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Dynamic balance of pro- and anti-inflammatory signals controls disease and limits pathology.
Cicchese, Joseph M; Evans, Stephanie; Hult, Caitlin; Joslyn, Louis R; Wessler, Timothy; Millar, Jess A; Marino, Simeone; Cilfone, Nicholas A; Mattila, Joshua T; Linderman, Jennifer J; Kirschner, Denise E.
Afiliação
  • Cicchese JM; Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA.
  • Evans S; Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI, USA.
  • Hult C; Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA.
  • Joslyn LR; Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI, USA.
  • Wessler T; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
  • Millar JA; Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA.
  • Marino S; Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI, USA.
  • Cilfone NA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
  • Mattila JT; Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI, USA.
  • Linderman JJ; Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA.
  • Kirschner DE; Department of Infectious Diseases and Microbiology, University of Pittsburgh, Pittsburgh, PA, USA.
Immunol Rev ; 285(1): 147-167, 2018 09.
Article em En | MEDLINE | ID: mdl-30129209
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Tuberculose / Modelos Imunológicos / Biologia Computacional / Inflamação / Pulmão / Mycobacterium tuberculosis Tipo de estudo: Prognostic_studies Limite: Animals / Humans Idioma: En Revista: Immunol Rev Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Tuberculose / Modelos Imunológicos / Biologia Computacional / Inflamação / Pulmão / Mycobacterium tuberculosis Tipo de estudo: Prognostic_studies Limite: Animals / Humans Idioma: En Revista: Immunol Rev Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos