The Influence Of Obesity‐Associated Metabolic Disturbance On The Profile Of Angiogenic Regulators And Capillary Number Within Skeletal Muscle
Bibliographic record
Abstract
Skeletal muscle capillaries are critical determinants of nutrient delivery and utilization and capillary network density is thought to correlate with insulin sensitivity. Conflicting data exist regarding the consequence of obesity‐associated metabolic disturbances on skeletal muscle capillarization, with positive, negative and no effect having been reported. The purpose of this investigation is to assess the influence of obesity induced by high fat feeding or by leptin receptor mutation, on the angiogenic profile within the skeletal muscle microenvironment, and ultimately, on muscle capillarization. In FVB/n mice fed a high‐fat (HF) or normal chow (NC) diet for 16‐weeks, mRNA levels of VEGF‐A did not change (NC: 1.06 vs. HF: 1.13; P >0.05) but VEGF protein levels were elevated (NC: 81 vs HF: 104 pg/mg; P =0.02). Relative FoxO1 protein levels increased in capillaries isolated from muscle of HF vs. NC mice (NC: 0.67 vs HF: 1.55; P =0.03). Capillary‐to‐fibre ratio (C:F) was not altered in HF‐ compared to NC‐ fed mice (2.22 and 2.04, P =0.34). In contrast, 13 week old mice with leptin receptor activity deficiency (Lepr db ) had a significant reduction in VEGF‐A mRNA (1.85 vs. 1.09, P =0.03) and protein (WT: 98 vs Lepr db : 86 pg/mg; P <0.05) relative to age‐matched C57BL/6 (WT) mice. Both FoxO1 (0.58 vs. 0.86) and THBS1 (0.37 vs. 0.81) mRNA levels tended to increase in Lepr db vs. WT mice. Skeletal muscle C:F was substantially reduced in Lepr db vs. WT mice (1.92 vs. 1.39, P <0.001). Comprehensive profiling of angiogenic regulators will be conducted by microarray analysis. The skeletal muscle microenvironment differs substantially between HF and Lepr db models. Our data suggest that muscle capillarization is maintained during HF feeding due to a balance between pro and anti‐angiogenic factors, which may include VEGF‐A and FoxO1. This balance is disrupted in leptin receptor mutant mice, which results in a loss of capillaries and raises the intriguing possibility that leptin signaling itself modulates muscle capillarization. Thus, the Lepr db model may not be a suitable model to study obesity‐induced vascular alterations in skeletal muscle. Funded by CIHR.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".