In Vivo Anti-Inflammatory Activity of Four Edible Cactaceae Flowers from Mexico
Bibliographic record
Abstract
Background/Objectives: The therapeutic properties of edible flowers are widely used to improve human health. The phenolic compounds present in edible flowers, such as phenols and flavonoids, among others, play an important role as effective antioxidant compounds against diseases related to oxidative stress. These compounds exhibit biological activities such as anti-ulcerogenic, antimicrobial, neuroprotective, anti-cancer, and anti-inflammatory properties. The objective of this study was to evaluate the in vivo anti-inflammatory activity of hydroethanolic extracts of four Mexican cacti flowers. Methods: A hydroethanolic extract was obtained via maceration for each cactus flower and evaluated using a model of edema induced in mouse ears by 12-O-tetradecanoylphorbol-13-acetate (TPA) as a guide for the anti-inflammatory activity. Compounds in cacti flower extracts were quantified by HPLC. Results: All of the hydroalcoholic flower extracts showed an anti-inflammatory effect. The greatest effect of inhibition of auricular edema (61.2 ± 4.23%) was observed in the group of mice treated with the Cardon extract at a dose of 3 mg/ear. This effect can be attributed to the main compounds detected by HPLC in the extract such as p-coumaric acid, catechin, kaempferol, and quercetin. These compounds are involved in the inhibition of pro-inflammatory mediators and enzymes such as cyclooxygenases and lipoxygenases. Conclusions: This preliminary evidence supports further preclinical evaluation of the Cardon flower.
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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) | 0.002 | 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".