Chronic exposure to selenium through a natural diet (Lumbriculus variegatus) resulted in endocrine disruption, and reproductive impairment in zebrafish (Danio rerio)
Bibliographic record
Abstract
Aquatic ecosystems face increasing threats from selenium (Se) contamination arising from mining activities. Selenium acts as a potent reproductive toxicant in fish at elevated exposure levels; however, the molecular and physiological underpinnings of its reproductive toxicity remain poorly understood. The current study investigated the reproductive impacts of trophic Se exposure in zebrafish (Danio rerio). The Se-exposed benthic oligochaete (Lumbriculus variegatus), with Se body burdens of 0.65 (control), 17 (low), and 43 (high) μg/g dry weight, was fed to adult zebrafish for 60 days to assess the endocrine and reproductive effects of Se. Trophic Se exposure induced significant increases in the gonadosomatic index (GSI) in females and hepatosomatic index (HSI) in both sexes. Moreover, Se exposure resulted in reduced fecundity, smaller egg diameters, and diminished sperm motility and velocity. The hypothalamic-pituitary-gonadal (HPG) axis was disrupted by Se exposure, with downregulation of gnrh, fshβ, fshr, cyp19b, vtg, and erα genes in females, and altered expression of vtgr, cyp11a, and 3βhsd genes in males. Circulating estradiol (E2) levels decreased in females and males (only with high Se treatment), while 11-ketotestosterone (11 KT) declined in males compared to the respective controls. Plasma vitellogenin (Vtg) also decreased in females but increased in males following dietary Se exposure. Histopathological analysis showed that Se induced ovarian adhesion and oocyte degeneration in females, and degeneration of Sertoli and Leydig cells in males. Collectively, these findings demonstrate that chronic environmentally relevant dietary exposure to Se decreases reproductive fitness of zebrafish by HPG axis dysregulation, underscoring ecological risks from Se contamination.
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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".