Dual Template, Three-Dimensional Hierarchical Porous Scaffolds Based on Graphene Oxide for Bone Tissue Engineering
Notice bibliographique
Résumé
Objectives Scaffolds for bone tissue engineering (BTE) are three-dimensional (3D) porous matrices that provide the necessary sites for cell adhesion and proliferation, where the architecture plays an important role. Ideally, BTE scaffolds should have an interconnected network of both large and small pores to facilitate the infiltration of cells and the diffusion of growth factors and nutrients1. Scaffolds for BTE should also enhance osteogenic differentiation to improve bone regeneration. Graphene oxide (GO) can promote osteogenic differentiation of mesenchymal stem cells (MSCs) because it can provide biophysical cues and adsorb biological factors2. However, due to the lack of fabrication strategies, it remains a challenge to develop GO and GO composite scaffolds with a hierarchical architecture for BTE. In this study, we aim to develop a dual-templating method to control the assembly of GO sheets, in order to design and achieve this architecture. Experimental Methods We modified the amphiphilicity of GO by adding different amounts of cetyltrimethylammonium bromide (CTAB), hydroxyapatite (HA), polyacrylic acid (PAA) and elastin from bovine neck ligament. Then we developed GO-CTAB, GO-CTAB-HA, GO-CTAB-PAA and GO-elastin stabilized oil in water emulsions. Afterwards, we froze the emulsions at different temperatures (-190 oC and -20 oC), and upon freeze-drying we produced free-standing scaffolds. We reduced GO-CTAB scaffolds in different conditions to obtain rGO scaffolds. We studied the formation of emulsions and the structural and chemical properties of scaffolds through optical microscopy, scanning electron microscopy (SEM), X-ray photoelectron spectroscopy, attenuated total reflectance Fourier transform infrared, and compressive strength tests. We seeded mouse bone marrow MSCs on 2D GO substrates and 3D GO-based scaffolds. Then, we compared the cell proliferation after 10 days of incubation. We also analyzed the cells on GO-based scaffolds after 7 days of incubation using SEM and confocal microscopy, in order to study cell morphology, attachment and infiltration in the scaffolds. Results and Discussion The scaffolds based on GO, GO-HA, GO-GO-PAA, GO-elastin and rGO have interconnected primary pores of 150-300 µm in diameter (Figure 1 a-j), which matches the size of the hexane droplet templates. Freezing at -190 oC results in smaller secondary pores around 10 µm in diameter (Figure 1 a-e) while freezing at -20 oC results in larger secondary pores with diameters around 30-50 µm (Figure 1 f-j). This result shows that the secondary pore formation is controlled by ice nucleation and growth in the aqueous phase of the emulsions at different temperatures. Scaffolds based on GO-HA, GO-PAA and especially GO-elastin show an improved modulus of compression compared to GO-based scaffolds (Figure 1 k). The cell culture using MSCs reveals cell proliferation up to 10 days on 2D GO substrates and 3D GO-based scaffolds (Figure 1 l). Compared to 2D substrates, the large and interconnected pores in 3D scaffolds contribute to the higher cell proliferation result. The cells are well spread on the scaffolds with an elongated shape and filamentous extensions at day 7 (Figure 1m). They infiltrate all the way to the center of GO-based scaffolds through primary pores (Figure 1 m, n). These results indicate that primary pores can facilitate the cell infiltration. Conclusions The rapid development and broad application of graphene-based porous materials requires efficient and facile fabrication methods. We developed a novel strategy to control the assembly of GO sheets using emulsions and ice templates to fabricate GO-based scaffolds with an interconnected and hierarchical porous structure. The ability to fabricate rGO and GO composite scaffolds with similar architectures demonstrates the versatility of this strategy. The GO-based scaffolds show biocompatibility and allow cell infiltration. We expect that this strategy can lead to improvements in the fabrication of GO-type scaffolds for BTE. References 1. Karageorgiou V et al. Biomaterials 26 (27):5474-91. 2005 2. Lee WC et al. Acs Nano 5 (9):7334-41. 2011 Acknowledgements We acknowledge support from NSERC, the Canada Research Chair Foundation and McGill Engineering Doctoral Award. Figure 1
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».