Role of epigenetic effectors in maintenance of the long-term persistent bystander effect in spleen in vivo
Bibliographic record
Abstract
Radiation therapy is a primary treatment modality for brain tumors, yet it has been linked to the increased incidence of secondary, post-radiation therapy cancers. These cancers are thought to be linked to indirect radiation-induced bystander effect. Bystander effect occurs when irradiated cells communicate damage to nearby, non-irradiated 'bystander' cells, ultimately contributing to genome destabilization in the non-exposed cells. Recent evidence suggests that bystander effect may be epigenetic in nature; however, characterization of epigenetic mechanisms involved in bystander effect generation and its long-term persistence has yet to be defined. To investigate the possibility that localized X-ray irradiation induces persistent bystander effects in distant tissue, we monitored the induction of epigenetic changes (i.e. alterations in DNA methylation, histone methylation and microRNA (miRNA) expression) in the rat spleen tissue 24 h and 7 months after localized cranial exposure to 20 Gy of X-rays. We found that localized cranial radiation exposure led to the induction of bystander effect in lead-shielded, distant spleen tissue. Specifically, this exposure caused the profound epigenetic dysregulation in the bystander spleen tissue that manifested as a significant loss of global DNA methylation, alterations in methylation of long interspersed nucleotide element-1 (LINE-1) retrotransposable elements and down-regulation of DNA methyltransferases and methyl-binding protein methyl CpG binding protein 2 (MeCP2). Further, irradiation significantly altered expression of miR-194, a miRNA putatively targeting both DNA methyltransferase-3a and MeCP2. This study is the first to report conclusive evidence of the long-term persistence of bystander effects in radiation carcinogenesis target organ (spleen) upon localized distant exposure using the doses comparable with those used for clinical brain tumor treatments.
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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) | 0.001 | 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".