Inhibition of smooth muscle cell proliferation by adiponectin requires proteolytic conversion to its globular form
Bibliographic record
Abstract
Accelerated atherosclerosis is the primary cardiovascular manifestation of diabetes and correlates inversely with levels of circulating adiponectin, an anti-atherosclerotic adipokine that declines in diabetes. We therefore initiated a study to examine the mechanisms by which adiponectin, a hormone released from adipose tissue, influences the proliferation of vascular smooth muscle cells (SMCs). Addition of adiponectin to quiescent porcine coronary artery SMCs increased both protein and DNA synthesis and concurrently activated ERK1/2 and Akt. By contrast, globular adiponectin, a truncated form of this protein, exhibited anti-mitogenic properties as indicated by the inhibition of protein and DNA synthesis in SMCs stimulated with platelet-derived growth factor (PDGF). Whereas globular adiponectin did not stimulate growth-related signal transduction pathways, it was able to block the PDGF-dependent phosphorylation of eukaryotic elongation factor 2 kinase, a regulator of protein synthesis. Proteolysis of adiponectin with trypsin, which produces globular adiponectin, reversed the growth-stimulating actions of the undigested protein. As the existence of globular adiponectin remains controversial, western blotting was used to establish its presence in rat serum. We found that globular adiponectin was detectable in rat serum, but this result was not obtained with all antibodies. The contrasting properties of adiponectin and its globular form with respect to SMC proliferation suggest that protection against atherosclerosis may therefore be mediated, in part, by the level of globular adiponectin.
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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".