Change in metallothionein phosphorylation state in Mya arenaria clams: implication in metal metabolism and oxidative stress
Bibliographic record
Abstract
The contamination of the benthic environment poses a threat to long-lived sessile organisms such as clams. The purpose of this study was to investigate metal contamination in tissues and changes in metallothioneins (MT) in respect to its redox status in Mya arenaria clams collected at three polluted sites. The phosphorylation state of MT was also investigated to determine whether this state is changed in clams collected at heavy-metal contaminated site and its involvement in cytoprotective signaling during stress contamination. The results show that clams collected at least one of the three polluted sites presented significantly higher concentrations of silver (Ag), arsenic (As), cobalt (Co), copper (Cu), mercury (Hg), nickel (Ni), tin (Sn) and lead (Pb) in tissues. In the visceral tissue, total MT levels and the reduced, metal-binding form of the protein were significantly induced at the sites. The phosphorylation of MT and mitochondrial activity, as determined by electron transport and cytochrome c oxidase activities, were also significantly reduced at the contaminated sites. Reduced phosphate levels in MT were negatively correlated with total MT levels, suggesting that decreased phosphorylation was involved in kinase-mediated signaling during cellular stress and could possibly alter the protein’s affinity to confer cytoprotection against heavy metal contamination. These preliminary investigations revealed that the phosphorylation state could change in polluted environment and provide some clues on the modulation of binding affinities during heavy-metal and oxidative stress in clams.
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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".