Three-dimensional outcomes of twin-block appliance treatment and the influence of the postured wax bite

Aims 1 To identify the 3D soft tissue volumetric and linear landmark changes following treatment with the Twin-Block Appliance TBA. 2 To estimate the TBA treatment outcome on the soft tissue facial profile volumetric and linear landmark changes from the Postured Wax Bite (PWB). 3 To identify if there is any association between certain soft tissue landmark variables and successful treatment outcome of the TBA as measured by the reduction in overjet. 4 To assess the effects of TBA treatment on facial expressions. Materials and Methods Forty-seven Caucasian subjects with Class II division 1 were recruited. 3D images captured of each subject, pre-treatment (T1), with the PWB (T2) and at the end of treatment (T3). Soft tissue volumetric and linear changes as well as the correlation between facial parameters and successful treatment were calculated. Results The mean soft tissue volumetric change from T1 to T3 was 22.24 ± 16.73 cm³. Soft tissue profile linear changes from T1-T3 for lower facial landmarks were 4-5 mm. From T1-T3, the mean soft tissue volumetric change of the total sample was 60% of the change produced by the PWB (T1 to T2). Correlations were weak for all 3D facial parameters and successful overjet reduction. Facial expression changes were only significant for the lower landmarks. Conclusions 1 TBA treatment, in growing subjects, increased the lower facial soft tissue volume and caused forward movement of the lower soft tissue facial profile landmarks.2 The PWB can be used to estimate the treatment outcome of the TBA on soft tissue profile changes.3 No association was found between soft tissue landmark variables and successful overjet reduction.4 TBA treatment had no effect on the upper facial landmarks for each facial expression but it changed the lower facial expressions significantly except for maximal smile in males.

Correlation between pre-treatment quasispecies complexity and treatment outcome in chronic HCV genotype 3a

Pre-treatment HCV quasispecies complexity and diversity may predict response to interferon based anti-viral therapy. The objective of this study was to retrospectively (1) examine temporal changes in quasispecies prior to the start of therapy and (2) investigate extensively quasispecies evolution in a group of 10 chronically infected patients with genotype 3a, treated with pegylated alpha 2a-Interferon and ribavirin. The degree of sequence heterogeneity within the hypervariable region 1 was assessed by analyzing 20-30 individual clones in serial serum samples. Genetic parameters, including amino acid Shannon entropy, Hamming distance and genetic distance were calculated for each sample. Treatment outcome was divided into (1) sustained virological responders (SVR) and (2) treatment failure (TF).Our results indicate, (1) quasispecies complexity and diversity are lower in the SVR group, (2) quasispecies vary temporally and (3) genetic heterogeneity at baseline can be used to predict treatment outcome. We discuss the results from the perspective of replicative homeostasis. We discuss the results from the perspective of replicative homeostasis.

On classical and other methods of discriminant analysis and estimation of log-odds

For two multinormal populations with equal covariance matrices the likelihood ratio discriminant function, an alternative allocation rule to the sample linear discriminant function when n1 ≠ n2 ,is studied analytically. With the assumption of a known covariance matrix its distribution is derived and the expectation of its actual and apparent error rates evaluated and compared with those of the sample linear discriminant function. This comparison indicates that the likelihood ratio allocation rule is robust to unequal sample sizes. The quadratic discriminant function is studied, its distribution reviewed and evaluation of its probabilities of misclassification discussed. For known covariance matrices the distribution of the sample quadratic discriminant function is derived. When the known covariance matrices are proportional exact expressions for the expectation of its actual and apparent error rates are obtained and evaluated. The effectiveness of the sample linear discriminant function for this case is also considered. Estimation of true log-odds for two multinormal populations with equal or unequal covariance matrices is studied. The estimative, Bayesian predictive and a kernel method are compared by evaluating their biases and mean square errors. Some algebraic expressions for these quantities are derived. With equal covariance matrices the predictive method is preferable. Where it derives this superiority is investigated by considering its performance for various levels of fixed true log-odds. It is also shown that the predictive method is sensitive to n1 ≠ n2. For unequal but proportional covariance matrices the unbiased estimative method is preferred. Product Normal kernel density estimates are used to give a kernel estimator of true log-odds. The effect of correlation in the variables with product kernels is considered. With equal covariance matrices the kernel and parametric estimators are compared by simulation. For moderately correlated variables and large dimension sizes the product kernel method is a good estimator of true log-odds.