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Record W2415020792 · doi:10.1088/1748-6041/11/3/035013

Polyvinyl alcohol-graft-polyethylene glycol hydrogels improve utility and biofunctionality of injectable collagen biomaterials

2016· article· en· W2415020792 on OpenAlexafffund
Ryan Hartwell, Ben Chung-Lap Chan, Keenan Elliott, Hatem Alnojeidi, Aziz Ghahary

Bibliographic record

VenueBiomedical Materials · 2016
Typearticle
Languageen
FieldMaterials Science
TopicCollagen: Extraction and Characterization
Canadian institutionsInternational Collaboration On Repair DiscoveriesUniversity of British Columbia
FundersCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsPolyvinyl alcoholSelf-healing hydrogelsPolyethylene glycolMaterials sciencePulmonary surfactantPolymerChemical engineeringPolyvinyl acetatePolymer chemistryComposite material

Abstract

fetched live from OpenAlex

Collagen-based materials have become a staple in both research and the clinic. In wound care, collagen-based materials comprise a core gamut of biological dressings and therapeutic strategies. In research, collagen-based materials are employed in everything from 3D cultures to bioprinting. Soluble collagen is well characterized to undergo fibrillation at neutral pH and 37 °C. To remain stable, a neutralized collagen solution must be maintained at 4 °C. These physical characteristics of collagen impose limitations on its utility. In our previous work, we identified that the incorporation of a simple polyvinyl alcohol:borate hydrogel could improve the rate of collagen gel fibrillation. In this work we sought to further investigate the interactions of polyvinyl alcohol blend variants, as surfactant-like polymers, in comparison with known non-polymer surfactants. To conduct our investigations scaffold variants were created using increasing concentrations of polyvinyl alcohol, differing combinations of polymers, and non-polymer surfactants Tweens 20 and 80, and TritonX-100. Activation energy for collagen fibrillation was found to significantly decrease in the presence of polyvinyl alcohols (p < 0.01) at and above 0.4%w/v concentration. Further, addition of polyvinyl alcohol-graft-polyethylene glycol had the greatest enhancement (2.02 fold) on the fibrillation kinetics (p < 0.01), wetting properties and the stability of the collagen scaffolds post-freeze drying. Our results demonstrated that the addition of polyvinyl alcohol hydrogels to a collagen solution could stabilize collagen solution such that the solution could easily be lyophilized (at pH 7) and then reconstituted with water. Cells cultured in polyvinyl alcohol scaffolds also exhibited more organized F-actin, as well as a reduced abundance of pro-collagen and α-smooth actin. In conclusion, our results demonstrate for the first time that polyvinyl alcohol, preferably polyvinyl alcohol-graft-polyethylene glycol, directly affects the physical properties of collagen and the physiology of cells cultured within improving the utility of the combined material for both research and clinic needs.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.254
Teacher spread0.238 · 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 source (direct Gemma or distilled Codex), 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

Citations17
Published2016
Admission routes2
Has abstractyes

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