Acne treatment: research progress and new perspectives.

Acne is a chronic inflammatory skin disease that primarily affects adolescents and is attributed to various factors, including hormonal changes, genetic predisposition, and environmental influences. It typically manifests in areas rich in sebaceous glands such as the face, chest, and back. Symptoms of acne can range from mild to severe and may present as pimples, pustules, nodules, cysts, and scarring. The appearance of acne can significantly impact both the physical and mental well-being of patients, potentially leading to feelings of anxiety, depression, and social withdrawal. The pathogenesis of acne is multifaceted involving genetic predisposition as well as environmental factors such as hormonal imbalances, inflammation, abnormal follicular sebaceous unit keratinization, proliferation of follicular microorganisms like Propionibacterium acnes, increased sebum production, and dietary influences. Traditional treatment methods for acne include topical drug therapy, oral drug therapy, photoelectric therapy, and chemical peeling. With ongoing research into the pathogenesis of acne, treatment methods are rapidly evolving with novel antibiotics, probiotics, biological agents, topical anti-androgen drugs, topical vitamin A acid metabolism blockers, antimicrobial peptides, immunotherapy, micro-needling, and micro-needling patches. This article aims to provide a comprehensive review of recent advancements in acne treatment.

The stratified win statistics (win ratio, win odds, and net benefit).

The win odds and the net benefit are related directly to each other and indirectly, through ties, to the win ratio. These three win statistics test the same null hypothesis of equal win probabilities between two groups. They provide similar p-values and powers, because the Z-values of their statistical tests are approximately equal. Thus, they can complement one another to show the strength of a treatment effect. In this article, we show that the estimated variances of the win statistics are also directly related regardless of ties or indirectly related through ties. Since its introduction in 2018, the stratified win ratio has been applied in designs and analyses of clinical trials, including Phase III and Phase IV studies. This article generalizes the stratified method to the win odds and the net benefit. As a result, the relations of the three win statistics and the approximate equivalence of their statistical tests also hold for the stratified win statistics.

Win statistics (win ratio, win odds, and net benefit) can complement one another to show the strength of the treatment effect on time-to-event outcomes.

Conventional analyses of a composite of multiple time-to-event outcomes use the time to the first event. However, the first event may not be the most important outcome. To address this limitation, generalized pairwise comparisons and win statistics (win ratio, win odds, and net benefit) have become popular and have been applied to clinical trial practice. However, win ratio, win odds, and net benefit have typically been used separately. In this article, we examine the use of these three win statistics jointly for time-to-event outcomes. First, we explain the relation of point estimates and variances among the three win statistics, and the relation between the net benefit and the Mann-Whitney U statistic. Then we explain that the three win statistics are based on the same win proportions, and they test the same null hypothesis of equal win probabilities in two groups. We show theoretically that the Z-values of the corresponding statistical tests are approximately equal; therefore, the three win statistics provide very similar p-values and statistical powers. Finally, using simulation studies and data from a clinical trial, we demonstrate that, when there is no (or little) censoring, the three win statistics can complement one another to show the strength of the treatment effect. However, when the amount of censoring is not small, and without adjustment for censoring, the win odds and the net benefit may have an advantage for interpreting the treatment effect; with adjustment (e.g., IPCW adjustment) for censoring, the three win statistics can complement one another to show the strength of the treatment effect. For calculations we use the R package WINS, available on the CRAN (Comprehensive R Archive Network).

Design of paediatric trials with benefit-risk endpoints using a composite score of adverse events of interest (AEI) and win-statistics.

