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Record W4416247483 · doi:10.1021/acsabm.5c01744

Controlling Enzymatic Degradation of Carboxyl-Modified Chitosan and Hyaluronic Acid Biopolymers Using Dynamic Covalent Cross-Linking

2025· article· en· W4416247483 on OpenAlexafffund
Wasitha P. D. W. Thilakarathna, Emma G. Welshman, Namita Bhasin, William Austin, Jonah M. Glazebrook, Zeeshan Sheikh, Vahid Adibnia

Bibliographic record

VenueACS Applied Bio Materials · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHydrogels: synthesis, properties, applications
Canadian institutionsDalhousie University
FundersDalhousie UniversityNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsCovalent bondHyaluronic acidDegradation (telecommunications)HyaluronidaseViscoelasticityChitosanAqueous solution

Abstract

fetched live from OpenAlex

The enzymatic degradation of hyaluronic acid (HA) and carboxyl-modified chitosan (CC) polymers in aqueous dispersions can be controlled by dynamic covalent cross-linking. Unlike un-cross-linked HA, dynamic covalent cross-linking preserves the viscoelastic behavior of HA dispersions when exposed to hyaluronidase enzyme. Among the dynamic covalent cross-linked CC dispersions, only dispersions with degrees of deacetylation of 98% (CC98) partially upheld the viscoelastic behavior under lysozyme-mediated degradation. Overall, our results suggest that dynamic covalent cross-linking can produce injectable HA and CC dispersions with partial enzymatic degradation resistance.

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 score0.000
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)0.0000.000

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 head0.014
GPT teacher head0.266
Teacher spread0.252 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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