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Record W2050842091 · doi:10.1115/sbc2011-53161

Degree of Retrograde Flow and Its Effect on Local Hemodynamics and Plaque Distribution in an Aortic Regurgitation Murine Model of Atherosclerosis

2011· article· en· W2050842091 on OpenAlexaff
Yiemeng Hoi, Mark Van Doormaal, Yuqing Zhou, Xiaoli Zhang, R. Mark Henkelman, David A. Steinman

Bibliographic record

VenueASME 2011 Summer Bioengineering Conference, Parts A and B · 2011
Typearticle
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsHemodynamicsRegurgitation (circulation)Blood flowCardiologyInternal medicineMedicineDiastoleLesionAortic valveDoppler effectAbdominal aortaUltrasoundAortaAnatomyBlood pressureRadiologyPathologyPhysics

Abstract

fetched live from OpenAlex

Previously, Zhou et al. [1] presented a novel mouse model of aortic valve regurgitation (AR) to explore the effect of altered hemodynamics on atherogenesis. In these ldlr−/− mice with AR, extensive atherosclerotic plaque was found along the naturally lesion-free descending thoracic (DTAo) and abdominal aorta (AbAo), with distinct spatial distributions suggestive of a strong local hemodynamic influence (Fig. 1, top). Doppler ultrasound measurement showed that both DTAo and AbAo of the AR mice experienced an oscillatory flow pattern induced by the diastolic retrograde flow, as opposed to the consistent antegrade flow found in the non-AR mice. The study also suggested that the fraction of the DTAo surface covered by lesions tends to increase with the absolute diastolic retrograde Time-Velocity Integral (TVI) as measured from the Doppler ultrasound.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.063
GPT teacher head0.265
Teacher spread0.202 · 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 designSimulation or modeling
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

Citations1
Published2011
Admission routes1
Has abstractyes

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Same venueASME 2011 Summer Bioengineering Conference, Parts A and BSame topicCoronary Interventions and DiagnosticsFrench-language works237,207