Molecular characteristics of granulosa and cumulus cells and oocyte competence in Nelore cows with low and high numbers of antral follicles
Bibliographic record
Abstract
The aims of this study were to investigate whether the number of antral follicles (AF) in the ovaries of Nelore cows is influenced with the developmental competence of oocytes to reach the blastocyst stage and to quantify the mRNA abundance of genes associated with folliculogenesis and oogenesis in granulosa and cumulus cells. A total of 168 cows were distributed into two experimental groups according to the number of AF, low (≤31) and high AF (≥92), which were determined based on the mean number of AF (61.14) ± SD (30.43). Granulosa and cumulus cells were used to assess the mRNA expression of 16 genes. Cumulus cells from cows with low AF had higher mRNA expression of genes involved in meiosis resumption (NPR-2, NPR-3) and cumulus cell expansion (FGF10), as well as a transcription factor involved in the regulation of oocyte maturation and cell proliferation (STAT3). Conversely, granulosa cells from females with high AF had higher expression of PGR and AMHR2a, which are involved in meiosis resumption and cumulus cell expansion. Cumulus-oocyte complexes (COCs) were collected from 356 cows with low and high AF populations to evaluate embryo development. Cleavage and blastocyst rates did not differ between the groups. In conclusion, our findings revealed that genes involved in folliculogenesis and oogenesis are differently expressed in cumulus and granulosa cells of cows having low and high numbers of AF. These molecular differences suggest that the regulation of oocyte maturation, meiotic resumption and cumulus expansion may be influenced by the number of AFs. However, the variations in gene expression were not associated with in vitro oocyte developmental competence to reach the blastocyst stage, which confirms that oocytes from Nelore cows with low and high numbers of AF are similarly able to mature, regulate the fertilization process and support pre-implantation embryo development.
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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 | 0.000 | 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 | 0.001 |
| 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".