Enhanced Diagnosis of Breast Cancer through Detection of Exosomes using ex-situ, in-situ, and Solid State Dewetted Nanoplasmonic Platforms
Notice bibliographique
Résumé
Breast cancer is one of the leading causes of death and the second most common among women in Canada. This thesis aims to develop sensing nanoplasmonic platforms for the early diagnosis of breast cancer through the detection of exosomes. The adsorption of bio or organic molecules on metallic nanoparticles leads to a plasmon band shift towards longer wavelengths; a phenomenon central to Localized Surface Plasmon Resonance (LSPR). This study aims to develop nano-structured arrays of plasmonic platforms for the high-performance detection of sub-micron biological entities such as viruses, exosomes, and other extracellular vesicles (EVs) ranging from 30 - 1000 nm. This thesis particularly focuses on developing and optimizing unique plasmonic platforms for detecting EVs/exosomes derived from breast cancer cell lines. These EVs/exosomes are nano-sized (30 - 100 nm), cargo-bearing vesicles secreted by almost all cell types, consisting of a lipid bilayer encasing a semi-fluid core of cytoplasmic materials, including proteins, nucleic acids, and exhibit significant heterogeneity, reflecting their cellular origin. Despite their potential as biomarkers for diseases like cancer, their heterogeneity and overlapping physicochemical properties with other vesicles pose challenges for effective detection, separation, and purification. In the beginning, two different types of platforms, one fabricated by an ex-situ method and the other by an in-situ method, were investigated to find out which was more convenient in terms of sensitivity for detecting EVs/exosomes. Different fabrication conditions have been explored and the sensitivity of the platforms has been measured. A sensing protocol involving several steps has been developed and optimized for detecting EVs/exosomes. It has been found that the platform prepared by an ex-situ method, that is, by convective assembly of gold colloidal particles, is more sensitive than the silver (Ag)-PDMS and gold (Au)-PDMS nanocomposite platforms fabricated by an in-situ method. In the case of gold (Au)-PDMS, gold is segregated under the surface of the polymer, without direct contact with the environment, and thus not suitable for detection. Additionally, to improve the refractive index sensitivity, novel platforms have been investigated. This thesis is further dedicated to developing and characterizing new plasmonic platforms, based on nano-islands/particles, fabricated from thin gold films e-beam deposited on an adhesion layer. The nano-islands/particles fabricated by the dewetting of the uniform gold films deposited on Chromium (Cr) (Cr-Au) and Indium Tin Oxide (ITO) adhesion layers (ITO-Au), respectively. Subsequently, based on the characterization results, the Cr-Au platform has been identified for the detection of EVs/exosomes. In addition, a direct detection method as well was developed without any surface chemistry modification of the plasmonic platform. The detection results obtained by using this novel platform and method were compared with the results of the ex-situ, and in-situ platforms studied earlier in this thesis work. It was found that, with the novel platform and method, the sensitivity of detection improved around 1.5 times, and the time taken for the detection was reduced by around one-fourth of the time of the earlier method. This work also provided invaluable information, regarding the adhesion layers, and their characteristics, especially stability, in association with very thin gold films. The phenomena of interdiffusion and oxidation during the deposition and heat treatment and their effect on detection have been studied as well. Overall, this work contributes to the development of cost-effective, high-performance nanoplasmonic platforms, for early diagnosis of breast cancer establishing a foundation for their broader application in detecting and analyzing diverse biological and environmental samples.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».