Quantification of rainbow trout (Oncorhynchus mykiss) estrogen receptor-alpha messenger RNA and its expression in the ovary during the reproductive cycle
Bibliographic record
Abstract
This study developed a quantitative reverse transcription-polymerase chain reaction (RT-PCR) method to measure estrogen receptor-alpha (ERalpha) mRNA in the rainbow trout (Oncorhynchus mykiss). Using RT-PCR, and primers based on the known ERalpha DNA sequence in this species, cDNA sequences representing most of the protein coding region were obtained from ovary poly A(+) RNA. Using these DNA sequences as probes in Northern blot hybridizations confirmed that a single transcript of 4.2 kilobases in poly A(+) RNA could be detected in liver and ovary RNA. For the quantitative RT-PCR assay an internal standard RNA molecule was produced to control for inherent inter-tube differences in amplification efficiency and permit accurate quantification of ERalpha mRNAs. The quantitative RT-PCR assay proved to be highly specific for ERalpha mRNA with a detection limit of 6.9 fg, which corresponds to 273 fg ERalpha mRNA/microg total RNA. The quantitative RT-PCR assay was used to measure the levels of ERalpha mRNA in ovaries of rainbow trout at different stages of reproductive development. Ovarian ERalpha mRNA expression was found during two distinct periods of reproductive development, in pre-vitellogenic ovaries of fish with ovarian follicle diameters (OFDs) </=100 microm and in mid-vitellogenic ovaries with OFDs >1000 microm. ERalpha mRNA could not be detected in the ovaries of fish with OFDs >100 microm but </=1000 microm. The highest levels of ERalpha mRNA were found in late vitellogenic ovaries of fish with OFDs >2000 microm.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".