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Record W2777517924 · doi:10.1177/2045893217752912

Endothelial dysfunction in pulmonary arterial hypertension: an evolving landscape (2017 Grover Conference Series)

2017· article· en· W2777517924 on OpenAlexaff
Benoît Ranchoux, Lloyd D. Harvey, Ramon J. Ayon, Aleksandra Babicheva, Sébastien Bonnet, Stephen Y. Chan, Jason X.‐J. Yuan, Vinicio de Jesús Pérez

Bibliographic record

VenuePulmonary Circulation · 2017
Typearticle
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de QuébecCentre de Recherche Industrielle du Québec
FundersNational Center for Advancing Translational SciencesNational Institute of Environmental Health SciencesNational Heart, Lung, and Blood InstituteNational Institutes of HealthPfizer
KeywordsMedicineEndothelial dysfunctionAngiogenesisEpigeneticsPulmonary hypertensionPathogenesisEndotheliumHypoxia (environmental)BioinformaticsCancer researchCardiologyPathologyInternal medicineBiologyGeneticsGene

Abstract

fetched live from OpenAlex

Endothelial dysfunction is a major player in the development and progression of vascular pathology in pulmonary arterial hypertension (PAH), a disease associated with small vessel loss and obstructive vasculopathy that leads to increased pulmonary vascular resistance, subsequent right heart failure, and premature death. Over the past ten years, there has been tremendous progress in our understanding of pulmonary endothelial biology as it pertains to the genetic and molecular mechanisms that orchestrate the endothelial response to direct or indirect injury, and how their dysregulation can contribute to the pathogenesis of PAH. As one of the major topics included in the 2017 Grover Conference Series, discussion centered on recent developments in four areas of pulmonary endothelial biology: (1) angiogenesis; (2) endothelial-mesenchymal transition (EndMT); (3) epigenetics; and (4) biology of voltage-gated ion channels. The present review will summarize the content of these discussions and provide a perspective on the most promising aspects of endothelial dysfunction that may be amenable for therapeutic development.

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)0.003
metaresearch head score (Gemma)0.004
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0150.005

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 head0.049
GPT teacher head0.286
Teacher spread0.237 · 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

Citations163
Published2017
Admission routes1
Has abstractyes

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