Performance of Polymerase Chain Reaction Techniques Detecting Perforin in the Diagnosis of Acute Renal Rejection: A Meta-Analysis

BACKGROUND: Studies in the past have shown that perforin expression is up-regulated during acute renal rejection, which provided hopes for a non-invasive and reliable diagnostic method to identify acute rejection. However, a systematic assessment of the value of perforin as a diagnostic marker of acute renal rejection has not been performed. We conducted this meta-analysis to document the diagnostic performance of perforin mRNA detection and to identify potential variables that may affect the performance. METHODOLOGY/PRINCIPAL FINDINGS: Relevant materials that reported the diagnostic performance of perforin mRNA detection in acute renal rejection patients were extracted from electronic databases. After careful evaluation of the studies included in this analysis, the numbers of true positive, true negative, false positive and false negative cases of acute renal rejection identified by perforin mRNA detection were gathered from each data set. The publication year, sample origin, mRNA quantification method and housekeeping gene were also extracted as potential confounding variables. Fourteen studies with a total of 501 renal transplant subjects were included in this meta-analysis. The overall performance of perforin mRNA detection was: pooled sensitivity, 0.83 (95% confidence interval: 0.78 to 0.88); pooled specificity, 0.86 (95% confidence interval: 0.82 to 0.90); diagnostic odds ratio, 28.79 (95% confidence interval: 16.26 to 50.97); and area under the summary receiver operating characteristic curves value, 0.9107±0.0174. The univariate analysis of potential variables showed some changes in the diagnostic performance, but none of the differences reached statistical significance. CONCLUSIONS/SIGNIFICANCE: Despite inter-study variability, the test performance of perforin mRNA detected by polymerase chain reaction was consistent under circumstances of methodological changes and demonstrated both sensitivity and specificity in detecting acute renal rejection. These results suggest a great diagnostic potential for perforin mRNA detection as a reliable marker of acute rejection in renal allograft recipients

Calcineurin-Inhibitor Minimization in Liver Transplant Patients with Calcineurin-Inhibitor-Related Renal Dysfunction: A Meta-Analysis

BACKGROUND: Introduction of calcineurin-inhibitor (CNI) has made transplantation a miracle in the past century. However, the side effects of long-term use of CNI turn out to be one of the major challenges in the current century. Among these, renal dysfunction attracts more and more attention. Herein, we undertook a meta-analysis to evaluate the efficacy and safety of calcineurin-inhibitor (CNI) minimization protocols in liver transplant recipients with CNI-related renal dysfunction. METHODS: We included randomized trials with no year and language restriction. All data were analyzed using random effect model by Review Manager 5.0. The primary endpoints were glomerular filtration rate (GFR), serum creatinine level (sCr) and creatinine clearance rate (CrCl), and the secondary endpoints were acute rejection episodes, incidence of infection and patient survival at the end of follow-up. RESULTS: GFR was significantly improved in CNI minimization group than in routine CNI regimen group (Z = 5.45, P<0.00001; I(2) = 0%). Likely, sCr level was significantly lower in the CNI minimization group (Z = 2.84, P = 0.005; I(2) = 39%). However, CrCl was not significantly higher in the CNI minimization group (Z = 1.59, P = 0.11; I(2) = 0%). Both acute rejection episodes and patient survival were comparable between two groups (rejection: Z = 0.01, P = 0.99; I(2) = 0%; survival: Z = 0.28, P = 0.78; I(2) = 0%, respectively). However, current CNI minimization protocols may be related to a higher incidence of infections (Z = 3.06, P = 0.002; I(2) = 0%). CONCLUSION: CNI minimization can preserve or even improve renal function in liver transplant patients with renal impairment, while sharing similar short term acute rejection rate and patient survival with routine CNI regimen

Multi-Omics Analysis Reveals the Gut Microbiota Characteristics of Diarrheal Piglets Treated with Gentamicin

The involvement of alterations in gut microbiota composition due to the use of antibiotics has been widely observed. However, a clear picture of the influences of gentamicin, which is employed for the treatment of bacterial diarrhea in animal production, are largely unknown. Here, we addressed this problem using piglet models susceptible to enterotoxigenic Escherichia coli (ETEC) F4, which were treated with gentamicin. Gentamicin significantly alleviated diarrhea and intestinal injury. Through 16s RNS sequencing, it was found that gentamicin increased species richness but decreased community evenness. Additionally, clear clustering was observed between the gentamicin-treated group and the other groups. More importantly, with the establishment of a completely different microbial structure, a novel metabolite composition profile was formed. KEGG database annotation revealed that arachidonic acid metabolism and vancomycin resistance were the most significantly downregulated and upregulated pathways after gentamicin treatment, respectively. Meanwhile, we identified seven possible targets of gentamicin closely related to these two functional pathways through a comprehensive analysis. Taken together, these findings demonstrate that gentamicin therapy for diarrhea is associated with the downregulation of arachidonic acid metabolism. During this process, intestinal microbiota dysbiosis is induced, leading to increased levels of the vancomycin resistance pathway. An improved understanding of the roles of these processes will advance the conception and realization of new therapeutic and preventive strategies

Efficacy and Tolerability of Telaprevir for Chronic Hepatitis Virus C Genotype 1 Infection: A Meta-Analysis

