Protein kinases influence bovine oocyte competence during short-term treatment with recombinant human follicle stimulating hormone
Bibliographic record
Abstract
The aim of this study was to investigate the effect of short-term treatment (first 2 or 6 h) with recombinant human follicle-stimulating hormone (r-hFSH) during in vitro maturation (IVM) on the developmental competence of bovine oocytes. The roles of protein kinase A (PKA) and protein kinase C (PKC) (possibly involved in FSH response), were investigated using activators (Sp-cAMPS, PMA) or inhibitors (Rp-cAMPS, sphingosine) of these two protein kinases, respectively. The developmental competence of bovine oocytes was measured by the rate of blastocyst formation after in vitro fertilization (IVF). Our results showed that when cumulus-oocyte complexes (COCs) were cultured with r-hFSH for the first 6 h, a highly significant (P < 0.0001) improvement is seen in blastocyst development rate as a proportion of oocytes in culture compared with those matured with r-hFSH for the first 2 or 24 h. A transient exposure (6 h) to the highest dose (100 microM) of forskolin (an activator of adenylate cyclase) increased (P < 0.05) the rate of blastocyst formation. But the PKA inhibitors (Rp-cAMPS) did not affect the stimulatory effects of r-hFSH on the blastocyst yield. However, stimulation of PKC by low doses of PMA (0.1-0.5 microM) during short-term treatment, enhanced (P < 0.0001) the developmental capacity of oocytes, while sphingosine (a specific inhibitor of PKC) inhibited (P < 0.05) the stimulatory effects of r-hFSH on the rate of blastocyst formation. Our results indicate that although the developmental capacity of bovine oocytes in vitro can be modulated by both the PKA, and the PKC pathways, the activation of PKC during short-term treatment can mimic the effect of r-hFSH on the cytoplasmic maturation in bovine oocytes in vitro.
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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".