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Record W4388944204 · doi:10.3390/gels9120923

Metal Organic Framework-Incorporated Three-Dimensional (3D) Bio-Printable Hydrogels to Facilitate Bone Repair: Preparation and In Vitro Bioactivity Analysis

2023· article· en· W4388944204 on OpenAlex

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

VenueGels · 2023
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsWestern University
FundersDivision of Administrative Services
KeywordsSelf-healing hydrogelsMaterials scienceDrug deliveryGelatinNanotechnologyTissue engineeringBiomedical engineeringRegenerative medicine3D cell cultureNanoparticleChemistryCellPolymer chemistry

Abstract

fetched live from OpenAlex

Hydrogels are three-dimensional (3D) water-swellable polymeric matrices that are used extensively in tissue engineering and drug delivery. Hydrogels can be conformed into any desirable shape using 3D bio-printing, making them suitable for personalized treatment. Among the different 3D bio-printing techniques, digital light processing (DLP)-based printing offers the advantage of quickly fabricating high resolution structures, reducing the chances of cell damage during the printing process. Here, we have used DLP to 3D bio-print biocompatible gelatin methacrylate (GelMA) scaffolds intended for bone repair. GelMA is biocompatible, biodegradable, has integrin binding motifs that promote cell adhesion, and can be crosslinked easily to form hydrogels. However, GelMA on its own is incapable of promoting bone repair and must be supplemented with pharmaceutical molecules or growth factors, which can be toxic or expensive. To overcome this limitation, we introduced zinc-based metal-organic framework (MOF) nanoparticles into GelMA that can promote osteogenic differentiation, providing safer and more affordable alternatives to traditional methods. Incorporation of this nanoparticle into GelMA hydrogel has demonstrated significant improvement across multiple aspects, including bio-printability, and favorable mechanical properties (showing a significant increase in the compressive modulus from 52.14 ± 19.42 kPa to 128.13 ± 19.46 kPa with the addition of ZIF-8 nanoparticles). The designed nanocomposite hydrogels can also sustain drug (vancomycin) release (maximum 87.52 ± 1.6% cumulative amount) and exhibit a remarkable ability to differentiate human adipose-derived mesenchymal stem cells toward the osteogenic lineage. Furthermore, the formulated MOF-integrated nanocomposite hydrogel offers the unique capability to coat metallic implants intended for bone healing. Overall, the remarkable printability and coating ability displayed by the nanocomposite hydrogel presents itself as a promising candidate for drug delivery, cell delivery and bone tissue engineering applications.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.166
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.020
GPT teacher head0.231
Teacher spread0.211 · 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