Role of immune cells in hypertension
Bibliographic record
Abstract
Inflammatory processes have been shown to play an important role in the mechanisms involved in the pathogenesis of hypertension. Innate and adaptive immune responses participate in BP elevation and end-organ damage. Here, we discuss recent studies focusing on novel inflammatory and immune mechanisms that play roles in BP elevation. Different subpopulations of cells involved in innate and adaptive immune responses, such as dendritic cells, monocytes/macrophages and NK cells, on the one hand, and B and T lymphocytes, on the other, contribute to the vascular and kidney injury in hypertension. Unconventional innate-like T cells such as γδ T cells also participate in hypertensive mechanisms by priming both innate and adaptive immune cells, contributing to trigger vascular inflammation and BP elevation. These cells exert their effects in part via production of various cytokines including pro-inflammatory IFN-γ and IL-17 and anti-inflammatory IL-10. The present review summarizes some of these immune mechanisms that participate in the pathophysiology of hypertension. LINKED ARTICLES: This article is part of a themed section on Immune Targets in Hypertension. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v176.12/issuetoc.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".