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Record W3125330298 · doi:10.1183/13993003.03957-2020

Endothelial cells in the pathogenesis of pulmonary arterial hypertension

2021· review· en· W3125330298 on OpenAlexaff
Colin E. Evans, Nicholas D Cober, Duncan J. Stewart, You‐Yang Zhao

Bibliographic record

VenueEuropean Respiratory Journal · 2021
Typereview
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersNational Heart, Lung, and Blood InstituteAmerican Heart Association
KeywordsMedicinePathogenesisVasoconstrictionHypoxic pulmonary vasoconstrictionPathophysiologyOxidative stressInflammationVascular remodelling in the embryoPulmonary hypertensionAngiogenesisEndothelial dysfunctionPathologyImmunologyCardiologyCancer researchInternal medicine

Abstract

fetched live from OpenAlex

Pulmonary arterial hypertension (PAH) is a devastating disease that involves pulmonary vasoconstriction, small vessel obliteration, large vessel thickening and obstruction, and development of plexiform lesions. PAH vasculopathy leads to progressive increases in pulmonary vascular resistance, right heart failure and, ultimately, premature death. Besides other cell types that are known to be involved in PAH pathogenesis ( e.g. smooth muscle cells, fibroblasts and leukocytes), recent studies have demonstrated that endothelial cells (ECs) have a crucial role in the initiation and progression of PAH. The EC-specific role in PAH is multi-faceted and affects numerous pathophysiological processes, including vasoconstriction, inflammation, coagulation, metabolism and oxidative/nitrative stress, as well as cell viability, growth and differentiation. In this review, we describe how EC dysfunction and cell signalling regulate the pathogenesis of PAH. We also highlight areas of research that warrant attention in future studies, and discuss potential molecular signalling pathways in ECs that could be targeted therapeutically in the prevention and treatment of PAH.

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)0.000
metaresearch head score (Gemma)0.000
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
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.103
GPT teacher head0.330
Teacher spread0.227 · 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

Citations307
Published2021
Admission routes1
Has abstractyes

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