. C.; +1 Authors

    Additional file 6: Table S1. Comparison of COSMIC mutational signature contributions to non-seminomatous (n = 56) and seminomatous (n = 44) testicular tumors. Entries are number (proportion) of cases with a signature present above a threshold of 6% in each histologic group. P-values were calculated adjusting for age of onset * indicates statistical significance at a 0.05 level.

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    Dataset . 2021
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    Dataset . 2021
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      Dataset . 2021
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    Pairwise t-test results for sampsize intra-parameter groups for the combined NSCLC validation data. All p-values were adjusted using a Benjamini-Hochberg procedure. Significant differences were observed between large and small sampsize values, in particular, sampsize 26 from sampsize 102 − 255; sampsize 51 from sampsize 128 − 255; sampsize 77 from sampsize 128 − 255, etc. (TXT 1 kb)

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    Dataset . 2016
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