Oocyte developmental stage influences ovary selenium concentrations in fish—implications for ovary selenium monitoring
Bibliographic record
Abstract
Monitoring selenium (Se) concentrations in fish ovaries is an important tool for evaluating the ecological risk posed by Se in aquatic systems. Most guidance recommends sampling fish ovaries as closely as possible to when fish spawn on the premise that Se is mobilized from the liver to the ovary during vitellogenesis, and therefore, sampling ovaries during the early phases of oocyte maturation may underestimate egg Se concentrations at the time of spawning. In this study, we evaluated ovary Se data from two species with synchronous oocyte development (Ptychocheilus oregonensis and Prosopium williamsoni), one species with asynchronous oocyte development (Richardsonius balteatus) and one where the mode of development is unclear (Mylocheilus caurinus). A multivariate analysis of ovary Se as a function of fish sampling location, size, and gonado-somatic index (GSI) demonstrated ovary Se was strongly negatively correlated with GSI in fish species with synchronous oocyte development but only weakly correlated in a species with asynchronous development. In R. balteatus, a relationship between expressible (released) egg Se and remaining ovary Se was observed, with egg concentrations approximately 54% of ovary concentrations on average. Overall, our findings suggest that current understanding of the mechanisms by which Se is maternally transferred to oocytes is not entirely correct and raises questions regarding how and when during the reproductive cycle Se is mobilized to ovaries. Further, our findings have significant implications for interpretation of ovary Se monitoring data collected from unripe fish. We developed regression-based models to correct ovary Se data that are biased by sampling females not in spawning condition and demonstrate how this bias can impact evaluation of Se risk to fish.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".