A Comprehensive Survey of the Genes Involved in Maturation and Development of the Rainbow Trout Ovary1
Bibliographic record
Abstract
Development and maturation of the ovary requires precisely coordinated expression of specific gene classes to produce viable oocytes. We undertook identification of some of the genes involved in these processes by creating ovary-specific cDNA libraries by suppression subtractive hybridization and by microarray-based analyses. We present 5778 tissue- and sex-specific genes from subtracted ovary and testis libraries, many of which remain unidentified. A microarray containing 3557 salmonid cDNAs was used to compare the transcriptomes of precocious ovary at three different stages during the second year of life with a reference (normal ovary) transcriptome. On average, approximately 240 genes were developmentally regulated during the study period from June to October. Classes of genes maintaining relatively steady-state levels of expression, such as those controlling tissue remodeling, immunoregulation, cell-cycle progression, apoptosis, and growth also were identified. Concurrent expression of various cell division and ubiquitin-mediated proteolysis regulators revealed the utility of microarray analysis to monitor important maturation events. We also report unequivocal evidence for expression of the transcripts that encode the common glycoprotein alpha, LH beta, FSH beta, thyroid-stimulating hormone beta, and retinol-binding protein in both the ovary and testis of trout.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
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".