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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: Mostafa, Mahmoud; Rider, Christopher; Suharsh Shah; Traves, Suzanne; +4 Authors

    Genes significantly modulated by budesonide or dexamethasone in A549 cells. The 330 genes showing significant induction (fold ≥2, P ≤ 0.05), or repression (fold ≤0.5, P ≤ 0.05), by budesonide (300 nM) or dexamethasone (1 μM), compared to control at 6 h, are listed along with the fold change and P value for each glucocorticoid. Genes are sorted alphabetically according to their official gene symbol. (XLSX 30 kb)

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    Dataset . 2019
    License: CC BY
    Data sources: Datacite
    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
    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/
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      Dataset . 2019
      License: CC BY
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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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    Authors: Henderson, Sara; Teft, Wendy; Kim, Richard;

    Spreadsheet of analyte concentrations and metabolite/parent ratios for tamoxifen and its metabolites. (XLSX 10 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: Gagarinova, Alla; Phanse, Sadhna; Miroslaw Cygler; Babu, Mohan;

    Introduction: The threat bacterial pathogens pose to human health is increasing with the number and distribution of antibiotic-resistant bacteria, while the rate of discovery of new antimicrobials dwindles. Proteomics is playing key roles in understanding the molecular mechanisms of bacterial pathogenesis, and in identifying disease outcome determinants. The physical associations identified by proteomics can provide the means to develop pathogen-specific treatment methods that reduce the spread of antibiotic resistance and alleviate the negative effects of broad-spectrum antibiotics on beneficial bacteria. Areas covered: This review discusses recent trends in proteomics and introduces new and developing approaches that can be applied to the study of protein-protein interactions (PPIs) underlying bacterial pathogenesis. The approaches examined encompass options for mapping proteomes as well as stable and transient interactions in vivo and in vitro. We also explored the coverage of bacterial and human-bacterial PPIs, knowledge gaps in this area, and how they can be filled. Expert commentary: Identifying potential antimicrobial candidates is confounded by the complex molecular biology of bacterial pathogenesis and the lack of knowledge about PPIs underlying this process. Proteomics approaches can offer new perspectives for mechanistic insights and identify essential targets for guiding the discovery of next generation antimicrobials.

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    Dataset . 2017
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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 . 2017
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      Dataset . 2017
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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 . 2017
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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: Kerr, Craig H.; Skinnider, Michael A.; Andrews, Daniel D. T.; Madero, Angel M.; +5 Authors

    Additional file 6. Autocorrelation z scores between pairs of stimulated and unstimulated chromatograms.

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    Dataset . 2020
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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 . 2020
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      Dataset . 2020
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      Dataset . 2020
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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: Tuor, Ursula; Zonghang Zhao; Barber, Philip; Qiao, Min;

    Additional file 4. Histological assessments for Figure 4. Shown are the data for each animal at either 1d or 3d post a single mild ischemic insult. Positive staining counts for TNF, Iba1 and EBA in addition to the Lectin scores and IgG gray level measures are presented.

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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: 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: Tianyuan Lu; Klein, Kathleen; InĂŠs Colmegna; Lora, Maximilien; +2 Authors

    Additional file 2: Table S2. Summary of CHG-based DMGs.

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    Dataset . 2019
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    Dataset . 2019
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      Dataset . 2019
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    Authors: Im, Doo Soon; Joselin, Alvin; Svoboda, Devon; Takano, Tesuya; +7 Authors

    Additional file 4. Individual data values.

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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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    Authors: Ryall, Scott; Krishnatry, Rahul; Arnoldo, Anthony; Buczkowicz, Pawel; +12 Authors

    Droplet digital PCR H3K27M detection validation raw droplet counts. (XLSX 12Â kb)

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    Authors: Mostafa, Mahmoud; Rider, Christopher; Suharsh Shah; Traves, Suzanne; +4 Authors

    Genes significantly modulated by budesonide or dexamethasone in A549 cells. The 330 genes showing significant induction (fold ≥2, P ≤ 0.05), or repression (fold ≤0.5, P ≤ 0.05), by budesonide (300 nM) or dexamethasone (1 μM), compared to control at 6 h, are listed along with the fold change and P value for each glucocorticoid. Genes are sorted alphabetically according to their official gene symbol. (XLSX 30 kb)

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    Authors: Henderson, Sara; Teft, Wendy; Kim, Richard;

    Spreadsheet of analyte concentrations and metabolite/parent ratios for tamoxifen and its metabolites. (XLSX 10 kb)

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    Authors: Gagarinova, Alla; Phanse, Sadhna; Miroslaw Cygler; Babu, Mohan;

    Introduction: The threat bacterial pathogens pose to human health is increasing with the number and distribution of antibiotic-resistant bacteria, while the rate of discovery of new antimicrobials dwindles. Proteomics is playing key roles in understanding the molecular mechanisms of bacterial pathogenesis, and in identifying disease outcome determinants. The physical associations identified by proteomics can provide the means to develop pathogen-specific treatment methods that reduce the spread of antibiotic resistance and alleviate the negative effects of broad-spectrum antibiotics on beneficial bacteria. Areas covered: This review discusses recent trends in proteomics and introduces new and developing approaches that can be applied to the study of protein-protein interactions (PPIs) underlying bacterial pathogenesis. The approaches examined encompass options for mapping proteomes as well as stable and transient interactions in vivo and in vitro. We also explored the coverage of bacterial and human-bacterial PPIs, knowledge gaps in this area, and how they can be filled. Expert commentary: Identifying potential antimicrobial candidates is confounded by the complex molecular biology of bacterial pathogenesis and the lack of knowledge about PPIs underlying this process. Proteomics approaches can offer new perspectives for mechanistic insights and identify essential targets for guiding the discovery of next generation antimicrobials.

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    Authors: Kerr, Craig H.; Skinnider, Michael A.; Andrews, Daniel D. T.; Madero, Angel M.; +5 Authors

    Additional file 6. Autocorrelation z scores between pairs of stimulated and unstimulated chromatograms.

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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 . 2020
      License: CC BY
      Data sources: Datacite
      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/
      figshare
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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