A fundamental problem in the regulatory evaluation of a therapy is assessing whether the benefit outweighs the associated risks. This work proposes designing a trial that assesses a composite endpoint consisting of benefit and risk, hence, making the core of the design of the study, to assess benefit and risk. The proposed benefit risk measure consists of efficacy measure(s) and a risk measure that is based on a composite score obtained from pre-defined adverse events of interest (AEI). This composite score incorporates full aspects of adverse events of interest (i.e. the incidence, severity, and duration of the events). We call this newly proposed score the AEI composite score. After specifying the priorities between the components of the composite endpoint, a win-statistic (i.e. win ratio, win odds, or net benefit) is used to assess the difference between treatments in this composite endpoint. The power and sample size requirements of such a trial design are explored via simulation. Finally, using Dupixent published adult study results, we show how we can design a paediatric trial where the primary outcome is a composite of prioritized outcomes consisting of efficacy endpoints and the AEI composite score endpoint. The resulting trial design can potentially substantially reduce sample size compared to a trial designed to assess the co-primary efficacy endpoints, therefore it may address the challenge of slow enrollment and patient availability for paediatric studies.

The win odds: statistical inference and regression.

Generalized pairwise comparisons and win statistics (i.e., win ratio, win odds and net benefit) are advantageous in analyzing and interpreting a composite of multiple outcomes in clinical trials. An important limitation of these statistics is their inability to adjust for covariates other than by stratified analysis. Because the win ratio does not account for ties, the win odds, a modification that includes ties, has attracted attention. We review and combine information on the win odds to articulate the statistical inferences for the win odds. We also show alternative variance estimators based on the exact permutation and bootstrap as well as statistical inference via the probabilistic index. Finally, we extend multiple-covariate regression probabilistic index models to the win odds with a univariate outcome. As an illustration we apply the regression models to the data in the CHARM trial.

Evidence synthesis analysis with prioritized benefit outcomes in oncology clinical trials.

Overall survival, progression-free survival, objective response/complete response, and duration of (complete) response are frequently used as the primary and secondary efficacy endpoints for designs and analyses of oncology clinical trials. However, these endpoints are typically analyzed separately. In this article, we introduce an evidence synthesis approach to prioritize the benefit outcomes by applying the generalized pairwise comparisons (GPC) method, and use win statistics (win ratio, win odds and net benefit) to quantify treatment benefit. Under the framework of GPC, the main advantage of this evidence synthesis approach is the ability to combine relevant outcomes of various types into a single summary statistic without relying on any parametric assumptions. It is particularly relevant since health authorities and the pharmaceutical industry are increasingly incorporating structured quantitative methodologies in their benefit-risk assessment. We apply this evidence synthesis approach to an oncology phase 3 study in first-line renal cell carcinoma to assess the overall effect of an investigational treatment by ranking the most clinically relevant endpoints in cancer drug development. This application and a simulation study demonstrate that the proposed approach can synthesize the evidence of treatment effect from multiple prioritized benefit outcomes, and has substantial advantage over conventional methods that analyze each individual endpoint separately. We also introduce a newly developed R package WINS for statistical inference based on win statistics.

Adjusting win statistics for dependent censoring.

For composite outcomes whose components can be prioritized on clinical importance, the win ratio, the net benefit and the win odds apply that order in comparing patients pairwise to produce wins and subsequently win proportions. Because these three statistics are derived using the same win proportions and they test the same hypothesis of equal win probabilities in the two treatment groups, we refer to them as win statistics. These methods, particularly the win ratio and the net benefit, have received increasing attention in methodological research and in design and analysis of clinical trials. For time-to-event outcomes, however, censoring may introduce bias. Previous work has shown that inverse-probability-of-censoring weighting (IPCW) can correct the win ratio for bias from independent censoring. The present article uses the IPCW approach to adjust win statistics for dependent censoring that can be predicted by baseline covariates and/or time-dependent covariates (producing the CovIPCW-adjusted win statistics). Theoretically and with examples and simulations, we show that the CovIPCW-adjusted win statistics are unbiased estimators of treatment effect in the presence of dependent censoring.

The inverse-probability-of-censoring weighting (IPCW) adjusted win ratio statistic: an unbiased estimator in the presence of independent censoring.

