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Ratcliffe, S. J.

Publications and source records attributed to Ratcliffe, S. J..

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Splenic MARCO+ marginal zone macrophages regulate rapid production of MCP-1 and KC but are dispensable for alloantibody generation in response to stored RBCs in a murine model.

BACKGROUNDAlloimmunization to transfused red blood cells (RBCs) remains a significant clinical problem. However, the cells that initiate immune responses to transfused RBCs remain incompletely characterized. Recently published work has identified splenic marginal zone B (MZB) cells as being critically required for the production of anti-RBC alloantibodies in response to RBCs. In infectious models, MZB cell activation has been shown to depend on a unique population of marginal zone macrophages (MZMs). We hypothesized that MZMs would capture stored RBCs and present them to MZBs, and ultimately MZMs would be required for generation of anti-RBC alloantibodies in response to stored RBC transfusion. STUDY DESIGN AND METHODSStored GFP+ murine RBCs were utilized to determine the splenic localization and erythrophagocytosis by splenic macrophage populations. To determine the functional impact of MZMs, we compared LXR-KO mice, which have been reported to lack MZMs, with wild type mice. Both innate and adaptive immune responses to stored HOD allogenic RBC transfusion were measured in LXR-KO and wild type mice. RESULTSRBC storage leads to a significant increase in the phagocytosis of transfused RBCs by splenic MZMs. LXR-KO mice demonstrated a lack of MZMs and had significantly decreased rapid phase production of cytokines MCP-1 and KC, but similar levels of IL-6. Surprisingly, anti-RBC alloantibody levels were unaffected by the absence of splenic MZMs. CONCLUSIONSSplenic MZMs are involved in the innate response to transfused stored HOD RBCs, contributing to both MCP-1 and KC cytokine production. However, MZMs are dispensable for anti-RBC alloantibody production.

immunology↗

Cell Maps for Artificial Intelligence: AI-Ready Maps of Human Cell Architecture from Disease-Relevant Cell Lines

This article describes the Cell Maps for Artificial Intelligence (CM4AI) project and its goals, methods, standards, current datasets, software tools, status, and future directions. CM4AI is the Functional Genomics Data Generation Project in the U.S. National Institute of Healths (NIH) Bridge2AI program. Its overarching mission is to produce ethical, AI-ready datasets of cell architecture, inferred from multimodal data collected for human cell lines, to enable transformative biomedical AI research.

systems biology↗