Bibliographic record
Abstract
Mercury is a potent neurotoxin, and increasing levels have led to concern for human and wildlife health in many regions of the world. During the past three decades, studies in fish have examined the effects of sublethal mercury exposure on a range of endpoints within the reproductive axis. Mercury studies have varied from highly concentrated aqueous exposures to ecologically relevant dietary exposures using levels comparable to those currently found in the environment. This review summarizes data from both laboratory and field studies supporting the hypothesis that mercury in the aquatic environment impacts the reproductive health of fish. The evidence presented suggests that the inhibitory effects of mercury on reproduction occur at multiple sites within the reproductive axis, including the hypothalamus, pituitary, and gonads. Accumulation of mercury in the fish brain has resulted in reduced neurosecretory material, hypothalamic neuron degeneration, and alterations in parameters of monoaminergic neurotransmission. At the level of the pituitary, mercury exposure has reduced and/or inactivated gonadotropin-secreting cells. Finally, studies have examined the effects of mercury on the reproductive organs and demonstrated a range of effects, including reductions in gonad size, circulating reproductive steroids, gamete production, and spawning success. Despite some variation between studies, there appears to be sufficient evidence from laboratory studies to link exposure to mercury with reproductive impairment in many fish species. Currently, the mechanisms underlying these effects are unknown; however, several physiological and cellular mechanisms are proposed within this review.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 0.001 |
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".