PDGF-BB regulates splitting angiogenesis in skeletal muscle by limiting VEGF-induced endothelial proliferation
Bibliographic record
Abstract
VEGF induces normal or aberrant angiogenesis depending on its dose in the microenvironment around each producing cell in vivo. This transition depends on the balance between VEGF-induced endothelial stimulation and PDGF-BB-mediated pericyte recruitment, and co-expression of PDGF-BB normalizes aberrant angiogenesis despite high VEGF doses. We recently found that VEGF over-expression induces angiogenesis in skeletal muscle through an initial circumferential vascular enlargement followed by longitudinal splitting, rather than sprouting. Here we investigated the cellular mechanism by which PDGF-BB co-expression normalizes VEGF-induced aberrant angiogenesis. Monoclonal populations of transduced myoblasts, expressing similarly high levels of VEGF alone or with PDGF-BB, were implanted in mouse skeletal muscles. PDGF-BB co-expression did not promote sprouting and angiogenesis that occurred through vascular enlargement and splitting. However, enlargements were significantly smaller in diameter, due to a significant reduction in endothelial proliferation, and retained pericytes, which were otherwise lost with high VEGF alone. A time-course of histological analyses and repetitive intravital imaging showed that PDGF-BB co-expression anticipated the initiation of vascular enlargement and markedly accelerated the splitting process. Interestingly, quantification during in vivo imaging suggested that a global reduction in shear stress favored the initiation of transluminal pillar formation during VEGF-induced splitting angiogenesis. Quantification of target gene expression showed that VEGF-R2 signaling output was significantly reduced by PDGF-BB co-expression compared to VEGF alone. In conclusion, PDGF-BB co-expression prevents VEGF-induced aberrant angiogenesis by modulating VEGF-R2 signaling and endothelial proliferation, thereby limiting the degree of circumferential enlargement and enabling efficient completion of vascular splitting into normal capillary networks despite high VEGF doses.
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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) | 0.000 | 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 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".