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1. BIOLOGIE
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2.6 ETIOLOGIE - ENVIRONNEMENT
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2.7 ETIOLOGIE - OBÉSITÉ
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A new genetic test can offer clues — and only clues — to a person’s risk of obesity [STAT]
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Built by a team of Harvard-affiliated researchers, the score looks to be more powerful than any past genetic test for obesity. But there’s no commercial version of it yet. And it remains to be seen whether it’ll be powerful enough to be useful in the clinic, as a way to inform adults why they’re heavy or to identify high-risk children and intervene before they become obese.
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Calculating genetic risk for obesity [Broad Institute]
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“DNA is not destiny. We know that a healthy lifestyle can offset a genetic predisposition, although those with a high genetic risk likely have to work much harder to maintain a normal weight. Prevention strategies could be especially impactful early in life for these individuals.”
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3. PRÉVENTION
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3.1 PRÉVENTION - TABAC
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4.7 DÉP., DIAG. & PRONO. - COL DE L'UTÉRUS
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5.1 TRAITEMENTS - PRÉ-CLINIQUE
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5.12.5 IMMUNOTHÉRAPIES - PHARMA
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Roche throws in the towel on Tecentriq bladder, myeloma trials [Fierce Pharma]
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Roche’s Tecentriq has scored some important victories lately, including a pair of first-in-class approvals. But in other types of cancer, the Swiss drugmaker has decided to pull the plug. In a Wednesday update to its pharma pipeline, Roche listed two phase 1 Tecentriq studies—one in non-muscle invasive bladder cancer and one in multiple myeloma—that it had cast aside.
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5.2 PHARMA
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5.4 TRAITEMENTS - ECONOMIE
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5.6 ESMO
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6.11 PATIENTS
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Many young cancer patients regret initial treatment decisions [Reuters]
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Researchers surveyed 203 cancer patients, ages 15 to 29, within six weeks of their diagnosis to ask about their decision-making preferences and experiences. They checked back with these young patients again after four months and one year to see if their feelings about treatment decisions changed over time.
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6.12 ETHIQUE
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6.7.1 IA/BIOINFORMATIQUE
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Farewell to “Watson For Drug Discovery” [In The Pipeline]
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IBM specifically sold the system as being ready to use for target identification, pathway elucidation, prediction of gene and protein function and regulation, drug repurposing, and so on. And it just wasn’t ready for those challenges, especially as early as they were announcing that they were.
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National experts chart roadmap for AI in medical imaging [NIH]
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The report describes innovations that would help to produce more publicly available, validated and reusable data sets against which to evaluate new algorithms and techniques, noting that to be useful for machine learning these data sets require methods to rapidly create labeled or annotated imaging data.
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6.9 CONTROVERSES
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‘Friendly’ reviewers rate grant applications more highly [Nature]
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The study examined more than 38,000 reviews from nearly 13,000 Swiss National Science Foundation (SNSF) grant applications by about 27,000 peer reviewers from all disciplines between 2006 and 2016. The authors found that reviewers nominated by applicants were more likely to give these applicants higher evaluation scores than referees chosen by the SNSF.
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