Advanced fluorescence in situ hybridization to localize and quantify gene expression in Japanese medaka (<i>Oryzias latipes</i>) exposed to endocrine-disrupting compounds
Bibliographic record
Abstract
In an earlier study, we described the development of fluorescence in situ hybridization (FISH) using confocal microscopy to localize and quantify gene expression in fish. Here, we report the results of FISH application to investigate effects of model endocrine-disrupting chemicals (EDCs), 17alpha-ethinylestradiol (EE2) and 17beta-trenbolone (TB), on expressions of EDC-responsive genes in Japanese medaka (Oryzias latipes) at the cellular/tissue level paired with histological observation. Gene expressions of vitellogenin-II (Vit-II), androgen receptor (AR), and cytochrome P450 gonadal aromatase (CYP19a) were determined after exposure to 5, 50, or 500 ng/L of EE2 or 50, 500, or 5,000 ng/L of TB for 7 d. Exposure to the greatest concentration of EE2 or TB significantly reduced fecundity and caused histological alterations in gonads. 17alpha-Ethinylestradiol induced Vit-II expression in both male gonads and liver relative to controls and resulted in greater intensity of hematoxylin staining in hepatocytes, which was significantly correlated with Vit-II induction in liver. When exposed to EE2 at less than 50 ng/L, CYP19a expression associated with early stage oocytes was greater than that in controls. However, at 500 ng/L, this trend was reversed. The greater Vit-II expression in testis from all EE2 groups, and the lesser expression of CYP19a in ovaries from the 500 ng/L group, likely is related to changes in the number of cells in which these genes are predominantly expressed rather than to an increase in expression per cell. 17beta-Trenbolone significantly induced AR expression in ovaries but did not alter AR expression in female liver. It was concluded that FISH combined with histology enables advanced elucidation of molecular effects of chemicals by associating changes in gene expression with certain tissues and/or cell types and allows these changes to be related to histological effects.
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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) | 0.002 | 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".