Laetrile and Methotrexate: A Dual-Drug Approach to Inhibiting Cervical Cancer Cell Proliferation
Bibliographic record
Abstract
Objective: This study was done to evaluate the efficacy of laetrile methotrexate combination in inhibiting cervical cancer proliferation and identify the synergistic effects between them Method: During three incubation periods, 24, 48, and 72 hours, the antiproliferative impact of the laetrile and methotrexate combination was assessed by employing the Hela cell line, a human cervical cancer cell line. The concentration range of the tested reagent varied from 0.1 to 1000 µg/ml for each laetrile and methotrexate. At the same time, the concentration of the mixture varied from 0.05 to 500 µg/ml for both laetrile and methotrexate. The combination index value was used to identify whether there was a synergistic impact between laetrile and methotrexate in the combination. The dose reduction index was employed to ascertain the extent of the reduction in the concentration of the constituent mix, which resulted in a notable cytotoxic impact. Result: The study results revealed that the combination of laetrile and methotrexate successfully inhibited the proliferation of cervical cancer cells in a manner that depended on the concentration and duration of treatment. The combination index value exhibited a significant synergistic impact between laetrile and methotrexate in all concentrations except 1000 µg/ml. Furthermore, the dose reduction index outcomes showed that the combination minimized the required concentration of laetrile and methotrexate. Conclusion: Concerning the study findings and their defined pharmacokinetic and safety characteristics of mixture drugs. The laetrile-methotrexate mixture offers an attractive and safer option for the treatment of cervical 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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".