Diabetes Impaired Ischemia-Induced PDGF (Platelet-Derived Growth Factor) Signaling Actions and Vessel Formation Through the Activation of Scr Homology 2-Containing Phosphatase-1
Bibliographic record
Abstract
Objective: Critical limb ischemia is a major complication of diabetes characterized by insufficient collateral vessel development and proper growth factor signaling unresponsiveness. Although mainly deactivated by hypoxia, phosphatases are important players in the deregulation of proangiogenetic pathways. Previously, SHP-1 (Scr homology 2-containing phosphatase-1) was found to be associated with the downregulation of growth factor actions in the diabetic muscle. Thus, we aimed to gain further understanding of the impact of SHP-1 on smooth muscle cell (SMC) function under hypoxic and diabetic conditions. Approach and Results: Despite being inactivated under hypoxic conditions, high glucose level exposure sustained SHP-1 phosphatase activity in SMC and increased its interaction with PDGFR (platelet-derived growth factor receptor)-β, thus reducing PDGF proangiogenic actions. Overexpression of an inactive form of SHP-1 fully restored PDGF-induced proliferation, migration, and signaling pathways in SMC exposed to high glucose and hypoxia. Nondiabetic and diabetic mice with deletion of SHP-1 specifically in SMC were generated. Ligation of the femoral artery was performed, and blood flow was measured for 4 weeks. Blood flow reperfusion, vascular density and maturation, and limb survival were all improved while vascular apoptosis was attenuated in diabetic SMC-specific SHP-1 null mice as compared to diabetic mice. Conclusions: Diabetes and high glucose level exposure maintained SHP-1 activity preventing hypoxia-induced PDGF actions in SMC. Specific deletion of SHP-1 in SMC partially restored blood flow reperfusion in the diabetic ischemic limb. Therefore, local modulation of SHP-1 activity in SMC could represent a potential therapeutic avenue to improve the proangiogenic properties of SMC under ischemia and diabetes.
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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".