Seasonally Related Disruption of Metabolism by Environmental Contaminants in Male Goldfish (Carassius auratus)
Bibliographic record
Abstract
Endocrine disrupting chemicals mimic or disrupt action of the natural hormones, adversely impacting hormonal function as well as cardiovascular, reproductive, and metabolic health. Goldfish are seasonal breeders with an annual reproductive cycle regulated by neuroendocrine signaling which involves allocation of metabolic energy to sustain growth and reproduction. We hypothesize that seasonal changes in physiology alter overall vulnerability of goldfish to metabolic perturbation induced by environmental contaminants. In this study, we assess effects of endogenous hormones, individual contaminants and their mixture on metabolism of goldfish at different reproductive stages. Exposure effects were assessed using 1H-NMR metabolomics profiling of male goldfish midbrain, gonad and liver harvested during early recrudescence (October), mid-recrudescence (February) and late recrudescence (June). Compounds assessed include bisphenol A, nonylphenol, bis(2-ethylhexyl) phthalate, fucosterol and a tertiary mixture (DEHP + NP + FS). Metabolome-level responses induced by contaminant exposure across tissues and seasons were benchmarked against responses induced by 17β-estradiol, testosterone and thyroid hormone (T3). We observe a clear seasonal dependence to metabolome-level alteration induced by hormone or contaminant exposures, with February (mid-recrudescence) the stage at which male goldfish are most vulnerable to metabolic perturbation. Responses induced by contaminant exposures differed from those induced by the natural hormones in a season-specific manner. Exposure to the tertiary mixture induced a functional gain at the level of biochemical pathways modeling over responses induced by individual components in select tissues and seasons. We demonstrate the importance of seasonally driven changes in physiology altering overall vulnerability of goldfish to metabolic perturbation induced by environmental contaminants, the relevance of which likely extends to other seasonally-breeding species.
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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".