3D Bioprinted Respiratory Tissue Scaffolds for Disease Modelling Applications
Notice bibliographique
Résumé
Respiratory tissue engineering (RTE) aims to develop functional tissue constructs for regenerative \nor modelling applications by using engineering approaches. Among these approaches, the recently \nemerging technique of bioprinting is promising as it allows for the repeatable creation of \nhierarchical cell-containing structures, thus providing the ability to create functional tissue \nconstructs/ models. However, there are still challenges in the use of this approach in RTE, primarily \nrelated to generating physiologically relevant constructs that recapitulate the complexity of native \ntissues. Aspects including biomaterial selection, incorporating accurate biomechanical stimuli, and \nproviding natural biochemical signals are all different facets requiring consideration in increasing \nthe physiological relevance of bioprinted respiratory tissues. Based on the promise of RTE, this \nthesis aims at developing novel in vitro respiratory tissue constructs by means of bioprinting. To \naddress research issues in the field of RTE, four specific objectives are set in this thesis including, \n(1) synthesis and characterization of an optimal bioink, (2) incorporation of biomechanical stimuli \nmimicking the native respiratory environment, (3) incorporation of biochemical stimuli through \nuse of a nanoparticle-controlled release system, and (4) proof of concept application of the \ndeveloped constructs in disease modelling. \nObjective (1) involves the investigation and synthesis of bioinks from hydrogels and \ncharacterization of the bioinks in terms of mechanical properties, printability, and biocompatibility. \nAlginate was selected as the base material due to its lack of biotoxicity and its ability to undergo \nionic cross-linking, which allows for a high degree of printability; however, alginate expresses \nnegligible cell-adhesion motifs. As collagen type I is the primary protein found throughout the \nconnective tissue of the respiratory tract, its addition increases biocompatibility and cell adhesion. \nAfter synthesis, rheological characterization was used to inform selection of printing parameters \nand printability was assessed to ensure consistent structures that closely recapitulated the design \ncould be created. Bulk compression testing was carried out to determine the compressive modulus, \nwhile tensile testing of printed scaffolds was used for determination of the 3D printed lattice \nproperties. These mechanical properties were compared to that of native respiratory tissues to \ndetermine similitude. Finally, human pulmonary fibroblast proliferation and viability within the \nmaterials was assessed to ensure biocompatibility. The cumulation of all of these results was then \nused to select the most promising alginate/collagen biomaterial for further use in creation of a \nrespiratory tissue construct.\nWork then continued in Objectives (2) and (3) to increase the physiological relevance of the \nengineered construct through two different pathways. First, a bioreactor mimicking the pressure \nchanges and airflow conditions of the human lung was developed and tested to determine the effect \nthat biomechanical stimulus had on cell growth within the construct. Conditions recapitulating \nshallow, normal, and heavy breathing were tested to determine the effect on degradation, tensile \nproperties, and human pulmonary fibroblast and bronchial epithelial cell proliferation and viability. \nThese experiments provided insight into the influence of mechanical stimulus on cell growth and \nECM production, with normal breathing conditions leading to an increase in cell proliferation. \nSecond, a nanoparticle system for controlled release of growth factor was developed and tested to \ndetermine the effect of including relevant biochemical stimulus had on cell development within the \nbioprinted construct. For investigation into biochemical stimulus, a chitosan-coated alginate \nnanoparticle system was synthesized using an emulsion technique. These particles were loaded \nwith growth factor aimed at stimulating epithelial growth. Initially, release kinetics of the particle \nsystem were tested comparing coated/uncoated and static/dynamic conditions. Rheology and \nprintability of the bioink containing the loaded particles was tested along with tensile properties of \nthe printed scaffolds. Finally, the bioactivity of the loaded nanoparticles was assessed to determine \nthe functionality of the controlled release system. Although cell proliferation appeared unaffected, \nconfocal imaging demonstrated an increase in the formation of an epithelial barrier layer. \nFinally, in Objectives (4) the application of the designed constructs, including both biomechanical \nand biochemical stimulus, in disease modelling was then investigated. The bioink used was varied \nslightly through the addition of gelatin and characterized accordingly in terms of rheology, \nmechanical properties, printability, and biological properties. Following this, structures containing \nhuman pulmonary fibroblasts and monocytes were printed before seeding with human bronchial \nepithelial cells. These structures were cultured at an air-liquid interface before being infected with \nan influenza A virus. Cell viability, metabolism, and chemokine release were measured to \ndetermine the ability of these constructs to function as a disease model. \nThis thesis presents comprehensive work on the creation of bioprinted respiratory tissue scaffolds \nfor disease modelling applications. This work may pave the way to improving disease modelling \nand therapeutic screening pathways by providing a humanized intermediary between 2D and \nanimal models.
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 | 0,001 |
| 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 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 ».