Rhynchophylline Attenuates LPS‐induced Pro‐inflammatory Responses through Down‐regulation of MAPK/NF‐κB Signaling Pathways in Primary Microglia
Bibliographic record
Abstract
Excessive activation of microglial cells has been implicated in various types of neuroinflammation. Suppression of microglial activation would have therapeutic benefits, leading to the alleviation of the progression of neurodegeneration. In this study, the inhibitory effects of rhynchophylline (RIN), a tetracyclic oxindole alkaloid component isolated from Uncaria rhynchophylla (Miq.) Jacks., on the production of pro-inflammatory mediators were investigated in lipopolysaccharide (LPS)-stimulated microglia. The results showed that RIN markedly reduced the production of nitric oxide (NO), prostaglandins E(2) (PGE(2) ), monocyte chemoattractant protein (MCP-1), tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β) in LPS-activated microglia. The mRNA expression levels of iNOS and COX-2 were also depressed by RIN in a concentration-dependent manner. Further studies revealed that RIN blocked IκBα phosphorylation and degradation, inhibited the phosphorylation of mitogen-activated protein kinases (MAPKs). In summary, these data suggest that RIN suppresses inflammatory responses of microglia and may act as a potential therapeutic agent for various neurodegenerative diseases involving neuroinflammation.
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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) | 0.001 | 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".