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    The mutational landscape of ARMC5 in Primary Bilateral Macronodular Adrenal Hyperplasia: an update by Lucas Bouys, Anna Vaczlavik, Isadora P. Cavalcante, Florian Violon, Anne Jouinot, Annabel Berthon, Patricia Vaduva, Stéphanie Espiard, Karine Perlemoine, Peter Kamenicky, Marie-Christine Vantyghem, Antoine Tabarin, Gérald Raverot, Cristina L. Ronchi, Ulrich Dischinger, Martin Reincke, Maria C. Fragoso, Constantine A. Stratakis, Albain Chansavang, Eric Pasmant, Bruno Ragazzon, Jérôme Bertherat, for the COMETE and ENSAT Networks

    Published 2025-02-01
    “…The pathogenicity of ARMC5 variants is established on the basis of their frequency in the general population, in silico predictions, familial segregation and tumor DNA sequencing. Conclusions This is the first extensive review of ARMC5 pathogenic variants. …”
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    Personalized prediction of glycemic responses to food in women with diet-treated gestational diabetes: the role of the gut microbiota by Polina V. Popova, Artem O. Isakov, Anastasiia N. Rusanova, Stanislav I. Sitkin, Anna D. Anopova, Elena A. Vasukova, Alexandra S. Tkachuk, Irina S. Nemikina, Elizaveta A. Stepanova, Angelina I. Eriskovskaya, Ekaterina A. Stepanova, Evgenii A. Pustozerov, Maria A. Kokina, Elena Y. Vasilieva, Lyudmila B. Vasilyeva, Soha Zgairy, Elad Rubin, Carmel Even, Sondra Turjeman, Tatiana M. Pervunina, Elena N. Grineva, Omry Koren, Evgeny V. Shlyakhto

    Published 2025-02-01
    “…Machine learning models were created using CGM data, meal content, lifestyle factors, biochemical parameters, and microbiota data (16S rRNA gene sequence analysis). Adding microbiome data increased the explained variance in peak glycemic levels (GLUmax) from 34 to 42% and in incremental area under the glycemic curve (iAUC120) from 50 to 52%. …”
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