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Record W4415559862 · doi:10.3390/ijms262110383

Oxidized Hyaluronic Acid-Based Sponges: A Promising Biomaterial for Oral Mucosa Lesion Application

2025· article· en· W4415559862 on OpenAlexaff
Clara Alicia Muñoz-Trejo, Martha Gabriela Chuc-Gamboa, Juan Valerio Cauich‐Rodríguez, Rossana Faride Vargas‐Coronado, Diana María Escobar‐García, Amaury Pozos‐Guillén, Fernando Javier Aguilar‐Pérez, Alicia Leonor Pinzón-Te, Gualberto Antonio Zumbardo‐Bacelis

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2025
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicAdvanced Drug Delivery Systems
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHyaluronic acidBiocompatibilityChitosanBiomaterialDiglycidyl etherPolyethylene glycolSponge

Abstract

fetched live from OpenAlex

Chitosan (CHT) and hyaluronic acid (HA) are biomaterials with diverse properties. While each has been individually employed for the treatment of oral lesions, there is a need for further evidence regarding their combined properties. This study compares the effects on the properties and biocompatibility of chitosan sponges, CHT crosslinked with oxidized hyaluronic acid (OHA) (oxidized at 1:1 and 1:2 ratios, respectively), and CHT crosslinked with oxidized hyaluronic acid and polyethylene glycol diglycidyl ether (PEGDE). Spectroscopy revealed reduced free amino groups and the amide I/II ratio in CHT sponges crosslinked with OHA. SEM confirmed the porous network morphology with an average pore size ranging from 155 to 213 μm. TGA indicated the scaffolds' decomposition temperature (Td) increased from 253° to 308°, with the CHT-OHA 1:2 sponge exhibiting the highest thermal stability. Compression testing highlighted that the chitosan sponges crosslinked with AHO and PEGDE at a 1:2 ratio displayed a higher elastic modulus than the other studied scaffolds. The MTS assay confirmed that the fabricated biomaterials were not cytotoxic. This study demonstrates the enhanced properties and biocompatibility of CHT-OHA and CHT-OHA-PEGDE sponges, highlighting their potential for oral lesion treatment.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.206
Threshold uncertainty score0.430

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.094
GPT teacher head0.480
Teacher spread0.386 · 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.

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 routes1
Has abstractyes

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