Selection methodology of femoral stems under fatigue loading conditions

Abstract

Bioaccessibility analysis and antioxidant activity along in vitro digestion and a consumer-oriented sensory analysis were conducted in three potential functional foods based on Ca(II)-alginate beads containing bioactive compounds extracted from beet stems. Ca(II)-alginate beads per se, and two selected products (cookies and turkish delights supplemented with the beads) were prepared. Regarding the beads, among the attributes rated by consumers, visual appreciation predominates, being color in the just-as-right (JAR) category and in the like preference. Instead, both flavor and sweet taste were attributes highly penalized and should be improved in beads to be accepted as food per se. A higher percentage of customers preferred cookies and turkish delights instead of only beads, considering global satisfaction. Regarding in vitro digestion, there was a significant content of phenolic compounds in the products with beads, showing a bioaccessibility greater than 80% (for cookies) and 26% (for turkish delights). Also, the antioxidant capacity measured by ABTS ranged between 50 and 109% for cookies and turkish delights, being lower when measured by FRAP (between 20 and 30%, respectively). Thus, including the beads with beet stem extract in both products leads to a significant increase in the content of phenolic compounds and in the antioxidant capacity compared to their counterparts, protecting the compound during oral and gastric phases. These results allow the generation of improved Ca(II)-alginate systems with promising functional properties for the development of ingredients and functional foods.

Se deben conocer las propiedades de resistencia de un vástago femoral bajo carga de fatiga y la metodología propuesta en este trabajo proporciona las herramientas matemáticas para que los diseñadores de vástagos femorales y cirujanos ortopédicos seleccionen el material y el diseño del vástago femoral adecuado con un nuevo gráfico que condensa la información en un proceso de selección fácil de usar. Inicialmente, el desarrollo teórico y computacional del análisis de fatiga proporciona resultados comparables con un error medio del 8,3%. Y la metodología formulada con el objetivo de seleccionar el dispositivo mecánico con mejor comportamiento a fatiga con un error promedio del 8,7%.