Antimicrobial, Anti-Inflammatory, Antiparasitic, and Cytotoxic Activities of<i>Laennecia confusa</i>
Bibliographic record
Abstract
The current paper investigated the potential benefit of the traditional Mexican medicinal plant Laennecia confusa (Cronquist) G. L. Nesom (Asteraceae). Fractions from the hexane, chloroform, methanol, and aqueous extracts were analyzed for antibacterial, antifungal, anti-inflammatory, and antiparasitic activities. The antimicrobial activity of the extracts and fractions was assessed on bacterial and fungal strains, in addition to the protozoa Leishmania donovani, using a microdilution assay. The propensity of the plant's compounds to produce adverse effects on human health was also evaluated using propidium iodine to identify damage to human macrophages. The anti-inflammatory activity of the extracts and fractions was investigated by measuring the secretion of interleukin-6. Chemical analyses demonstrated the presence of flavonoids, cyanogenic and cardiotonic glycosides, saponins, sesquiterpene lactones, and triterpenes in the chloroform extract. A number of extracts and fractions show antibacterial activity. Of particular interest is antibacterial activity against Staphylococcus aureus and its relative methicillin-resistant strain, MRSA. Hexanic and chloroformic fractions also exhibit antifungal activity and two extracts and the fraction CE 2 antiparasitic activity against Leishmania donovani. All bioactive extracts and fractions assayed were also found to be cytotoxic to macrophages. In addition, the hexane and methane extracts show anti-inflammatory activity by suppressing the secretion of interleukine-6.
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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 | 0.001 | 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".