Control of maleic acid-propylene diepoxide hydrogel for 3D printing application for flexible tissue engineering scaffold with high resolution by end capping and graft polymerization
Notice bibliographique
Résumé
Abstract Background Control of 3D printing of highly tough hydrogel inks with adequate printability, scaffold fidelity and mechanical properties are highly desirable for biomedical and tissue engineering applications. However, developing a biocompatible tough ink with high-resolution printability, biodegradability, self-healing, adhesion, and integration with surrounding tissues is a big challenge in 3D printing. The aim of this study was to develop extrusion-based 3D printing of viscous hydrogel composing of maleic acid and propylene diepoxide by controlling continuous mechanisms of condensation and radical polymerization. Methods The molecular weight of highly adhesive propagating poly(malate-co-propylene oxide) copolymer was controlled by capping its growing chain with mono-functional lipoic acid with different compositions during condensation reaction to form lipoic acid capped gel (LP-capped gel). Poly(ethylene oxide)-diacrylate, PEGDA, is graft-polymerized to the LP-capped backbone polymer (MPLE gel) by UV irradiation during 3D printing process to control the properties of gel printability, mechanical properties, and cell adhesiveness and post-printing fidelity of the printed scaffolds with high resolution and mechanical properties (MPLE scaffold). The scaffolds in complex geometries have been printed out in diverse forms with addition of model drugs with different molecular weights and chemical structures. Both the highly adhesive LP-capped gel and printing-controlled MPLE gel/scaffolds are diversely characterized and compared with for their applications to the extrusion-based printability, including biocompatibility, self-healing, drug releasing, adhesiveness, multi-layered high-resolution printing. Further in vitro/in vivo tests were done to observe cytotoxicity, immune response and tissue formation by using different cells in mice model. Results LP-capped hydrogel from maleic acid and propylene diepoxide gel showed control of gel properties with lipoic acid with one function group of thiol during condensation reaction, and the ratio at 1:0.3 (w/v) between LP-capped gel and PEGDA was chosen for the optimal results during radical polymerization process for 3D printing at high resolution (90-140 μm in strut thickness) with various complex geometries (lattice, rhombus, and honeycomb). The hydrogel showed excellent properties of self-healing, mechanical strength, biocompatibility, etc. In addition, the long-term release profiles of bioactive molecules were well-controlled by incorporating drugs of high molecular bovine serum albumin (BSA, 21 days, 98.4 ± 0.69%), or small molecule ornidazole (ORN, 14 days, 97.1 ± 1.98%) into the MPLE gel scaffolds for the tests of potential therapeutic applications. More importantly, the MPLE gels represents excellent in vitro cyto-compatibility against osteoblast-like cells (MC3T3) with viability value at 96.43% ± 7.48% over 7 culturing days. For in-vivo studies, the flexible MPLE scaffolds showed significant improvement on angiogenesis with minor inflammatory response after 4-week implantation in mice. Conclusion The MPLE gel inks was well-controlled for the fabrication of flexible complex tissue engineering scaffold with high resolutions, shear-thinning, 3D printability and post-printing fidelity, by modulating the composition of the highly adhesive LP-capped gel and inert PEGDA as well as end capping of lipoic acid to the propagating poly(malate-co-propylene oxide) copolymer. The gel ink demonstrated its excellent printability, in vitro/in vivo biocompatibility and mechanical properties as well as sustained drug release from the gel. Graphical Abstract
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| 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) | 0,004 | 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 tête enseignante, 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 ».