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Record W2256646073 · doi:10.1160/th15-10-0791

Shear stress, arterial identity and atherosclerosis

2015· article· en· W2256646073 on OpenAlexafffund
Elizabeth A. V. Jones, Stéphanie Lehoux

Bibliographic record

VenueThrombosis and Haemostasis · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAngiogenesis and VEGF in Cancer
Canadian institutionsMcGill University
FundersCanadian Institutes of Health Research
KeywordsBlood flowBlood vesselMedicineNotch signaling pathwayBiologyAnatomyInternal medicineCell biologyCardiologyPathologyReceptor

Abstract

fetched live from OpenAlex

In the developing embryo, the vasculature first takes the form of a web-like network called the vascular plexus. Arterial and venous differentiation is subsequently guided by the specific expression of genes in the endothelial cells that provide spatial and temporal cues for development. Notch1/4, Notch ligand delta-like 4 (Dll4), and Notch downstream effectors are typically expressed in arterial cells along with EphrinB2, whereas chicken ovalbumin upstream promoter transcription factor II (COUP-TFII) and EphB4 characterise vein endothelial cells. Haemodynamic forces (blood pressure and blood flow) also contribute importantly to vascular remodelling. Early arteriovenous differentiation and local blood flow may hold the key to future inflammatory diseases. Indeed, despite the fact that atherosclerosis risk factors such as smoking, hypertension, hypercholesterolaemia, and diabetes all induce endothelial cell dysfunction throughout the vasculature, plaques develop only in arteries, and they localise essentially in vessel branch points, curvatures and bifurcations, where blood flow (and consequently shear stress) is low or oscillatory. Arterial segments exposed to high blood flow (and high laminar shear stress) tend to remain plaque-free. These observations have led many to investigate what particular properties of arterial or venous endothelial cells confer susceptibility or protection from plaque formation, and how that might interact with a particular shear stress environment.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.311
Threshold uncertainty score0.509

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.092
GPT teacher head0.330
Teacher spread0.238 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations56
Published2015
Admission routes2
Has abstractyes

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