Bisphenol A diglycidyl ether-induced DNA methylation abnormalities may disrupt testis development in adult male zebrafish
Bibliographic record
Abstract
Bisphenol A diglycidyl ether (BADGE) is commonly used to stabilize products synthesized from epichlorohydrin and bisphenol A. Although recent studies suggest that BADGE may adversely affect the male reproductive system, its underlying mechanisms remain unclear. This study investigates the impact of BADGE exposure on steroidogenesis via DNA methylation changes in adult zebrafish gonads. Adult male zebrafish were exposed to BADGE (10 μM) for 21 days (n = 15 per group). Genomic DNA and mRNA were extracted from the testes. Whole-genome bisulfite sequencing revealed differentially methylated (DM) regions, and the expression levels of genes associated with these DM sites and steroidogenesis were analyzed using quantitative reverse transcription polymerase chain reaction. Among the 2,673 DM sites (1,311 hypomethylated and 1,362 hypermethylated), 1,533 were successfully annotated. Pathway enrichment analysis showed that DM sites were associated with the phosphatidylinositol signaling system, inositol phosphate metabolism, cardiac muscle contraction, insulin resistance, insulin signaling, and the forkhead box O signaling pathway. Notably, the gene expression of insulin receptor substrate 1 (irs1) was significantly upregulated in the BADGE-treated group. In addition, the mRNA expression of steroidogenic enzymes, including steroidogenic acute regulatory protein, cytochrome P450 family 17 subfamily A member 1, and cytochrome P450 family 11 subfamily A member 1, was significantly increased in BADGE-treated group compared to the control group. These findings suggest that while BADGE may directly influence steroidogenesis, DNA methylation of insulin signaling-related molecules, including irs1, may also contribute to this process.
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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) | 0.002 | 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".