Protection from radiation-induced DNA single-strand breaks by induction of nuclear metallothionein
Bibliographic record
Abstract
PURPOSE: To examine the extent to which nuclear metallothionein protects from radiation-induced DNA damage under aerobic and hypoxic conditions. MATERIALS AND METHODS: A semiquantitative fluorescence image analysis method measured the nuclear content of metallothionein (MT) in ME180 and SiHa human squamous cervical carcinoma cell lines under normal growth conditions, and following MT induction by zinc. The extent of initial DNA damage following 60Co irradiation under aerobic and hypoxic conditions was assessed using the alkaline comet assay. RESULTS: Provided that cells were maintained at 37 degrees C, most of the cellular content of MT was in the nucleus. Incubation at 4 degrees C caused the rapid translocation of MT from the nucleus into the cytoplasm in both cell lines, with no net loss of cellular MT. Baseline nuclear MT levels were about four times greater in ME180 cells, and were much more readily induced by treatment with 100 microM zinc acetate, compared with SiHa cells. Under aerobic conditions, MT induction by zinc resulted in no protection in either of the cell lines. Under hypoxic conditions, however, the number of DNA single-strand breaks in zinc-treated cells was reduced by approximately 40% in ME180, but not in SiHa cells, when compared with non-induced controls. CONCLUSIONS: Nuclear MT can exert a significant level of protection from radiation by a mechanism that involves competition with oxygen for DNA radical sites and/or scavenging of free radicals. Because increased MT levels have been reported in hypoxic micro-regions of some solid tumours, this protective mechanism might have clinical relevance.
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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".