Radiation‐induced bystander effects in vivo are epigenetically regulated in a tissue‐specific manner
Bibliographic record
Abstract
Exposure of animal body parts to ionizing radiation (IR) can lead to molecular changes in distant shielded "bystander" tissues and organs. Nevertheless, tissue specificity of bystander responses within the same organism has not been examined in detail. Studies on in vivo bystander effect conducted so far analyzed changes induced by single-dose exposure. The potential of fractionated irradiation to induce bystander effects in vivo has never been studied. We analyzed changes in global DNA methylation and microRNAome in skin and spleen of animals subjected to single-dose (acute or fractionated) whole-body or cranial exposure to 0.5 Gy of X-rays. We found that IR-induced DNA methylation changes in bystander spleen and skin were distinct. Acute radiation exposure resulted in a significant loss of global DNA methylation in the exposed and bystander spleen 6 hr, 96 hr, and 14 days after irradiation. Fractionated irradiation led to hypomethylation in bystander spleen 6 hr after whole-body exposure, and 6 hr, 96 hr, and 14 days after cranial irradiation. Contrarily, changes in the skin of the same animals were seen only 6 hr after acute whole-body and head exposure. DNA hypomethylation observed in spleen was paralleled by a reduction of methyl-binding protein MeCP2 expression. Irradiation also induced tissue-specific microRNAome alterations in skin and spleen. For the first time, we have shown that IR-induced epigenetic bystander effects that occur in the same organism are triggered by both acute and fractionated exposure and are very distinct in different bystander organs. Future studies are clearly needed to address organismal and carcinogenic repercussions of those changes.
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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".