NOD-Like Receptor Protein 3 Inflammasome-Dependent IL-1β Accelerated ConA-Induced Hepatitis
Bibliographic record
Abstract
Autoimmune hepatitis (AIH) is a progressive inflammatory disorders of unknown etiology, characterized by immune-mediated destruction of hepatocytes and massive production of cytokines. Interleukin-1β is a pleiotropic proinflammatory cytokine and well known to be critical in a variety of autoimmune diseases. However, the role of interleukin-1β (IL-1β) in AIH is still indistinct. Here, we first investigated the significance of NOD-like receptor protein 3 (NLRP3) inflammasome-dependent IL-1β in the pathogenesis of AIH with a murine model of immune-mediated hepatitis induced by Concanavalin A (ConA). In ConA-treated mice, pathogenic elevated NLRP3, Cleaved caspase-1 and IL-1β levels, as well as an inflammatory cell death known as pyroptosis predominantly occurred in the livers. Strikingly, NLRP3-/- and caspase-1-/- mice were broadly protected from hepatitis as determined by decreased histological liver injury, serum aminotransferase (ALT)/aspartate transaminase (AST) levels and pyroptosis. In vivo intervention with recombinant human interleukin-1 receptor antagonist (rhIL-1Ra) strongly suppressed ConA-induced hepatitis by decreasing tumor necrosis factor-alpha (TNF-α) and interleukin-17 (IL-17) secretion, and inflammatory cell infiltration into livers. Additionally, rhIL-1Ra-pretreated mice developed significantly reduced NLRP3 inflammasome activation and reactive oxygen species (ROS) generation. Scavenging of ROS by N-acetyl-cysteine (NAC) also attenuated NLRP3 inflammasome activation and liver inflammation, indicating that the essential role of ROS in mediating NLRP3 inflammasome activation in ConA-induced hepatitis. In conclusion, our results demonstrated that NLRP3 inflammasome-dependent IL-1β production was crucial in the pathogenesis of ConA-induced hepatitis, which shed light on the development of promising therapeutic strategies for AIH by blocking NLRP3 inflammasome and IL-1β.
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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) | 0.001 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".