Assessment of supra-additive effects of cytotoxic drugs and low dose rate irradiation in an in vitro model for hepatocellular carcinoma
Bibliographic record
Abstract
The use of 5-fluorouracil, topotecan, or gemcitabine was tested for enhancement of the effects of low dose rate (LDR) irradiation in an in vitro model for hepatocellular carcinoma. For comparison, all drugs were tested in combination with high dose rate (HDR) gamma-irradiation as well. Multicellular spheroids of HepG2 cells were exposed to HDR or LDR irradiation by means of external beam cobalt-60 or rhenium-188 (188Re), respectively, dissolved in the culture medium. Secondly, exposure to irradiation was combined with the cytotoxic drug. Toxicity was evaluated by means of a quantitative spheroid outgrowth assay and histology. For 5-fluorouracil, supra-additive effects were observed in combination with HDR irradiation. With 188Re, the supra-additive toxicity was only transient. For topotecan and 188Re, no supra-additive effects were seen, whereas the addition of HDR irradiation at the end of the topotecan exposure yielded lasting supra-additive effects. Incubation with gemcitabine followed by exposure to HDR irradiation, induced a synergistic toxicity on the outgrowth. No supra-additive effects were observed when HDR irradiation was added at the start of the incubation with gemcitabine or combined with LDR irradiation. For all drugs tested, supra-additive effects were observed with HDR irradiation if the timing of the irradiation was appropriate. For 188Re, no lasting supra-additive effects were observed.
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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 | 0.001 |
| 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) | 0.002 | 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".