Improvement of radiation efficacy for brain cancer F98 glioma by adding concomitant platinum compounds
Bibliographic record
Abstract
Background: Free platinum formulation: cisplatin, carboplatin and oxaliplatin as well as their liposomal formulation (Lipoplatin for cisplatin and Lipoxal for oxaliplatin) are largely used as cytotoxic agents in the treatment of many tumor types. However, free platinum formulation are known to cause sever adverse reactions. In treatment against glioblastoma multiform, the development of an aggressive but selective therapy is needed. In this project, we tested different platinum compounds to identify which one shows the best synergy with radiation. Material and methods: The cytotoxicity of platinum compounds against F98 glioma cell line was assessed by colony formation assay. Cell uptake for the same cell line and platinum was measured by Induced coupled plasma mass spectrometer. After four hours exposure to platinum, cells were irradiated (1.5 to 6.6 Gy) with a 60Co source. Results: The relative cytotoxcicity induced by the five platinum formulations was oxaliplatin > Lipoxal > cisplatin > Lipoplatin > carboplatin. On the other hand, when F98 cell line incubated with platinum were irradiated, the combination index calculated and the relative potency were Lipoplatin > carboplatin > oxaliplatin > Lipoxal > cisplatin. Conclusions: In the present work, Lipoplatin shows the best cytotoxic combination with radiation to treat F98 cell line in vitro.
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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".