A virtual host model of Mycobacterium tuberculosis infection identifies early immune events as predictive of infection outcomes.

Joslyn, Louis R; Linderman, Jennifer J; Kirschner, Denise E

Joslyn, Louis R; Linderman, Jennifer J; Kirschner, Denise E.

Afiliación

Joslyn LR; Department of Microbiology and Immunology, University of Michigan Medical School, 1150 W Medical Center Drive, 5641 Medical Science II, Ann Arbor, MI 48109-5620, United States; Department of Chemical Engineering, University of Michigan, G045W NCRC B28, 2800, Plymouth Rd, Ann Arbor, MI 48109-2136, United States.
Linderman JJ; Department of Chemical Engineering, University of Michigan, G045W NCRC B28, 2800, Plymouth Rd, Ann Arbor, MI 48109-2136, United States. Electronic address: linderma@umich.edu.
Kirschner DE; Department of Microbiology and Immunology, University of Michigan Medical School, 1150 W Medical Center Drive, 5641 Medical Science II, Ann Arbor, MI 48109-5620, United States. Electronic address: kirschne@umich.edu.

J Theor Biol ; 539: 111042, 2022 04 21.

Article en En | MEDLINE | ID: mdl-35114195

Asunto(s)

Mycobacterium tuberculosis; Tuberculosis; Animales; Granuloma/patología; Pulmón/microbiología; Primates

Palabras clave

Digital twins; Mechanistic modeling; Multi-scale modeling; Systems biology; T cells; Tuberculosis

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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Tuberculosis / Mycobacterium tuberculosis Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Animals Idioma: En Revista: J Theor Biol Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

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