ReviewFrontiers in immunology2026
α2-3-sialylated glycosphingolipids in neuroinflammation, immunity, and programmed cell death: mechanistic evidence and context-dependent regulation: a comprehensive review.
Review in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
α2-3-sialylated glycosphingolipids (α2-3-GSLs) are major constituents of neuronal membranes and lipid rafts, where they shape receptor compartmentalization, signal-complex assembly, and cell-cell communication. Their biological effects, however, vary by molecular subtype, cell type, disease stage, concentration, and local microenvironment. This review synthesizes evidence on spatiotemporal alterations in α2-3-GSL profiles and their relationships to neuroinflammation, immune responses, proteostasis, and programmed cell death across Parkinson's disease, Alzheimer's disease, Huntington's disease, multiple sclerosis, and Guillain-Barré syndrome. Particular attention is given to GM1, GD1a, and GD3 and to mechanisms involving TLR4/NF-κB, PI3K/AKT, autophagy-lysosomal function, complement, damage-associated molecular patterns (DAMPs) recognition, and death-receptor signaling. Evidence is stratified into relatively well-supported, model-specific or incomplete, and conceptually inferred mechanisms. On this basis, we propose a lipid-inflammation-immunity-cell death framework that organizes potentially shared downstream processes while explicitly retaining disease-specific differences. This framework is not a validated universal causal pathway; rather, it provides an analytical structure for identifying evidence gaps and testable hypotheses. Disease-specific and parallel cross-disease studies, coupled with spatial lipidomics,
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