Novel dihydroartemisinin dimer containing nitrogen atoms inhibits growth of endometrial cancer cells and may correlate with increasing intracellular peroxynitrite
Bibliographic record
Abstract
Abstract In the present study, a novel dimer, SM1044, selected from a series of dihydroartemisinin (DHA) derivatives containing nitrogen atoms comprising simple aliphatic amine linkers, showed strong growth inhibition in six types of human endometrial cancer (EC) cells, with half maximal inhibitory concentration (IC 50 ) and 95% confidence interval (CI) < 3.6 (1.16~11.23) μM. SM1044 evoked apoptosis and activated caspase-3, −8 and −9 in a concentration- and time-dependent manner, and these effects were manifested early in RL95-2 compared to KLE cells, possibly correlated with the induction of intracellular ONOO − . Catalase and uric acid attenuated the growth inhibitory effects of SM1044 on EC cells, but sodium pyruvate did not. In vivo , the average xenograft tumour growth inhibition rates ranged from 35.8% to 49.9%, respectively, after 2.5 and 5.0 mg/kg SM1044 intraperitoneal treatment, and no obvious behavioural and histopathological abnormalities were observed in SM1044-treated mice in this context. SM1044 predominantly accumulated in the uteri of mice after a single injection. SM1044 displayed efficacy as a tumour suppressor with distinct mechanism of action and unique tissue distribution, properties that distinguish it from other artemisinin analogues. Our findings provide a new clue for artemisinin analogue against cancer.
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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".