MétaCan
Menu
Back to cohort
Record W2009372345 · doi:10.1042/cs20060337

Arterial adaptations to chronic changes in haemodynamic function: coupling vasomotor tone to structural remodelling

2007· review· en· W2009372345 on OpenAlexaff
Dorota Dajnowiec, B. Lowell Langille

Bibliographic record

VenueClinical Science · 2007
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAngiogenesis and VEGF in Cancer
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsVascular remodelling in the embryoHemodynamicsContext (archaeology)PathologicalExtracellular matrixVasomotorMedicineCardiologyInternal medicineNeuroscienceBiologyCell biology

Abstract

fetched live from OpenAlex

Healthy mature arteries are usually extremely quiescent tissues with cell proliferation rates much below 1%/day and with extracellular matrix constituents exhibiting half-lives of years to decades. However, chronic physiological or pathological changes in haemodynamic function elicit arterial remodelling processes that may involve substantial tissue synthesis, degradation or turnover. Although these remodelling processes accommodate changing demands placed upon the cardiovascular system by physiological adaptations, they can compromise further perfusion in the context of arterial occlusive disease and they entrench hypertension and may exacerbate its progression. Recent findings indicate that some of the most important such remodelling responses involve the integrated effects of persistently altered vascular tone that feed into restructuring responses, with common signalling pathways frequently interacting in the control of both phases of the response. Current efforts to define these signals and their targets may provide new directions for therapeutic interventions to treat important vascular disorders.

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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.004

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 head0.136
GPT teacher head0.462
Teacher spread0.326 · 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

Citations98
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueClinical ScienceSame topicAngiogenesis and VEGF in CancerFrench-language works237,207