Subtractive hybridization used to identify mRNA associated with the maturation of bovine oocytes
Bibliographic record
Abstract
The main objective of this project is to identify mRNA associated with oocyte maturation and embryonic developmental competency. The knowledge of genes and their accumulated mRNA is essential to better understand the mechanisms involved in the oocyte maturation and the survival of the in vitro produced embryo. We used bovine slaughterhouse-recovered ovaries and collected the oocytes from two follicle size categories: <2 mm and 3-5 mm. The mRNA content of oocytes from follicles 3-5 mm where considered to be more competent when compared to the content of oocytes from follicles <2 mm. In this report we compare two different technical approaches both involving PCR to compare the mRNA pools of the oocytes. In the first approach we performed the differential display (DDRT) technique to amplify and display side by side the cDNAs of groups of 10 denuded oocytes. From this approach, we isolated 28 different bands. After analysis, three of those bands had strong homology with known genes. In the second approach pools of 50 denuded oocytes were submitted to suppressive subtraction hybridization (SSH). We identified several known genes like cyclin B1, splicing factor ccl.4, cytochrome c oxidase, and mineralocorticoid receptor while numerous other clones remain unidentified. The cyclin B1 clone was used as a probe to evaluate its follicular size specificity on virtual Northern blot. The PCR basis of these techniques allows comparison of mRNA from tissues of low abundance such as oocytes. In this study the SSH resulted in longer clones than DDRT and showed high specificity.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".