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Connection

Co-Authors

This is a "connection" page, showing publications co-authored by Le Shen and Romuald Girard.
Connection Strength

0.571
  1. Micro-computed tomography in murine models of cerebral cavernous malformations as a paradigm for brain disease. J Neurosci Methods. 2016 09 15; 271:14-24.
    View in: PubMed
    Score: 0.139
  2. Corrigendum to "Antibodies in cerebral cavernous malformations react with cytoskeleton autoantigens in the lesional milieu" [J. Autoimmun. 113 (2020) 102469]. J Autoimmun. 2023 Nov; 140:103116.
    View in: PubMed
    Score: 0.058
  3. Plasma metabolites with mechanistic and clinical links to the neurovascular disease cavernous angioma. Commun Med (Lond). 2023 Mar 03; 3(1):35.
    View in: PubMed
    Score: 0.055
  4. Circulating Plasma miRNA Homologs in Mice and Humans Reflect Familial Cerebral Cavernous Malformation Disease. Transl Stroke Res. 2023 08; 14(4):513-529.
    View in: PubMed
    Score: 0.053
  5. Novel Murine Models of Cerebral Cavernous Malformations. Angiogenesis. 2020 11; 23(4):651-666.
    View in: PubMed
    Score: 0.046
  6. Permissive microbiome characterizes human subjects with a neurovascular disease cavernous angioma. Nat Commun. 2020 05 27; 11(1):2659.
    View in: PubMed
    Score: 0.046
  7. Antibodies in cerebral cavernous malformations react with cytoskeleton autoantigens in the lesional milieu. J Autoimmun. 2020 09; 113:102469.
    View in: PubMed
    Score: 0.046
  8. Distinct cellular roles for PDCD10 define a gut-brain axis in cerebral cavernous malformation. Sci Transl Med. 2019 11 27; 11(520).
    View in: PubMed
    Score: 0.044
  9. Transcriptome clarifies mechanisms of lesion genesis versus progression in models of Ccm3 cerebral cavernous malformations. Acta Neuropathol Commun. 2019 08 19; 7(1):132.
    View in: PubMed
    Score: 0.043
  10. Phenotypic characterization of murine models of cerebral cavernous malformations. Lab Invest. 2019 03; 99(3):319-330.
    View in: PubMed
    Score: 0.040
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.