Regulation of Gap-Junctional Communication Between Cumulus Cells During In Vitro Maturation in Swine, a Gap-FRAP Study1
Bibliographic record
Abstract
Intercellular gap-junctional communication (GJC) plays an important role in ovarian cell physiology. Closure of GJC has been proposed to be involved in oocyte maturation, particularly in the resumption of meiosis, both in vivo and in vitro, by controlling the flow of meiosis inhibitors, such as cAMP and cGMP. Understanding how GJC dynamics are regulated during in vitro maturation (IVM) could provide a powerful tool for controlling meiotic resumption and oocyte maturation in vitro. Since little is known about the GJC dynamic regulation between cumulus cells, we have developed an assay based on recovery of calcein fluorescence in photobleached cumulus cells, a gap-FRAP assay. The GJC profile has been characterized during the first hours of porcine IVM. We showed that equine chorionic gonadotropin (eCG) and epidermal growth factor (EGF) down-regulated GJC effectiveness between cumulus cells. However, human chorionic gonadotropin was not down-regulating GJC effectiveness. We also showed that the GJC network expanded during this period and that this effect was not regulated by gonadotropins. Porcine follicular fluid present in the maturation medium also had an impact on GJC regulation, increasing GJC network establishment and the effectiveness of calcein transfer rate between cumulus cells. These results show that both eCG and EGF are regulating the decrease in GJC effectiveness after 4.5 h of IVM, while the network extension is gonadotropin independent. Regulation of GJC between cumulus cells would then be specifically regulated during in vitro IVM.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".