Effects of Di-Isononyl Phthalate (DiNP) on Follicular Atresia in Zebrafish Ovary
Bibliographic record
Abstract
Di-isononyl phthalate (DiNP) is a plasticizer reported to elicit hormone-like activity and disrupt metabolism and reproduction in fish and other vertebrates. In general, phthalates have been used at high concentrations beyond reported environmental levels to assess their adverse effects on fish gonadal physiology. The present study exposed adult female zebrafish to a wide range of DiNP concentrations [0.42 µg L−1 (10−9 M), 4.2 µg L−1 (10−8 M), and 42 µg L−1 (10−7 M)] for 21 days. We evaluated gene expression profiles related to apoptosis, autophagy, and oxidative stress; DNA fragmentation (TUNEL assay: terminal deoxynucleotidyl transferase dUTP nick end labeling) and caspase activity (CAS3) were also examined. Exposure to 0.42 and 4.2 µg L−1 upregulated the genes coding for tnfa and baxa, sod1, prkaa1, respectively. CAS3 immunohistochemistry revealed a higher number of positive vitellogenic oocytes in ovaries exposed to 0.42 µg L−1. Subsequently, we examined the relationship between CAS3 signaling and DNA fragmentation. Accordingly, DNA fragmentation was observed in vitellogenic follicles of fish exposed to 0.42 and 4.2 μg L−1. Our results demonstrate that follicular atresia can occur after exposure to environmental levels of DiNP for 21 days, which may adversely affect the reproductive performance of female zebrafish in a non-monotonic manner.
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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 | 0.001 |
| 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".