Statin-Induced Insulin Resistance Through Inflammasome Activation: Sailing Between Scylla and Charybdis
Bibliographic record
Abstract
Elevated LDL cholesterol is an independent risk factor for cardiovascular disease (CVD), and current clinical guidelines recommend aggressive reduction as the preferred course of treatment (1). Type 2 diabetes (T2D) also is a major and independent risk factor for development of CVD (2). A plethora of clinical data exists substantiating the beneficial effects of treatment with inhibitors of 3-hydroxy-3-methylglutaryl-CoA (HMG-CoA) reductases—commonly known as statins—on cardiovascular morbidity and mortality in both nondiabetic people and those with T2D (3). While statin therapy clearly reduces cardiovascular events, accumulating evidence indicates that statins also may confer increased risk for T2D (4). Recent analyses of both clinical trials and population-based cohort studies suggest that the cardiovascular benefits of statin therapy outweigh the risk of developing T2D (5,6). Nevertheless, findings that suggest increased incidence of T2D in some high-risk patients (e.g., those with elevated fasting glucose [5]) or in certain populations (e.g., postmenopausal women [7]) may call for greater caution in statin use, particularly at a time when its over-the-counter availability is being considered (8). Given the overwhelming consensus from both meta-analyses and prospective studies that statin treatment can result in an increased risk of developing T2D, it is critical to identify the underlying causes of this unfavorable side effect. It has been suggested that statins increase T2D risk by impairing β-cell insulin secretion and promoting insulin resistance (9), but the precise molecular mechanisms are still unknown. Numerous studies have demonstrated intimate involvement of the innate immune system in both obesity and the pathogenesis of T2D (10,11). In recent years, pattern recognition receptors of the innate immune system, such as Toll-like receptors and Nod-like receptors (NLRs), have been increasingly recognized as links between immune function and metabolism (12,13). The NLR family, pyrin domain containing 3 …
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".