Radiation-induced bystander effects: Relevance for radiation protection of human and non-human biota
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this paper our current knowledge of the mechanisms underlying the induction of bystander effects by low dose low LET ionizing radiation is reviewed in the context of relevance to radiation protection issues. The question of how bystander effects may be related to observed adaptive responses, systemic genomic instability or other effects of low doses exposures is also considered. Bystander effects appear to be the result of a generalized stress response in tissues or cells. The signals may be produced by all exposed cells, but the response may require additional system parameters to exist in order to be expressed. The major response involving low LET radiation exposure discussed in the existing literature is a death response. This can manifest as apoptotic cell death, terminal differentiation, reproductive cell death or necrosis. While a death response might appear to be adverse, the position is argued in this paper, that it can in fact be protective and remove damaged cells from the reproducing population. Since many cell populations carry damaged cells without being exposed to radiation (so-called “background damage”), it is possible that low dose radiation exposures cause removal of cells damaged by agents other than the test dose of radiation. This mechanism would lead to the production of “u- or n-shaped” dose response curves. In this scenario, the level of harmful or beneficial response will be related to the background damage carried by the cell population and the genetic program determining response to damage. This model may be particularly important when attempting to predict the consequences of mixed exposures involving radiation and other environmental stressors on biota.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 it