The win ratio method has received much attention in methodological research, ad hoc analyses, and designs of prospective studies. As the primary analysis, it supported the approval of tafamidis for the treatment of cardiomyopathy to reduce cardiovascular mortality and cardiovascular-related hospitalization. However, its dependence on censoring is a potential shortcoming. In this article, we propose the inverse-probability-of-censoring weighting (IPCW) adjusted win ratio statistic (i.e., the IPCW-adjusted win ratio statistic) to overcome censoring issues. We consider independent censoring, common censoring across endpoints, and right censoring. We develop an asymptotic variance estimator for the logarithm of the IPCW-adjusted win ratio statistic and evaluate it via simulation. Our simulation studies show that, as the amount of censoring increases, the unadjusted win proportions may decrease greatly. Consequently, the bias of the unadjusted win ratio estimate may increase greatly, producing either an overestimate or an underestimate. We demonstrate theoretically and through simulation that the IPCW-adjusted win ratio statistic gives an unbiased estimate of treatment effect.

The win ratio: Impact of censoring and follow-up time and use with nonproportional hazards.

The win ratio has been studied methodologically and applied in data analysis and in designing clinical trials. Researchers have pointed out that the results depend on follow-up time and censoring time, which are sometimes used interchangeably. In this article, we distinguish between follow-up time and censoring time, show theoretically the impact of censoring on the win ratio, and illustrate the impact of follow-up time. We then point out that, if the treatment has long-term benefit from a more important but less frequent endpoint (eg, death), the win ratio can show that benefit by following patients longer, avoiding masking by more frequent but less important outcomes, which occurs in conventional time-to-first-event analyses. For the situation of nonproportional hazards, we demonstrate that the win ratio can be a good alternative to methods such as landmark survival rate, restricted mean survival time, and weighted log-rank tests.

[High expression of DNMT3B promotes proliferation and invasion of hepatocellular carcinoma cells via Hippo signaling pathway].

OBJECTIVE: To explore the role of DNMT3B in regulating the proliferation and invasion of hepatocellular carcinoma (HCC) cells. METHODS: We collected the tumor tissues and adjacent tissues from a total of 175 patients with HCC diagnosed in the Second Affiliated Hospital of Chongqing Medical University between May, 2008 and May, 2013 to prepare the tissue microarrays. The association of the expression of DNMT3B with the prognosis and the tumor-free survival and tumor-specific survival rates of the patients was analyzed. Univariate and multivariate Cox regression analyses were used to analyze the effect of DNMT3B expression on the prognosis of HCC. We used RNA interference technique to knock down the expression of DNMT3B in Huh-7 hepatoma cells and observed the changes in cell proliferation using CCK-8 assay and EDU staining and in cell migration and invasion ability using Transwell assay. RESULTS: The positive rates of DNMT3B was significantly higher in HCC tissues than in paired adjacent tissues (67.4% vs 41.1%, P=0.015). A high DNMT3B expression in HCC was significantly associated with the tumor size (P=0.001), vascular invasion (P=0.004), and intrahepatic metastasis (P=0.018). The patients with high DNMT3B expressions had significantly lower tumor-free and tumor-specific survival rates than those with low DNMT3B expressions (P < 0.005). In Huh-7 cells, silencing DNMT3B significantly inhibited the cell proliferation and inhibited cell migration and invasion. Western blotting showed that silencing DNMT3B obviously increased LATS1 expression, decreased the expression of YAP1, and activated Hippo signaling pathway. Methylation-specific PCR showed that the methylation level of LATS1 was decreased in the cells with DNMT3B silencing. CONCLUSIONS: The expression level of DNMT3B is significantly higher HCC tissues than in the adjacent tissues, and the high expression of DNMT3B is closely related to the low survival rate of the patients. Silencing DNMT3B inhibits the proliferation, migration and invasion of HCC cells. DNMT3B promotes the progression of HCC primarily by enhancing the expression of YAP1 through methylation of LATS1 and inhibition of its expression, which inhibits the anti-cancer effect of Hippo signaling pathway.

The stratified win ratio.

