Leptin-Mediated Activation of Human Platelets: Involvement of a Leptin Receptor and Phosphodiesterase 3A Cellular Signaling Complex.
Bibliographic record
Abstract
Abstract Leptin, a 16-KDa peptide-hormone produced primarily by adipocytes, was reported previously to promote platelet aggregation by a yet undefined mechanism. In this study, we investigated the effect of leptin on human platelet activation and delineate a molecular basis for this effect. Thus, we report that leptin potentiates ADP-induced platelet aggregation and directly stimulates adhesion of platelets to fibronectin. Using a combination of pharmacological and biochemical approaches we demonstrate that leptin mediates these effects by activating a signaling cascade that includes the leptin receptor (OB-R) and the kinases Jak2, phosphatidylinositol 3-kinase (PI3K) and protein kinase B (PKB/Akt). Consistent with an important role for PKB-mediated phosphorylation and activation of the dominant cAMP hydrolyzing phosphodiesterase, phosphodiesterase 3A (PDE3A), in this system, incubation of platelets with leptin activated PDE3A and stimulated a PKB-mediated phosphorylation of PDE3A. A selective PDE3 inhibitor, cilostamide, attenuated leptin effects in these cells. While leptin did not alter platelet cAMP levels, our identification of an OB-R/PDE3A complex is consistent with leptin acting locally to regulate a “pool” of cAMP that controls platelet activity. This is the first report of leptin-induced platelet adhesion which provides a mechanistic basis for this potentially important effect of this peptide hormone.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".