Enhanced Antitumor Effect of Combined Triptolide and Ionizing Radiation
Bibliographic record
Abstract
PURPOSE: The lack of effective treatment for pancreatic cancer results in a very low survival rate. This study explores the enhancement of the therapeutic effect on human pancreatic cancer via the combination of triptolide and ionizing radiation (IR). EXPERIMENTAL DESIGN: In vitro AsPC-1 human pancreatic cancer cells were treated with triptolide alone, IR alone, or triptolide plus IR. Cell proliferation was analyzed with sulforhodamine B (SRB) method and clonogenic survival; comparison of apoptosis induced by the above treatment was analyzed by annexin V-propidium iodide (PI) staining. Furthermore, the expression of apoptotic pathway intermediates was measured by the assay of caspase activity and Western blot. Mitochondrial transmembrane potential was determined by JC-1 assay. In vivo, AsPC-1 xenografts were treated with 0.25 mg/kg triptolide, 10 Gy IR, or triptolide plus IR. The tumors were measured for volume and weight at the end of the experiment. Tumor tissues were tested for terminal nucleotidyl transferase-mediated nick end labeling (TUNEL) and immunohistochemistry. RESULTS: The combination of triptolide plus IR reduced cell survival to 21% and enhanced apoptosis, compared with single treatment. In vivo, tumor growth of AsPC-1 xenografts was reduced further in the group treated with triptolide plus IR compared with single treatment. TUNEL and immunohistochemistry of caspase-3 cleavage in tumor tissues indicated that the combination of triptolide plus IR resulted in significantly enhanced apoptosis compared with single treatments. CONCLUSIONS: Triptolide in combination with ionizing radiation produced synergistic antitumor effects on pancreatic cancer both in vitro and in vivo and seems promising in the combined modality therapy of pancreatic 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".