Glomerular VEGF resistance induced by PKCδ/SHP‐1 activation and contribution to diabetic nephropathy
Bibliographic record
Abstract
ABSTRACT This study characterizes the effect of glucose‐induced activation of protein kinase Cδ (PKCδ) and Src homology‐2 domain‐containing phosphatase‐1 (SHP‐1) expression on vascular endothelial growth factor (VEGF) actions in glomerular podocytes in cultures and in glomeruli of diabetic rodents. Elevation of glucose levels induced PKCδ and p38 mitogen‐activated protein kinase (p38 MAPK) to increase SHP‐1 expression, increased podocyte apoptosis, and inhibited VEGF activation in podocytes and glomerular endothelial cells. The adverse effects of high glucose levels can be negated by molecular inhibitors of PKCδ, p38MAPK and SHP‐1 and only partially reduced by antioxidants and nuclear factor‐κB (NF‐κB) inhibitor. Increased PKCδ activation and SHP‐1 expression correlated with loss of VEGF signaling and podocyte numbers in the glomeruli of diabetic rats and mice. In contrast, diabetic PKCδ‐knockout ( Prkcd –/– ) mice did not exhibit activation of p38 MAPK and SHP‐1 or inhibition of VEGF signaling in renal glomeruli. Functionally, diabetic Prkcd –/– mice had decreased expressions of TGFβ, VEGF, and extracellular matrix and less albuminuria than diabetic Prkcd +/+ mice. Hyperglycemia and diabetes can cause glomerular podocyte apoptosis and endothelial dysfunction partly due to increased PKCδ/p38 MAPK activation and the expression of SHP‐1 to cause VEGF resistance, independent of NF‐κB activation.—Mima, A., Kitada, M., Geraldes, P., Li, Q., Matsumoto, M., Mizutani, K., Qi, W., Li, C., Leitges, M., Rask‐Madsen, C., King, G. L. Glomerular VEGF resistance induced by PKCδ/SHP‐1 activation and contribution to diabetic nephropathy. FASEB J. 26, 2963–2974 (2012). www.fasebj.org
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".