Reduction and Prevention of the Cardiovascular Sequelae of the Insulin Resistance Syndrome
Bibliographic record
Abstract
Insulin resistance and hyperinsulinemia are the critical characteristics of the metabolic syndrome that is associated with abdominal obesity and are the early manifestations of its progression to type 2 diabetes. These metabolic abnormalities are becoming recognized as a major contributor to cardiovascular disease. The experimental studies required to elucidate the underlying mechanisms and to develop effective preventative strategies will require the use of appropriate animal models and these are available. The evidence from such research indicates that a wide range of interventions (including peroxisome proliferator activator receptor agonists, insulin-sensitizing agents, statins, fibrates, angiotensin-converting enzyme inhibitors, estrogen receptor modulators, lipid-based nutriceuticals, and ethanol) can markedly reduce or prevent vasculopathy and ischemic cardiac lesions in animal models. Overall, the results suggest that early damage to the vascular wall, both in function and presenting as atherosclerotic lesions, is secondary to long-term hyperinsulinemia and, especially, to postprandial peaks in plasma insulin levels, and is exacerbated by the accompanying hyperlipidemia. Effective treatment will, of necessity, be preventative and will necessitate diagnostic approaches that can identify asymptomatic individuals at high risk for vascular damage and eventual progression to type 2 diabetes. Therapeutic targets in this population include insulin sensitivity and the associated signal transduction pathways, the peroxisome proliferator activator receptor-alpha and -gamma systems, and the complex pathways leading from acetyl CoA and the citric acid cycle to the synthesis of fatty acid and the storage of triglyceride. These pharmacological approaches offer the prospect of preventing a significant proportion of cardiovascular disease.
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 | 0.001 |
| 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 | 0.001 |
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".