ArticleFrontiers in immunology2026
Amplification cycles through innate lymphoid cells at the onset of lupus nephritis.
Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Global research landscape and emerging trends of tertiary lymphoid structures in autoimmune diseases: a bibliometric analysis.Frontiers in immunology · 2026Pooled it
- Decoding cellular population dynamics through mechanistic modelling and statistical data analysis.NPJ systems biology and applications · 2026Review
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Authors and funding
6 authors.
Funding
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Abstract
Disease progression in autoimmune conditions such as systemic lupus erythematosus (SLE) is highly heterogeneous, and the cellular and molecular mechanisms driving disease-onset dynamics remain incompletely understood. Here, based on single-cell transcriptomics data on lupus-prone NZB/W F1 mice, we derived a mathematical cell-cell interaction model recapitulating early dynamics of innate immune cells in lupus nephritis. We identified a diverse landscape of tissue-associated ILC and vessel-associated NK cell populations. We conceived a scalable mathematical framework for analysis of immune-cell interaction dynamics. A specific model formulation considers ILC as amplifiers of inflammatory processes in the presence of autoantibodies in lupus-prone individuals. Systematic model analyses highlight the impact of positive feedback loops and spontaneous inflammatory events or environmental stimuli, and the timing-dependent effectiveness of depletion therapies. Additionally, our model links the critical role of ILC populations to hallmarks of SLE such as highly heterogeneous disease dynamics. Overall, our findings lay the groundwork towards a mathematical model of immune-tissue cellular crosstalk, enabling quantification of disease severity and prediction of responses to biologic treatments in autoimmune diseases.
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Registered trials
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