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Rapid label-free electronic detection of biomarker using miniturized microfluidic system
Descriptive
TitleInfo
Title
Rapid label-free electronic detection of biomarker using miniturized microfluidic system
Name
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NamePart
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Lin
NamePart
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Zhongtian
NamePart
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1991-
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Zhongtian Lin
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(authority = RULIB)
author
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Javanmard
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Mehdi
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Mehdi Javanmard
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Advisory Committee
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chair
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Wu
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Michael
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Michael Wu
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Advisory Committee
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internal member
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(type = family)
Najafizadeh
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Laleh
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Laleh Najafizadeh
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Advisory Committee
Role
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(authority = RULIB)
internal member
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(type = family)
Sengupta
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(type = given)
Kaushik
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Kaushik Sengupta
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Advisory Committee
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outside member
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Rutgers University
Role
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degree grantor
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NamePart
School of Graduate Studies
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school
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Text
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theses
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ETD doctoral
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2020
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2020-10
Language
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English
Abstract
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The application of Lab-on-a-Chip or microfluidic technologies to perform protein assays is an emerging field and has a potential to be used for point-of-care device. In order to achieve this goal, the miniaturization of the biochip and high sensitivity is required. In this proposal, we addressed multiple novel solutions for biomarker detections in purified buffer, cancer cells and saliva sample using a micro sized biochip which includes sensor fabrication, sample preparation, theoretical consideration, impedance cytometry and data analysis.
We started with detecting protein in purified buffer. We performed a sandwich immunoassay, where the complementary antibody pairs are immobilized on two different bead types, and the presence of target antigen results in bead aggregation, the amount of which depends on antigen quantity. When single beads or bead aggregates pass through the impedance sensor, differences in impedance change are detected.
As for cancer cells, we focused on the rapid qualitative assessment of surface markers on cancer cells which can allow for point-of care prediction of patient response to various cancer drugs. Preclinical studies targeting cells with an antibody to “activated” matriptase conjugated to a potent toxin show promise as a selective treatment for a variety of solid tumors. We implemented a novel technique for electrical detection of proteins on surfaces of cancer cells using multi-frequency microfluidic impedance cytometry. The sensor is capable of differentiating between bare magnetic beads, cancer cells and bead-cell aggregates based on their various impedance and frequency responses.
The use of saliva as a diagnostic fluid has always been appealing due to the ability for rapid and non-invasive sampling for monitoring health status and treatment progress. Saliva is rich in protein biomarkers and provides a wealth of information for diagnosis and prognosis of various disease conditions. Portable electronic tools that can monitor protein biomarkers rapidly can enable point-of-care diagnosis and monitoring of various health conditions. we have developed an electronic assay using impedance cytometry in conjunction with supervised machine learning, capable of quantifying immunoglobulins G and immunoglobulins A in saliva within two minutes.
We started with detecting protein in purified buffer. We performed a sandwich immunoassay, where the complementary antibody pairs are immobilized on two different bead types, and the presence of target antigen results in bead aggregation, the amount of which depends on antigen quantity. When single beads or bead aggregates pass through the impedance sensor, differences in impedance change are detected.
As for cancer cells, we focused on the rapid qualitative assessment of surface markers on cancer cells which can allow for point-of care prediction of patient response to various cancer drugs. Preclinical studies targeting cells with an antibody to “activated” matriptase conjugated to a potent toxin show promise as a selective treatment for a variety of solid tumors. We implemented a novel technique for electrical detection of proteins on surfaces of cancer cells using multi-frequency microfluidic impedance cytometry. The sensor is capable of differentiating between bare magnetic beads, cancer cells and bead-cell aggregates based on their various impedance and frequency responses.
The use of saliva as a diagnostic fluid has always been appealing due to the ability for rapid and non-invasive sampling for monitoring health status and treatment progress. Saliva is rich in protein biomarkers and provides a wealth of information for diagnosis and prognosis of various disease conditions. Portable electronic tools that can monitor protein biomarkers rapidly can enable point-of-care diagnosis and monitoring of various health conditions. we have developed an electronic assay using impedance cytometry in conjunction with supervised machine learning, capable of quantifying immunoglobulins G and immunoglobulins A in saliva within two minutes.
Subject
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Topic
Biosensing
Subject
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Topic
Electrical and Computer Engineering
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Rutgers University Electronic Theses and Dissertations
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ETD_11213
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Extent
1 online resource (xiii, 87 pages) : illustrations
Note
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Ph.D.
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Includes bibliographical references
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School of Graduate Studies Electronic Theses and Dissertations
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rucore10001600001
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NjNbRU
Identifier
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doi:10.7282/t3-9zhx-9188
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Rights
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The author owns the copyright to this work.
RightsHolder
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Name
FamilyName
Lin
GivenName
Zhongtian
Role
Copyright Holder
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Permission or license
DateTime
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2020-09-27 00:17:29
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Name
Zhongtian Lin
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Affiliation
Rutgers University. School of Graduate Studies
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Author Agreement License
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I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
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Embargo
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2020-10-31
DateTime
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2024-10-31
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after October 31st, 2024.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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