Caffeine prevents restenosis and inhibits vascular smooth muscle cell proliferation through the induction of autophagy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Caffeine is among the most highly consumed substances worldwide, and it has been associated with decreased cardiovascular risk. Although caffeine has been shown to inhibit the proliferation of vascular smooth muscle cells (VSMCs), the mechanism underlying this effect is unknown. Here, we demonstrated that caffeine decreased VSMC proliferation and induced macroautophagy/autophagy in an in vivo vascular injury model of restenosis. Furthermore, we studied the effects of caffeine in primary human and mouse aortic VSMCs and immortalized mouse aortic VSMCs. Caffeine decreased cell proliferation, and induced autophagy flux via inhibition of MTOR signaling in these cells. Genetic deletion of the key autophagy gene Atg5, and the Sqstm1/p62 gene encoding a receptor protein, showed that the anti-proliferative effect by caffeine was dependent upon autophagy. Interestingly, caffeine also decreased WNT-signaling and the expression of two WNT target genes, Axin2 and Ccnd1 (cyclin D1). This effect was mediated by autophagic degradation of a key member of the WNT signaling cascade, DVL2, by caffeine to decrease WNT signaling and cell proliferation. SQSTM1/p62, MAP1LC3B-II and DVL2 were also shown to interact with each other, and the overexpression of DVL2 counteracted the inhibition of cell proliferation by caffeine. Taken together, our in vivo and in vitro findings demonstrated that caffeine reduced VSMC proliferation by inhibiting WNT signaling via stimulation of autophagy, thus reducing the vascular restenosis. Our findings suggest that caffeine and other autophagy-inducing drugs may represent novel cardiovascular therapeutic tools to protect against restenosis after angioplasty and/or stent placement.
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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 it