Endothelial FoxO proteins impair insulin sensitivity and restrain muscle angiogenesis in response to a high‐fat diet
Bibliographic record
Abstract
Skeletal muscle microvascular dysfunction contributes to disease severity in type 2 diabetes. Recent studies indicate a role for Forkhead box O (FoxO) transcription factors in modulating endothelial cell phenotype. We hypothesized that a high-fat (HF) diet generates a dysfunctional vascular niche through an increased expression of endothelial FoxO. FoxO1 protein increased (+130%) in the skeletal muscle capillaries from HF compared to normal chow-fed mice. FoxO1 protein was significantly elevated in cultured endothelial cells exposed to the saturated fatty acid palmitate or the proinflammatory cytokine TNF-α. In HF-fed mice, endothelium-directed depletion of FoxO1/3/4 (FoxO(Δ)) improved insulin sensitivity (+110%) compared to that of the controls (FoxO(L/L)). The number of skeletal muscle capillaries increased significantly in the HF-FoxO(Δ) mice. Transcript profiling of skeletal muscle identified significant increases in genes associated with angiogenesis and lipid metabolism in HF-FoxO(Δ) vs. HF-FoxO(L/L) mice. HF-FoxO(Δ) muscle also was characterized by a decrease in inflammation-related genes and an enriched M2 macrophage signature. We conclude that endothelial FoxO proteins promote insulin resistance in HF diet, which may in part result from FoxO proteins establishing an antiangiogenic and proinflammatory microenvironment within skeletal muscle. These findings provide mechanistic insight into the development of microvascular dysfunction in the progression of type 2 diabetes.-Nwadozi, E., Roudier, E., Rullman, E., Tharmalingam, S., Liu, H.-Y., Gustafsson, T., Haas, T. L. Endothelial FoxO proteins impair insulin sensitivity and restrain muscle angiogenesis in response to a high-fat diet.
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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) | 0.000 | 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 | 0.000 |
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 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".