Plasma proteomic signature predicts who will get persistent symptoms following SARS-CoV-2 infection | Zendy

Gabriella Captur | Zendy; James Moon | Zendy; ConstantinCristian Topriceanu | Zendy; George Joy | Zendy; Leo Swadling | Zendy; Jenny Hällqvist | Zendy; Ivan Doykov | Zendy; Nina Patel | Zendy; Justyna Śpiewak | Zendy; Tomas Baldwin | Zendy; Matt Hamblin | Zendy; Katia Menacho | Zendy; Marianna Fontana | Zendy; Thomas A. Treibel | Zendy; Charlotte Manisty | Zendy; Benjamin O’Brien | Zendy; Joseph M. Gibbons | Zendy; Corrina Pade | Zendy; Tim Brooks | Zendy; Daniel M. Altmann | Zendy; Rosemary J. Boyton | Zendy; Áine McKnight | Zendy; Mala K. Maini | Zendy; Mahdad Noursadeghi | Zendy; Kevin Mills | Zendy; Wendy Heywood | Zendy

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Plasma proteomic signature predicts who will get persistent symptoms following SARS-CoV-2 infection

Author(s) -

Gabriella Captur,

James Moon,

ConstantinCristian Topriceanu,

George Joy,

Leo Swadling,

Jenny Hällqvist,

Ivan Doykov,

Nina Patel,

Justyna Śpiewak,

Tomas Baldwin,

Matt Hamblin,

Katia Menacho,

Marianna Fontana,

Thomas A. Treibel,

Charlotte Manisty,

Benjamin O’Brien,

Joseph M. Gibbons,

Corrina Pade,

Tim Brooks,

Daniel M. Altmann,

Rosemary J. Boyton,

Áine McKnight,

Mala K. Maini,

Mahdad Noursadeghi,

Kevin Mills,

Wendy Heywood

Publication year - 2022

Publication title -

ebiomedicine

Language(s) - English

Resource type - Journals

ISSN - 2352-3964

DOI - 10.1016/j.ebiom.2022.104293

Subject(s) - medicine , asymptomatic , interquartile range , seroconversion , cohort , subclinical infection , immunology , antibody , proteome , young adult , cohort study , bioinformatics , biology

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