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Macrophages are subject to a wide range of cytokine and pathogen signals in vivo, which contribute to differential activation and modulation of inflammation. Understanding the response to multiple, often-conflicting cues that macrophages experience requires a network perspective. In this study, we integrate data from literature curation and mRNA expression profiles obtained from wild type C57/BL6J mice macrophages to develop a large-scale computational model of the macrophage signaling network. In response to stimulation across all pairs of nine cytokine inputs, the model predicted activation along the classic M1-M2 polarization axis but also a second axis of macrophage activation that distinguishes unstimulated macrophages from a mixed phenotype induced by conflicting cues. Along this second axis, combinations of conflicting stimuli, IL-4 with LPS, IFN-γ, IFN-β, or TNF-α, produced mutual inhibition of several signaling pathways, e.g., NF-κB and STAT6, but also mutual activation of the PI3K signaling module. In response to combined IFN-γ and IL-4, the model predicted genes whose expression was mutually inhibited, e.g., iNOS or Nos2 and Arg1, or mutually enhanced, e.g., Il4rα and Socs1, validated by independent experimental data. Knockdown simulations further predicted network mechanisms underlying functional cross-talk, such as mutual STAT3/STAT6-mediated enhancement of Il4rα expression. In summary, the computational model predicts that network cross-talk mediates a broadened spectrum of macrophage activation in response to mixed pro- and anti-inflammatory cytokine cues, making it useful for modeling in vivo scenarios.Circulating nonadherent monocytes can migrate to extravascular sites by a process that involves adherence. Alterations in intracellular metabolism shape the immunological phenotype of phagocytes upon activation. To determine the effect of adherence on their metabolic and functional response human monocytes were stimulated with LPS under nonadherent and adherent conditions. Adherent monocytes (relative to nonadherent monocytes) produced less TNF and IL-1β (proinflammatory) and more IL-10 (anti-inflammatory) upon LPS stimulation and had an increased capacity to phagocytose and produce reactive oxygen species. RNA sequencing analysis confirmed that adherence modified the LPS-induced response of monocytes, reducing expression of proinflammatory genes involved in TLR signaling and increasing induction of genes involved in pathogen elimination. Adherence resulted in an increased glycolytic response as indicated by lactate release, gene set enrichment, and [13C]-glucose flux analysis. To determine the role of glycolysis in LPS-induced immune responses, this pathway was inhibited by glucose deprivation or the glucose analogue 2-deoxy-d-glucose (2DG). Although both interventions equally inhibited glycolysis, only 2DG influenced monocyte functions, inhibiting expression of genes involved in TLR signaling and pathogen elimination, as well as cytokine release. 2DG, but not glucose deprivation, reduced expression of genes involved in oxidative phosphorylation. Inhibition of oxidative phosphorylation affected TNF and IL-10 release in a similar way as 2DG. Collectively, these data suggest that adherence may modify the metabolic and immunological profile of monocytes and that inhibition of glycolysis and oxidative phosphorylation, but not inhibition of glycolysis alone, has a profound effect on immune functions of monocytes exposed to LPS.Donor-derived lymphocytes from allogeneic hematopoietic cell transplantation (allo-HCT) or donor lymphocyte infusion can mediate eradication of host tumor cells in a process labeled the graft-versus-tumor (GVT) effect. Unfortunately, these treatments have produced limited results in various types of leukemia because of an insufficient GVT effect. In this context, molecular engineering of donor lymphocytes to increase the GVT effect may benefit cancer patients. Activating MyD88 signaling in CD8+ T cells via TLR enhances T cell activation and cytotoxicity. However, systemic administration of TLR ligands to stimulate MyD88 could induce hyperinflammation or elicit protumor effects. To circumvent this problem, we devised a synthetic molecule consisting of MyD88 linked to the ectopic domain of CD8a (CD8αMyD88). We used this construct to test the hypothesis that MyD88 costimulation in donor CD8+ T cells increases tumor control following allo-HCT in mice by increasing T cell activation, function, and direct tumor cytotoxicity. Indeed, an increase in both in vitro and in vivo tumor control was observed with CD8αMyD88 T cells. This increase in the GVT response was associated with increased T cell expansion, increased functional capacity, and an increase in direct cytotoxic killing of the tumor cells. However, MyD88 costimulation in donor CD8+ T cells was linked to increased yet nonlethal graft-versus-host disease in mice treated with these engineered CD8+ T cells. read more Given these observations, synthetic CD8αMyD88 donor T cells may represent a unique and versatile approach to enhance the GVT response that merits further refinement to improve the effectiveness of allo-HCT.
The coronavirus disease (COVID-19) pandemic has affected stroke care globally. In this study, we aim to evaluate the impact of the current pandemic on racial disparities among stroke patients receiving mechanical thrombectomy (MT).
We used the prospectively collected data in the Stroke Thrombectomy and Aneurysm Registry from 12 thrombectomy-capable stroke centers in the US and Europe. We included acute stroke patients who underwent MT between January 2017 and May 2020. We compared baseline features, vascular risk factors, location of occlusion, procedural metrics, complications, and discharge outcomes between patients presenting before (before February 2020) and those who presented during the pandemic (February to May 2020).
We identified 2083 stroke patients of those 235 (11.3%) underwent MT during the COVID-19 pandemic. Compared with pre-pandemic, stroke patients who received MT during the pandemic had longer procedure duration (44 vs 38 min, P=0.006), longer length of hospitalization (6 vs 4 days, P<0.
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