MétaCan
Menu
Retour à la cohorte
Enregistrement W3029909430

Mucoadhesive Nanocomposite Derived from Cellulose Nanocrystal and Chitosan for the Delivery of Hydrophobic Compounds

2020· dissertation· en· W3029909430 sur OpenAlexfundaboutno aff
Dae Sung Kim

Notice bibliographique

RevueUWSpace (University of Waterloo) · 2020
Typedissertation
Langueen
DomaineMaterials Science
ThématiqueElectrospun Nanofibers in Biomedical Applications
Établissements canadiensnon disponible
Organismes subventionnairesUniversity of Waterloo
Mots-clésChitosanNanocompositeNanocrystalCelluloseMaterials scienceChemical engineeringNanotechnologyChemistryOrganic chemistryEngineering
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The sea lice are a major ectoparasite of salmon aquaculture that anchor to host fish’s mucus membrane, epidermis, and vascular system, thereby compromising the fish immunity. The surging amount of sea lice has caused enormous financial damage to the global salmon farming industries. Current sea lice treatment has relied on conventional drug delivery system that reduces drug efficacy that poses an environmental risk due to the excessive use of toxic chemical compounds. Nanomedicine and nano delivery system are rapidly developing to serve as therapeutic agents for targeting specific sites in a controlled manner, thereby enhancing the therapeutic effects at lower drug dosages. The objective of this research is to develop novel mucoadhesive nano drug delivery platforms that can encapsulate hydrophobic compounds, thereby enhancing the pharmaceutical effects of various applications including biomedical and agricultural fields. The thesis describes various mucoadhesive drug delivery platforms comprising of cellulose nanocrystals (CNC) and chitosan (CS) with different moieties. The scope of the research focuses on the development of mucoadhesive nanocomposite using green chemistry and facile synthesis methods through electrostatic gelation. To improve the functionality of the nanocomposite, colloidal behavior and mucoadhesive properties, various chemical modification techniques were employed to modify the functional groups and to decorate different moieties using nano-polysaccharide based materials. \nThrough this study, we found that the particle size CNC/CS nanoparticles was in the range of 200 nm to 2 μm, depending on the mass ratio of CNC and CS. The optimal mass ratio was 10:1 (CNC:CS w/w) yielding the smallest average particle size (~200 nm), highest zeta potentials (+40 mV), and highest drug loading efficiency. It was confirmed that polyvinylpyrrolidone (PVP) enhanced the colloidal stability of hydrophobic compounds by making the system hydrophilic. Chitosan coating enhanced colloidal stability and drug encapsulation efficiency via electrostatic repulsion. The loading and encapsulation efficiency of CNC/CS nanocomposite was 11.6 and 65.6 %, respectively. CNC/CS nanoparticle exhibited good antifungal properties against S. cerevisiae and mucoadhesive studies confirmed that nanoparticles could bind to mucus surface of zebrafish. CNC/CS modified with quaternary ammonium groups (Gch) exhibited permanent positive charge at all pH values, resulting in enhanced solubility of CS. The optimal mass ratio was 1:4 (CNC:Gch w/w), and the shape of CNC/CS based nanocomposite depended on the synthesis order, reaction time, and sonication power. To produce nanocomplexes with a homogenous structure, polymeric CS solution should be added to the CNC to coat the surface. Finally, the optimal mass ratio of CNC/CS nanoparticles modified with catechol groups (cat) was 7:1 (CNC:CS-cat w/w). After functionalizing with poly(diallyldimethylammonium chloride) (PDADMAC), the colloidal stability was enhanced yielding a particle size of ~150 nm and a zeta potential of +50 mV. Mucoadhesive studies using confocal microscopy confirmed that CNC/CS nanoparticles modified catechol groups could bind to the zebrafish mucus after 30 mins exposure, as the fluorescence signals were significantly enhanced compared to control study without modification. \nThe significant discovery of this research are: (1) a facile and reproducible method to prepare CNC/CS based nanocomposite that encapsulate large amount of hydrophobic drugs via electrostatic gelation was developed, (2) the colloidal behavior and stabilization effect of CNC/CS based nanocomposites were elucidated, (3) mucoadhesive nano-drug delivery systems by incorporating bio-inspired active compounds were produced, and (4) the potentials of mucoadhesive CNC/CS based nanocomposite for the treatment of livestock’s parasitic \ndiseases by demonstrating mucoadhesive capabilities of prepared nanoparticles on zebrafish was demonstrated. \nWith these findings, it is expected that CNC/CS based nanoparticles can serve as targeted drug delivery agents for the delivery of hydrophobic molecules, increasing colloidal stability, drug efficacy, and bioavailability. Furthermore, CNC/CS based nanocomposite will be applied for the treatment of various mucosal infections in agricultural and biomedical fields. This research establishes the foundation for the design and development of mucoadhesive delivery systems for the treatment of sea lice and other parasites found in fish farms in Canada.

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 enseignants0,002
Score d'incertitude au seuil0,005

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 Opus0,007
Tête enseignante GPT0,194
Écart entre enseignants0,187 · 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
Publié2020
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revueUWSpace (University of Waterloo)Même sujetElectrospun Nanofibers in Biomedical ApplicationsTravaux en français237 207