Functional significance and physiological regulation of essential trace metals in fish
Bibliographic record
Abstract
Trace metals such as iron, copper, zinc and manganese play essential roles in various biological processes in fish, including development, energy metabolism and immune response. At embryonic stages, fish obtain essential metals primarily from the yolk, whereas in later life stages (i.e. juvenile and adult), the gastrointestine and the gill are the major sites for the acquisition of trace metals. On a molecular level, the absorption of metals is thought to occur at least in part via specific metal ion transporters, including the divalent metal transporter-1 (DMT1), copper transporter-1 (CTR1), and Zrt- and Irt-like proteins (ZIP). A variety of other proteins are also involved in maintaining cellular and systemic metal homeostasis. Interestingly, the expression and function of these metal transport- and metabolism-related proteins can be influenced by a range of trace metals and major ions. Increasing evidence also demonstrates an interplay between the gastrointestine and the gill for the regulation of trace metal absorption. Therefore, there is a complex network of regulatory and compensatory mechanisms involved in maintaining trace metal balance. Yet, an array of factors is known to influence metal metabolism in fish, such as hormonal status and environmental changes. In this Review, we summarize the physiological significance of iron, copper, zinc and manganese, and discuss the current state of knowledge on the mechanisms underlying transepithelial metal ion transport, metal-metal interactions, and cellular and systemic handling of these metals in fish. Finally, we identify knowledge gaps in the regulation of metal homeostasis and discuss potential future research directions.
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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".