Induction of alpha‐caveolin‐1 (αCAV1) expression in bovine granulosa cells in response to an ovulatory dose of human chorionic gonadotropin
Bibliographic record
Abstract
Caveolins are implicated in endocytosis, cholesterol trafficking and signal transduction. A cDNA fragment corresponding to caveolin-1 (CAV1) was identified in a mRNA profiling expression study in bovine granulosa cells (GC) following human chorionic gonadotropin (hCG)-induced ovulation. Thus, we have characterized CAV1 cDNA and studied its spatio-temporal expression pattern in bovine ovarian follicles. The full-length bovine alphaCAV1 cDNA was cloned and encodes a putative 22 kDa protein. Expression of alphaCAV1 was studied in bovine GC obtained from follicles at different developmental stages: small follicles (SF: 2-4 mm), dominant follicles (DF), ovulatory follicles (OF: 24 hr post-hCG), and corpus luteum (CL). Semiquantitative RT-PCR analysis showed a 6.5-fold increase in alphaCAV1 mRNA in GC of OF versus DF (P < 0.0001), whereas CAV2 mRNA was increased by only twofold (P < 0.0007). Temporal expression of alphaCAV1 mRNA from OF recovered at 0, 6, 12, 18, and 24 hr after hCG injection showed an 8.5-fold increase of alphaCAV1 mRNA after 24 hr compared to 0 hr (P < 0.0018) whereas no significant variation was detected for CAV2. Immunoblot demonstrated an initial increase in alphaCAV1 protein level 12 hr post-hCG, reaching a maximum at 24 hr. Immunohistochemical localization of CAV1 was observed in GC of OF isolated 18 and 24 hr after hCG injection, whereas no signal was detected in GC of DF and SF. The induction of alphaCAV1 in GC of OF suggests that alphaCAV1 likely contributes to control the increase in membrane signaling that occurs at the time of ovulation and luteinization.
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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".