In vivo anticancer activity of maesopsin 4- O - β -glucoside isolated from leaves of Artocarpus tonkinensis A. Chev. Ex Gagnep
Bibliographic record
Abstract
OBJECTIVE: To investigate the antitumor effect of maesopsin 4-O-β-glucoside (TAT2) isolated from the leaves of Artocarpus tonkinensis (A. tonkinensis) A. Chev. ex Gagnep. METHODS: The antitumor activity of TAT2 was evaluated in Lewis lung carcinoma (LLC) tumor-bearing mice. BALB/c mice had tumors induced by implantation with 2 × 10(6) LLC cells into the subcutaneous right posterior flank. Tumor-bearing mice were treated orally with a range of doses of TAT2 and a standard drug, doxorubicin. Animals were observed for tumor growth and mortality rate. Blood was collected to determine hematological and biochemical parameters. RESULTS: TAT2 was isolated from an ethanolic extract of A. tonkinensis leaves. Its structure was determined by MS and NMR spectroscopy, and identified as TAT2. The compound did not show acute toxicity at the highest dose tested (2000 mg/kg body weight). TAT2 exhibited antitumor activity by decreasing tumor growth, increasing the survival rate, and ameliorating some hematological and biochemical parameters at doses of 100 and 200 mg/kg body weight (P < 0.05). CONCLUSIONS: These results indicate that TAT2 possesses clear antitumor activity. Due to its bioavailability and low toxicity, and the fact that it could be isolated in a large scale from A. tonkinensis leaves, the compound shows promise as a potential anticancer drug.
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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".