Phytochemical Screening and Bioactivities of Cactaceae Family Members Endemic to Mexico
Bibliographic record
Abstract
Mexico is a center of diversification for the Cactaceae family, with 69% of the species recorded as endemic. Certain members of the Cactaceae family have been chemically analyzed to relate their medicinal use with their phytochemistry. Here, the phytochemistry and bioactivity of ethanol extracts of Ferocactus echidne, F. latispinus, and Mammillaria geminispina were evaluated. A preliminary phytochemical analysis was performed, detecting the presence of saponins, tannins, cardiotonic glycosides, and sesquiterpene lactones. The presence of nicotinic acid in F. echidne and F. latispinus was identified by GC-MS. Other compounds found in the extracts of these three species were gentisic acid, diosmetin, chlorogenic acid, N-methyltyramide, and hordenine. The antioxidant activity was estimated with the DPPH free radical scavenging test. To determine the toxicity of the extracts, the in vivo model of Artemia spp. was used. In addition, the cytotoxicity of the extract was tested on C6, HaCaT, THP-1, and U937 cell lines, while the inflammatory activity was tested by measuring the secretion of cytokines using macrophage cells. The three species showed different bioactivities, including antioxidant, antimicrobial, cytotoxic, and anti-inflammatory activities. To the best of our knowledge, the results presented here are the first described for these species.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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".