Lifespan extension by calorie restriction relies on the Sty1 MAP kinase stress pathway

Either calorie restriction, loss of function of the nutrient-dependent PKA or TOR/SCH9 pathways, or activation of stress defences improves longevity in different eukaryotes. However, the molecular links between glucose depletion, nutrient-dependent pathways and stress responses are unknown. Here we show that either calorie restriction or inactivation of nutrient-dependent pathways induces life-span extension in fission yeast, and that such effect is dependent on the activation of the stress-dependent Sty1 MAP kinase. During transition to stationary phase in glucose-limiting conditions, Sty1 becomes activated and triggers a transcriptional stress program, whereas such activation does not occur under glucose-rich conditions. Deletion of the genes coding for the SCH9-homologue Sck2 or the Pka1 kinases, or mutations leading to constitutive activation of the Sty1 stress pathway increase life span under glucose-rich conditions, and importantly such beneficial effects depend ultimately on Sty1. Furthermore, cells lacking Pka1 display enhanced oxygen consumption and Sty1 activation under glucose-rich conditions. We conclude that calorie restriction favours oxidative metabolism, reactive oxygen species production and Sty1 MAP kinase activation, and this stress pathway favours life-span extension.

Towards the Fully Automatic Merging of Lexical Resources: A Step Forward

This article reports on the results of the research done towards the fully automatically merging of lexical resources. Our main goal is to show the generality of the proposed approach, which have been previously applied to merge Spanish Subcategorization Frames lexica. In this work we extend and apply the same technique to perform the merging of morphosyntactic lexica encoded in LMF. The experiments showed that the technique is general enough to obtain good results in these two different tasks which is an important step towards performing the merging of lexical resources fully automatically.