- Title Information
- Title
- Development and Validation of High-Sensitivity Analytical Frameworks for Low-Abundance Pathological Cargo in Human Biofluids.
- Type of Resource (primo)
- dissertations
- Name:
Personal
- Name Part
- Pollock, Jennifer Margaret
- Role
- Role Term:
Text
- creator
- Name:
Personal
- Name Part
- Hurt, Robert
- Role
- Role Term:
Text
- Reader
- Name:
Personal
- Name Part
- Kreiling, Jill
- Role
- Role Term:
Text
- Reader
- Name:
Personal
- Name Part
- Tripathi, Anubhav
- Role
- Role Term:
Text
- Advisor
- Name:
Personal
- Name Part
- Desai, Tejal
- 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
- 2026
- Physical Description
- Extent
- xxvii, 189 p.
- digitalOrigin
- born digital
- Note:
thesis
- Thesis (Ph. D.)--Brown University, 2026
- Genre (aat)
- theses
- Abstract
- Liquid biopsies offer immense potential for non-invasive disease monitoring, yet their clinical adoption is hindered by the analytical difficulty of detecting scarce biomarkers within complex biofluids. While extracellular vesicles (EVs) and proteopathic aggregates like amyloid-beta (Aβ) provide a window into systemic and central nervous system (CNS) pathologies, traditional isolation-based workflows suffer from low recovery and poor reproducibility. This dissertation describes the development of high-sensitivity analytical frameworks designed to bypass these hurdles through direct, digital quantification of pathological cargo.
The first phase of this research addresses ultra-low-abundance protein monomers. By developing a dual-functionalized microparticle interface—utilizing magnetic capture beads and DNA-tagged detection beads coupled with qPCR amplification—we achieved a femtomolar limit of detection (0.05 pg/mL) for Aβ (1-42). This provides a highly sensitive tool for the early detection of Alzheimer’s pathology. Building on this, we established a robust digital Single Molecule Array (SiMoA) platform for the direct detection of intact EVs in human plasma and serum. By implementing a continuous piecewise mathematical model for Average Enzymes per Bead (AEB) determination, we successfully addressed EV polyvalency. This framework maintained a dynamic range over four orders of magnitude and achieved a limit of detection of 1.61 x 107 particles/mL, outperforming commercial assays in both reproducibility and sensitivity.
Finally, we extended this SiMoA framework to neuro-diagnostics to quantify brain-derived EVs (bdEVs). By targeting CNS-specific markers, our findings identified ATP1A3 and NCAM as superior, stable alternatives to L1CAM for longitudinal monitoring. Proteomic characterization revealed that NCAM+ populations exhibit a significantly higher loading density for neurodegenerative biomarkers, such as NfL and GFAP, compared to canonical populations. This suggests that subtype-specific targeting can enhance the resolution of CNS signals in peripheral biofluids. Collectively, this research provides a scalable, high-throughput toolbox that shifts the liquid biopsy paradigm from tedious sample preparation to direct, high-precision molecular profiling. These frameworks offer a standardized path forward for early disease detection and treatment monitoring across oncology and neurology.
- Subject (fast)
(authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/01045739")
- Topic
- Oncology
- Subject
- Topic
- extracellular vesicles
- Subject (fast)
(authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/01036390")
- Topic
- Neurology
- Subject (fast)
(authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/00967921")
- Topic
- Immunoassay
- Language
- Language Term (ISO639-2B)
- English
- Record Information
- Record Content Source (marcorg)
- RPB
- Record Creation Date
(encoding="iso8601")
- 20260516