A point-of-care testing system with giant magnetoresistive biosensors
Abstract/Contents
- Abstract
- Point-of-care testing (POCT) is an important diagnostic tool used in many areas of clinical medicine, especially in critical care settings. Its development is driven by the goal of bringing diagnostic tests close to patients in order to make fast triage and treatment decisions. The rapid worldwide spread and impact of COVID-19 has validated and further prompted the need for accurate, fast, and portable testing technologies. Many attempts have been made to bring lab-quality molecular tests to point-of-care settings, but in order to meet the portability requirement, most technologies compromise sensitivity and multiplexing capability. In this work, we present a portable testing platform with magnetoresistive biosensors that can perform automated, accurate, multiplexed, and fast tests. In this dissertation, we first summarize the use of giant magnetoresistive (GMR) biosensor arrays in medical detection and diagnosis. We also describe the development of a fully automated platform that can perform both protein detection and nucleic acid amplification tests in various types of samples. We demonstrate its wide usage in detecting human immunodeficiency virus (HIV), leukocytosis, hepatocellular carcinoma (HCC), gene expressions of the influenza immune response, and DNA polymorphisms in catechol-o-methyltransferase (COMT) and show that the presented platform has excellent performance and multiplex capability. We expect this new platform to dramatically improve the usability, efficacy, and availability of future molecular tests.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2020; ©2020 |
| Publication date | 2020; 2020 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Yao, Chengyang |
|---|---|
| Degree supervisor | Wang, Shan X |
| Thesis advisor | Wang, Shan X |
| Thesis advisor | Rao, Jianghong |
| Thesis advisor | de la Zerda, Adam |
| Degree committee member | Rao, Jianghong |
| Degree committee member | de la Zerda, Adam |
| Associated with | Stanford University, Department of Electrical Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Chengyang Yao. |
|---|---|
| Note | Submitted to the Department of Electrical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2020. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2020 by Chengyang Yao
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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