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Record W2810785966 · doi:10.1111/bph.14427

Role of immune cells in hypertension

2018· review· en· W2810785966 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBritish Journal of Pharmacology · 2018
Typereview
Languageen
FieldNursing
TopicSodium Intake and Health
Canadian institutionsMcGill UniversityJewish General Hospital
FundersCanadian Institutes of Health Research
KeywordsInnate immune systemImmune systemImmunologyInflammationInnate lymphoid cellAcquired immune systemBiology

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.958
Threshold uncertainty score0.898

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.043
GPT teacher head0.365
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it