PKCδ Impaired Vessel Formation and Angiogenic Factor Expression in Diabetic Ischemic Limbs
Bibliographic record
Abstract
Decreased collateral vessel formation in diabetic peripheral limbs is characterized by abnormalities of the angiogenic response to ischemia. Hyperglycemia is known to activate protein kinase C (PKC), affecting the expression and activity of growth factors such as vascular endothelial growth factor (VEGF) and platelet-derived growth factor (PDGF). The current study investigates the role of PKCδ in diabetes-induced poor collateral vessel formation and inhibition of angiogenic factors expression and actions. Ischemic adductor muscles of diabetic Prkcd(+/+) mice exhibited reduced blood reperfusion, vascular density, and number of small vessels compared with nondiabetic Prkcd(+/+) mice. By contrast, diabetic Prkcd(-/-) mice showed significant increased blood flow, capillary density, and number of capillaries. Although expression of various PKC isoforms was unchanged, activation of PKCδ was increased in diabetic Prkcd(+/+) mice. VEGF and PDGF mRNA and protein expression were decreased in the muscles of diabetic Prkcd(+/+) mice and were normalized in diabetic Prkcd(-/-) mice. Furthermore, phosphorylation of VEGF receptor 2 (VEGFR2) and PDGF receptor-β (PDGFR-β) were blunted in diabetic Prkcd(+/+) mice but elevated in diabetic Prkcd(-/-) mice. The inhibition of VEGFR2 and PDGFR-β activity was associated with increased SHP-1 expression. In conclusion, our data have uncovered the mechanisms by which PKCδ activation induced poor collateral vessel formation, offering potential novel targets to regulate angiogenesis therapeutically in diabetic patients.
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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".