Antioxidant Polyphenols from Lespedeza bicolor Turcz. Honey: Anti-Inflammatory Effects on Lipopolysaccharide-Treated RAW 264.7 Macrophages
Bibliographic record
Abstract
Although the honey produced by Lespedeza bicolor Turcz. is precious because of its medicinal value, its pharmacological mechanism is still unclear. Here, its anti-inflammatory and antioxidant functions on lipopolysaccharide (LPS)-treated murine RAW 264.7 macrophages were analyzed using targeted and non-targeted metabolomics. Results showed that twelve polyphenols were identified in L. bicolor honey using UHPLC-QQQ-MS/MS. L. bicolor honey extract could scavenge the free radicals DPPH• and ABTS+ and reduce Fe3+. Furthermore, pretreatment with L. bicolor honey extract significantly decreased NO production; suppressed the expression of COX-2, IL-10, TNF-α, and iNOS; and upregulated HO-1′s expression in the cells with LPS application. UHPLC-Q-TOF-MS/MS-based metabolomics results revealed that L. bicolor honey extract could protect against inflammatory damage caused by LPS through the reduced activation of sphingolipid metabolism and necroptosis pathways. These findings demonstrate that L. bicolor honey possesses excellent antioxidant and anti-inflammatory activities.
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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 | 0.001 | 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".