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Showing 1–8 of 8 results
Advanced filters: Author: Robyn J. Tapp Clear advanced filters

  • Prediabetes phenotype can influence the effectiveness of lifestyle intervention-based diabetes prevention programmes. This Perspectives suggests that diabetes prevention programmes are not effective in individuals with isolated impaired fasting glucose and calls for further research to improve prevention of type 2 diabetes mellitus in this population.

    • Matthew D. Campbell
    • Thirunavukkarasu Sathish
    • Robyn J. Tapp
    Reviews
    Nature Reviews Endocrinology
    Volume: 16, P: 395-400

  • Primary open-angle glaucoma (POAG) is highly heritable, yet not well understood from a genetic perspective. Here, the authors perform a meta-analysis of genome-wide association studies in 34,179 POAG cases, identifying 44 previously unreported risk loci and mapping effects across multiple ethnicities.

    • Puya Gharahkhani
    • Eric Jorgenson
    • Janey L. Wiggs
    ResearchOpen Access
    Nature Communications
    Volume: 12, P: 1-16

  • RETFound, a foundation model for retinal images that learns generalizable representations from unlabelled images, is trained on 1.6 million unlabelled images by self-supervised learning and then adapted to disease detection tasks with explicit labels.

    • Yukun Zhou
    • Mark A. Chia
    • Pearse A. Keane
    ResearchOpen Access
    Nature
    Volume: 622, P: 156-163

  • Thirunavukkarasu et al. discuss how standard lifestyle interventions prove ineffective in preventing type 2 diabetes in individuals with isolated impaired fasting glucose, a highly prevalent prediabetes phenotype globally. They propose low-calorie diets as a promising strategy for diabetes prevention in this high-risk population.

    • Sathish Thirunavukkarasu
    • Roy Taylor
    • Jonathan E. Shaw
    Comments & OpinionOpen Access
    Communications Medicine
    Volume: 4, P: 1-4

  • Kruper et al. investigate the impact of glaucoma on brain tissue by comparing MRI data from 856 people with glaucoma to matched controls without glaucoma. They find that neural networks using tissue properties from visual brain connections more accurately detect glaucoma than those trained on non-visual brain connections.

    • John Kruper
    • Adam Richie-Halford
    • Yalin Zheng
    ResearchOpen Access
    Communications Medicine
    Volume: 4, P: 1-10