Speciation of Hepatic Zn in Trout Exposed to Elevated Waterborne Zn Using X-ray Absorption Spectroscopy
Bibliographic record
Abstract
The long-term impacts of chronic metal exposure for aquatic biota are not well understood, partly due to a lack of understanding of metal speciation within tissues. The objective of this study was to determine hepatic Zn speciation of rainbow trout (Oncorhnychus mykiss) exposed to Zn-enriched water in relation to unexposed (control) fish,through direct analysis of freeze-dried liver samples using synchrotron X-ray absorption spectroscopy (XAS). Juvenile rainbow trout (n=30) were exposed to Zn in a two-step process, 200 microg L(-1) for 14 days, followed by 370 microg L(-1) for 23 days. Thirty other trout were grown in a control treatment (10 microg Zn L(-1)). At the end of the experiment, three liver samples per treatment were collected, freeze-dried, ground, and mixed homogeneously. Although Zn concentration was higher in the Zn-exposed livers than in the control livers (22.32 vs 13.73 mg kg(-1), respectively; p < 0.05), Zn speciation was similar for both groups. Extended X-ray absorption fine structure (EXAFS) spectroscopy indicated that Zn was coordinated to 4 sulfur atoms with an average Zn-S bond distance of 2.31 +/- 0.02 A. Sulfur K-XANES analysis confirmed that S was predominantly in reduced organic form analogous to cysteine. Our results are consistent with previous evidence for Zn(II) bonding to S in metallothionein proteins. These results suggest that the mechanisms for dealing with the extra load of bioaccumulated Zn in high exposure conditions were the same as in the control group.
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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".