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Record W2791004319 · doi:10.1093/cvr/cvy022

Smooth muscle cell fate and plasticity in atherosclerosis

2018· review· en· W2791004319 on OpenAlexafffund
Sima Allahverdian, Chiraz Chaâbane, Kamel Boukais, Gordon A. Francis, Marie‐Luce Bochaton‐Piallat

Bibliographic record

VenueCardiovascular Research · 2018
Typereview
Languageen
FieldImmunology and Microbiology
TopicAtherosclerosis and Cardiovascular Diseases
Canadian institutionsSt. Paul's HospitalUniversity of British ColumbiaProvidence Health Care Research Institute
FundersCanadian Institutes of Health ResearchSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsPhenotypeSmooth muscleBiologyPathologyPopulationCellPlasticityCell biologyPhenotypic plasticityFibrous capMedicineEndocrinologyGenetics

Abstract

fetched live from OpenAlex

Current knowledge suggests that intimal smooth muscle cells (SMCs) in native atherosclerotic plaque derive mainly from the medial arterial layer. During this process, SMCs undergo complex structural and functional changes giving rise to a broad spectrum of phenotypes. Classically, intimal SMCs are described as dedifferentiated/synthetic SMCs, a phenotype characterized by reduced expression of contractile proteins. Intimal SMCs are considered to have a beneficial role by contributing to the fibrous cap and thereby stabilizing atherosclerotic plaque. However, intimal SMCs can lose their properties to such an extent that they become hard to identify, contribute significantly to the foam cell population, and acquire inflammatory-like cell features. This review highlights mechanisms of SMC plasticity in different stages of native atherosclerotic plaque formation, their potential for monoclonal or oligoclonal expansion, as well as recent findings demonstrating the underestimated deleterious role of SMCs in this disease.

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.115
GPT teacher head0.339
Teacher spread0.224 · 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

Citations505
Published2018
Admission routes2
Has abstractyes

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