Muscle-derived vascular endothelial growth factor regulates microvascular remodelling in response to increased shear stress in mice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIM: The source of vascular endothelial growth factor-A (VEGF-A) may influence vascular function. Exercise-induced vascular growth has been attributed to elevated metabolic demand and to increased blood flow, involving the production of VEGF-A by skeletal muscle and by endothelial cells respectively. We hypothesized that muscle-derived VEGF-A is not required for vascular adaptations to blood flow in skeletal muscle, as this remodelling stimulus originates within the capillary. METHODS: Myocyte-specific VEGF-A (mVEGF(-/-) ) deleted mice were treated for 7-21 days with the vasodilator prazosin to produce a sustained increase in skeletal muscle blood flow. RESULTS: Capillary number increased in the extensor digitorum longus (EDL) muscle in response to prazosin in wild type but not mVEGF(-/-) mice. Prazosin increased the number of smooth muscle actin-positive blood vessels in the EDL of wild-type but not mVEGF(-/-) mice. The average size of smooth muscle actin-positive blood vessels also was smaller in knockout mice after prazosin treatment. In response to prazosin treatment, VEGF-A mRNA was elevated within the EDL of wild-type but not mVEGF(-/-) mice. Ex vivo incubation of wild-type EDL with a nitric oxide donor increased VEGF-A mRNA. Likewise, we demonstrated that nitric oxide donor treatment of cultured myoblasts stimulated an increase in VEGF-A mRNA and protein. CONCLUSION: These results suggest a link through which flow-mediated endothelial-derived signals may promote myocyte production of VEGF-A. In turn, myocyte-derived VEGF-A is required for appropriate flow-mediated microvascular remodelling. This highlights the importance of the local environment and paracrine interactions in the regulation of tissue perfusion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it