Filter By:

Journal Check one or more journals to show results from those journals only.

Choose more journals

Article type Check one or more article types to show results from those article types only.
Subject Check one or more subjects to show results from those subjects only.
Date Choose a date option to show results from those dates only.

Custom date range

Clear all filters
Sort by:
Showing 1–7 of 7 results
Advanced filters: Author: Jonathan A. Roco Clear advanced filters
  • Vinuesa et al. identify patients with systemic autoimmunity and a TNIP1 variant that result in dysregulated B cell function. Mice with the orthologous Tnip1 mutation develop spontaneous autoimmunity associated with impaired mitophagy and autophagic silencing of proteins downstream of Toll-like receptor 7 signaling.

    • Arti Medhavy
    • Vicki Athanasopoulos
    • Carola G. Vinuesa
    ResearchOpen Access
    Nature Immunology
    Volume: 25, P: 1678-1691
  • The genome of Ectocarpus siliculosis, a model for the study of brown algae, has been sequenced. These seaweeds are complex photosynthetic organisms that have adapted to rocky coastal environments. Genome analysis sheds light on this adaptation, revealing an extended set of light-harvesting and pigment biosynthesis genes, and new metabolic processes such as halide metabolism. Comparative analyses are also significant with respect to the evolution of multicellularity in plants, animals and brown algae.

    • J. Mark Cock
    • Lieven Sterck
    • Patrick Wincker
    ResearchOpen Access
    Nature
    Volume: 465, P: 617-621
  • Function-altering variants of immune-related genes cause rare autoimmune syndromes, whereas their contribution to common autoimmune diseases remains uncharacterized. Here the authors show that rare variants of lupus-associated genes are present in the majority of lupus patients and healthy controls, but only the variants found in lupus patients alter gene function.

    • Simon H. Jiang
    • Vicki Athanasopoulos
    • Carola G. Vinuesa
    ResearchOpen Access
    Nature Communications
    Volume: 10, P: 1-12
  • Patrick Stumpf et al. use a machine learning technique called transfer learning to compare bone marrow cell-type information between mice and humans, based on single-cell RNA-seq data. Using their model, they identify aspects of cellular expression profiles that transfer and those that don’t, which can be used to understand when mouse models of human disease are appropriate.

    • Patrick S. Stumpf
    • Xin Du
    • Ben D. MacArthur
    ResearchOpen Access
    Communications Biology
    Volume: 3, P: 1-11