Immune response deviation and enhanced expression of chemokine receptor CCR4 in TBI patients due to unknown serum factors

BACKGROUND: Severe brain trauma leads to an activation of the immune system. To this date, neither the exact perturbation of the specific immune reaction induced by the traumatic brain injury (TBI), nor the interactions leading to the infiltration of peripheral immune cells into the brain are fully understood. PATIENTS AND METHODS: Serum was collected from 17 patients with TBI and a long bone fracture, 24 patients with an isolated long bone fracture and from healthy individuals. The effect of the serum on normal human monocytes and T-lymphocytes was tested in vitro by assessing proliferation and expression of surface markers, chemokine receptors and cytokines. RESULTS: Serum collected from patients with a TBI and a long bone fracture increased the expression of the chemokine receptor CCR4 in monocytes when compared to patients with an isolated long bone fracture. Extending this comparison to T-lymphocytes, the serum from TBI patients induced lower proliferation rates and decreased expression of the pro-inflammatory cytokine TNF-alpha, while simultaneously increasing the secretion of immune-modulatory cytokines (IL-4, IL-10 and TGF-beta) (p<0.05). CONCLUSION: Patients with a TBI release currently unknown soluble factors into the circulating blood that up regulate expression of chemokine receptor CCR4 in peripheral blood monocytes whilst concurrently inducing expression of immunosuppressive cytokines by activated T-lymphocytes.

Estimating and quantifying uncertainties on level sets using the Vorob'ev expectation and deviation with Gaussian process models

Several methods based on Kriging have recently been proposed for calculating a probability of failure involving costly-to-evaluate functions. A closely related problem is to estimate the set of inputs leading to a response exceeding a given threshold. Now, estimating such a level set—and not solely its volume—and quantifying uncertainties on it are not straightforward. Here we use notions from random set theory to obtain an estimate of the level set, together with a quantification of estimation uncertainty. We give explicit formulae in the Gaussian process set-up and provide a consistency result. We then illustrate how space-filling versus adaptive design strategies may sequentially reduce level set estimation uncertainty.

Deviation of the alloimmune response toward tolerance by chimeric class I MHC molecules

