Differential ANG II-induced growth activation pathways in mesenteric artery smooth muscle cells from SHR
Bibliographic record
Abstract
Angiotensin II-induced growth signaling mechanisms were investigated in vascular smooth muscle cells (VSMCs) from mesenteric arteries of spontaneously hypertensive (SHR) and Wistar-Kyoto rats (WKY). In WKY, angiotensin II significantly increased protein synthesis ([(3)H]leucine incorporation) but not DNA synthesis ([(3)H]thymidine incorporation). In SHR, angiotensin II increased protein and DNA synthesis. VSMCs from both strains expressed angiotensin type 1 (AT(1)) and type 2 (AT(2)) receptors. Losartan (an AT(1) receptor antagonist) but not PD-123319 (an AT(2) receptor antagonist) attenuated angiotensin II-stimulated protein synthesis in WKY VSMCs. In SHR, losartan and PD-123319 partially inhibited angiotensin II-induced VSMC proliferation. The mitogen-activated protein kinase or extracellular signal-regulated protein kinase (ERK) kinase inhibitor PD-98059 blocked VSMC growth responses to angiotensin II in both strains. Angiotensin II increased ERK1/2 activation more in SHR than WKY, an effect inhibited by losartan but not PD-123319. LY-294002 [a phosphatidylinositol-3 (PI3) kinase inhibitor] blocked angiotensin II-stimulated ERK1/2 activation in SHR but not in WKY, whereas bisindolylmaleimide [a protein kinase C (PKC) inhibitor] was ineffective. In conclusion, angiotensin II stimulates VSMC proliferation via AT(1) and AT(2) receptors in SHR. In WKY, angiotensin II induces VSMC hypertrophy via AT(1) receptors. ERK1/2-dependent pathways regulated by intracellular Ca(2+) but not PKC mediate these effects. In SHR VSMCs, PI3 kinase plays a role in augmented angiotensin II-induced ERK1/2 phosphorylation. These angiotensin II-mediated signaling events could contribute to vascular remodeling in SHR.
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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) | 0.001 | 0.001 |
| 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".