Bibliographic record
Abstract
Revascularization procedures used for the treatment of cardiovascular disease can be associated with restenosis, although drug-coated stents have greatly reduced this complication. Both type 2 diabetes (T2DM) and metabolic syndrome (MetS) are associated with a high risk for atherosclerosis and restenosis. Insulin resistance, defined as the inability of insulin to exert its metabolic actions, characterizes both T2DM and MetS. Recent data suggest that insulin resistance is directly implicated in atherosclerosis/restenosis, because of the unresponsiveness to the vasculoprotective action of insulin, including its phosphoinositide 3-kinase (PI3K)-Akt-endothelial nitric oxide synthase mediated enhancement of endothelial function. However, insulin also has 'atherogenic' actions, including enhancement of vascular smooth muscle cell (VSMC) proliferation, which are mitogen-activated protein kinase-mediated. These 'atherogenic' actions are less affected by insulin resistance, which mainly involves the PI3K pathway. The role of insulin in the atherosclerotic disease process is still highly controversial, where some investigators view insulin as a growth factor with pro-atherogenic effects while some others believe insulin resistance to be pro-atherogenic rather than insulin itself. We attempt to produce a balanced review with a focus on the effect of insulin in vivo, in animal models of atherosclerosis and restenosis.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".