50 research outputs found

    Commensal bacteria regrowth inhibited with <i>Clostridium difficile</i> infection.

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    <p>(a) The <i>baiCD</i> content is decreased by antibiotic treatment in both control and <i>C</i>. <i>difficile</i> challenged mice and further decreased post-infection in the <i>C</i>. <i>difficile</i> challenged mice compared to the controls. (b and c) The expression of anti-microbial peptides DefB1 and S100A8 are upregulated with infection. Data points and error bars represent mean ± standard error of the mean (SEM). Asterisks (*) mark significance (p≤0.05) in comparison between control and <i>C</i>. <i>difficile</i> infected mice (n = 10).</p

    Simulated dynamics of mucosal immune response to <i>Clostridium difficile</i>.

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    <p>Modeling results following calibration and validation of the host response model in populations of (a) <i>C</i>. <i>difficile</i>, (b) protective commensal bacteria, (c) infection-exacerbating commensal bacteria, (d) lamina propria T helper 17 cells, (e) effector dendritic cells, (f) infiltrating neutrophils, (g) regulatory T cells, (h) tolerogenic dendritic cells and (i) activated macrophages. Lines represent simulation results, filled points represent experimental calibration data and unfilled points represent experimental validation data.</p

    Modeling the Mechanisms by Which HIV-Associated Immunosuppression Influences HPV Persistence at the Oral Mucosa

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    <div><p>Human immunodeficiency virus (HIV)-infected patients are at an increased risk of co-infection with human papilloma virus (HPV), and subsequent malignancies such as oral cancer. To determine the role of HIV-associated immune suppression on HPV persistence and pathogenesis, and to investigate the mechanisms underlying the modulation of HPV infection and oral cancer by HIV, we developed a mathematical model of HIV/HPV co-infection. Our model captures known immunological and molecular features such as impaired HPV-specific effector T helper 1 (Th1) cell responses, and enhanced HPV infection due to HIV. We used the model to determine HPV prognosis in the presence of HIV infection, and identified conditions under which HIV infection alters HPV persistence in the oral mucosa system. The model predicts that conditions leading to HPV persistence during HIV/HPV co-infection are the permissive immune environment created by HIV and molecular interactions between the two viruses. The model also determines when HPV infection continues to persist in the short run in a co-infected patient undergoing antiretroviral therapy. Lastly, the model predicts that, under efficacious antiretroviral treatment, HPV infections will decrease in the long run due to the restoration of CD4+ T cell numbers and protective immune responses.</p></div

    <i>In silico</i> simulation of altered commensal bacteria regrowth during <i>Clostridium difficile</i> infection.

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    <p>Four cases were tested with variations to the inhibition of the commensal bacteria growth: inhibited by both neutrophils and inflamed epithelial cells (N and E_i), by only neutrophils (N), by only inflamed epithelial cells (E_i), and by neither (none). Resulting changes in species populations for each case are shown: (a) <i>baiCD</i>-containing commensal species, (b) <i>C</i>. <i>difficile</i>, (c) activated neutrophils, and (d) iTreg cells in the lamina propria.</p

    HIV HPV Diagram.

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    <p>A diagram for the co-infection model (5). The left side of the figure represents the HIV dynamics wherein the interaction between target CD4+ T cells (<i>T</i>), productively infected CD4+ T cells (<i>I</i>) and HIV (<i>V</i>) are shown. The figure also includes the effect of reverse transcriptase (<i>RT</i>) and protein inhibitor (<i>PI</i>) (shown by red line—inhibition). The right side of the figure represents the HPV dynamics wherein the interaction between infected basal cells (<i>Y</i><sub><i>1</i></sub>), suprabasal transit-amplifying cells (<i>Y</i><sub><i>2</i></sub>), HPV specific (<i>E</i>) cells and HPV (<i>W</i>) are shown. The systems biology markup language (SBML) compliant network of interactions between HIV (<i>V</i>) and HPV (<i>W</i>) is created using CellDesigner [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0168133#pone.0168133.ref040" target="_blank">40</a>] (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0168133#pone.0168133.s001" target="_blank">S1 Fig</a>).</p

    HIV/HPV co-infection.

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    <p>(a) HPV <i>W</i> and (b) CTL <i>E</i> as given by model (6) for <i>ε</i> = 0.5 per day, parameters are listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0168133#pone.0168133.t001" target="_blank">Table 1</a>, and = 10<sup>6</sup> cells per ml (blue solid lines); = 5x10<sup>5</sup> cells per ml (red dashed lines); = 3.3x10<sup>5</sup> cells per ml (green dotted lines); and = 2x10<sup>5</sup> cells per ml (purple dashed-dotted lines).</p

    Relative effects of parameters on <i>Clostridium difficile</i> population and epithelial cell death.

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    <p>(a and b) Histograms showing the distribution of parameter impact on <i>C</i>. <i>difficile</i> population and epithelial cell death, respectively. Measurements are based on sensitivity analysis of the calibrated model. (c and d) Highest impact parameters for each quantity in which positive amounts indicate an increasing effect on the quantity and negative amounts indicate a decreasing effect. For the <i>C</i>. <i>difficile</i> population results, P1 contributes to effector dendritic cell production, P2 to neutrophil activation and migration, P3 to protective commensal bacteria regrowth, P4 to macrophage activation, P5 to commensal bacteria death, P6 to macrophage death, P7 to Th17 cell death, and P8 to neutrophil death. For epithelial cell death, P1 contributes to tolerogenic dendritic cell production, P2 to Th17 to Treg cell plasticity, P3 to commensal bacteria death, P4 to Treg to Th17 cell plasticity, P5 to macrophage activation and P6 to <i>C</i>. <i>difficile</i> growth.</p

    Time course of <i>Clostridium difficile</i> infection in mice.

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    <p>(a and b) Flow cytometry analysis of colonic lamina propria lymphocytes from days 1 to 10 post-infection showing the differences in CD4+ CD25+ FoxP3+ regulatory T (Treg) and CD4+ IL17+ T helper 17 (Th17) cells, respectively, between control and <i>C</i>. <i>difficile</i> challenged wild type mice. (c) Re-isolation data of <i>C</i>. <i>difficile</i> from colonic contents from day 1 to day 8 post-infection. Data points and error bars represent mean ± standard error of the mean (SEM). Asterisks (*) mark significance (<i>P</i>≤0.05) in comparison between control and <i>C</i>. <i>difficile</i> infected mice (n = 10).</p

    Varying oncogene expression rates.

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    <p>(a) Bifurcation diagram showing cleared <i>W</i> (area below the curve) versus chronic <i>W</i> (area above the curve) as the <i>tat</i> effect and CTL carrying capacity vary. Here, the criterion for HPV clearance is given by Eq (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0168133#pone.0168133.e011" target="_blank">7</a>); (b) HPV <i>W;</i> and (c) CTL <i>E</i> as given by model (6) for parameters listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0168133#pone.0168133.t001" target="_blank">Table 1</a> and <i>ε =</i> 0.1 (blue solid lines), <i>ε =</i> 0.5 (red dashed lines), and <i>ε =</i> 0.9 (green dotted lines).</p
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