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Record W1978762059 · doi:10.1002/jbm.b.31616

Acetaldehyde plasma polymer‐coated PET fibers for endothelial cell patterning: Chemical, topographical, and biological analysis

2010· article· en· W1978762059 on OpenAlexaff
Afra Hadjizadeh

Bibliographic record

VenueJournal of Biomedical Materials Research Part B Applied Biomaterials · 2010
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsMaterials sciencePolyethylene terephthalateSurface modificationPolymerAdhesionAdhesiveX-ray photoelectron spectroscopyAcetaldehydeChemical engineeringDextranNanotechnologyComposite materialChemistryChromatographyOrganic chemistryLayer (electronics)

Abstract

fetched live from OpenAlex

The objective of this study was to produce fibrous biomaterials with cell adhesive and cell repulsive capabilities for biomedical applications. To this aim, the surface of 100-mum diameter polyethylene terephthalate fibers were functionalized with acetaldehyde plasma polymer deposition followed by carboxymethyl dextran grafting onto the aldehyde-coated surfaces via a polyethyleneimine interlayer. The performance of the surface modification steps were confirmed by surface chemical composition analysis using X-ray photoelectron spectroscopy, surface topography analysis by atomic force microscopy, and scanning electron microscopy. The acetaldehyde plasma polymer-coated and polyethyleneimine-grafted substrates promoted human umbilical vein endothelial cells attachment, spreading and actin filaments/focal adhesions formation. In contrast, carboxymethyl dextran-grafted substrates resisted cell adhesion. These observations demonstrate that the current surface-modified polymer fibers can be used in tissue engineering applications, such as cell patterning substrates or vascular prosthesis development.

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)0.009
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
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 score0.014
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0010.004
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.030
GPT teacher head0.322
Teacher spread0.293 · 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.

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

Citations23
Published2010
Admission routes1
Has abstractyes

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