MCL Plays an Anti-Inflammatory Role in<i>Mycobacterium tuberculosis</i>-Induced Immune Response by Inhibiting NF-<i>κ</i>B and NLRP3 Inflammasome Activation
Bibliographic record
Abstract
Mycobacterium tuberculosis (Mtb) remains a significant menace to global health as it induces granulomatous lung lesions and systemic inflammatory responses during active tuberculosis (TB). Micheliolide (MCL), a sesquiterpene lactone, was recently reported to have a function of relieving LPS-induced inflammatory response, but the regulative role of MCL on the immunopathology of TB still remains unknown. In this experiment, we examined the inhibitory effect of MCL on Mtb-induced inflammatory response in mouse macrophage-like cell line Raw264.7 by downregulating the activation of nuclear factor kappa B (NF- κ B) and NLRP3 inflammasome. Evidences showed that MCL decreased the secretion of Mtb-induced inflammatory cytokines (IL-1 β and TNF- α ) in a dose-dependent manner. Meanwhile, MCL dramatically suppressed Mtb-induced activation of iNOS and COX2 as well as subsequent production of NO. Furthermore, MCL inhibited Mtb-induced phosphorylation of Akt (Ser 473) in Raw264.7. According to our results, MCL plays an important role in modulating Mtb-induced inflammatory response through PI3K/Akt/NF- κ B pathway and subsequently downregulating the activation of NLRP3 inflammasome. Therefore, MCL may represent as a potential drug candidate in the adjuvant treatment of TB by regulating host immune response.
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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 | 0.000 | 0.000 |
| 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".