Leptin Enhances Oocyte Nuclear and Cytoplasmic Maturation via the Mitogen-Activated Protein Kinase Pathway
Bibliographic record
Abstract
Recent studies have suggested that leptin has a central role in female reproduction, including ovarian function. The leptin receptor (Ob-R) has six isoforms and can signal through either the MAPK or the Janus-activated kinase/signal transducer and activator of transcription signal-transduction pathway, depending on the isoform. Expression of Ob-R has been reported in human and mouse oocytes; however, the physiological role of leptin during follicular development and oocyte maturation is largely unknown. In the current study, expression of Ob-R during oocyte growth and maturation was investigated in porcine oocytes from small, medium, and large follicles and in oocytes in the germinal vesicle (GV), GV breakdown, and metaphase II (MII) stages at both the mRNA and protein levels. The proportion of oocytes expressing Ob-R was maximal in oocytes from medium follicles and at the GV breakdown stage (P < 0.05), whereas the proportion of oocytes expressing the long isoform, Ob-Rb, was found to be consistently low throughout growth and maturation. When included in oocyte maturation medium, leptin significantly increased the proportion of oocytes reaching MII (P < 0.01), elevated cyclin B1 protein content in MII-stage oocytes (P < 0.05), and enhanced embryo developmental potential (P < 0.05), suggesting that leptin plays a role in both nuclear and cytoplasmic maturation. During oocyte maturation, leptin increased phosphorylated MAPK content by 2.8-fold (P < 0.05), and leptin-stimulated oocyte maturation was blocked when leptin-induced MAPK phosphorylation was suppressed by a specific MAPK activation inhibitor, U0126 (P < 0.01), demonstrating that leptin enhances nuclear maturation via activation of the MAPK pathway.
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 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".