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Record W4398210000 · doi:10.1038/s41440-024-01731-6

Immunological insights into hypertension: unraveling triggers and potential therapeutic avenues

2024· review· en· W4398210000 on OpenAlexaff
Brandon Shokoples, Pierre Paradis, Ernesto L. Schiffrin

Bibliographic record

VenueHypertension Research · 2024
Typereview
Languageen
FieldNursing
TopicSodium Intake and Health
Canadian institutionsJewish General HospitalMcGill University
Fundersnot available
KeywordsMedicineComputational biologyBiology

Abstract

fetched live from OpenAlex

Hypertension remains the leading cause of morbidity and mortality worldwide. Despite its prevalence, the development of novel antihypertensive therapies has only recently accelerated, with novel agents not yet commercialized, leaving a substantial proportion of individuals resistant to existing treatments. The intricate pathophysiology of hypertension is now understood to involve chronic low-grade inflammation, which places the immune system in the spotlight as a potential target for new therapeutics. This review explores the factors that initiate and sustain an immune response in hypertension, offering insights into potential targets for new treatments. Several factors contribute to immune activation in hypertension, including diet and damage-associated molecular pattern (DAMP) generation. Diets rich in fat or sodium can promote inflammation by inducing intestinal barrier dysfunction and triggering salt-sensitive receptors in T cells and dendritic cells. DAMPs, such as extracellular adenosine triphosphate and heat-shock protein 70, are released during episodes of increased blood pressure, contributing to immune cell activation and inflammation. Unconventional innate-like γδ T cells contribute to initiating and maintaining an immune response through their potential involvement in antigen presentation and regulating cytokine-mediated responses. Immunologic memory, sustained through the formation of effector memory T cells after exposure to hypertensive insults, likely contributes to maintaining an immune response in hypertension. When exposed to hypertensive insults, these memory cells are rapidly activated and contribute to elevated blood pressure and end-organ damage. Evidence from human hypertension, although limited, supports the relevance of distinct immune pathways in hypertension, and highlights the potential of targeted immune interventions in human hypertension. Diet and acute bouts of high blood pressure result in the release of dietary triggers, neoantigens, and damage-associated molecular patterns (DAMPs), which promote immune system activation. Elements such as lipopolysaccharides (LPS), sodium, heat-shock protein (HSP)70, extracellular adenosine triphosphate (eATP), and growth arrest-specific 6 (GAS6) promote activation of innate immune cells such as dendritic cells (DCs) and monocytes (Mo) through their respective receptors (toll-like receptor [TLR]4, amiloride-sensitive epithelial sodium channel [ENaC], TLR2/4, P2X7 receptor [P2RX7], and Axl) leading to costimulatory molecule expression and interleukin (IL)-1β and IL-23 production. The neoantigens HSP70 and isolevuglandins (IsoLGs) are presented to T cells by DCs and possibly γδ T cells, triggering T cell activation, IL-17 and interferon (IFN)-γ production, and the formation of T effector memory (T EM ) cells in the kidney, perivascular adipose tissue, bone marrow, and spleen. Exposure of T EM cells to their cognate antigen or previous activating stimuli causes these cells rapid expansion and activation. Cumulatively, this inflammatory state contributes to hypertension and end-organ damage. The figure was created using images from smart.servier.com and is licensed under a Creative Commons Attribution 4.0 license (CC BY 4.0).

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.282
GPT teacher head0.450
Teacher spread0.168 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations16
Published2024
Admission routes1
Has abstractyes

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