Comparison of rivaroxaban concentrations between groups with tablet crushing [TC (+)] and those without [TC (−)].

<p>TC indicates tablet crushing.</p

Linear mixed-effect model to determine variables that influence rivaroxaban concentration.

<p>NIHSS, National Institutes of Health Stroke Scale; TIA, transient ischemic attack.</p><p>Linear mixed-effect model to determine variables that influence rivaroxaban concentration.</p

Coagulation markers and estimated rivaroxaban concentration.

<p>aPTT, activated partial thromboplastin time; PT, prothrombin time; INR, international normalized ratio.</p><p>Coagulation markers and estimated rivaroxaban concentration.</p

Correlations of estimated rivaroxaban concentration (C_riv) with PT (sec) and aPTT (sec) at 0 h (A, B), 4 h (C, D), and 9 h (E, F).

<p>Correlations of estimated rivaroxaban concentration (C_riv) with PT (sec) and aPTT (sec) at 0 h (A, B), 4 h (C, D), and 9 h (E, F).</p

PT (A), aPTT (B), and rivaroxaban concentration (C_riv) at 0 h, 4 h, and 9 h after administration.

<p>PT (A), aPTT (B), and rivaroxaban concentration (C_riv) at 0 h, 4 h, and 9 h after administration.</p

Interferon gamma (IFN-γ) production by CD3 and CD28 costimulated CD4T cells in the presence of IL-10 in patients with rheumatoid arthritis (RA) and in healthy controls (HC)

<p><b>Copyright information:</b></p><p>Taken from "Resistance to IL-10 inhibition of interferon gamma production and expression of suppressor of cytokine signaling 1 in CD4T cells from patients with rheumatoid arthritis"</p><p>Arthritis Research & Therapy 2004;6(6):R567-R577.</p><p>Published online 13 Oct 2004</p><p>PMCID:PMC1064873.</p><p>Copyright © 2004 Yamana et al., licensee BioMed Central Ltd.</p> CD4T cells (5 × 10cells in 0.5 ml culture medium with 10% FCS) were stimulated by anti-CD3 antibody and anti-CD28 antibody with or without 1 ng/ml IL-10. Concentrations of IFN-γ in culture supernatants were measured in duplicate by ELISA. RA patients were divided into those with active disease (multiple inflammatory joints and CRP level ≥ 10 mg/l) and inactive disease (in remission and CRP level ≤ 4 mg/l). The results are represented as a box plot; upper and lower bars, 90th and 10th percentiles, respectively; upper, center and lower lines of box, 75th, 50th, and 25th percentiles, respectively. Percentage of IFN-γ production. IFN-γ production with IL-10 expressed as % IFN-γ production without IL-10. Values are the mean ± standard error of the mean. n, number of samples tested

Dose response of IL-10 inhibition of interferon gamma (IFN-γ) production by CD4T cells after CD3 and CD28 costimulation in patients with rheumatoid arthritis (RA) and in healthy controls (HC)

<p><b>Copyright information:</b></p><p>Taken from "Resistance to IL-10 inhibition of interferon gamma production and expression of suppressor of cytokine signaling 1 in CD4T cells from patients with rheumatoid arthritis"</p><p>Arthritis Research & Therapy 2004;6(6):R567-R577.</p><p>Published online 13 Oct 2004</p><p>PMCID:PMC1064873.</p><p>Copyright © 2004 Yamana et al., licensee BioMed Central Ltd.</p> CD4T cells were purified from peripheral blood mononuclear cells of three RA patients and three HC by positive selection with anti-CD4 antibody. CD4T cells (5 × 10cells in 0.5 ml culture medium with 10% FCS) were stimulated by immobilized anti-CD3 antibody and anti-CD28 antibody in the presence or absence of diluted IL-10 concentrations for 36 hours. Culture supernatants were measured for concentrations of IFN-γ by ELISA. IFN-γ production with IL-10 expressed as % IFN-γ production without IL-10. Values are the mean ± standard error of the mean

Intestinal Dysbiosis and Lowered Serum Lipopolysaccharide-Binding Protein in Parkinson’s Disease

<div><p>Background</p><p>The intestine is one of the first affected organs in Parkinson’s disease (PD). PD subjects show abnormal staining for <i>Escherichia coli</i> and α-synuclein in the colon.</p><p>Methods</p><p>We recruited 52 PD patients and 36 healthy cohabitants. We measured serum markers and quantified the numbers of 19 fecal bacterial groups/genera/species by quantitative RT-PCR of 16S or 23S rRNA. Although the six most predominant bacterial groups/genera/species covered on average 71.3% of total intestinal bacteria, our analysis was not comprehensive compared to metagenome analysis or 16S rRNA amplicon sequencing.</p><p>Results</p><p>In PD, the number of <i>Lactobacillus</i> was higher, while the sum of analyzed bacteria, <i>Clostridium coccoides</i> group, and <i>Bacteroides fragilis</i> group were lower than controls. Additionally, the sum of putative hydrogen-producing bacteria was lower in PD. A linear regression model to predict disease durations demonstrated that <i>C</i>. <i>coccoides</i> group and <i>Lactobacillus gasseri</i> subgroup had the largest negative and positive coefficients, respectively. As a linear regression model to predict stool frequencies showed that these bacteria were not associated with constipation, changes in these bacteria were unlikely to represent worsening of constipation in the course of progression of PD. In PD, the serum lipopolysaccharide (LPS)-binding protein levels were lower than controls, while the levels of serum diamine oxidase, a marker for intestinal mucosal integrity, remained unchanged in PD.</p><p>Conclusions</p><p>The permeability to LPS is likely to be increased without compromising the integrity of intestinal mucosa in PD. The increased intestinal permeability in PD may make the patients susceptible to intestinal dysbiosis. Conversely, intestinal dysbiosis may lead to the increased intestinal permeability. One or both of the two mechanisms may be operational in development and progression of PD.</p></div

Comparisons of bacterial counts between control subjects and PD patients.

<p>^aDetection rate represents the percentage of fecal samples that contained specific bacterial groups/genera/species above the detection threshold.</p><p>^bMean and SD are indicated</p><p>^cStatistical difference is examined with Mann-Whitney <i>U</i> test.</p><p>^d<i>q</i> value is calculated using the Benjamini and Hochberg method.</p><p>^eStatistical difference is analyzed with Fisher’s exact test.</p><p>^fGram-negative bacteria. The sum of Gram-negative bacteria in PD (9.5 ± 0.6 log₁₀ cells/g) was lower than that in controls (9.9 ± 0.6 log₁₀ cells/g) (<i>p</i> < 0.001, Mann-Whitney <i>U</i> test).</p><p>*<i>p</i> or <i>q</i> value is less than 0.05.</p><p>n.s., not significant.</p><p>Comparisons of bacterial counts between control subjects and PD patients.</p

Linear regression models to predict disease durations and stool frequencies.

<p><b>(A)</b> Scatter plot of the actual and predicted disease durations. <b>(B)</b> Scatter plot of the actual and predicted stool frequencies. <b>(C)</b> Scatter plot of the coefficients of each bacterial groups/genera/species to predict disease durations and stool frequencies. Positive and negative coefficients indicate that the bacterial group has a positive and negative effect on disease duration or stool frequency. Higher coefficients indicate higher effects on these parameters. The names of bacterial groups/genera/species that are addressed in discussion are indicated with closed symbols. The coefficients of each bacterial group/genus/species are indicated in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0142164#pone.0142164.s005" target="_blank">S5 Table</a>.</p