Nickel essentiality and homeostasis in aquatic organisms
Bibliographic record
Abstract
It has been well established that a number of trace metals are essential for various biological functions and are critical in many of the enzymatic and metabolic reactions occurring within an organism. The essentiality of nickel is now generally accepted, based on the numerous symptoms caused by nickel deficiency (mainly in terrestrial vertebrates) and its essential role in various enzymes in bacteria and plants. The information on optimal and deficient concentrations of nickel, however, is limited and the essentiality of nickel to aquatic animals is not established. The purpose of this review is to synthesize the available information on nickel essentiality and homeostasis in aquatic organisms. There is less information on these topics compared to that for other essential metals. Nickel essentiality to aquatic organisms can only be confirmed for plants and (cyano)bacteria due to the documented role of nickel in the urease and hydrogenase metabolism. Deficiency levels ranged from 10-12 M to 2 × 10-6 M Ni in different species. No studies were identified that had the explicit objective of evaluating homeostatic mechanisms for nickel in aquatic life. However, inferences could be made through the evaluation of nickel bioconcentration and tissue distribution data and a comparison to other metals that have been more thoroughly studied. Data suggest active regulation and therefore nickel essentiality, since there are no known examples of active regulation of non-essential metals in invertebrates. Key words: nickel, essentiality, homeostasis, bioconcentration, regulation.
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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".