Pre-exposure to Waterborne Nickel Downregulates Gastrointestinal Nickel Uptake in Rainbow Trout: Indirect Evidence for Nickel Essentiality
Bibliographic record
Abstract
Nickel (Ni) may be both a toxicant and a micronutrient, but its essentiality to aquatic animals is not established. Interactions between branchial and gastrointestinal routes of metal uptake are important for understanding metal regulation and essentiality in aquatic animals. Adult rainbowtrout (Oncorhynchus mykiss) were pre-exposed to a sublethal concentration of waterborne Ni (7.43 micromol L(-1)) or a control water (0.12 micromol L(-1)) for 45 days, and subsequently, a gastrointestinal dose of radiolabeled Ni (1.08 micromol kg(-1) wet wt) was infused into the stomach of both non-pre-exposed and Ni pre-exposed trout to test whether pre-exposure to waterborne Ni would affect gastrointestinal uptake. The fish pre-exposed to waterborne Ni exhibited a markedly greater level of total Ni in the blood plasma (approximately 10-fold) but not in red blood cells (RBC). Pre-exposure downregulated the gastrointestinal uptake of radiolabeled Ni (new Ni) in the plasma and RBCs, providing evidence for the first time of homeostatic interaction between the two routes of Ni uptake. The plasma and RBC concentrations of new Ni in the non-pre-exposed and Ni pre-exposed groups were linear in the first 2 h and then approached a plateau. Only a small fraction of the infused dose (1.6-3.7%) was found in the internal organs of both groups at 24 h. Waterborne Ni, but not the infused Ni, greatly increased total Ni levels in the gills (6.1 fold), kidney (5.6 fold), scales (4.2 fold), and gut tissues (1.5-4.2 fold). It appears that gut, kidney and scales play important roles for Ni homeostasis by providing uptake, clearance and storage sites. Overall, our results suggest that Ni is subject to homeostatic regulation in the rainbow trout, a property that is characteristic of essential metals.
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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 | 0.001 |
| 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".