Application of Bioelectrical Impedance Analysis (BIA) to Assess Carcass Composition and Nutrient Retention in Rabbits from 25 to 77 Days of Age.

The aim of this study was to assess and validate, using independent data, the prediction equations obtained to estimate in vivo carcass composition using bioelectrical impedance analysis (BIA) to determine the nutrient retention and overall energy and nitrogen retention efficiencies of growing rabbits. Seventy-five rabbits grouped into five different ages (25, 35, 49, 63 and 77 days) were used in the study. A four-terminal body-composition analyzer was applied to obtain resistance (Rs, Ω) and reactance (Xc, Ω) values.

Application of bioelectrical impedance analysis to assess rabbit's body composition from 25 to 77 days of age.

The aim of the study was to develop prediction equations for assessing, in vivo, the whole body composition of growing rabbits. The accuracy of the models obtained was externally validated with independent data sets. One hundred fifty rabbits grouped at 5 different ages (25, 35, 49, 63, and 77 d) were used.

[Clinical intervention of nicotine dependence from a systemic-relational focus. Results of a descriptive study of series of cases].

We present in this work a descriptive study of series of cases in treatment for nicotine addiction with a multicomponent program focusing on a systemic-relational therapy. While a good number of smokers are able to stop smoking, with the help of different programs with different levels of complexity depending on their level of addiction, there is a group of smokers who associate their difficulty to stop smoking with aspects related to their life cycle situation, problems with their family of origin or with their social network. We revised the most relevant clinical aspects of the model and presented the results of a descriptive study of a series of 128 patients, of wich 60.

Predicting average feed intake of lactating Holstein cows fed totally mixed rations.

A dry matter intake (DMI) prediction equation was estimated by using a data file that contained 124 treatment means collected from published studies. Animal factors considered for inclusion in the prediction model were body weight (BW) and its natural logarithm, BW(0.75), milk yield (MY) and its natural logarithm, milk fat and protein yields, month of lactation and its square, as well as its natural logarithm.

Evaluation of equations based on animal factors to predict intake of lactating Holstein cows.

The accuracy of seven DMI prediction equations based only on animal factors was evaluated with 11 independent data files. Mean square prediction error was used to compare equation accuracy, which was considered to be unsatisfactory when the square root of the mean square prediction error was greater than +/-20% of the observed mean DMI. Robust intake equations that have a tolerable level of prediction errors for most data files would be less risky for practical use than models that are highly accurate for some data files but highly inaccurate for others.