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Enregistrement W2580442242

Self-Assembling Peptide-Carbon Nanotube Dispersions and Hydrogels for Tissue Engineering and Biosensor Applications

2015· dissertation· en· W2580442242 sur OpenAlexfundno aff
Mohammadali Sheikholeslam

Notice bibliographique

RevueUWSpace (University of Waterloo) · 2015
Typedissertation
Langueen
DomaineMaterials Science
ThématiqueSupramolecular Self-Assembly in Materials
Établissements canadiensnon disponible
Organismes subventionnairesUniversity of Waterloo
Mots-clésSelf-healing hydrogelsCarbon nanotubeBiosensorNanotechnologyTissue engineeringSelf-assembling peptideMaterials sciencePeptideSelf-assemblyEngineeringBiomedical engineeringChemistryPolymer chemistryBiochemistry
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Carbon nanotubes (CNTs) are attractive functional materials for use in a broad range of fields due to their unique mechanical and electrical properties. However, their hydrophobic nature is a major problem for some of these applications. Several approaches such as dispersing them in organic solutions and covalently or non-covalently modifying them have been developed to make CNTs usable for desired applications. Since organic solutions can be problematic for bio-applications and covalent modification can introduce defects into the CNT structure (responsible for its unique properties), the approach of making non-covalent modification is more promising. Different types of polymers and surfactants have been used so far in this way. In the past two decades, self-assembling peptides have emerged as promising functional nanomaterials capable of use for different bio-applications. Employing biocompatible self-assembling peptides for CNT dispersion not only removes the first obstacle to use CNTs in solution, but also can result in a new class of hybrid nanomaterials benefitting from the synergistic effects of peptides and CNTs. To the best of our knowledge, this is the first work reporting the dispersion of CNTs using β-sheet-forming self-assembling ionic-complementary peptides. Also this is the first study on the application of peptide-CNT hybrid dispersions and hydrogels for biosensor and tissue engineering applications. \nThis thesis focuses on the modification of CNTs with self-assembling peptides, characterization of the resulting hybrid dispersions and their application for biosensor development and scaffolding for tissue engineering and cancer spheroid studies. In particular, the study includes the following topics: (i) characterization of the dispersions of multi-walled carbon nanotubes (MWNTs) modified with EFK16-II peptide, (ii) AFM characterization of dispersions of single-walled carbon nanotubes (SWNTs) modified with EFK8 peptide, (iii) formation of hybrid EFK8-SWNT hydrogels, (iv) application of the hybrid EFK8-SWNT dispersion in electrode modification and design of a hemoglobin biosensor, and (v) application of the EFK8 and EFK8-SWNT hydrogels as scaffolds for tissue engineering and 3D cancer cell spheroid formation. \nFirst, we have shown that by non-covalently modifying MWNTs with the ionic-complementary peptide EFK16-II, very stable dispersions of MWNTs can be formed due to the electrostatic repulsion between self-assembled peptides on the MWNTs. Zeta potential and DLS measurements indicated that as the pH diverges from the isoelectric point of ~ 6.7 for EFK16-II, the repulsion between the particles increases and their resulting sizes decrease. AFM, SEM and TEM studies revealed a uniform distribution of individual modified MWNTs. Finally, tissue culture plates treated with these hybrid dispersions were found to have enough biocompatibility for cell attachment and growth. \nIn the next step, the peptide EFK8, a shorter version of EFK16-II, was used to disperse SWNTs in water. Scanning probe microscopy (SPM) techniques based on nano-mechanical measurements and electric force microscopy (EFM) were used to more closely examine the structure formed between nanotubes and peptides. The SPM images reveal a structure consistent with EFK8 fibers wrapping around SWNTs and rendering their outer surfaces hydrophilic which enables their dispersion in water. Also it was shown that the hybrid dispersions can form uniform composite EFK8-SWNT hydrogels upon adding solutions containing ≥1mM monovalent salts. \nIn the third part of the study, EFK8 and EFK8-SWNT hybrid hydrogels were prepared and used to culture NIH-3T3 fibroblast and A549 lung cancer cells. The effect of the presence of SWNTs in the peptide hydrogel on NIH-3T3 cells behavior cultured on hydrogels was first investigated. Inverted light and confocal microscopy images showed that although cells grow they tend to maintain spherical morphology and form colonies on the EFK8 hydrogel. The presence of SWNTs significantly improved cell behavior so that they exhibited a stretched morphology, spread individually and homogeneously over the surface and proliferated faster. In addition, the cells were observed to migrate into the hydrogel after being seeded on top of the hydrogel. Micro-indentation tests showed that increasing EFK8 solution concentration led to an increase in the hydrogel compressive modulus, whereas the presence of SWNTs did not have any effect in this case. So the beneficial effect of SWNTs on cell behavior cannot be attributed to mechanical property modification and is probably due to their providing locations for cell anchorage that facilitate attachment, spreading and migration. The cells encapsulated in both hydrogels showed the same behavior as in 2D environments (i.e., forming colonies on EFK8 and spreading individually on the hybrid hydrogel). In the second part of this study, the potential of EFK8 hydrogels for spheroid formation of cancer cells was explored. These cancer cell spheroids can be used as models for real tumors, to carry out drug screening in 3D cell cultures and to investigate the effect of the microenvironment on tumor progression and metastasis. It was observed that cells formed spheroids on EFK8 hydrogels at normal peptide concentrations, but exhibited a more stretched morphology and migratory phenotype when seeded on the stiffer hydrogel. The cells also adopted a stretched morphology with higher migration when seeded on the EFK8-SWNT hydrogels. Again this behavior can be attributed to the effect of SWNTs to facilitate cell adhesion and migration. This effect can be used to study another effect of the microenvironment, namely cell-binding motifs, on tumor progression and metastasis. \nIn the last step of the study, the application of the hybrid EFK8-SWNT dispersion was investigated for immobilization and direct electrochemistry of hemoglobin (Hb) on a glassy carbon electrode (GCE) as well as the efficacy of this platform for making a hydrogen peroxide (H2O2) biosensor. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) experiments showed that the presence of SWNTs in the modifying peptide layer on GCE significantly enhances the electrochemical response of the electrode. Furthermore, this response was further increased as more layers of the EFK8-SWNT dispersion were applied. The next step was to immobilize hemoglobin on the electrode by a casting method. The effectiveness of this approach was confirmed by CV and EIS experiments which showed that immobilized Hb retained its bio-catalytic activity for Fe ions in Hb chains and could form the basis of a mediatorless H2O2 biosensor. \nOverall, by expanding the functionalities of both CNTs and self-assembling peptides, this work has introduced a new hybrid nanomaterial for bio-applications, especially biosensors, 3D cell cultures and tissue engineering.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,004

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,009
Tête enseignante GPT0,222
Écart entre enseignants0,213 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2015
Routes d'admission1
Résumé présentoui

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