eLife

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1. We couldn't get details of this article at this time:
   10.21203/rs.3.rs-3329601/v3

2. We couldn't get details of this article at this time:
   10.1101/2024.07.31.606111

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   10.1101/2024.09.30.615805

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   10.1101/2024.06.18.599596

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   10.1101/2024.05.01.590702

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   10.1101/2024.08.06.606748

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   10.1101/2024.10.07.616983

8. We couldn't get details of this article at this time:
   10.1101/2024.09.23.614477

9. Estimating bone marrow adiposity from head MRI and identifying its genetic architecture

   This article has 10 authors:

   1. Tobias Kaufmann
   2. Pål Marius Bjørnstad
   3. Martin Falck
   4. Stener Nerland
   5. Kevin O'Connell
   6. Oleksandr Frei
   7. Ole A Andreassen
   8. Lars T Westlye
   9. Srdjan Djurovic
   10. Timothy Hughes

   This article has been curated by 1 group:

   • Curated by eLife

     eLife Assessment

     This study introduces an artificial-intelligence tool that estimates fat in skull bone marrow from routine brain scans, enabling large studies that were previously impractical. The evidence for the method's repeatability and for identifying genetic links is convincing overall. The authors identify genes, diseases, and other biological characteristics that are linked to skull marrow fat, which represents an important advance. The work will be of most interest to researchers using large imaging biobanks and those studying ageing-related changes across bone, blood, and brain.

   Reviewed by eLife

10. We couldn't get details of this article at this time:
    10.1101/2024.07.11.603152