- Title Information
- Title
- Exploring the Diagnostic Potential of Extracellular Vesicles
- Type of Resource (primo)
- dissertations
- Name:
Personal
- Name Part
- Lujuo, Christine
- Role
- Role Term:
Text
- creator
- Name:
Personal
- Name Part
- Tripathi, Anubhav
- Role
- Role Term:
Text
- Advisor
- Name:
Personal
- Name Part
- Mathiowitz, Edith
- Role
- Role Term:
Text
- Reader
- Name:
Personal
- Name Part
- Gatsonis, Constantine
- Role
- Role Term:
Text
- Reader
- Name:
Corporate
- Name Part
- Brown University. Biology and Medicine: Biomedical Engineering
- Role
- Role Term:
Text
- sponsor
- Origin Information
- Copyright Date
- 2025
- Physical Description
- Extent
- , None p.
- digitalOrigin
- born digital
- Note:
thesis
- Thesis (Sc. M.)--Brown University, 2025
- Genre (aat)
- theses
- Abstract
- Extracellular vesicles (EVs) have emerged as a key biomarker in liquid biopsy diagnostics, due to their abundance in bodily fluids and their ability to reflect the physiological state of their cells of origin. Their diverse functions, including immune regulation to intercellular communication, underscore their potential in biomedical research. This study focused on two main objectives: (1) optimization of digital ELISA assays for the detection of breast cancer-derived EVs, and (2) improvement of EV extraction methods from dried blood spots (DBS). The Single Molecule Array technology was used for the detection of both EVs. In the first study, breast cancer samples showed an increase in CD63 expression compared to normal controls. In the second study, there is evidence of faster EV extraction (from 1 hr. to 5 minutes) after applying an electric field to the dried blood spot compared to existing methods in literature.
- Subject
- Topic
- extracellular vesicles
- Subject
- Topic
- Breast Cancer
- Subject
- Topic
- dried blood spots
- Subject
- Topic
- digital ELISA
- Language
- Language Term (ISO639-2B)
- English
- Record Information
- Record Content Source (marcorg)
- RPB
- Record Creation Date
(encoding="iso8601")
- 20250707