Role of VEGF in maintaining renal structure and function under normotensive and hypertensive conditions
Bibliographic record
Abstract
Inhibiting the actions of VEGF is a new therapeutic paradigm in cancer management with antiangiogenic therapy also under intensive investigation in a range of nonmalignant diseases characterized by pathological angiogenesis. However, the effects of VEGF inhibition on organs that constitutively express it in adulthood, such as the kidney, are mostly unknown. Accordingly, we examined the effect of VEGF inhibition on renal structure and function under physiological conditions and in the setting of the common renal stressors: hypertension and activation of the renin-angiotensin system. When compared with normotensive Sprague-Dawley (SD) rats, glomerular VEGF mRNA was increased 2-fold in transgenic (mRen-2)27 rats that overexpress renin with spontaneously hypertensive rat (SHR) kidneys showing VEGF expression levels that were intermediate between them. Administration of either an orally active inhibitor of the type 2 VEGF receptor (VEGFR-2) tyrosine kinase or a VEGF neutralizing antibody to TGR(mRen-2)27 rats resulted in loss of glomerular endothelial cells and transformation to a malignant hypertensive phenotype with severe glomerulosclerosis. VEGFR-2 kinase inhibition treatment was well tolerated in SDs and SHRs; although even in these animals there was detectable endothelial cell loss and rise in albuminuria. Mild mesangial expansion was also noted in hypertensive SHR, but not in SD rats. These studies illustrate: (i) VEGF has a role in the maintenance of glomerular endothelial integrity under physiological circumstances, (ii) glomerular VEGF is increased in response to hypertension and activation of the renin-angiotensin system, and (iii) VEGF signaling plays a protective role in the setting of these renal stressors.
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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".