<div><h3>Background</h3><p>Chronic hepatitis C virus (HCV) infection is one of the leading causes of hepatic cirrhosis and hepatocellular carcinoma, and HCV genotype 1 is the most prevalent genotype and is resistant to current standard therapy. We performed this meta-analysis to evaluate the efficacy and safety of telaprevir-based therapy for chronic HCV genotype 1 infection.</p> <h3>Methods</h3><p>We included randomized controlled trials with no year or language restriction. All data were analyzed using a random-effects model by Review Manager v5.0. The primary outcome was the proportion of patients achieving sustained virologic response (SVR), and the secondary outcomes were HCV relapse rate, incidence of severe adverse events (SAEs), and discontinuation due to adverse events.</p> <h3>Results</h3><p>The proportion of achieving SVR was significantly higher in the telaprevir group (odds ratio [OR] = 3.40 [1.92, 6.00], <em>P</em><0.0001; <em>I²</em> = 87%) regardless of a patients’ previous treatment status. It was also significantly higher in the 24-week and 48-week treatment groups (OR = 4.52 [2.08, 9.81], <em>P</em><0.001; <em>I²</em> = 85%, and OR = 4.05 [1.56, 10.56], <em>P</em> = 0.004; <em>I²</em> = 92%, respectively), while it was comparable in the 12-week treatment group (OR = 1.32 [0.63, 2.75], <em>P</em> = 0.46; <em>I²</em> = 35%). In addition, the HCV relapse rate was significantly reduced in the telaprevir group (OR = 0.28 [0.16, 0.49], <em>P</em><0.001; <em>I²</em> = 76%). However, the incidence of SAE (OR = 1.56 [1.15, 2.10], <em>P</em> = 0.004; <em>I²</em> = 0%) and study discontinuation due to adverse events (OR = 2.24 [1.43, 3.50], <em>P</em><0.001; <em>I²</em> = 37%) were significantly higher in the telaprevir group.</p> <h3>Conclusion</h3><p>Despite its higher incidence of SAEs and discontinuation due to adverse events, telaprevir-based therapy can increase the proportion of achieving SVR in both previously treated and untreated chronic HCV-1 infected patients.</p> </div

Genetic Effects and Heterosis of Yield and Yield Component Traits Based on Gossypium Barbadense Chromosome Segment Substitution Lines in Two Gossypium Hirsutum Backgrounds.

We hybridized 10 chromosome segment substitution lines (CSSLs) each from two CSSL populations and produced 50 F1 hybrids according to North Carolina Design II. We analyzed the genetic effects and heterosis of yield and yield components in the F1 hybrids and parents in four environments via the additive-dominance genetic model. Yield and yield components of the CSSLs were controlled by combined additive and dominance effects, and lint percentage was mainly controlled by additive effects, but boll weight, boll number, seedcotton yield and lint yield were mainly controlled by dominance effects. We detected significant interaction effects between genetics and the environment for all yields traits. Similar interactions were detected between two CSSL populations (Pop CCRI 36 and Pop CCRI 45). Significant positive mid-parent heterosis was detected for all yield traits in both populations, and significant positive better-parent heterosis was also detected for all yield traits except lint percentage. The differences among parents were relatively small, but significant heterosis was detected for yield and yield components. Therefore, the relationship between heterosis and genetic distance for yield traits is complicated and requires further study. These CSSLs represent useful tools for improving yield and yield components in cotton

Characteristics of included studies.

<p>T, telaprevir; P, peg-interferon; R, ribavirin; Q8H, every 8 hours.</p

Flow diagram of study identification.

<p>Flow diagram of study identification.</p

Meta-analysis of telaprevir plus peginterferon and ribavirin therapy on HCV relapse rate according to previous treatment.

<p>The incidence of relapse was significantly reduced in previously untreated (OR = 0.40 [0.16, 1.00], <i>P</i> = 0.05; <i>I²</i> = 78%), treated (OR = 0.18 [0.09, 0.36], <i>P</i><0.001; <i>I²</i> = 71%), and overall population (OR = 0.28 [0.16, 0.49], <i>P</i><0.001; <i>I²</i> = 76%). OR = odds ratio, <i>I²</i> = heterogeneity index. Columns in green represent the mean difference of each study and column size represents the study weight in the analysis. Lanes represent the 95% CI of each study. Diamonds in black represent the overall effect size and diamond width represents the overall 95% CI.</p

Univariate analysis of potential variables influencing the test performance of perforin during AR.

a<p>Three independent data points are required at least to draw an SROC curve.</p><p>Abbreviations: DOR, diagnostic odds ratio; CI, confidence interval; AUC, area under the curve of the SROC curve; PBL, peripheral blood leukocyte; PCR, polymerase chain reaction; RT-PCR, reverse transcription polymerase chain reaction; GAPDH, glyceraldehyde-3-phosphate dehydrogenase.</p

Meta-analysis of telaprevir plus peginterferon and ribavirin therapy on SVR according to previous treatment.

<p>The proportion of achieving SVR was significantly higher in the telaprevir group than in the PR group in the previously untreated (OR = 2.25 [1.35, 3.77], <i>P</i> = 0.002; <i>I²</i> = 77%), treated (OR = 6.7 [3.35, 13.41], <i>P</i><0.001; <i>I²</i> = 71%), and overall population (OR = 3.40 [1.92, 6.00], <i>P</i><0.001; I² = 87%). OR = odds ratio, <i>I²</i> = heterogeneity index. Columns in green represent the mean difference of each study and column size represents the study weight in the analysis. Lanes represent the 95% CI of each study. Diamonds in black represent the overall effect size, and diamond width represents the overall 95% CI.</p