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Record W2056618914 · doi:10.1097/mnh.0b013e328335eec9

Role of extracellular matrix in vascular remodeling of hypertension

2010· review· en· W2056618914 on OpenAlexaff
Ana M. Briones, Silvia M. Arribas, Mercedes Salaíces

Bibliographic record

VenueCurrent Opinion in Nephrology & Hypertension · 2010
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAngiogenesis and VEGF in Cancer
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsExtracellular matrixElastinExtracellularCell biologyArterial stiffnessFibrosisVascular smooth muscleMedicineChemistryBiologyPathologyInternal medicineBlood pressureSmooth muscle

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Arterial stiffness due to alterations in extracellular matrix is one of the mechanisms responsible for increased peripheral resistance in hypertension. Recent evidence points to arterial stiffness as an independent predictor of cardiovascular events. This review focuses on recent advances in the biology of extracellular matrix proteins involved in hypertension-associated vascular changes. RECENT FINDINGS: The vascular extracellular matrix is a complex heterogeneous tissue comprising collagens, elastin, glycoproteins, and proteoglycans. These constituents not only provide mechanical integrity to the vessel wall but also possess a repertoire of insoluble ligands that induce cell signaling to control proliferation, migration, differentiation, and survival. It is now evident that it is not only the quantity but also the quality of the new synthesized extracellular matrix that determines changes in vascular stiffness in hypertension. Also, the control of cross-linking and the interactions between the extracellular matrix and vascular cells seem to be important. SUMMARY: It is now evident that some of the currently used antihypertensive therapies can correct vascular stiffness and fibrosis. A better understanding of molecular mechanisms underlying alterations in extracellular matrix in hypertension will provide insights into novel therapies to reduce arterial stiffness and will identify new roles of established antihypertensive drugs.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.064
GPT teacher head0.334
Teacher spread0.270 · 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 teacher head, not a consensus.

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

Citations98
Published2010
Admission routes1
Has abstractyes

Explore more

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