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Record W2790454938 · doi:10.1177/2045893218757596

Inflammation and autoimmunity in pulmonary hypertension: is there a role for endothelial adhesion molecules? (2017 Grover Conference Series)

2018· article· en· W2790454938 on OpenAlexaff
Wolfgang M. Kuebler, Sébastien Bonnet, Arata Tabuchi

Bibliographic record

VenuePulmonary Circulation · 2018
Typearticle
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsCegep de Sainte Foy
Fundersnot available
KeywordsMedicineInflammationPulmonary hypertensionEndotheliumImmunologyImmune systemLungAutoimmunityEndothelial dysfunctionCardiologyInternal medicine

Abstract

fetched live from OpenAlex

While pulmonary hypertension (PH) has traditionally not been considered as a disease that is directly linked to or, potentially, even caused by inflammation, a rapidly growing body of evidence has demonstrated the accumulation of a variety of inflammatory and immune cells in PH lungs, in and around the wall of remodeled pulmonary resistance vessels and in the vicinity of plexiform lesions, respectively. Concomitantly, abundant production and release of various inflammatory mediators has been documented in both PH patients and experimental models of PH. While these findings unequivocally demonstrate an inflammatory component in PH, they have fueled an intense and presently ongoing debate as to the nature of this inflammatory aspect: is it a mere bystander of or response to the actual disease process, or is it a pathomechanistic contributor or potentially even a trigger of endothelial injury, smooth muscle hypertrophy and hyperplasia, and the resulting lung vascular remodeling? In this review, we will discuss the present evidence for an inflammatory component in PH disease with a specific focus on the potential role of the endothelium in this scenario and highlight future avenues of experimental investigation which may lead to novel therapeutic interventions.

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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0170.006

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 head0.038
GPT teacher head0.279
Teacher spread0.241 · 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
GenreCommentary

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

Citations57
Published2018
Admission routes1
Has abstractyes

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