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Record W3093256436 · doi:10.20381/ruor-25442

Three-Dimensional Plant-Derived Biomaterials - Scaffolds for Tissue Engineering and Biophysical Manipulation

2020· dissertation· en· W3093256436 on OpenAlexfundno aff
Ryan J. Hickey

Bibliographic record

VenueuO Research (University of Ottawa) · 2020
Typedissertation
Languageen
FieldEngineering
TopicAdvanced Materials and Mechanics
Canadian institutionsnot available
FundersFonds de Recherche du Québec - SantéNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsTissue engineeringNanotechnologyBiomedical engineeringEngineeringMaterials science

Abstract

fetched live from OpenAlex

Cells are complex active materials that display fascinating phenomena in response to changes in their physical environments. It is well established that the physical environment dictates cell fate and function; nevertheless, the standard method of culturing and studying cells is on stiff 2- dimensional Petri dishes and glass cover slips. The difference in the magnitude of the stiffness of the substrate in addition to the 2-dimensional character, leads to an incomplete and perhaps misleading picture of the cellular process under scrutiny. As such, an entire field has been dedicated to developing materials that more closely match the characteristics of the natural cellular milieu: biomaterials. Despite significant progress in the field, we are still far from fully recapturing the native environment. Importantly, many of the current strategies for engineering 3-dimensional biomaterials have specific applications yet lack flexibility to be adapted to a wide variety of functions. Our approach is to repurpose existing complex, readily available materials to create a platform for biomaterial production; our biomaterials are derived from plant tissue. Plants have evolved over millions of years to attain structures with intricate geometries for specialized functions. Due to the wide variety of plant structures, one can easily select a plant-based material with analogous features to the tissue of interest. A series of investigations are presented on these novel biomaterials to demonstrate this approach, quantify the mechanical properties, and study the cellular responses. First, we developed a method of processing plant materials to yield decellularized, cellulose-based, biocompatible scaffolds that can be repopulated with mammalian cells. We then created composite materials by casting hydrogels around the cellulose-based scaffolds, which allowed us to incorporate distinct temporal and spatial cues to the local cell populations. Spatial organization of tissues and tissue interfaces remains a primary challenge in biomedical engineering, as tissue interfaces mark complex transitional zones between distinct cell populations. Replicating and repairing this intricate delineation of cell types and mechanical profiles has proven to be a major concern in regenerative medicine. As such, we sought to develop a platform for engineered tissue interfaces, wherein components are combined in a modular fashion into a functional unit. The mechanical cues of the microenvironment affect a plethora of cellular processes, namely cell migration, proliferation, and differentiation. Consequently, the rheological properties of our decellularized, plant-based scaffolds were thoroughly investigated. An in-depth knowledge of the mechanics of the underlying substrate is required to guide future applications and refinements of this technology. The potential applications of these 3-dimensional constructs, as demonstrated through our findings, include designing in vitro models of tissue interactions, new biomaterials for in vivo applications, and studies on fundamental cellular processes. We highlight the significance of our results in a collection of scientific articles, which are presented in the body of this thesis (Chapters 2-5). This work is focused on the use of plant- derived cellulose materials, which forms a subsection of the cellulose biomaterial field. A review article centered on the use of cellulose materials for tissue engineering serves as an introductory chapter.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.927

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.035
GPT teacher head0.268
Teacher spread0.233 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2020
Admission routes1
Has abstractyes

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