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Record W2168518422 · doi:10.1177/0954411911399826

Nanocomposite biomaterial mimicking aortic heart valve leaflet mechanical behaviour

2011· article· en· W2168518422 on OpenAlexafffund
Hadi Mohammadi

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine · 2011
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health ResearchCentre International de Recherche sur le Cancer
KeywordsMaterials scienceComposite materialSelf-healing hydrogelsPolyvinyl alcoholBiomaterialHeart valveUltimate tensile strengthNanocompositeVinyl alcoholComposite numberAortic valveBiomedical engineeringPolymerNanotechnologySurgeryPolymer chemistryMedicine

Abstract

fetched live from OpenAlex

The main problem with polymeric heart valves (which are already biocompatible) is that they usually fail in the long term owing to tearing and calcification of the leaflets under high dynamic tensile bending stress and oxidative reactions with blood. To overcome this shortcoming, it is hypothesized that synthetic valve leaflets which mimic native valve leaflet structure fabricated from fibre-reinforced composite material will optimize leaflet stresses and decrease tears and perforations. The objective of this study is to develop a PVA-BC (polyvinyl alcohol-bacterial cellulose)-based hydrogel that mimics not only the non-linear mechanical properties displayed by porcine heart valves, but also their anisotropic behaviour. By applying a controlled strain to the PVA samples, while undergoing low-temperature thermal cycling, it was possible to create oriented mechanical properties in PVA hydrogels. The oriented stress-strain properties of porcine aortic valves were matched simultaneously by a PVA hydrogel (15 per cent PVA, 0.5 BC cycle 4, 75 per cent initial tensile strain). This novel technique allows the control of anisotropy to PVA hydrogel, and gives a broad range of control of its mechanical properties, for specific medical device applications.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.691

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.018
GPT teacher head0.244
Teacher spread0.227 · 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 designBench or experimental
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

Citations73
Published2011
Admission routes2
Has abstractyes

Explore more

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