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Record W4410176466 · doi:10.1183/13993003.00322-2025

Pulmonary arterial hypertension and targeting pulmonary vascular remodelling: are we there yet?

2025· letter· en· W4410176466 on OpenAlexaff
James Lordan, Jason Weatherald

Bibliographic record

VenueEuropean Respiratory Journal · 2025
Typeletter
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineVascular remodelling in the embryoPulmonary hypertensionCardiologyInternal medicinePulmonary vasculaturePulmonary arterial pressure

Abstract

fetched live from OpenAlex

Extract Pulmonary arterial hypertension (PAH) is a rare, progressive disorder of the pre-capillary pulmonary circulation, characterised by progressive pulmonary vascular remodelling and vasoconstriction, increased pulmonary vascular resistance, right ventricular hypertrophy, right heart failure and premature death, despite the development of several effective therapies [1–3]. Several factors have been implicated in the pulmonary vascular remodelling, including inflammatory, immunological, epigenetic and genetic factors, such as bone morphogenetic protein receptor type 2 (BMPR2) genetic variants, the most prevalent genetic variant identified in hereditable PAH [4]. Strong associations have been identified between the development of PAH, and 1) aberrant bone morphogenetic protein (BMP) signalling via BMPR2 receptors, 2) dysregulated growth factors, manifesting an imbalance in proliferative and anti-proliferative transforming growth factor (TGF)-β signalling and upregulation of the activin pathway regulated by ActRIIA, 3) progressive endothelial cell dysfunction, 4) pathological distal fibro-proliferation, and 5) plexogenic pulmonary vascular remodelling [4, 5].

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)0.006
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: Editorial · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0140.012
Insufficient payload (model declined to judge)0.0120.008

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 head0.055
GPT teacher head0.270
Teacher spread0.215 · 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
GenreEditorial

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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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