Reproductive and Developmental Effects of Sex-Specific Chronic Exposure to Dietary Arsenic in Zebrafish (Danio rerio)
Bibliographic record
Abstract
) were exposed to environmentally realistic doses of arsenic via diet [0 (control; no added arsenic), 30 (low), 60 (medium), and 100 (high) μg/g dry weight, as arsenite] for 90 days. Following exposure, arsenic-exposed females from each dietary treatment were mated with control males, and similarly, arsenic-exposed males from each dietary treatment were mated with control females. In females, arsenic exposure resulted in a dose-dependent decrease in reproductive performance (fecundity, fertilization success, and hatching success). Moreover, a dose-dependent increase in developmental toxicity (larval deformities and larval mortality) was observed with maternal exposure to arsenic. In contrast, in males, arsenic exposure also induced similar reproductive and developmental toxicity; however, the adverse effects were mainly evident only in the medium and high dietary arsenic treatment groups. We also examined the sex-specific effects of dietary arsenic exposure on the expression of genes that regulate the hypothalamus-pituitary-gonadal-liver (HPG-L) axis in fish. The gene expression results indicated the downregulation of HPG-L axis genes in females irrespective of the arsenic treatment dose; however, the reduced expression of HPG-L axis genes in males was recorded only in the medium and high arsenic treatment groups. These observations suggest that chronic arsenic exposure in either females or males causes reproductive and developmental toxicity in zebrafish. However, these toxic effects are markedly higher in females than in males. Our results also suggest that arsenic can act as an endocrine disruptor and mediate reproductive and developmental toxicity by disrupting the HPG-L axis in zebrafish.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".