The win ratio was first proposed in 2012 by Pocock and his colleagues to analyze a composite endpoint while considering the clinical importance order and the relative timing of its components. It has attracted considerable attention since then, in applications as well as methodology. It is not uncommon that some clinical trials require a stratified analysis. In this article, we propose a stratified win ratio statistic in a similar way as the Mantel-Haenszel stratified odds ratio, derive a general form of its variance estimator with a plug-in of existing or potentially new variance/covariance estimators of the number of wins for the two treatment groups, and assess its statistical performance using simulation studies. Our simulations show that our proposed Mantel-Haenszel-type stratified win ratio performs similarly to the Mantel-Haenszel stratified odds ratio for the simplified situation when the win ratio reduces to the odds ratio, and our proposed stratified win ratio is preferred compared to the inverse-variance weighted win ratio and unweighted win ratio particularly when the data are sparse. We also formulate a homogeneity test following Cochran's approach that assesses whether the stratum-specific win ratios are homogeneous across strata, as this method is used frequently in meta-analyses and a better test for the win ratio homogeneity is not available yet.

Effect of Early Everolimus-Facilitated Reduction of Tacrolimus on Efficacy and Renal Function in De Novo Liver Transplant Recipients: 24-Month Results for the North American Subpopulation.

BACKGROUND: A recent randomized phase III study of 719 de novo liver transplant recipients showed that early everolimus plus reduced-dose tacrolimus (EVR + rTAC) led to significantly better kidney function than standard TAC (TAC-C), without compromising efficacy. In that study, patients from North America (n = 211) had increased risk factors for posttransplant renal insufficiency at study start, relative to patients from Europe and rest of world (eg, worse renal function, more diabetes, older age). METHODS: A post hoc analysis was performed to assess whether these regional disparities affected study outcomes in North American patients. RESULTS: In this subpopulation, estimated glomerular filtration rates at randomization were higher in TAC-C over EVR + rTAC (76.4 vs 69.3 mL/min per 1.73 m). Mean changes in estimated glomerular filtration rate values (mL/min per 1.73 m) favored EVR + rTAC over TAC-C at months 12 (+3.7 vs -4.5; P = 0.032), 24 (+2.7 vs -6.6; P = 0.042), and 36 (+4.3 vs -8.1; P = 0.059). The composite efficacy endpoint of treated biopsy-proven acute rejection, graft loss, or death was 10.9%, 14.1%, and 14.1% for EVR + rTAC and 13.1%, 17.2%, and 19.3% for TAC-C at months 12, 24, and 36, respectively. CONCLUSIONS: Although the North American cohort had more comorbidities, results were consistent with the overall population for efficacy and renal function.

A generalized analytic solution to the win ratio to analyze a composite endpoint considering the clinical importance order among components.

A composite endpoint consists of multiple endpoints combined in one outcome. It is frequently used as the primary endpoint in randomized clinical trials. There are two main disadvantages associated with the use of composite endpoints: a) in conventional analyses, all components are treated equally important; and b) in time-to-event analyses, the first event considered may not be the most important component. Recently Pocock et al. (2012) introduced the win ratio method to address these disadvantages. This method has two alternative approaches: the matched pair approach and the unmatched pair approach. In the unmatched pair approach, the confidence interval is constructed based on bootstrap resampling, and the hypothesis testing is based on the non-parametric method by Finkelstein and Schoenfeld (1999). Luo et al. (2015) developed a close-form variance estimator of the win ratio for the unmatched pair approach, based on a composite endpoint with two components and a specific algorithm determining winners, losers and ties. We extend the unmatched pair approach to provide a generalized analytical solution to both hypothesis testing and confidence interval construction for the win ratio, based on its logarithmic asymptotic distribution. This asymptotic distribution is derived via U-statistics following Wei and Johnson (1985). We perform simulations assessing the confidence intervals constructed based on our approach versus those per the bootstrap resampling and per Luo et al. We have also applied our approach to a liver transplant Phase III study. This application and the simulation studies show that the win ratio can be a better statistical measure than the odds ratio when the importance order among components matters; and the method per our approach and that by Luo et al., although derived based on large sample theory, are not limited to a large sample, but are also good for relatively small sample sizes. Different from Pocock et al. and Luo et al., our approach is a generalized analytical method, which is valid for any algorithm determining winners, losers and ties. Copyright © 2016 John Wiley & Sons, Ltd.

A modified varying-stage adaptive phase II/III clinical trial design.

Conventionally, adaptive phase II/III clinical trials are carried out with a strict two-stage design. Recently, a varying-stage adaptive phase II/III clinical trial design has been developed. In this design, following the first stage, an intermediate stage can be adaptively added to obtain more data, so that a more informative decision can be made. Therefore, the number of further investigational stages is determined based upon data accumulated to the interim analysis. This design considers two plausible study endpoints, with one of them initially designated as the primary endpoint. Based on interim results, another endpoint can be switched as the primary endpoint. However, in many therapeutic areas, the primary study endpoint is well established. Therefore, we modify this design to consider one study endpoint only so that it may be more readily applicable in real clinical trial designs. Our simulations show that, the same as the original design, this modified design controls the Type I error rate, and the design parameters such as the threshold probability for the two-stage setting and the alpha allocation ratio in the two-stage setting versus the three-stage setting have a great impact on the design characteristics. However, this modified design requires a larger sample size for the initial stage, and the probability of futility becomes much higher when the threshold probability for the two-stage setting gets smaller. Copyright © 2016 John Wiley & Sons, Ltd.

Do patient characteristics influence efficacy and renal outcomes in liver transplant patients receiving everolimus?

Data from the 24-month randomized, multicenter, open-label H2304 study in 719 de novo liver transplant recipients were analyzed to evaluate the influence of variables potentially affecting immunological or renal response: recipient age, gender, end-stage disease, hepatitis C virus (HCV) status, and Model for End-stage Liver Disease score and estimated glomerular filtration rate (eGFR) at randomization (day 30). Treated BPAR was similar between everolimus with reduced tacrolimus (EVR + Reduced TAC) vs. conventional tacrolimus-based therapy (TAC Control) in all subpopulations, with a trend to lower risk under everolimus with reduced tacrolimus (EVR + Reduced TAC) in patients < 60 yrs and HCV-negative recipients. Risk of graft loss or death was similar in both treatment groups for all subpopulations. The change in eGFR to month 24 showed a benefit for EVR + Reduced TAC vs. TAC Control in all subpopulations other than those with the lowest baseline eGFR (30 to < 55 mL/min/1.73 m(2)), with a significant difference in favor of EVR + Reduced TAC for younger recipients (< 60 yr), female patients, HCV-negative patients and those with baseline eGFR of 55 to < 70 mL/min/1.73 m(2). Everolimus with reduced tacrolimus maintains efficacy to at least two yr after liver transplantation even in patients with risk factors for rejection, with particular renal benefits in specific patient subpopulations.

Three-year Outcomes in De Novo Liver Transplant Patients Receiving Everolimus With Reduced Tacrolimus: Follow-Up Results From a Randomized, Multicenter Study.

BACKGROUND: Data are lacking regarding the long-term effect of preemptive conversion to everolimus from calcineurin inhibitors early after liver transplantation to avoid renal deterioration. METHODS: In a prospective, multicenter, open-label study, de novo liver transplant patients were randomized at day 30 to (i) everolimus + reduced exposure tacrolimus (EVR + Reduced TAC), (ii) everolimus + tacrolimus elimination (TAC Elimination), or (iii) standard exposure tacrolimus (TAC Control). RESULTS: Randomization to TAC Elimination was terminated prematurely due to a higher rate of treated biopsy-proven acute rejection (tBPAR) during TAC withdrawal. Of 370 patients who completed the 24-month core study on-treatment, 282 (76.2%) entered an additional 12-month extension phase. The composite efficacy failure endpoint (tBPAR, graft loss or death) occurred in 11.5% of EVR+Reduced TAC patients versus 14.6% TAC Controls from randomization to month 36 (difference, -3.2%; 95% confidence interval, -10.5% to 4.2%; P = 0.334). Treated BPAR occurred in 4.8% versus 9.2% of patients (P = 0.076). From randomization to month 36, mean (SD) estimated glomerular filtration rate decreased by 7.0 (31.3) mL/min per 1.73 m in the EVR+Reduced TAC group, and 15.5 (22.7) mL/min per 1.73 m in the TAC Control group (P = 0.005). Rates of adverse events, serious adverse events, and discontinuation due to adverse events were similar in both groups during the extension. CONCLUSIONS: A clinically relevant renal benefit after introduction of everolimus with reduced-exposure tacrolimus at 1 month after liver transplantation was maintained to 3 years in patients who continued everolimus therapy to the end of the core study, with comparable efficacy and no late safety concerns.

