Growth curves of Nile tilapia (Oreochromis niloticus) strains cultivated at different temperatures

Growth of Red, GIFT and Supreme Nile tilapia strains were evaluated. Fish were cultivated in indoor recirculation systems in 0.5 m³ tanks with controlled temperatures of 22, 28 and 30°C. Random samples of 20 fish from each strain (10 fish tank-1) were weighed at day 7, 30, 60, 90 and 120. Exponential model (y=AeKx) and Gompertz model (y = Aexp(-Be-Kx)) were fitted and the estimates parameters were obtained by Weighted Least Squares. At 22°C, Red, GIFT and Supreme strain presented similar growth and fit of exponential model. GIFT and Supreme strain presented higher growth rate at 30°C of cultivation when compared to Red strain. Temperature influences weight and age at the inflection point. The temperature of cultivation influences the growth description of Red, GIFT and Supreme tilapia strains. It changes the age and weight at inflection point and the qualities of growth model fits, changing the variation of the batch.

Experimental model for transanal endorectal pull-through surgery. Technique of de la Torre and Ortega

Background: We describe an experimental model for transanal endorectal pull-through surgery using the method of de]a Torre and Ortega that can be used for training purposes in experimental laboratories.Methods: Ten rabbits were submitted to the transanal endorectal pull-through technique of de la Torre and Ortega. Animals were randomly selected in the Botucatu School of Medicine experimental laboratory. Animals weighted between 2800 and 4400 g. Colons were not prepared, and antibiotic therapy was not used; dipyrone(1) was administered postoperatively for analgesic purposes. We standardized resected segment size, recorded surgical time, and observed Survival and possible complications for 1 month.Results: All animals survived the initial follow-up period without infection. Bowel movements returned quickly, and all animals were evacuating regularly within the first 24 hours. Mean surgical time was 48.6 minutes.Conclusions: the experimental model proposed in this study is very useful for training and improving surgical techniques using the method of de la Torre and Ortega. The rabbit is an excellent animal for this surgery because of its size and postoperative resistance. (c) 2005 Elsevier B.V. All rights reserved.

Inferring a weighted elastic network from partial unfolding with coarse-grained simulations

A number of studies have demonstrated that simple elastic network models can reproduce experimental B-factors, providing insights into the structure-function properties of proteins. Here, we report a study on how to improve an elastic network model and explore its performance by predicting the experimental B-factors. Elastic network models are built on the experimental C coordinates, and they only take the pairs of C atoms within a given cutoff distance r(c) into account. These models describe the interactions by elastic springs with the same force constant. We have developed a method based on numerical simulations with a simple coarse-grained force field, to attribute weights to these spring constants. This method considers the time that two C atoms remain connected in the network during partial unfolding, establishing a means of measuring the strength of each link. We examined two different coarse-grained force fields and explored the computation of these weights by unfolding the native structures. Proteins 2014; 82:119-129. (c) 2013 Wiley Periodicals, Inc.

Method validation using weighted linear regression models for quantification of UV filters in water samples

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A note on model uncertainty in linear regression

We consider model selection uncertainty in linear regression. We study theoretically and by simulation the approach of Buckland and co-workers, who proposed estimating a parameter common to all models under study by taking a weighted average over the models, using weights obtained from information criteria or the bootstrap. This approach is compared with the usual approach in which the 'best' model is used, and with Bayesian model averaging. The weighted predictor behaves similarly to model averaging, with generally more realistic mean-squared errors than the usual model-selection-based estimator.