Differential Molecular Stress Responses to Low Compared to High Doses of Ionizing Radiation in Normal Human Fibroblasts
Bibliographic record
Abstract
Understanding the mechanisms producing low dose ionizing radiation specific biological effects represents one of the major challenges of radiation biology. Although experimental evidence does suggest that various molecular stress response pathways may be involved in the production of low dose effects, much of the detail of those mechanisms remains elusive. We hypothesized that the regulation of various stress response pathways upon irradiation may differ from one another in complex dose-response manners, causing the specific and subtle low dose radiation effects. In the present study, the transcription level of 22 genes involved in stress responses were analyzed using RT-qPCR in normal human fibroblasts exposed to a range of gamma-doses from 1 to 200 cGy. Using the alkali comet assay, we also measured the level of DNA damages in dose-response and time-course experiments. We found non-linear dose responses for the repair of DNA damage after exposure to gamma-radiation. Alterations in gene expression were also not linear with dose for several of the genes examined and did not follow a single pattern. Rather, several patterns could be seen. Our results suggest a complex interplay of various stress response pathways triggered by low radiation doses, with various low dose thresholds for different genes.
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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) | 0.002 | 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".