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Enregistrement W2963974679

Protein Interactions With Nitrogen-Doped Amorphous Carbon Surfaces

2019· dissertation· en· W2963974679 sur OpenAlexfundno aff
Jason Maley

Notice bibliographique

Revuenon disponible
Typedissertation
Langueen
DomaineMaterials Science
ThématiqueCarbon Nanotubes in Composites
Établissements canadiensnon disponible
Organismes subventionnairesCanadian Light Source
Mots-clésDopingCarbon fibersNitrogenMaterials scienceAmorphous carbonNanotechnologyChemical engineeringAmorphous solidChemistryOptoelectronicsCrystallographyEngineeringComposite materialOrganic chemistry
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Amorphous carbon is a very promising material for biocompatible devices. It can be made by a variety of plasma-assisted deposition techniques and is readily doped with other elements, such as nitrogen, which allows tuneable mechanical and tribological properties, including high hardness, low coefficient of friction, and high chemical resistance. It has also been applied to polymer surfaces like poly(tetrafluoroethylene) which gives it the potential for coating applications to hemocompatible devices such as vascular grafts. Although advances in biomaterials used in both surgical and biomedical applications have steadily improved over the past 30 years, improvements towards their biocompatibility and longevity are still needed. Proteins immediately adsorb to the biomaterial interface when it is exposed to bodily fluids such as blood, and this protein layer mediates cellular adsorption on the biomaterial, ultimately playing a major role in the overall success of the biomaterial. Despite advances over the past 40 years in understanding protein interactions at biomaterial interface, there is still a lack of understanding on many of the mechanisms and factors affecting protein adsorption. The main objective of the work presented in this thesis is to (1) develop a surface plasmon resonance (SPR) assay to measure the initial binding kinetics of two major serum proteins, human serum albumin (HSA) and fibrinogen (Fib), to amorphous carbon films prepared with different amounts of nitrogen incorporation. The nitrogen incorporation was controlled by adjusting the %N2 plasma discharge gas during plasma enhanced chemical sputtering using a graphite target onto a Au sensor surface. The initial binding kinetics measurements from SPR experiments found the dissociation kinetics (kd) for both Fib and HSA were comparable onto fullerene-like carbon nitride films (FL-CNx). The association kinetics (ka) was determined to be an important factor for protein adsorption, and the ka was an order of magnitude larger for Fib than HSA. In addition, nitrogen incorporation into the FL-CNx initially decreased ka for both Fib and HSA. However, increasing the nitrogen incorporation due to higher %N2 plasma discharge gas ratios during FL-CNx film deposition increased the ka values for both Fib and HSA. Atomic force microscopy, Raman spectroscopy, and sessile contact angle measurements on the FL-CNx films indicated that the surface hydrophobicity, and the film structure played roles in the changes in protein binding kinetics. The FL-CNx films prepared in the original deposition chamber were also found to contain trace amounts of metals, mainly Fe, incorporated into the films during the deposition process. A second objective (2) of the thesis was to characterize the trace Fe in FL-CNx films deposited onto poly(tetrafluoroethylene). X-ray photoelectron spectroscopy, Fe L-edge x-ray absorption near edge spectroscopy, and electron spin resonance spectroscopy were used to elucidate the Fe structure in the FL-CNx films. The Fe was found to exist in different Fe(III)-oxide and Fe(II) oxide forms, and the Fe valency and concentration was dependent on the %N2 plasma discharge gas during film deposition, and differences were observed for the Fe in the surface and bulk regions of the film. A third objective (3) of this thesis was to design a “metal free” plasma deposition chamber. The films generated using this new chamber were amorphous carbon nitride (a-C:N), and the nitrogen incorporation was controlled by changing the %N2 plasma discharge during a-C:N film deposition. The SPR measurements on the a-C:N films found that the kd values were very similar for HSA and Fib, indicating that the protein/surface interaction is very stable and independent of the protein. The ka(Fib) > ka(HSA) by and order of magnitude. The incorporation of nitrogen into a-C:N film initially decreased the ka for both HSA and Fib, but incorporation of nitrogen using higher %N2 plasma discharge gas during a-C:N film formation increased the ka values for both HSA and Fib. Film characterization suggested that changes in the a-C:N film surface wettability, the type of nitrogen functionalization within the film matrix, and the electronic workfunction may play a role in the changes in ka values measured for HSA and Fib. In addition, it was found that Fe-doping (1.3 at.% Fe) into a-C:N film did not change the HSA and Fib binding kinetics compared to the “metal-free” a-C:N film. Overall, a SPR assay was successfully developed and the initial binding kinetics of HSA and Fib onto amorphous carbon surfaces prepared with different amounts of nitrogen incorporation are reported for the first time. The kinetic results show that the major differences in the binding strength between the two different proteins are the differences in the protein’s ka (recognition rate) towards the surface. This fundamental assay can be expanded in future experiments to study specific surface properties and quantitatively measure the effects of protein binding.

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 seuil0,002

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 GPT0,250
Écart entre enseignants0,241 · 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

Citations1
Publié2019
Routes d'admission1
Résumé présentoui

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