Functional Effects of Adiponectin on Endothelial Progenitor Cells
Bibliographic record
Abstract
Adiponectin is an adipokine whose plasma levels are inversely correlated to metabolic syndrome components. Adiponectin protects against atherosclerosis and decreases risks in myocardial infarction. Endothelial progenitor cells (EPCs) are a heterogeneous population of circulating cells involved in vascular repair and neovascularization. EPCs number is reduced in patients with cardiovascular disease. We hypothesize that the positive effects of adiponectin against atherosclerosis are explained in part by its interactions with EPCs. Cells were obtained from healthy volunteers' blood by mononuclear cell isolation and plating on collagen-coated dishes. Three sub-populations of EPCs were identified and characterized using flow cytometry. EPCs' expression of adiponectin receptors, AdipoR1, and AdipoR2 was evaluated by quantitative PCR. The effects of recombinant adiponectin on EPCs' susceptibility to apoptosis were assessed. Finally, expression of neutrophil elastase by EPCs and activity of this enzyme on adiponectin processing were assessed. Quantitative PCR analysis of EPCs mRNAs showed that AdipoR1 mRNA is expressed at higher levels than AdipoR2. Expression of AdipoR1 protein was confirmed by western blot. Adiponectin significantly increased survival of two sub-populations of EPCs in conditions of serum deprivation. Such effect could not be demonstrated in the third EPCs sub-population. We also demonstrated that EPCs, particularly one sub-population, express neutrophil elastase. Neutrophil elastase activity was confirmed in EPCs' conditioned media. Adiponectin protects some EPCs sub-populations against apoptosis and therefore could modulate EPCs ability to induce repair of vascular damage. Neutrophil elastase activity of EPCs could locally modulate adiponectin activity by its involvement in the generation of the globular form of adiponectin.
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".