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High-Throughput Refractive Index Qua...

DeLuna, Frank.

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High-Throughput Refractive Index Quantification via Photonic-Crystal Biosensor Microscopy.

Record Type:	Electronic resources : Monograph/item
Title/Author:	High-Throughput Refractive Index Quantification via Photonic-Crystal Biosensor Microscopy./
Author:	DeLuna, Frank.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2023,
Description:	106 p.
Notes:	Source: Dissertations Abstracts International, Volume: 84-11, Section: B.
Contained By:	Dissertations Abstracts International84-11B.
Subject:	Biomedical engineering. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30489134
ISBN:	9798379578145

High-Throughput Refractive Index Quantification via Photonic-Crystal Biosensor Microscopy.
DeLuna, Frank.

High-Throughput Refractive Index Quantification via Photonic-Crystal Biosensor Microscopy. - Ann Arbor : ProQuest Dissertations & Theses, 2023 - 106 p.

Source: Dissertations Abstracts International, Volume: 84-11, Section: B.

Thesis (Ph.D.)--The University of Texas at San Antonio, 2023.

This item must not be sold to any third party vendors.

The work presented in this dissertation describes the development and application of a Photonic-Crystal based biosensor in a Total-Internal-Reflection (PC-TIR) configuration for various biomedical applications. The biosensor utilizes refractive index (RI) as a means of detecting and distinguishing between different cell types and biomolecules. Specifically, we demonstrate the use of the PC-TIR biosensor for the detection of prostate cancer cells and the evaluation of prostate cancer progression using cellular RI as the only contrast parameter. Additionally, we report the development of a high-throughput, multiplexed, antibody-antigen biosensor based on the PC-TIR biosensor for accurate analysis of biomarkers pertinent to traumatic brain injury (TBI). This study highlights the potential of the PC-TIR biosensor as a powerful and versatile platform for various biosensing applications.

ISBN: 9798379578145Subjects--Topical Terms:

535387
Biomedical engineering.
Subjects--Index Terms:

Photonic-Crystal biosensor

High-Throughput Refractive Index Quantification via Photonic-Crystal Biosensor Microscopy.
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020 $a 9798379578145
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100 1 $a DeLuna, Frank. $3 3763108
245 1 0 $a High-Throughput Refractive Index Quantification via Photonic-Crystal Biosensor Microscopy.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2023
300 $a 106 p.
500 $a Source: Dissertations Abstracts International, Volume: 84-11, Section: B.
500 $a Advisor: Yong Ye, Jing.
502 $a Thesis (Ph.D.)--The University of Texas at San Antonio, 2023.
506 $a This item must not be sold to any third party vendors.
520 $a The work presented in this dissertation describes the development and application of a Photonic-Crystal based biosensor in a Total-Internal-Reflection (PC-TIR) configuration for various biomedical applications. The biosensor utilizes refractive index (RI) as a means of detecting and distinguishing between different cell types and biomolecules. Specifically, we demonstrate the use of the PC-TIR biosensor for the detection of prostate cancer cells and the evaluation of prostate cancer progression using cellular RI as the only contrast parameter. Additionally, we report the development of a high-throughput, multiplexed, antibody-antigen biosensor based on the PC-TIR biosensor for accurate analysis of biomarkers pertinent to traumatic brain injury (TBI). This study highlights the potential of the PC-TIR biosensor as a powerful and versatile platform for various biosensing applications.
590 $a School code: 1283.
650 4 $a Biomedical engineering. $3 535387
650 4 $a Oncology. $3 751006
650 4 $a Analytical chemistry. $3 3168300
653 $a Photonic-Crystal biosensor
653 $a Biomedical applications
653 $a Traumatic brain injury
653 $a Cancer cells
690 $a 0541
690 $a 0486
690 $a 0992
710 2 $a The University of Texas at San Antonio. $b Biomedical Engineering. $3 1672276
773 0 $t Dissertations Abstracts International $g 84-11B.
790 $a 1283
791 $a Ph.D.
792 $a 2023
793 $a English
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30489134