Single‐cell transcriptomic analyses of skin vascular endothelial cells in sedentary and voluntary wheel running young mice
Bibliographic record
Abstract
Physical activity (PA) is a fundamental aspect of preventive medicine, offering profound benefits for cardiovascular health and overall well-being. Despite its widespread benefits, the molecular mechanisms underlying PA-induced improvements in microvascular functions remain poorly understood. The skin microvasculature is uniquely affected by exercise-induced shear stress, especially during thermoregulation. We assigned 20 mice to either a sedentary group or a 1-month voluntary exercise program involving running wheels. We assessed endothelial function in mesenteric arteries and found no significant difference between groups, consistent with prior reports of minimal vascular effects from short-term PA in young healthy mice. Post-intervention, we collected skin biopsies from 12 mice for single-cell transcriptomic analyses. The differential expression analysis showed a significant difference in the expression of the Zbtb16 gene in vascular endothelial cells (vECs), with higher levels in the physically active group. Additionally, Gene Set Enrichment Analysis (GSEA) with nominally differentially expressed genes in vECs highlighted the suppression of pathways related to oxidative stress, cell proliferation, and metabolism in the exercise group. This suggests an exercise-triggered transition towards improved metabolic efficiency and enhanced homeostasis in vECs. These results begin to reveal transcriptomic differences in vECs of the skin microvasculature between physically active and sedentary mice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".