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Record W2785078942 · doi:10.1021/acs.biomac.7b01707

Self-Healing Hydrogels of Low Molecular Weight Poly(vinyl alcohol) Assembled by Host–Guest Recognition

2018· article· en· W2785078942 on OpenAlexafffund
Yong‐Guang Jia, Jiahong Jin, Sa Liu, Li Ren, Juntao Luo, X. X. Zhu

Bibliographic record

VenueBiomacromolecules · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHydrogels: synthesis, properties, applications
Canadian institutionsUniversité de Montréal
FundersFonds Québécois de la Recherche sur la Nature et les TechnologiesNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsVinyl alcoholSelf-healing hydrogelsPolymerAqueous solutionChemistryChemical engineeringPolymer chemistryCyclodextrinMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Poly(vinyl alcohol) (PVA) is a cytocompatible synthetic polymer and has been commonly used to prepare hydrogels. Bile acids and β-cyclodextrin are both natural compounds and they form stable host-guest inclusion complexes. They are attached covalently onto a low molecular weight PVA separately. Self-healing hydrogels can be easily formed by mixing the aqueous solutions of these PVA based polymers. The mechanical properties of the hydrogels can be tuned by varying the molar fractions of bile acid units on PVA. The dynamic inclusion complexation of the host-guest pair of the hydrogel allows the self-healing rapidly under ambient atmosphere and their mechanical properties could recover their original values in 1 min after incision. These PVA based polymers exhibited the good cytocompatibility and high hemocompatibility as shown by their biological evaluations. The use of natural compounds for host-guest interaction make such gels especially convenient to use as biomaterials, an advantage over conventional hydrogels prepared through freeze-thaw method.

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)0.000
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 score0.028
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 science0.0010.000
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 head0.013
GPT teacher head0.249
Teacher spread0.235 · 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

Citations84
Published2018
Admission routes2
Has abstractyes

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