Expression of Leptin Receptors and Potential Effects of Leptin on the Cell Growth and Activation of Mitogen-Activated Protein Kinases in Ovarian Cancer Cells
Bibliographic record
Abstract
Leptin, a secreted protein of the ob gene by white adipose tissue, plays an important role in the regulation of food intake and energy consumption in the brain and acts as a potential growth stimulator in normal and neoplastic breast cancer cells. However, a potential role of leptin as an endocrine regulator is unknown in ovarian cancer. In the present study, we investigated the expression of leptin receptors in immortalized ovarian surface epithelium (IOSE) and ovarian cancer cell lines, and potential effect of leptin on the cell growth and activation of mitogen-activated protein kinases (MAPKs) in the BG-1 ovarian cancer cell line. Both short and long isoforms of leptin receptors are expressed in IOSE-80PC (a post-crisis line), BG-1, OVCAR-3, and SKOV-3 cells. In addition, treatment with leptin resulted in the growth stimulation of BG-1 cells, an activation of ERK1/2 and inhibition of constitutive phosphorylation of p38 MAPK. These results suggest that further studies are necessary to validate whether leptin may be a potential regulator for ovarian cancer.
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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".