Understanding the importance of selenium and selenoproteins in muscle function

Selenium is an essential trace element. In cattle, selenium deficiency causes dysfunction of various organs, including skeletal and cardiac muscles. In humans as well, lack of selenium is associated with many disorders, but despite accumulation of clinical reports, muscle diseases are not generally considered on the list. The goal of this review is to establish the connection between clinical observations and the most recent advances obtained in selenium biology. Recent results about a possible role of selenium-containing proteins in muscle formation and repair have been collected. Selenoprotein N is the first selenoprotein linked to genetic disorders consisting of different forms of congenital muscular dystrophies. Understanding the muscle disorders associated with selenium deficiency or selenoprotein N dysfunction is an essential step in defining the causes of the disease and obtaining a better comprehension of the mechanisms involved in muscle formation and maintenance

Impact of Agromanagement Practices on Rice Elongation: Analysis and Modelling

Plant height has a deep influence on the productivity of many crops, as it involves susceptibility to lodging, crop-weed competition, and the achievement of favorable harvest index. Nevertheless, modellers have practically ignored related ecophysiological processes, especially those modulated by management practices. The aim of this study was to analyze and model the processes involved with the effects of management on rice (Oryza sativa L.) elongation. Data were collected in two greenhouse experiments (2010-2011) where three factors (floodwater level, N fertilization, sowing density) were arranged in a split-plot design with three replicates. The model proposed demonstrated its suitability in reproducing both the dynamics involved with tissue elongation in the different phenological phases and the effects of submergence and N luxury consumption on elongation rates. Relative root mean square error (RRMSE) ranged between 4.23 and 12.41% for different treatments and years. The inclusion of algorithms for the impact of agronomic practices on plant height in cropping system models would increase their suitability for scenario analyses and for in silico ideotyping studies, owing to the great interest shown by geneticists in related traits. Moreover, this study-performed with students of a Cropping Systems MS course-demonstrated once more the power of modeling within educational activities. In this case, models were not the subject of the teaching but tools for analyzing processes and formalizing new knowledge