Researchers led by Mehdi Touat (Sorbonne Université/AP-HP) and Franck Bielle (Sorbonne Université/AP-HP) working in the Genetics and Development of Brain Tumours team at the Brain Institute (Sorbonne Université/Inserm/CNRS) and the Neuro-oncology and Neuropathology departments of the Pitié-Salpêtrière Hospital AP-HP, have identified the genetic changes in certain recurrent gliomas, which are responsible for the acquisition of chemotherapy resistance. As well as its very comprehensive approach to various aspects of molecular and mechanistic analysis, the new study, published in Nature, has treated the largest sample ever explored in brain tumours.
Source: Sorbonne University
The Ka`epaoka`awela asteroid surprised the world in 2018 because it was the first object in the solar system identified to be of extrasolar origin. The researchers, Fathi Namouni of the Laboratoire Lagrange (CNRS/Observatoire de la Côte d’Azur/Université Côte d’Azur) and Helena Morais from the UNESP in Brazil, who discovered the asteroid, have now announced that it is not alone. The finding, published in MNRAS, proves that at least 19 other asteroids orbited another star before joining our solar system.
Anyone who has used YouTube sometimes has the feeling that the successive recommendations generated by the site’s algorithm seem to « confine » us in a « bubble » of similar content. CNRS researcher Camille Roth at the Centre Marc Bloch – Franco-German Research Centre for the Social Sciences (CNRS/MEAE/MESRI/BMBF),and colleagues Antoine Mazières and Telmo Menezes have now studied this phenomenon by analyzing recommendations from a thousand videos on different subjects, thereby running through half a million recommendations.
The results show that contrary to the algorithms of other platforms, which seem to promote novelty and serendipity, YouTube’s is different, generating a number of confinement phenomena. A user’s navigation based on recommendations can be seen as a movement within a network of interconnected videos: by starting out from a particular video, the recommendation network is more or less closed. In other words it leads to content that is more or less similar. What is more, the content that leads to the most confined recommendation networks also seems to revolve around the most viewed videos, or the ones with the longest viewing time. These findings were published in PLOS ONE.
Reference: PLOS ONE