IEX-1 promotes TSA- and Fas-induced apoptosis in RA-SFs.

<p>IEX-1 was knocked down in RA-SFs using siRNA, and the cells were seeded in 96-well plates and incubated with TSA (1 μM) and/or anti-Fas mAb (500 ng/ml) for 18 h. (A) Viable cells were quantified with a WST-8 assay. Results are expressed as O.D. The means ± SD are shown for 5 experiments with different RA-SFs. Statistical significance was analyzed by a paired Student’s <i>t-</i>test. (B) Apoptosis was measured with a Cell Death Detection ELISA; results shown are representative of 3 experiments. (C) FACS analysis of annexin V–positive cells. Data shown are representative of 3 experiments with similar results.</p

TSA upregulates IEX-1 in RA-SFs.

<p>SFs from 5 RA patients were stimulated with TSA (1 μg/ml) or vehicle for 24 h, and IEX-1 was measured by quantitative RT-PCR (left) and western blotting (right).</p

IEX-1 is upregulated by certain HDAC inhibitors.

<p>RA-SFs were stimulated with the HDAC inhibitors TSA (HDACs1-10), CI994 (HDAC1), romidepsin (HDAC1, 2), RGFP966 (HDAC3), tubastatin (HDAC6), or PCI-34051 (HDAC8) for 24 h at the indicated doses, and the IEX-1 expression was measured by quantitative RT-PCR. The means ± SD are shown from 4 experiments from different patients. ANOVA was applied and followed by Tukey Method; *P<0.05, **P<0.01.</p

TNFα and IL-1β induce IEX-1 in RA-SFs.

<p>RA-SFs were stimulated with LPS (1 μg/ml) or the indicated doses of PDGF, IL-1β, TNFα, IL-17, or IL-6 and IL-6R for 24 h. IEX-1 mRNA levels were measured using quantitative RT-PCR. The means ± SD are shown for 3–4 experiments with different RA-SFs. ANOVA was applied (ANOVA) was applied and followed by either Tukey Method or MannWhitney test for IL-1β; *P<0.05.</p

IEX-1 is expressed in RA-SFs.

<p>SFs from 6 OA and 8 RA patients were grown in vitro. (A) IEX-1 mRNA was measured by quantitative RT-PCR. (B) Immunohistochemical analysis of the IEX-1 expression in RA and OA synovium; data shown are representative of three RA and two OA patients.</p

IEX-1 is also induced in OA-SF and affects its cytokine and chemokine production.

<p>(A) OA-SFs were stimulated with the indicated doses of TSA, TNFα, or IL-1β for 24 h. IEX-1 mRNA levels were measured using quantitative RT-PCR. The means ± SD are shown for 5 experiments with different OA-SFs. Statistical significance was determined by ANOVA followed by Tukey Method; *P<0.05. (B) IEX-1 was knocked down in OA-SF samples using siRNA, after which the cells were stimulated with LPS (1 μg/ml) for 16 h. Cytokine and chemokine mRNAs were measured by quantitative RT-PCR, and the results were expressed as a ratio to the G3PD mRNA. The CXCL-10 and CCL-5 results were expressed as the fold-change compared to LPS-stimulated, scrambled siRNA–transfected cells. The means ± SD are shown for 4 experiments with different OA-SFs. Statistical significance was determined by a paired Student’s <i>t-</i>test.</p

IEX-1 promotes TSA- and Fas-induced apoptosis in RA-SFs.

<p>IEX-1 was knocked down in RA-SFs using siRNA, and the cells were seeded in 96-well plates and incubated with TSA (1 μM) and/or anti-Fas mAb (500 ng/ml) for 18 h. (A) Viable cells were quantified with a WST-8 assay. Results are expressed as O.D. The means ± SD are shown for 5 experiments with different RA-SFs. Statistical significance was analyzed by a paired Student’s <i>t-</i>test. (B) Apoptosis was measured with a Cell Death Detection ELISA; results shown are representative of 3 experiments. (C) FACS analysis of annexin V–positive cells. Data shown are representative of 3 experiments with similar results.</p

Relationships between the serum trough concentrations of digoxin and the reciprocal values of serum levels of Cys-C (a) and Cr (b) in 18 patients treated with digoxin

<p><b>Copyright information:</b></p><p>Taken from "Serum cystatin C levels to predict serum concentration of digoxin in Japanese patients"</p><p>International Journal of Medical Sciences 2006;3(3):92-96.</p><p>Published online 17 May 2006</p><p>PMCID:PMC1475426.</p><p>© Ivyspring International Publisher. This is an open access article. Reproduction is permitted for personal and noncommerical use, provided that the article is in whole, unmodified, and properly cited.</p> The correlation coefficients were r=0.383 and 0.667 for Cys-C and Cr, respectively

Serum concentration of digoxin for three patient groups substratified based on the serum levels of Cys-C and Cr

<p><b>Copyright information:</b></p><p>Taken from "Serum cystatin C levels to predict serum concentration of digoxin in Japanese patients"</p><p>International Journal of Medical Sciences 2006;3(3):92-96.</p><p>Published online 17 May 2006</p><p>PMCID:PMC1475426.</p><p>© Ivyspring International Publisher. This is an open access article. Reproduction is permitted for personal and noncommerical use, provided that the article is in whole, unmodified, and properly cited.</p> Group I (normal), serum Cr o

Prediction of Response to Treatment by Gene Expression Profiling of Peripheral Blood in Patients with Microscopic Polyangiitis

<div><p>The JMAAV study was an open-labeled prospective clinical trial, which proposed severity-based treatment protocols for patients with microscopic polyangiitis (MPA). The results suggest that the proposed protocols are useful (remission rate: 89.4%), but are also indicative of relapse or patient demise regardless of the treatment (recurrence rate: 19.0%; mortality rate: 10.6%). The aim of this study is to develop the method to predict response to the treatment in patients with MPA. In the present study, transcriptome analysis was performed using peripheral blood from patients enrolled in the JMAAV study before and 1-week after the beginning of treatment. The gene expression profile before treatment was not directly related to the response to the treatment. However, when the samples from 9 patients with good response (persistent remission for 18 months) were examined, the expression of 88 genes was significantly altered by the treatment. Thirty statistically reliable genes were selected, and then the alteration of expression by the treatment was examined among 22 patients, including 17 with good response, which was defined as persistent remission for 18 months and 5 with poor response, which was defined as relapse after remission or no remission. Discrimination analysis between the alteration of expression of the 30 genes by the treatment and the response identified a combination of 16 genes as the most valuable gene set to predict the response to the treatment. This preliminary study identified IRF7, IFIT1, IFIT5, OASL, CLC, GBP-1, PSMB9, HERC5, CCR1, CD36, MS4A4A, BIRC4BP, PLSCR1, DEFA1/DEFA3, DEFA4, and COL9A2 as the important genes that can predict the response to the treatment in patients with MPA at an early point during the therapy.</p></div