Insulin sensitization by hepatic FoxO deletion is insufficient to lower atherosclerosis in mice
Bibliographic record
Abstract
Abstract Background Type 2 diabetes is associated with an increased risk of atherosclerotic cardiovascular disease. It has been suggested that insulin resistance underlies this link, possibly by altering the functions of cells in the artery wall. We aimed to test whether improving systemic insulin sensitivity reduces atherosclerosis. Methods We used mice that are established to have improved systemic insulin sensitivity: those lacking FoxO transcription factors in hepatocytes. Three hepatic FoxO isoforms (FoxO1, FoxO3, and FoxO4) function together to promote hepatic glucose output, and ablating them lowers glucose production, lowers circulating glucose and insulin, and improves systemic insulin sensitivity. We made these mice susceptible to atherosclerosis in two different ways, by injecting them with gain-of-function AAV8.mPcsk9 D377Y and by crossing with Ldlr −/− mice. Results We verified that hepatic FoxO ablation improves systemic insulin sensitivity in these atherosclerotic settings. We observed that FoxO deficiency caused no reductions in atherosclerosis, and in some cases increased atherosclerosis. These phenotypes coincided with large increases in circulating triglycerides in FoxO-ablated mice. Conclusions These findings suggest that systemic insulin sensitization is insufficient to reduce atherosclerosis. Non-standard Abbreviations and Acronyms Ldlr, low-density lipoprotein receptor; TRL, triglyceride-rich lipoprotein; VLDL, very low-density lipoprotein
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".