Antineoplastic 31-Norcycloartanones from Solanum cernuum Vell
Bibliographic record
Abstract
Triterpenoids with 31-norcycloartanone structure were isolated for the first time from the Solanum genus. Cycloeucalenone and 24-oxo-31-norcycloartanone were the main constituents of the dichloromethane extract of Solanum cernuum Vell. leaves [7% (w/w) and 1.47% (w/w)]. Both triterpenoids were tested against human tumour cell lines, and 24-oxo-31-norcycloartanone was significantly active and selective against the lung tumour cell line NCI-H460 with total growth inhibition at 1.10 microg/mL, growth inhibition 50 at 0.19 microg/mL and lethal concentration 50 at 8.43 microg/mL, while cycloeucalenone showed poor activity. A homologous series of alkanes (C25-C34), beta-sitosterol, and the xanthophyll lutein were also identified. The antiulcer activity was assayed for the dichloromethane extract. In the gastric ulcer model induced by 95% ethanol, administration of 500, 1000 and 2000 mg/kg/po dichloromethane extract gave ulcer lesion indices of, respectively, 38.2, 61.0 and 81.9%, while carbenoxolone inhibited 88.9% at 200 mg/kg. In the gastric ulcer model induced by indomethacin the dichloromethane extract showed a small percentage of lesion inhibition. The ethanol extract was also analyzed and was mainly composed of glycoalkaloids, peptides and disaccharides.
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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) | 0.001 | 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".