Gene expression profiling in the neuroendocrine brain of male goldfish (<i>Carassius auratus</i>) exposed to 17α-ethinylestradiol
Bibliographic record
Abstract
17-alpha ethinylestradiol (EE2), a pharmaceutical estrogen, is detectable in water systems worldwide. Although studies report on the effects of xenoestrogens in tissues such as liver and gonad, few studies to date have investigated the effects of EE2 in the vertebrate brain at a large scale. The purpose of this study was to develop a goldfish brain-enriched cDNA array and use this in conjunction with a mixed tissue carp microarray to study the genomic response to EE2 in the brain. Gonad-intact male goldfish were exposed to nominal concentrations of 0.1 nM (29.6 ng/l) and 1.0 nM (296 ng/l) EE2 for 15 days. Male goldfish treated with the higher dose of EE2 had significantly smaller gonads compared with controls. Males also had a significantly reduced level of circulating testosterone (T) and 17beta-estradiol (E2) in both treatment groups. Candidate genes identified by microarray analysis fall into functional categories that include neuropeptides, cell metabolism, and transcription/translation factors. Differentially expressed genes verified by real-time RT-PCR included brain aromatase, secretogranin-III, and interferon-related developmental regulator 1. Our results suggest that the expression of genes in the sexually mature adult brain appears to be resistant to low EE2 exposure but is affected significantly at higher doses of EE2. This study demonstrates that microarray technology is a useful tool to study the effects of endocrine disrupting chemicals on neuroendocrine function and suggest that exposure to EE2 may have significant effects on localized E2 synthesis in the brain by affecting transcription of brain aromatase.
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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".