3D Bioprinted Respiratory Tissue Scaffolds for Disease Modelling Applications
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".