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Across species prion transmission: the hidden side-door
Transmissible Spongiform Encephalopathies (TSEs) in mammals, better known as prion diseases, are caused by an infectious agent whose propagation ultimately leads to brain degeneration. For the first time, a team of scientists* from the French National Institute for Agricultural Research (INRA) report that while prion transmission across species may show no detectable sign of disease in brain, infection can burst in lymphatic tissues(1). These results were published in Science on 27 January 2012. 
Launch of the European research network Susfood
INRA is coordinating a new European Era-Net, Susfood, on Sustainable Food Production and Consumption. This programme involves 25 partners from 16 European countries. Its strategic goal is to reinforce the scientific cooperation between EU Member and Associated States in order to maximize the contribution of research to the development of more sustainable food systems from farm to fork.
What next for agriculture after Durban?
By 2050, the world population will reach 9 billion. Food production will have to increase substantially to meet the global needs, and this in the framework of climate change. Yet, agriculture plays an important role in climate change in several ways: it is a source of greenhouse gas (GHG) emissions through inappropriate use of fertilizer, land clearing and other practices. Thus, sustainable agriculture is needed to mitigate GHG emissions, preserve natural resources and the environment, and to ensure global food security. Marion Guillou, President of the French National Institute for Agricultural Research (INRA), along with members of an independent...
Scientists Use Artificial Intelligence to Construct Food Webs
Scientists at Rothamsted Research(1), which receives strategic funding from BBSRC(2), in collaboration with Syngenta, Imperial College London and the French National Institute for Agricultural Research (INRA) have developed an advanced technique, using a branch of artificial intelligence called Machine Learning that could greatly improve our understanding of the interaction between food and the environment.





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