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Mini-review: The role of mast cells in pulmonary hypertension

2017· article· en· W2931181884 on OpenAlexaff
Yijie Hu, Wolfgang M. Kuebler

Bibliographic record

VenueJournal of Rare Diseases Research & Treatment · 2017
Typearticle
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMast (botany)Pulmonary hypertensionMedicineCardiologyMast cellImmunology

Abstract

fetched live from OpenAlex

Of recent, inflammatory responses, formation of ectopic lymphoid tissue and autoantibodies have been increasingly implicated in the pathophysiology of pulmonary hypertension (PH).One of the earliest immune cells detected in PH and implicated in its pathogenesis were mast cells based on their demonstrated abundance in the vicinity of vascular lesions in PH patients, as well as in lungs of animal models of PH.Experimental studies using mast cell stabilizers or mast cell deficient rats in classic PH models provided proofof-principle for the functional relevance of mast cells in the initiation and/or progression of PH and lung vascular remodeling.Yet, the cellular mechanisms by which mast cells contribute to the development of PH and pulmonary vascular remodeling have so far remained largely unclear.Importantly, understanding the downstream effectors by which activated mast cells and their secretome trigger or promote vascular remodeling may lead to the development of novel therapies for PH.Notably, recent work has unveiled a novel interplay between mast cells and the adaptive immune system in PH, in that mast cell-targeted interventions attenuate the formation of tertiary lymphoid tissue in the lung and the formation of autoantibodies.This minireview will focus on the role of mast cells in PH and their possible downstream mechanism.

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)0.002
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 score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0100.005

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 head0.059
GPT teacher head0.372
Teacher spread0.313 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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