Epigenetic and genotoxic effects of tritium in marine mussels: Comparing waterborne and metal-associated forms
Bibliographic record
Abstract
Tritium ( 3 H), an isotope of hydrogen, is a by-product of the nuclear industry. Decommissioning and normal operations of nuclear facilities can generate tritiated stainless steel particles (T-SSPs) that could be unintentionally released into the environment. Considering tritium’s physicochemical properties and the proximity of nuclear facilities to water bodies, assessing the behaviour and potential effects of these particles in the aquatic environment is imperative. In the present study, the marine mussels, Mytilus galloprovincialis were exposed to: (a) hydrogenated, non-radioactive stainless steel particles (H-SSPs) (10 mg L -1 ) (b) T-SSPs (1 and 10 MBq L -1 ) and (c) tritiated water (HTO) (0.50 and 5.0 MBq L -1 ) for 5 h and 7 d. Exposure to T-SSPs resulted in significant DNA damage in mussel haemocytes. Tritium bioaccumulation was significantly higher in the digestive gland (DG), regardless of the exposure duration to T-SSPs. Positive correlation between tritium in DG tissues and DNA indicates that tritium is internalised in the cell. After 7 d, global DNA methylation increased in gills exposed to both 1 MBq L -1 of T-SSPs and 5 MBq L -1 of HTO treatments. In the DG tissue, DNA methylation increased following exposure to tritium (water and particulate forms) compared to H-SSPs, suggesting a tissue-specific and pollutant-dependent response. Our findings highlight the enhanced bioaccumulation of T-SSPs compared to HTO. Multivariate analyses of the results suggested an overall stress response in mussels exposed to T-SSPs compared to HTO exposure and controls. Potential epigenetic effects will require more attention as they can bring knowledge across levels of biological organisation and the transgenerational impact of radionuclides.
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.
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".