Juliano Bortolini

Density measurement of Demodex canis by qPCR and analysis of serum cytokine levels in dogs with different clinical forms of demodicosis

OBJECTIVES To quantify (by qPCR) the density of Demodex canis mites in the skin of dogs with demodicosis and in healthy dogs, as well as measuring the serum concentrations of interleukin (IL)-1β, IL-6, IL-8, IL-10, IL-12, and tumour necrosis factor-alfa (TNF-α). METHODS Fifty-four dogs were divided into three groups: localized demodicosis (LD, n = 16), generalized demodicosis (GD, n = 22), and control group (CG, n = 16). All dogs were subjected to skin scraping, blood collection, and skin biopsy. DNA extraction was performed and the parasite density was established by qPCR. Serum cytokine concentrations were obtained by flow cytometry. RESULTS The median number of mites in the skin of the GD (6.2 × 104 copies/μL) and LD dogs (1.2 × 104 copies/μL) was statistically higher than that in the CG dogs (8.7 × 102 copies/μL). Whereas there were no significant differences in median IL-1β, IL-8, IL-10, IL-12, and TNF-α levels among the study groups, there was a statistically higher IL-6 concentration in the LD dogs than in the healthy dogs. CONCLUSIONS According to our results, qPCR is an effective method for measuring the density of D. canis in the canine integument. In addition, the activation of the acute-phase immune response in localized demodicosis can be induced by IL-6 activity.

Ajuste de curvas de crescimento para à produção de cana-de-açúcar

The modeling of growth curves is very common in data from repeated measures in time, because it is possible to establish a functional relationship between the time and the treatments used. The main objective of this work is to obtain a functional relationship that establishes a polynomial association between the production, in tons, and the 5 years in which 3 sugarcane genotypes had their production measured in an experiment installed in the Puerto Rico Plant, in Alagoas, conducted by UFSC. The experimental design was the randomized blocks, with 4 replicates. In these models we assume fixed mean curves, around which there are random variations for the individual curves of the respective experimental units. It was verified by the AIC and BIC criteria that the best structure is the variance component (VC) to represent the covariance matrix of the experimental and unstructured error (UN) for the covariance matrix of the random effects parameters and that the polynomial of 3rd degree was selected to represent the average relation between production and the 5 years evaluated for the three genotypes.

The Extended Generalized Gamma Geometric Distribution

We propose and study the so-called extended generalized gamma geometric distribution. The proposed distribution has five parameters and it can be accommodate increasing, decreasing, bathtub and unimodal shaped hazard functions. The new distribution has a large number of well-known lifetime special sub-models such as the generalized gamma geometric, Weibull geometric, gamma geometric, exponential geometric, Rayleigh geometric, half-normal geometric among others. We provide a mathematical treatment of the new distribution including explicit expressions for moments, moment generating function, mean deviations, reliability and order statistics. The method of maximum likelihood and a Bayesian procedure are adopted for estimating the model parameters. Finally, an application of the new distribution is illustrated in a real data sets.