Investigating the <scp>NLRP3</scp> inflammasome and its regulator <scp>miR</scp>‐223‐3p in multiple sclerosis and experimental demyelination
Bibliographic record
Abstract
Innate immune signaling pathways are essential mediators of inflammation and repair following myelin injury. Inflammasome activation has recently been implicated as a driver of myelin injury in multiple sclerosis (MS) and its animal models, although the regulation and contributions of inflammasome activation in the demyelinated central nervous system (CNS) are not completely understood. Herein, we investigated the NLRP3 (NBD-, LRR- and pyrin domain-containing protein 3) inflammasome and its endogenous regulator microRNA-223-3p within the demyelinated CNS in both MS and an animal model of focal demyelination. We observed that NLRP3 inflammasome components and microRNA-223-3p were upregulated at sites of myelin injury within activated macrophages and microglia. Both microRNA-223-3p and a small-molecule NLRP3 inhibitor, MCC950, suppressed inflammasome activation in macrophages and microglia in vitro; compared with microglia, macrophages were more prone to inflammasome activation in vitro. Finally, systemic delivery of MCC950 to mice following lysolecithin-induced demyelination resulted in a significant reduction in axonal injury within demyelinated lesions. In conclusion, we demonstrate that NLRP3 inflammasome activity by macrophages and microglia is a critical component of the inflammatory microenvironment following demyelination and represents a potential therapeutic target for inflammatory-mediated demyelinating diseases, including MS. Cover Image for this issue: https://doi.org/10.1111/jnc.15422.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".