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1.
J Immunol ; 2017 Aug 09.
Artículo en Inglés | MEDLINE | ID: mdl-28794234

RESUMEN

Application of high-content immune profiling technologies has enormous potential to advance medicine. Whether these technologies reveal pertinent biology when implemented in interventional clinical trials is an important question. The beneficial effects of preoperative arginine-enriched dietary supplements (AES) are highly context specific, as they reduce infection rates in elective surgery, but possibly increase morbidity in critically ill patients. This study combined single-cell mass cytometry with the multiplex analysis of relevant plasma cytokines to comprehensively profile the immune-modifying effects of this much-debated intervention in patients undergoing surgery. An elastic net algorithm applied to the high-dimensional mass cytometry dataset identified a cross-validated model consisting of 20 interrelated immune features that separated patients assigned to AES from controls. The model revealed wide-ranging effects of AES on innate and adaptive immune compartments. Notably, AES increased STAT1 and STAT3 signaling responses in lymphoid cell subsets after surgery, consistent with enhanced adaptive mechanisms that may protect against postsurgical infection. Unexpectedly, AES also increased ERK and P38 MAPK signaling responses in monocytic myeloid-derived suppressor cells, which was paired with their pronounced expansion. These results provide novel mechanistic arguments as to why AES may exert context-specific beneficial or adverse effects in patients with critical illness. This study lays out an analytical framework to distill high-dimensional datasets gathered in an interventional clinical trial into a fairly simple model that converges with known biology and provides insight into novel and clinically relevant cellular mechanisms.

2.
J Immunol ; 197(11): 4482-4492, 2016 12 01.
Artículo en Inglés | MEDLINE | ID: mdl-27793998

RESUMEN

Preterm labor and infections are the leading causes of neonatal deaths worldwide. During pregnancy, immunological cross talk between the mother and her fetus is critical for the maintenance of pregnancy and the delivery of an immunocompetent neonate. A precise understanding of healthy fetomaternal immunity is the important first step to identifying dysregulated immune mechanisms driving adverse maternal or neonatal outcomes. This study combined single-cell mass cytometry of paired peripheral and umbilical cord blood samples from mothers and their neonates with a graphical approach developed for the visualization of high-dimensional data to provide a high-resolution reference map of the cellular composition and functional organization of the healthy fetal and maternal immune systems at birth. The approach enabled mapping of known phenotypical and functional characteristics of fetal immunity (including the functional hyperresponsiveness of CD4+ and CD8+ T cells and the global blunting of innate immune responses). It also allowed discovery of new properties that distinguish the fetal and maternal immune systems. For example, examination of paired samples revealed differences in endogenous signaling tone that are unique to a mother and her offspring, including increased ERK1/2, MAPK-activated protein kinase 2, rpS6, and CREB phosphorylation in fetal Tbet+CD4+ T cells, CD8+ T cells, B cells, and CD56loCD16+ NK cells and decreased ERK1/2, MAPK-activated protein kinase 2, and STAT1 phosphorylation in fetal intermediate and nonclassical monocytes. This highly interactive functional map of healthy fetomaternal immunity builds the core reference for a growing data repository that will allow inferring deviations from normal associated with adverse maternal and neonatal outcomes.


Asunto(s)
Linfocitos T CD4-Positivos/inmunología , Linfocitos T CD8-positivos/inmunología , Inmunidad Innata/fisiología , Células Asesinas Naturales/inmunología , Placenta/inmunología , Embarazo/inmunología , Quinasas MAP Reguladas por Señal Extracelular/inmunología , Femenino , Humanos , Proteínas Gestacionales/inmunología , Factor de Transcripción STAT1/inmunología
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