Fibrosis progression in maintenance liver transplant patients with hepatitis C recurrence: a randomised study of everolimus vs. calcineurin inhibitors.

BACKGROUND & AIMS: Robust clinical data evaluating fibrosis progression in hepatitis C virus (HCV) liver transplant patients receiving an mTOR inhibitor vs. calcineurin inhibitor (CNI) are lacking. To evaluate fibrosis progression in maintenance liver transplant patients receiving everolimus- or CNI-based immunosuppression. METHODS: In a randomised, multicentre, open-label study, 43 maintenance liver transplant patients with recurrent HCV infection were randomised to continue CNI-based immunosuppression or switch to everolimus. RESULTS: For patients with biopsy data at month 12, mean Ishak-Knodell fibrosis score at baseline was 2.6 ± 0.9 (n = 14) with everolimus vs. 1.9 ± 1.1 (n = 18) with CNI (P = 0.043), and 1.9 ± 1.2 vs. 2.2 ± 1.3 at month 12. Ishak-Knodell fibrosis score decreased from baseline to month 12 by a mean of -0.7 ± 1.1 with everolimus, but increased by 0.2 ± 1.2 with CNI (P = 0.046). No acute rejection or graft losses occurred up to month 12. Estimated GFR at month 12 was 65.6 ml/min/1.73 m² with everolimus and 62.2 ml/min/1.73 m² with CNI [mean difference 3.4 ml/min/1.73 m² compared to CNI control group, 95% CI -4.9, 11.8 ml/min/1.73 m², P = 0.411 (analysis of covariance adjusting for baseline GFR)]. Adverse events occurred in 95.5% of everolimus patients and 71.4% of CNI patients (serious adverse events 31.8% and 0.0%, respectively). Adverse events led to everolimus discontinuation in five patients (22.7%). CONCLUSIONS: This exploratory study suggests that conversion from CNI to everolimus reduces progression of liver fibrosis, and preserves renal function without jeopardising efficacy in liver transplant recipients with recurrent HCV, but is associated with a higher incidence of adverse events and serious adverse events. These preliminary findings merit examination in a larger trial.

A varying-stage adaptive phase II/III clinical trial design.

Currently, adaptive phase II/III clinical trials are typically carried out with a strict two-stage design. The first stage is a learning stage called phase II, and the second stage is a confirmatory stage called phase III. Following phase II analysis, inefficacious or harmful dose arms are dropped, then one or two promising dose arms are selected for the second stage. However, there are often situations in which researchers are in dilemma to make 'go or no-go' decision and/or to select 'best' dose arm(s), as data from the first stage may not provide sufficient information for their decision making. In this case, it is challenging to follow a strict two-stage plan. Therefore, we propose a varying-stage adaptive phase II/III clinical trial design, in which we consider whether there is a need to have an intermediate stage to obtain more data, so that a more informative decision could be made. Hence, the number of further investigational stages in our design is determined on the basis of data accumulated to the interim analysis. With respect to adaptations, we consider dropping dose arm(s), switching another plausible endpoint as the primary study endpoint, re-estimating sample size, and early stopping for futility. We use an adaptive combination test to perform final analyses. By applying closed testing procedure, we control family-wise type I error rate at the nominal level of α in the strong sense. We delineate other essential design considerations including the threshold parameters and the proportion of alpha allocated in the two-stage versus three-stage setting.

