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Record W2142856822 · doi:10.1093/cvr/cvn345

Vascular smooth muscle cells sense calcium: a new paradigm in vascular calcification

2008· letter· en· W2142856822 on OpenAlexaff
Rhian M. Touyz, A. C. Montezano

Bibliographic record

VenueCardiovascular Research · 2008
Typeletter
Languageen
FieldMedicine
TopicParathyroid Disorders and Treatments
Canadian institutionsUniversity of Ottawa
FundersAmgen
KeywordsCalcificationVascular smooth muscleAdventitiaMedicinePathologyVascular diseaseInternal medicineCardiologySmooth muscle

Abstract

fetched live from OpenAlex

Calcification of arteries is a complex and dynamic process frequently seen in atherosclerosis, diabetes, and chronic kidney disease. This phenomenon, now considered a distinct inflammatory arteriopathy, has important clinical significance because arterial calcification is associated with increased cardiovascular events and is a strong predictor of poor cardiovascular outcomes.1,2 Patients with high coronary artery calcification scores have a five- to seven-fold increase in the risk of a hard coronary event compared with patients with low calcium scores, and patients with chronic kidney disease and vascular calcification have a 20- to 30-fold increase in cardiovascular mortality.2 Arterial calcification is a pathological process involving the vascular media and adventitia.3 Medial vascular smooth muscle cells (VSMCs) lose their ability to express smooth muscle-specific markers and undergo phenotypic transformation to osteoblast-like cells. Perivascular adventitial cells, microvascular pericytes, and adventitial mesenchymal stem cells also have the potential to express osteoblastic transcription factors, suggesting that, in addition to VSMCs, other vascular cell types contribute to calcification. The course of vascular calcification shares many features with that of bone mineralization, except that whereas skeletal mineralization is a physiological and highly regulated process, vascular calcification is a pathological phenomenon associated with extraskeletal mineralization in the vascular wall.2,3 Passive calcium phosphate deposition, active cell-mediated processes, and inflammatory responses contribute to vascular calcification.4–7 Of the many cellular regulators, the bone morphogenic proteins (BMP) seem to be particularly important.7 BMP-2/BMP-4 binds the BMPR1/BMPR2 receptor complex and activates the Smad signalling pathway, which induces expression of transcription factors Cbfa1, osterix, and MSX-2. BMP-4 also stimulates the generation of reactive oxygen species. These events lead to a phenotypic change in VSMCs to an osteogenic phenotype, which expresses alkaline phosphatase and produces hydroxyapatite crystals. Calcification inhibitors such as fetuin-A, MGP, osteoprotegerin, osteopontin, BMP-7, and Smad 6 antagonize BMP-2/BMP-4 signalling and inhibit vascular calcification.4,5,8 Many other factors, both stimulatory and inhibitory, have also been implicated in vascular calcification (Table 1), indicating the complexity of the process.7–9

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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.027
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.003
Scholarly communication0.0030.004
Open science0.0020.001
Research integrity0.0270.028
Insufficient payload (model declined to judge)0.0060.005

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 head0.116
GPT teacher head0.350
Teacher spread0.234 · 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

Citations10
Published2008
Admission routes1
Has abstractyes

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