T Regulatory Lymphocytes Prevent Angiotensin II–Induced Hypertension and Vascular Injury
Bibliographic record
Abstract
Angiotensin (Ang) II induces hypertension by mechanisms mediated in part by adaptive immunity and T effector lymphocytes. T regulatory lymphocytes (Tregs) suppress T effector lymphocytes. We questioned whether Treg adoptive transfer would blunt Ang II-induced hypertension and vascular injury. Ten- to 12-week-old male C57BL/6 mice were injected IV with 3 ×10(5) Treg (CD4(+)CD25(+)) or T effector (CD4(+)CD25(-)) cells, 3 times at 2-week intervals, and then infused or not with Ang II (1 μg/kg per minute, SC) for 14 days. Ang II increased systolic blood pressure by 43 mm Hg (P<0.05), NADPH oxidase activity 1.5-fold in aorta and 1.8-fold in the heart (P<0.05), impaired acetylcholine vasodilatory responses by 70% compared with control (P<0.05), and increased vascular stiffness (P<0.001), mesenteric artery vascular cell adhesion molecule expression (2-fold; P<0.05), and aortic macrophage and T-cell infiltration (P<0.001). All of the above were prevented by Treg but not T effector adoptive transfer. Ang II caused a 43% decrease in Foxp3(+) cells in the renal cortex, whereas Treg adoptive transfer increased Foxp3(+) cells 2-fold compared with control. Thus, Tregs suppress Ang II-mediated vascular injury in part through anti-inflammatory actions. Immune mechanisms modulate Ang II-induced blood pressure elevation, vascular oxidative stress, inflammation, and endothelial dysfunction.
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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".