Plant Natural Products Calycosin and Gallic Acid Synergistically Attenuate Neutrophil Infiltration and Subsequent Injury in Isoproterenol-Induced Myocardial Infarction: A Possible Role for Leukotriene B4 12-Hydroxydehydrogenase?
Bibliographic record
Abstract
Leukotriene B4 12-hydroxydehydrogenase (LTB4DH) catalyzes the oxidation of proinflammatory LTB4 into less bioactive 12-oxo-LTB4. We recently discovered that LTB4DH was induced by two different natural products in combination. We previously isolated gallic acid from Radix Paeoniae through a bioactivity-guided fractionation procedure. The purpose of this study is to test the hypothesis that LTB4DH inducers may suppress neutrophil-mediated inflammation in myocardial infarction. We first isolated the active compound(s) from another plant, Radix Astragali, by the similar strategy. By evaluating LTB4DH induction, we identified calycosin and formononetin from Radix Astragali by HPLC-ESI-MS technique. We confirmed that gallic acid and commercial calycosin or formononetin could synergistically induce LTB4DH expression in HepG2 cells and human neutrophils. Moreover, calycosin and gallic acid attenuated the effects of LTB4 on the survival and chemotaxis of neutrophil cell culture. We further demonstrated that calycosin and gallic acid synergistically suppressed neutrophil infiltration and protected cardiac integrity in the isoproterenol-induced mice model of myocardial infarction. Calycosin and gallic acid dramatically suppressed isoproterenol-induced increase in myeloperoxidase (MPO) activity and malondialdehyde (MDA) level. Collectively, our results suggest that LTB4DH inducers (i.e., calycosin and gallic acid) may be a novel combined therapy for the treatment of neutrophil-mediated myocardial injury.
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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) | 0.001 | 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".