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Record W2626803273 · doi:10.1021/acs.biomac.7b00456

Hemocompatibility of Degrading Polymeric Biomaterials: Degradable Polar Hydrophobic Ionic Polyurethane versus Poly(lactic-<i>co</i>-glycolic) Acid

2017· article· en· W2626803273 on OpenAlexafffund
Kathryne S. Brockman, Benjamin Lai, Jayachandran N. Kizhakkedathu, J. Paul Santerre

Bibliographic record

VenueBiomacromolecules · 2017
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsUniversity of British ColumbiaTed Rogers Centre for Heart ResearchUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaMichael Smith Health Research BC
KeywordsBiomaterialBiocompatibilityPLGAGlycolic acidPolymerChemistryPolyurethanePlatelet adhesionPlatelet activationPolymer chemistryPlatelet adhesivenessLactic acidAdhesionPlateletChemical engineeringBiochemistryOrganic chemistryIn vitro

Abstract

fetched live from OpenAlex

The use of degradable polymers in vascular tissue regeneration has sparked the need to characterize polymer biocompatibility during degradation. While tissue compatibility has been frequently addressed, studies on polymer hemocompatibility during degradation are limited. The current study evaluated the differences in hemocompatibility (platelet response, complement activation, and coagulation cascade initiation) between as-made and hydrolyzed poly(lactic-co-glycolic) acid (PLGA) and degradable polar hydrophobic ionic polyurethane (D-PHI). Platelet activation decreased (in whole blood) and platelet adhesion decreased (in blood without leukocytes) for degraded versus as-made PLGA. D-PHI showed minimal hemocompatibility changes over degradation. Leukocytes played a major role in mediating platelet activation for samples and controls, as well as influencing platelet-polymer adhesion on the degraded materials. This study demonstrates the importance of assessing the blood compatibility of biomaterials over the course of degradation since the associated changes in surface chemistry and physical state could significantly change biomaterial hemocompatibility.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.018
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.315
Teacher spread0.289 · 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

Citations22
Published2017
Admission routes2
Has abstractyes

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