Genetic polymorphisms in the immune response: A focus on kidney transplantation.

The modulation of the immune system following solid organ transplantation has made considerable progress with new immunosuppressive regimens and has considerably improved rejections rates. The improvement in long-term allograft survival is, however, modest. A complex network of cytokines, chemokines, adhesion, activation and co-stimulatory molecules are the frontline contributors to allograft rejection, which in turn determines the evolution of graft function and its long-term survival. Polymorphisms in these genes influence protein levels and presumably their signaling effects. In this review, we present a relevant panel of candidate genes related to the immune system in the context of solid organ transplantation; we discuss the most convincing reports of genetic associations with outcomes in renal transplantation and highlight the most promising loci among the vast body of literature.

Finding confidence limits on population growth rates: bootstrap and analytic methods.

When predicting population dynamics, the value of the prediction is not enough and should be accompanied by a confidence interval that integrates the whole chain of errors, from observations to predictions via the estimates of the parameters of the model. Matrix models are often used to predict the dynamics of age- or size-structured populations. Their parameters are vital rates. This study aims (1) at assessing the impact of the variability of observations on vital rates, and then on model's predictions, and (2) at comparing three methods for computing confidence intervals for values predicted from the models. The first method is the bootstrap. The second method is analytic and approximates the standard error of predictions by their asymptotic variance as the sample size tends to infinity. The third method combines use of the bootstrap to estimate the standard errors of vital rates with the analytical method to then estimate the errors of predictions from the model. Computations are done for an Usher matrix models that predicts the asymptotic (as time goes to infinity) stock recovery rate for three timber species in French Guiana. Little difference is found between the hybrid and the analytic method. Their estimates of bias and standard error converge towards the bootstrap estimates when the error on vital rates becomes small enough, which corresponds in the present case to a number of observations greater than 5000 trees.