Mathematical modeling in assessing the risk of restenosis after carotid endarterectomy.

Carotid endarterectomy is the main way to combat atherosclerosis of the carotid arteries, which disrupts cerebral circulation. The generally accepted marker of atherogenesis risk are hemodynamic indices associated with near-wall shear stress. The purpose of the work is to conduct a comparative analysis of hemodynamic indices in various carotid bifurcation models. The influence of a virtual change in the geometric shape of the model in order to optimize hemodynamic indices is also being studied. On the basis of computed angiography data, carotid bifurcation models are constructed, in which critical zones of hemodynamic indices are built using computational fluid dynamics. A comparative analysis of the critical zones for different classes of models is carried out. Comparison of averaged indices for critical zones between 'normal' and post-operative groups gave more than 5-x worse results for the latter. The same results for the near-bifurcation parts of the zones give a 25% better result for postoperative models. Virtual 'removal' of insignificant plaques leads to a deterioration of the indices of up to 40% in the places of the plaque's former location. The described method makes it possible to build the indices critical zones and compare them for various types of models. A technique for virtual changing the shape of a vessel (virtual surgery) is proposed. The novelty of the approach lies in the use for comparative analysis both real vessel models and hypothetical 'improved' virtual ones, as well in the proposed division of post-operative model's critical zones into subzones of different genesis.

Productivity of steers of different genotypes: forecast based on interior indicators / [Produtividade de novilhos de diferentes genótipos: previsão com base em indicadores internos]

Meat productivity and quality of beef are determined by a number of factors, including pedigree traits of animals. Meat productivity is closely related to the biological patterns of their growth and development. Considering the patterns that affect meat productivity enables effective growing and fattening of livestock and obtaining commercially viable beef. To predict economically useful traits in beef cattle breeding, interior indicators can be used, as they reflect the metabolic picture of the animal's body. The research studies in physiology and biochemistry of livestock aimed at revealing the persistent mechanisms of a growing animal organism make them relevant. The article identifies a correlation between the interior indicators and the fattening indicators of three experimental groups of steers. The main forecasting factors of meat productivity indicators have been substantiated. Regression coefficients have been found and show how much the live weight varies depending on the determining factors. Meat productivity predicting procedures have been modeled with respect to the protein content in blood serum.(AU)

A produtividade e a qualidade da carne bovina são determinadas por diversos fatores, incluindo características de pedigree dos animais. A produtividade da carne tem relação íntima com os padrões biológicos de seu crescimento e desenvolvimento. A consideração dos padrões que afetam a produtividade da carne possibilita o crescimento e engorda eficazes dos rebanhos e a obtenção de carne bovina comercialmente viável. Para prever características economicamente úteis na criação de gado de corte, indicadores de interior podem ser usados, visto que refletem a imagem metabólica do corpo do animal. Tornam-se relevantes os estudos de pesquisa em fisiologia e bioquímica da pecuária com o objetivo de revelar os mecanismos persistentes de um organismo animal em crescimento. O artigo identifica uma correlação entre os indicadores internos e os indicadores de engorda de três grupos experimentais de novilhos. Os principais fatores de previsão dos indicadores de produtividade de carnes já foram comprovados. Coeficientes de regressão foram encontrados e mostram o quanto o peso vivo varia em função dos fatores determinantes. Os procedimentos de predição da produtividade da carne foram modelados em relação ao conteúdo de proteína no soro sanguíneo.(AU)