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Record W2008588146 · doi:10.3390/ma3042346

Versatile Biodegradable Poly(ester amide)s Derived from α-Amino Acids for Vascular Tissue Engineering

2010· article· en· W2008588146 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMaterials · 2010
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsWestern University
Fundersnot available
KeywordsBiodegradable polymerDispersityPolymerTissue engineeringHydrolysisMaterials scienceAmino acidPolymerizationPolymer chemistryAmideVascular tissuePolyesterBiodegradationOrganic chemistryChemistryBiochemistryBiomedical engineering

Abstract

fetched live from OpenAlex

Biodegradable poly(ester amide) (PEA) biomaterials derived from α-amino acids, diols, and diacids are promising materials for biomedical applications such as tissue engineering and drug delivery because of their optimized properties and susceptibility for either hydrolytic or enzymatic degradation. The objective of this work was to synthesize and characterize biodegradable PEAs based on the α-amino acids L-phenylalanine and L-methionine. Four different PEAs were prepared using 1,4-butanediol, 1,6-hexanediol, and sebacic acid by interfacial polymerization. High molecular weight PEAs with narrow polydispersity indices and excellent film-forming properties were obtained. The incubation of these PEAs in PBS and chymotrypsin indicated that the polymers are biodegradable. Human coronary artery smooth muscle cells were cultured on PEA films for 48 h and the results showed a well-spread morphology. Porous 3D scaffolds fabricated from these PEAs were found to have excellent porosities indicating the utility of these polymers for vascular tissue engineering.

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.

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 categoriesMeta-epidemiology (narrow), 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 score0.039
Threshold uncertainty score1.000

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)0.0050.000

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 head0.016
GPT teacher head0.216
Teacher spread0.200 · 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