Synthesis of 5-Alkynyltetrandrine Derivatives and Evaluation of their Anticancer Activity on A549 Cell Lines
Bibliographic record
Abstract
BACKGROUND: Lung cancer is one of the most prevalent malignancies and thus the development of novel therapeutic agents for managing lung cancer is imperative. Tetrandrine, a bis-benzyltetrahydroisoquinoline alkaloid isolated from Stephania tetrandra S. Moore, has been found to exert cytotoxic effects on cancerous cells. METHODS: A series of 5-alkynyltetrandrine derivatives was synthesized via the Sonogashira cross-coupling reactions and evaluated as potential anti-tumor agents. The anti-tumor activities of 12 compounds on lung cancer cells (A549) were evaluated using the MTT method. The population of apoptotic cells was measured using a TUNEL assay. Real-time PCR quantified the gene expression levels of Bcl-2, Bax, survivin and caspase-3. The content of Cyt-C was detected using a Human Cyt-C ELISA kit. RESULTS: Most of these compounds exhibited better activities than tetrandrine itself on A549 cells. Among them, compound 7 showed the highest cytotoxicity among the tested compounds against human lung adenocarcinoma A549 cells with an IC50 of 2.94 µM. Preliminary mechanistic studies indicated that compound 7 induced apoptosis of human lung cancer A549 cells and increased the level of the proapoptotic gene Bax, release of Cyt-C from mitochondria and activation of caspase-3 genes. CONCLUSION: The results suggest that compound 7 exerts its antitumor activity against A549 cells through the induction of the intrinsic (mitochondrial) apoptotic pathway. These findings will contribute to the future design of more effective anti-tumor agents in lung cancer therapy.
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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 | 0.001 |
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".