Radiation-induced adaptive response is not seen in cell lines showing a bystander effect but is seen in lines showing HRS/IRR response
Bibliographic record
Abstract
PURPOSE: A previous study comparing the bystander effect and low-dose hypersensitivity found that they were inversely correlated. In the current study seven cell lines with established bystander effect and hyper-radiosensitivity/increased radioresistance (HRS/IRR) were further screened for the presence of an adaptive response. MATERIALS AND METHODS: Cell survival after exposure to direct radiation with or without a 0.1 Gy priming dose, was determined using the colony forming assay for seven human cell lines (HaCAT, HPV-G, SW48, T98G, U373, HGL21 and HT29). Furthermore, the impact of the bystander effect on cell survival after exposure to irradiated cell culture medium was measured concurrently. RESULTS: An adaptive response was induced in four cell lines (U373, T98G, HGL21 and HT29) causing increased cell survival. In agreement with previous publications, a bystander effect was induced in three cell lines (HPV-G, HaCAT and SW48); while no bystander effect was seen in U373, T98G, HGL21 and HT29. An adaptive response was detected in cell lines known to produce hypersensitive response, and was inversely correlated with the bystander effect. CONCLUSIONS: These results suggest that for the cell lines tested the ability to induce an adaptive response may be mutually exclusive to the bystander effect.
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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 | 0.000 | 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) | 0.005 | 0.001 |
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".