The Dual Nature of Metallothioneins in the Metabolism of Heavy Metals and Reactive Oxygen Species in Aquatic Organisms: Implications of Use as a Biomarker of Heavy-Metal Effects in Field Investigations
Bibliographic record
Abstract
The purpose of this study was to examine the function of metallothioneins (MT) in respect to the mobilization of heavy metals and superoxide anion (O2–) scavenging in aquatic organisms. Using an O2– generating system, liberation of free zinc from native and zinc MT (Zn-MT) was measured in vitro. Addition of the O2– generating system and H2O2 readily increased the di- and trimeric forms of MT as determined by gel electrophoresis analysis. To determine whether the proportion of oxidized MT could change in contaminated environments, metal-contaminated Mya arenaria clams were collected from a harbour in the St. Lawrence Estuary. The levels of labile zinc, superoxide dismutase (O2– scavenging enzyme), lipid peroxidation (LPO) and the oxidized/metallic form of MT were determined in the digestive gland. The results revealed that the induction of total MT levels was the result of increased oxidized MT at the expense of the reduced or metallic form of MT. Both superoxide dismutase (SOD) and labile zinc (Zn) levels were induced and they were significantly correlated with the oxidized form of MT, but not the metallic form, in feral clam populations. We concluded that the level of total MT was related to Zn mobility and the activation of antioxidant mechanisms such as SOD, and corresponded to the levels of oxidized MT. The metallic form of MT was negatively associated with Zn mobility but positively associated with oxidative damage such as LPO. Overall, the oxidized fraction of MT appeared to be more closely related to detoxification, while the metallic form of MT was associated with metal mobility and toxicity via oxidative damage. The protective effect of MT during heavy-metal contamination depends on the availability of metals and on its capacity to sequester reactive oxygen species.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".