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Record W4417276390 · doi:10.1063/5.0272634

Defining the parameter space for construction of cardiac ventricle models

2025· article· en· W4417276390 on OpenAlexafffund
Sargol Okhovatian, Milica Radisic

Bibliographic record

VenueBiophysics Reviews · 2025
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchNational Institutes of HealthAdditional Ventures
KeywordsCardiac VentricleVentricleFabricationCardiac cellEndocardiumOrientation (vector space)Cardiac myocyteArtificial heart

Abstract

fetched live from OpenAlex

The human heart is essential for circulation of nutrients, oxygen, and signalling molecules, with the left ventricle (LV) ejecting approximately 2000 gallons of blood per day. At the μm-scale, the myocardium is comprised of diverse cell types, with multinucleated and elongated cardiomyocytes being the main driver of cardiac contractions. At the mm scale, the myocardium is composed of cardiac myofibers aligned in directions ranging from 60° to –60°. This unique fiber orientation drives the cardiac wringing motion, with the base rotating clockwise and the apex counterclockwise, to enhance the ejection fraction. Novel fabrication techniques have enabled creation of sophisticated and functionally relevant cardiac structures capturing various aspects of heart architecture, such as conical shape of the ventricle as well as multilayered and helical fiber directionality. Designing models of LV cavity faces complex challenges such as consideration of cell type and density, scaling, biomaterials of choice, fabrication technique and vascularization. Advancements in adjacent fields such as organoid biology, heart-on-a-chips and biomaterial design could inspire high-throughput fabrication of LV models for enhanced drug screening and enhanced insight into impacts of anatomical abnormalities. LV models also hold promise for upsizing them to human-sized transplantable ventricles that aid therapeutic strategies in cardiovascular medicine.

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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.870
Threshold uncertainty score0.210

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 head0.027
GPT teacher head0.306
Teacher spread0.278 · 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 designOther design
Domainnot available
GenreMethods

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

Citations0
Published2025
Admission routes2
Has abstractyes

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