Recurrent aphthous stomatitis (RAS) is a common painful, ulcerative oral inflammatory disorder with unknown aetiology. Immune system and aberrant cytokine cascade deemed to be critical in outbreaks of RAS ulcers. Interleukin-1 (IL-1) and IL-6 are the most potent pro-inflammatory cytokines. Single nucleotide polymorphisms (SNPs) of IL-1 and IL-6 genes can affect the secretion of these cytokines. The aim of this study was to investigate the association between RAS and IL-6 and IL-1 in Iranian subjects with minor RAS. Genomic DNA was obtained from 64 Iranian patients with RAS. IL-1α C -889 T, IL-1β C -511 T, IL-1β C +3962 T, IL-1R C pst-I 1970 T, IL-1Ra C Mspa-I11100 T, IL-6 C -174 G and IL-6 A nt +565 G polymorphisms were determined using polymerase chain reaction with sequence-specific primers (PCR-SSP). The frequency of C -174 C genotype in the patients group was significantly different from the healthy control. No other significant differences were found in genotype and alleles frequencies between the two groups. These results indicate that certain SNPs of IL-6 gene at position -174 which located in promoter have association with predisposition of individuals to RAS.

Gneiting (2002) proposed a nonseparable covariance model for spatial-temporal data. In present paper we show that in certain circumstances his model possesses a counterintuitive "dimple", which detracts from its modelling appeal.

Bayesian closed-skew Gaussian inversion is defined as a generalization of traditional Bayesian Gaussian inversion, which is used frequently in seismic amplitude-versus-offset ͑AVO͒ inversion. The new model captures skewness in the variables of interest; hence, the posterior model for log-transformed elastic material properties given seismic AVO data might be a skew probability density function. The model is analytically tractable, and this makes it applicable in high-dimensional 3D inversion problems.Assessment of the posterior models in high dimensions requires numerical approximations, however. The Bayesian closed-skew Gaussian inversion approach has been applied on real elastic material properties from a well in the Sleipner field in the North Sea. A comparison with results from traditional Bayesian Gaussian inversion shows that the mean square error of predictions of P-wave and S-wave velocities are reduced by a factor of two, although somewhat less for density predictions.

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