Surface-functionalized, electrically sensitive barcoded particles for microfluidic impedance detection of sepsis-related leukocyte receptors
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Ashley, Brandon Kenneth.
Surface-functionalized, electrically sensitive barcoded particles for microfluidic impedance detection of sepsis-related leukocyte receptors. Retrieved from
https://doi.org/doi:10.7282/t3-5f2r-1541Export
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TitleSurface-functionalized, electrically sensitive barcoded particles for microfluidic impedance detection of sepsis-related leukocyte receptors
Date Created2023
Other Date2023-05 (degree)
Extent165 pages : illustrations
DescriptionSepsis is an erroneous, hyperactive immune response to infection, and the highest cause of hospital deaths. Early treatment using pathogen-specific antibiotics can greatly improve survival, and while over 170 biomarkers have been linked with sepsis, existing diagnostic methods struggle to provide accurate or timely results. To deliver rapid, precise detection and progress treatment, the leading strategy is lab-on-a-chip technology to perform multiplexed analysis of critical immune cell receptors: the earliest biomarkers indicating sepsis. Herein, this project aims to design a microfluidic impedance cytometer to detect novel impedance-sensitive, metal oxide-coated Janus microparticles (MOJPs), which can be differentiated using a single multifrequency electric field. MOJP identification hinges on different metal oxide surface conductivities intrinsic to the material and nanometer coating thickness on 3 µm polystyrene cores. This work develops and characterizes an eco-conscious, high throughput protocol functionalizing MOJPs with antibodies targeting sepsis-related receptors. Streptavidin adsorbed to aluminum oxide-coated Janus particles with different layer thicknesses has facilitated biotinylated anti-CD11b and anti-CD66b antibody linkage (10nmCD11b and 20nmCD66b, respectively). This nonspecific functionalization protocol can readily translate to other MOJP types along with different sepsis-related receptors (e.g., C-type lectin receptor, nCD64, TLR, etc.), increasing the multiplexed receptor targeting potential and improve sepsis-diagnostic confidence. To improve notoriously weak signal acquisition from microfluidic impedance cytometers—the devices which detect MOJPs and their subsequent neutrophil conjugation—a high signal-to-noise ratio (SNR) signal processing algorithm is also formulated. Using transimpedance amplification, differential collection, a novel modified simple moving averaging algorithm, and optimizing noise-eliminating digital filters, Gaussian noise was reduced which improved the detection range and enumeration accuracy of the microfluidic impedance cytometer, increasing the SNR of single MOJPs by 73%. Finally, the microfluidic architecture is fabricated and optimized to detect unique cell-MOJPs conjugate electrical signals. Currently, gold coplanar electrodes generate a multifrequency electric field under a polydimethylsiloxane-based microfluidic channel, with narrow focusing regions between electrodes to increase object volume fraction and further ameliorate SNR. The microfluidic impedance cytometer has collected 10nmCD11b-neutrophil and 20nmCD66b-neutrophil conjugate signals with four electric field frequencies tuned for maximal MOJP signal disparities. Supervised machine learning along with simultaneous high-speed video microscopy is used to identify MOJPs, neutrophils, and neutrophil-MOJP conjugates with greater precision and sensitivity based on the type and number of MOJPs conjugated with cells (>90% accuracy between cell-particle conjugates versus cells alone). The design may further expand to include more MOJP types (hafnium oxide, titanium dioxide coatings) targeting more sepsis-related receptors in one sample, producing a less-limited multiplexed system. Along with miniaturized custom electrical components and integrated sample mixing, the modality may one day be a key option as an accurate and rapid point-of-care sensor on sepsis severity.
NotePh.D.
NoteIncludes bibliographical references
Genretheses
LanguageEnglish
CollectionSchool of Graduate Studies Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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