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Record W7065019532

3D Bioprinted Respiratory Tissue Scaffolds for Disease Modelling Applications

2024· dissertation· en· W7065019532 on OpenAlexfundno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2024
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaTechnische Universität BerlinInnovation SaskatchewanUniversity of Saskatchewan
KeywordsTissue engineeringBiomaterialRegenerative medicine3D bioprintingSelf-healing hydrogelsRegeneration (biology)
DOInot available

Abstract

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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.

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.

How this classification was reachedexpand

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.653
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.200
Teacher spread0.189 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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