Actions of radiation on living cells in the “post-bystander” era
Bibliographic record
Abstract
Over the past 20 years there has been increasing evidence that cells and the progeny of cells surviving a dose of ionizing radiation can exhibit a wide range of effects inconsistent with the level of dose received. Recently, the cause of these delayed effects has been ascribed to so-called bystander effects, occurring in cells not directly hit by an ionizing track, but which are influenced by signals from irradiated cells. These effects are not necessarily deleterious, although most of the literature deals with adverse delayed effects. What is important to consider is what, if anything, these effects mean for what is still the central dogma of radiobiology and radiation protection, i.e., that DNA double-strand breaks are the primary radiation-induced lesion that can be quantifiably related to received dose, and which determine the probability that a cancer will result from a radiation exposure. In this chapter we review the history of radiation biology which led to the DNA paradigm. We explore the issues and the evidence which are now challenging the view that dose deposition in DNA is all important. We conclude that in the low-dose region, the primary determinant of radiation exposure outcome is the genetic and epigenetic background of the individual and not the dose. This effectively dissociates dose from effect as a quantitative relationship, but it does not necessarily mean that the effect is unrelated to DNA damage somewhere in the system.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".