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Record W2255693119

Micro/nano-scale strategies for engineering in vitro the celular microenvironment using biodegradable biomaterials

2011· dissertation· en· W2255693119 on OpenAlexfundno aff
Daniela F. Coutinho

Bibliographic record

VenueRepositóriUM (Universidade do Minho) · 2011
Typedissertation
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsnot available
FundersEngineer Research and Development CenterSamsungSeoul National UniversityEuropean CommissionNational Science FoundationNational Institutes of HealthFundação para a Ciência e a TecnologiaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsNanotechnologyTissue engineeringBiodegradable polymerMaterials scienceEngineeringBiomedical engineeringPolymerComposite material
DOInot available

Abstract

fetched live from OpenAlex

Biological tissues result of a specific spatial organization of cells, extracellular matrix (ECM) molecules, and soluble factors. These micro and nanoscaled biological entities organize into regional tissue architectures, creating highly complex and heterogeneous cellular microenvironments. To generate functional tissue equivalents in vitro, engineered biomaterials should mimic the structural, chemical and cellular complexity by recapitulating the unique native microenvironments. Thus, the main goal of this thesis was to engineer biodegradable polymers using various micro and nanofabrication techniques, with specific structural, biochemical and cellular cues for improved performance. The main governing hypotheses of this thesis were: 1) substrates with improved structural properties can be engineered using biodegradable polymers that have previously shown good results in in vivo studies, 2) biochemical cues can be incorporated into biodegradable polymers, yielding biomaterials with integrated chemical cues for improved cellular performance, and 3) these structural and biochemical cues can be incorporated into a single system. To develop biomaterials with structural cues, micromolding of poly(butylene succinate) (PBS) was performed to engineer surfaces with features at a microscale that induced the alignment of human adipose stem cells. Although this polymeric material has been processed at a macroscale into scaffolds, this was the first report on the engineering of this material at a microscale, demonstrated by the development of twenty features with different dimensions. Improved substrates with structural cues were also engineered using the polysaccharide gellan gum (GG), which has been extensively studied at 3B’s Research Group. Microcapsules of GG, aimed at being used as drug or cell carriers and/or delivery agents, were engineered using a two-phase system. The principle of hydrophobic-hydrophilic repulsion forces was combined with a microfabrication process by means of a needle/syringe pump system. Microcapsules with different diameters were produced by varying the system parameters. As an original proof-of-concept, fluorescent beads, cell suspensions and cell aggregates were encapsulated within this microfabrication system. To develop biomaterials with enhanced biochemical cues, GG was chemically modified with ester bonds, yielding novel hydrogels crosslinkable by ultraviolet (UV) light. Methacrylated GG (MeGG) hydrogels were formed using physical and chemical mechanisms resulting in hydrogels with tunable mechanical properties, matching those of natural tissues from soft to hard, as the brain or collagenous bone. In a subsequent step, this material was combined with chitosan (CHT), a natural polysaccharide, resulting in a polyelectrolyte complex (PEC) hydrogel that combined the most advantageous properties of CHT and MeGG. PEC hydrogels are commonly formed by the interaction between the chains of oppositely charged polymers and are thus held together by ionic forces, which can be disrupted by changes in physiological conditions. However, in our new system, the biochemical cues earlier introduced in GG, allowed to crosslink the MeGG-CHT hydrogel using UV light, stabilizing the structure of the hydrogel. This rather important property also enabled for the development of microgels by photolithography. The encapsulation of rat cardiac fibroblasts within MeGG before PEC hydrogel production, led to the fabrication of microgels with combined biochemical, structural and cellular cues. The developed MeGG-CHT hydrogel was further engineered into a multi-hierarchical fibrous hydrogel by means of combining fluidics technology and chemistry principles of the interaction of two oppositely charged polymers. Two converging fluidic channels were used to extrude the MeGG-CHT hydrogel, formed by the assembly of the polymeric chains at the location where the channels converged. The resulting hydrogel closely mimicked the architecture of natural collagen fibers not only at a micro but also at a nanoscale. The developed hydrogel with relevant biological structural properties was enhanced by incorporating cell adhesive motifs (RGD peptides) into the MeGG backbone before processing. The research work described in this thesis addresses strategies to mimic several parameters of the native microenvironment of tissues. Biochemical and cellular cues were incorporated into biomaterials that were microprocessed with relevant biological micro and nanoscale features. In summary, the works reported in this thesis show the importance of combining different areas of knowledge into the development of improved systems for biomedical engineering applications. Undoubtfully, chemistry and micro and nanofabrication technologies are two areas of knowledge that allow the fabrication of micro and nanostructured materials. Herein, this synergy was achieved with a top-down approach (by micromolding, photolithography or fluidics technologies) and/or with a bottom-up approach (by the assembly of polymer chains). The last work of this thesis is the result of the original combination of both approaches for the development of enhanced micro and nanostructured biomaterials, thus presenting significant improved features compared to currently developed systems to be successfully used in several regenerative medicine approaches.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.014
GPT teacher head0.228
Teacher spread0.214 · 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 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
Published2011
Admission routes1
Has abstractyes

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