Class I major histocompatibility complex (MHC) molecules induce either accelerated rejection or prolonged survival of allografts, presumably because of the presence of immunogenic or tolerogenic epitopes, respectively. To explore the molecular basis of this phenomenon, three chimeric class I molecules were constructed by substituting the rat class I RT1.A$\sp{\rm a}$ sequences with the N-terminus of HLA-A2.1 (N$\sp{\rm HLA-A2.1}$-RT1.A$\sp{\rm a}$), the $\alpha\sb1$ helix (h) with $\rm\alpha\sb{1h}\sp{u}$ sequences ( ($\rm\alpha\sb{1h}\sp{u}$) -RT1.A$\sp{\rm a}$) or the entire $\alpha\sb2$ domain (d) with $\rm\alpha\sb{2d}\sp{u}$ sequences ( ($\rm\alpha\sb{2d}\sp{u}$) -RT1.A$\sp{\rm a}$). Wild type (WT) and chimeric cDNAs were sequenced prior to transfection into Buffalo (BUF; RT1$\sp{\rm b}$) hepatoma cells. Stable transfectants were injected subcutaneously (s.c.) into different hosts 7 days prior to challenge with a heart allograft. In BUF hosts, chimeric ($\rm\alpha\sb{1h}\sp{u}$) -RT1.A$\sp{\rm a}$ accelerated the rejection of Wistar Furth (WF; RT1$\sp{\rm u}$) heart allografts, but had no effect on the survival of ACI (RT1$\sp{\rm a}$) grafts. In contrast, the ($\rm\alpha\sb{2d}\sp{u}$) -RT1.A$\sp{\rm a}$ (containing $\rm\alpha\sb{1d}\sp{a}$ sequences) immunized BUF recipients toward RT1$\sp{\rm a}$ grafts. In WF hosts, WT-RT1.A$\sp{\rm a}$ was a potent immunogen and accelerated ACI graft rejection, N$\sp{\rm HLA-A2.1}$-RT1.A$\sp{\rm a}$ was less effective and ($\rm\alpha\sb{\rm 1h}\sp{u}\rbrack$-RT1.A$\sp{\rm a}$ was not immunogenic. Thus, dominant and subdominant epitopes inducing in vivo sensitization to cardiac allografts are present in the $\alpha\sb1$ helix and the N-terminus, respectively. The failure of ($\rm\alpha\sb{2d}\sp{u}$) -RT1.A$\sp{\rm a}$ transfectants (containing recipient-type $\alpha\sb{\rm 2d}$ sequences) to sensitize WF hosts toward ACI (RT1$\sp{\rm a}$) grafts, despite the presence of donor-type immunogenic $\alpha\sb{\rm 1d}\sp{\rm a}$, suggests that "self-$\alpha\sb2$" sequences displayed on chimeric antigens interfere with immunogenicity. The ($\rm\alpha\sb{1h}\sp{u}$) -RT1.A$\sp{\rm a}$ transfectants injected s.c. prolonged the survival of WF (RT1$\sp{\rm u}$) hearts in ACI (RT1$\sp{\rm a}$) recipients. Furthermore, intra-portal injection of extracts from ($\rm\alpha\sb{1h}\sp{u}$) -RT1.A$\sp{\rm a}$, but not WT-RT1.A$\sp{\rm a}$ or RT1.A$\sp{\rm u}$, in conjunction with a brief cyclosporine course rendered ACI hosts permanently and specifically tolerant to donor-type WF cardiac allografts. Thus, immunodominant allodeterminants are present in the $\alpha\sb1$, but not the $\alpha\sb2$, domain of rat class I MHC molecules. Furthermore, the $\rm\alpha\sb{1h}\sp{u}$ immunogenic epitopes trigger tolerogenic responses when flanked by host-type N-terminal$\sp{\rm a}$ and $\rm\alpha\sb{2d}\sp{a}$ sequences. ^

Estimating the mean and standard deviation of concentration distributions using censored samples

Environmental data sets of pollutant concentrations in air, water, and soil frequently include unquantified sample values reported only as being below the analytical method detection limit. These values, referred to as censored values, should be considered in the estimation of distribution parameters as each represents some value of pollutant concentration between zero and the detection limit. Most of the currently accepted methods for estimating the population parameters of environmental data sets containing censored values rely upon the assumption of an underlying normal (or transformed normal) distribution. This assumption can result in unacceptable levels of error in parameter estimation due to the unbounded left tail of the normal distribution. With the beta distribution, which is bounded by the same range of a distribution of concentrations, $\rm\lbrack0\le x\le1\rbrack,$ parameter estimation errors resulting from improper distribution bounds are avoided. This work developed a method that uses the beta distribution to estimate population parameters from censored environmental data sets and evaluated its performance in comparison to currently accepted methods that rely upon an underlying normal (or transformed normal) distribution. Data sets were generated assuming typical values encountered in environmental pollutant evaluation for mean, standard deviation, and number of variates. For each set of model values, data sets were generated assuming that the data was distributed either normally, lognormally, or according to a beta distribution. For varying levels of censoring, two established methods of parameter estimation, regression on normal ordered statistics, and regression on lognormal ordered statistics, were used to estimate the known mean and standard deviation of each data set. The method developed for this study, employing a beta distribution assumption, was also used to estimate parameters and the relative accuracy of all three methods were compared. For data sets of all three distribution types, and for censoring levels up to 50%, the performance of the new method equaled, if not exceeded, the performance of the two established methods. Because of its robustness in parameter estimation regardless of distribution type or censoring level, the method employing the beta distribution should be considered for full development in estimating parameters for censored environmental data sets. ^