Intercellular adhesion molecular-1, Fas, and Fas ligand as diagnostic biomarkers for acute allograft rejection of pancreaticoduodenal transplantation in pigs.

BACKGROUND: The early diagnosis of pancreas allograft dysfunction is crucial for the management and long-term survival of transplanted pancreases. We investigated whether intercellular adhesion molecular-1 (ICAM-1), Fas, and Fas ligand (FasL) can be used as novel biomarkers of acute pancreaticoduodenal allograft dysfunction in pigs. METHODS: Forty outbred landraces were randomly divided into three groups. In the control group (8 pigs), a sham operation was performed but no drugs were administered. In groups 1 and 2 (8 pairs each), pancreaticoduodenal transplantation was performed, with the latter administered immunosuppressive drugs and the former not administered drugs. The expression of ICAM-1, Fas, and FasL mRNA in the peripheral vein blood was assessed by flow cytometry and RT-PCR, pre-transplant and on days 1, 3, 5, and 7 after transplantation. Simultaneously, the levels of glucose, insulin, and glucagon in the serum of the recipients were evaluated. The allograft pancreas tissue was obtained to assess the pathological damage and the expression of Fas and FasL by immunohistochemistry. RESULTS: On the first 7 days after transplantation, ICAM-1, Fas, and FasL mRNA expression in the blood leukocytes of the recipient increased significantly in groups 1 and 2 compared with the control group (P < 0.01). However, the levels in group 2 were significantly lower than those in group 1 (P < 0.05). Interestingly, the FasL expression increased but the Fas expression decreased gradually in the graft pancreas tissue during the first week after transplantation in both groups 1 and 2 compared with the control group (P < 0.05). The levels of serous glucose, insulin, and glucagon in groups 1 and 2 obviously changed on day 1 after transplantation but returned to normal on day 2. The recipient's pancreas pathological sections did not exhibit any rejection changes on days 1 and 3 after transplantation but showed rejection damage on days 5 and 7. CONCLUSION: ICAM-1, Fas, and FasL were found to be sensitive biomarkers of acute pancreas allograft dysfunction after pancreaticoduodenal transplantation in pigs, and their monitoring could be used to evaluate the effectiveness of the immunosuppression therapy.

Association between gene polymorphisms of IRAK-M and the susceptibility of sepsis.

The aim of this study was to explore the association between the single-nucleotide polymorphisms of interleukin-1 receptor-associated kinase-M (IRAK-M) gene and the susceptibility of sepsis. The allele frequency and genotype distribution of IRAK-M gene polymorphisms were assessed in 118 controls and 82 sepsis patients by semiquantitative polymerase chain reaction and restriction fragment length polymorphism (RFLP) analysis. The plasma levels of tumor necrosis factor alpha (TNF-α) and interleukin 6 (IL-6) were detected by enzyme-linked immunosorbent assay. Associations between IRAK-M polymorphisms and the susceptibility of sepsis were analyzed by Cox regression. Data were analyzed by the χ(2) test and the Student's t test, whenever appropriate. Statistical calculations were performed by using statistical package SPSS version 18.0. The genotype distribution of IRAK-M+22148 polymorphism significantly differed between the sepsis and control groups (P < 0.0001). The frequency of the G allele was remarkably more common in the sepsis group than that of the control group (P < 0.0001). However, the frequency of the A allele was significantly less common in the sepsis group than that of control group (P < 0.0001). Moreover, the plasma levels (in picograms per milliliter) of TNF-α and IL-6 in patients with G/G genotype were greatly higher than those with A/A genotype after lipopolysaccharide stimulation (P < 0.05). The genetic polymorphism of IRAK-M+22148 G>A is associated with the susceptibility of sepsis. The G/G genotype of IRAK-M increases the risk of developing sepsis, and the A/A genotype may play a protective role in the process of developing sepsis.