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Hybrid GelMA-HAMA hydrogels incorporating dexamethasone-loaded PLGA nanoparticles for controlled release and osteogenic differentiation for bone tissue regeneration

2025· article· en· W4414462638 on OpenAlex
Brenda Velasco, Luis Díaz‐Gómez, Luis Carlos Rosales‐Rivera, Alberto Pardo, Sílvia Barbosa, J. F. A. Soltero, Pablo Taboada

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Polymer Journal · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHydrogels: synthesis, properties, applications
Canadian institutionsInstitute of Particle Physics
FundersAgencia Estatal de InvestigaciónXunta de GaliciaEuropean Regional Development FundConsellería de Cultura, Educación e Ordenación Universitaria, Xunta de Galicia
KeywordsSelf-healing hydrogelsGelatinControlled releaseHyaluronic acidMesenchymal stem cellPLGAAlkaline phosphataseRegeneration (biology)

Abstract

fetched live from OpenAlex

• Characterization of methacrylated gelatin (GelMA)/ hyaluronic acid (HAMA) hydrogels. • A single emulsion synthesized dexamethasone-loaded poly(lacticco-glycolic acid) nanoparticles (DEX-PLGA NPs). • 2. The DEX-PLGA NPs were incorporated into the polymeric hydrogels to achieve a controlled and sustained drug release. • The physicochemical properties of the NP-loaded hydrogels were not affected by the incorporation of DEX- PLGA NPs. • In vitro studies showed that these hybrid hydrogels are biocompatible and present excellent cell adhesion, proliferation, and differentiation properties. • The sustained release of dexamethasone ensures the progressive osteogenic differentiation of adipose-derived mesenchymal stem cells (adMSC) within the scaffold The development of novel approaches to bone regeneration remains a challenge in medicine. For such, the control release of biochemical factors appears key to successfully regulate the regeneration process. In this work, the characterization of methacrylated gelatin (GelMA)-hyaluronic acid (HAMA) hydrogels that incorporated dexamethasone-loaded poly(lactic-co-glycolic acid) nanoparticles (DEX-PLGA NPs) was explored as potential scaffolds for bone tissue regeneration. The DEX-PLGA NPs were synthesized and incorporated into the polymeric hydrogels to achieve a controlled and sustained release of the drug in order to ensure the progressive osteogenic differentiation of adipose-derived mesenchymal stem cells (adMSC) within the scaffold. The physicochemical properties of the NP-loaded hydrogels were not affected by the incorporation of DEX-PLGA NPs. In vitro studies demonstrated that these hybrid hydrogels are biocompatible and presented excellent cell adhesion, proliferation, and differentiation properties promoted by the sustained release of dexamethasone as observed, for example, by the alkaline phosphatase (ALP) assay, which confirmed large concentrations of phosphate ions after the first 14 days of incubation. Furthermore, Alizarin Red S staining corroborated a good mineralization, indicative of effective bone matrix formation.

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.

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 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 score0.089
Threshold uncertainty score0.815

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.013
GPT teacher head0.243
Teacher spread0.230 · 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