CD4 <sup>+</sup> Regulatory T Lymphocytes Prevent Impaired Cerebral Blood Flow in Angiotensin II‐Induced Hypertension
Bibliographic record
Abstract
Background Immune cells are key regulators of the vascular inflammatory response characteristic of hypertension. In hypertensive rodents, regulatory T lymphocytes (Treg, CD 4 + CD 25 + ) prevented vascular injury, cardiac damage, and endothelial dysfunction of mesenteric arteries. Whether Treg modulate the cerebrovascular damage induced by hypertension is unknown. Methods and Results C57 BL /6 mice were perfused with angiotensin II (Ang II ; 1000 ng/kg per minute) for 14 days and adoptive transfer of 3×10 5 CD 4 + CD 25 + T cells was performed via 2 intravenous injections. Control mice received a sham surgery and PBS . Treg prevented Ang II ‐induced neurovascular uncoupling ( P <0.05) and endothelial impairment ( P <0.05), evaluated by laser Doppler flowmetry in the somatosensory cortex. The neuroprotective effect of Treg was abolished when they were isolated from mice deficient in interleukin‐10. Administration of interleukin‐10 (60 ng/d) to hypertensive mice prevented Ang II ‐induced neurovascular uncoupling ( P <0.05). Treg adoptive transfer also diminished systemic inflammation induced by Ang II ( P <0.05), examined with a peripheral blood cytokine array. Mice receiving Ang II + Treg exhibited reduced numbers of Iba‐1+ cells in the brain cortex ( P <0.05) and hippocampus ( P <0.001) compared with mice infused only with Ang II. Treg prevented the increase in cerebral superoxide radicals. Overall, these effects did not appear to be directly modulated by Treg accumulating in the brain parenchyma, because only a nonsignificant number of Treg were detected in brain. Instead, Treg penetrated peripheral tissues such as the kidney, inguinal lymph nodes, and the spleen. Conclusions Treg prevent impaired cerebrovascular responses in Ang II ‐induced hypertension. The neuroprotective effects of Treg involve the modulation of inflammation in the brain and periphery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".