Triptolide Inhibits MCF-7 and HepG2 Cells Invasion and Migration by Inhibiting the Synthesis of Polylactosamine Chains
Bibliographic record
Abstract
Triptolide is a bioactive natural products isolated from Tripterygium wilfordii, a traditional Chinese herbal medicine. Clinical studies reveal that triptolide can be used in autoimmune disorders, such as rheumatoid arthritis, kidney disease and systemic lupus erythematosus. Recently, some studies revealed that triptolide has anti-tumor effects, which attracts more and more attention. This experiment aimed to explore the relationship between anti-tumor effects of triptolide and N-type polylactosamine. With increasing the concentration of triptolide, the viability of MCF-7 and HepG2 cells was reduced significantly and the polylactosamine expression on these cells declined as well. In addition, the expression of β1, 3-N-acetylglucosamine transferase (β3GnT8) participated in catalyzing the synthesis of N-type polylactosamine was also decreased and the expression of genes and proteins of downstream signaling was altered consequently. Finally, triptolide weakened the cancer cells invasion and migration. All of these indicate that triptolide can impair MCF-7 and HepG2 cells invasion and migration through downregulating the expression of polylactosamine chains. These studies establish that triptolide is a potential novel therapy in breast cancer and hepatic carcinoma
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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".