Dextromethorphan Attenuates NADPH Oxidase-Regulated Glycogen Synthase Kinase 3β and NF-κB Activation and Reduces Nitric Oxide Production in Group A Streptococcal Infection
Bibliographic record
Abstract
ABSTRACT Group A Streptococcus (GAS) is an important human pathogen that causes a wide spectrum of diseases, including necrotizing fasciitis and streptococcal toxic shock syndrome. Dextromethorphan (DM), an antitussive drug, has been demonstrated to efficiently reduce inflammatory responses, thereby contributing to an increased survival rate of GAS-infected mice. However, the anti-inflammatory mechanisms underlying DM treatment in GAS infection remain unclear. DM is known to exert neuroprotective effects through an NADPH oxidase-dependent regulated process. In the present study, membrane translocation of NADPH oxidase subunit p47 phox and subsequent reactive oxygen species (ROS) generation induced by GAS infection were significantly inhibited via DM treatment in RAW264.7 murine macrophage cells. Further determination of proinflammatory mediators revealed that DM effectively suppressed inducible nitric oxide synthase (iNOS) expression and NO, tumor necrosis factor alpha, and interleukin-6 generation in GAS-infected RAW264.7 cells as well as in air-pouch-infiltrating cells from GAS/DM-treated mice. GAS infection caused AKT dephosphorylation, glycogen synthase kinase-3β (GSK-3β) activation, and subsequent NF-κB nuclear translocation, which were also markedly inhibited by treatment with DM and an NADPH oxidase inhibitor, diphenylene iodonium. These results suggest that DM attenuates GAS infection-induced overactive inflammation by inhibiting NADPH oxidase-mediated ROS production that leads to downregulation of the GSK-3β/NF-κB/NO signaling pathway.
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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) | 0.001 | 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".