Curcumin suppresses NTHi-induced CXCL5 expression via inhibition of positive IKKβ pathway and up-regulation of negative MKP-1 pathway
Bibliographic record
Abstract
Otitis media (OM) is the most common childhood bacterial infection, and leading cause of conductive hearing loss. Nontypeable Haemophilus influenzae (NTHi) is a major bacterial pathogen for OM. OM characterized by the presence of overactive inflammatory responses is due to the aberrant production of inflammatory mediators including C-X-C motif chemokine ligand 5 (CXCL5). The molecular mechanism underlying induction of CXCL5 by NTHi is unknown. Here we show that NTHi up-regulates CXCL5 expression by activating IKKβ-IκBα and p38 MAPK pathways via NF-κB nuclear translocation-dependent and -independent mechanism in middle ear epithelial cells. Current therapies for OM are ineffective due to the emergence of antibiotic-resistant NTHi strains and risk of side effects with prolonged use of immunosuppressant drugs. In this study, we show that curcumin, derived from Curcuma longa plant, long known for its medicinal properties, inhibited NTHi-induced CXCL5 expression in vitro and in vivo. Curcumin suppressed CXCL5 expression by direct inhibition of IKKβ phosphorylation, and inhibition of p38 MAPK via induction of negative regulator MKP-1. Thus, identification of curcumin as a potential therapeutic for treating OM is of particular translational significance due to the attractiveness of targeting overactive inflammation without significant adverse effects.
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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 | 0.001 |
| 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".