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      Smartphone-Based Dual-Modality Imaging System for Quantitative Detection of Color or Fluorescent Lateral Flow Immunochromatographic Strips

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          Abstract

          Nowadays, lateral flow immunochromatographic assays are increasingly popular as a diagnostic tool for point-of-care (POC) test based on their simplicity, specificity, and sensitivity. Hence, quantitative detection and pluralistic popular application are urgently needed in medical examination. In this study, a smartphone-based dual-modality imaging system was developed for quantitative detection of color or fluorescent lateral flow test strips, which can be operated anywhere at any time. In this system, the white and ultra-violet (UV) light of optical device was designed, which was tunable with different strips, and the Sobel operator algorithm was used in the software, which could enhance the identification ability to recognize the test area from the background boundary information. Moreover, this technology based on extraction of the components from RGB format (red, green, and blue) of color strips or only red format of the fluorescent strips can obviously improve the high-signal intensity and sensitivity. Fifty samples were used to evaluate the accuracy of this system, and the ideal detection limit was calculated separately from detection of human chorionic gonadotropin (HCG) and carcinoembryonic antigen (CEA). The results indicated that smartphone-controlled dual-modality imaging system could provide various POC diagnoses, which becomes a potential technology for developing the next-generation of portable system in the near future.

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          Most cited references31

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          Membrane-based lateral flow immunochromatographic strip with nanoparticles as reporters for detection: A review.

          Membrane-based lateral flow immunochromatographic strip (LFICS) is widely used in various fields because of its simplicity, rapidity (detection within 10min), and low cost. However, early designs of membrane-based LFICS for preliminary screening only provide qualitative ("yes/no" signal) or semi-quantitative results without quantitative information. These designs often suffer from low-signal intensity and poor sensitivity and are only capable of single analyte detection, not simultaneous multiple detections. The performance of existing techniques used for detection using LFICS has been considerably improved by incorporating different kinds of nanoparticles (NPs) as reporters. NPs can serve as alternative labels and improve analytical sensitivity or limit of detection of LFICS because of their unique properties, such as optical absorption, fluorescence spectra, and magnetic properties. The controlled manipulation of NPs allows simultaneous or multiple detections by using membrane-based LFICS. In this review, we discuss how colored (e.g., colloidal gold, carbon, and colloidal selenium NPs), luminescent (e.g., quantum dots, up-converting phosphor NPs, and dye-doped NPs), and magnetic NPs are integrated into membrane-based LFICS for the detection of target analytes. Gold NPs are also featured because of their wide applications. Different types and unique properties of NPs are briefly explained. This review focuses on examples of NP-based LFICS to illustrate novel concepts in various devices with potential applications as screening tools. This review also highlights the superiority of NP-based approaches over existing conventional strategies for clinical analysis, food safety, and environmental monitoring. This paper is concluded by a short section on future research trends regarding NP-based LFICS.
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            A simple and compact smartphone accessory for quantitative chemiluminescence-based lateral flow immunoassay for salivary cortisol detection.

            We have developed a simple and accurate biosensor based on a chemiluminescent (CL)-lateral flow immunoassay (LFIA) method integrated in a smartphone to quantitatively detect salivary cortisol. The biosensor is based on a direct competitive immunoassay using peroxidase-cortisol conjugate, detected by adding the chemiluminescent substrate luminol/enhancer/hydrogen peroxide. The smartphone camera is used as light detector, for image acquisition and data handling via a specific application. We 3D-printed simple accessories to adapt the smartphone. The system comprises a cartridge, which houses the LFIA strip, and a smartphone adaptor with a plano-convex lens and a cartridge-insertion slot. This provides a mini-darkbox and aligned optical interface between the camera and the LFIA membrane for acquiring CL signals. The method is simple and fast, with a detection limit of 0.3 ng/mL. It provides quantitative analysis in the range of 0.3-60 ng/mL, which is adequate for detecting salivary cortisol in the clinically accepted range. It could thus find application in the growing area of home-self-diagnostic device technology for clinical biomarker monitoring, overcoming the current difficulties in achieving sensitive and quantitative information with conventional systems taking the advantage of smartphone connectivity and the enhanced performance of the included camera.
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              A smartphone algorithm with inter-phone repeatability for the analysis of colorimetric tests

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                Author and article information

                Contributors
                yafeihou@sjtu.edu.cn
                wk_xa@163.com
                450073755@qq.com
                1602701580@qq.com
                luwenting23@163.com
                taowei@sjtu.edu.cn
                dxcui@sjtu.edu.cn
                Journal
                Nanoscale Res Lett
                Nanoscale Res Lett
                Nanoscale Research Letters
                Springer US (New York )
                1931-7573
                1556-276X
                21 April 2017
                21 April 2017
                2017
                : 12
                : 291
                Affiliations
                [1 ]ISNI 0000 0004 0368 8293, GRID grid.16821.3c, Department of Instrument Science and Engineering, , School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, ; Shanghai, 200240 China
                [2 ]Shanghai Engineering Research Center for Intelligent Diagnosis and Treatment Instrument, Shanghai, 200240 China
                [3 ]ISNI 0000 0000 8877 7471, GRID grid.284723.8, Zhujiang Hospital, , Southern Medical University, ; 253 Gongye Road, Guangzhou, Guangdong 510280 China
                Article
                2078
                10.1186/s11671-017-2078-9
                5400777
                28438012
                001c76c5-f1fd-480b-ae31-02c16f988f07
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 15 March 2017
                : 13 April 2017
                Funding
                Funded by: National Key Basic Research Program
                Award ID: No.2015CB931802
                Award Recipient :
                Funded by: 863 High-Tech Project of China
                Award ID: No. 2014AA020700
                Award Recipient :
                Funded by: National Natural Scientific Foundation of China
                Award ID: No. 81571835, 61503246, 81672247 and 81671737
                Award Recipient :
                Categories
                Nano Express
                Custom metadata
                © The Author(s) 2017

                Nanomaterials
                smartphone,dual-modality imaging,lateral flow strip,quantitative detection
                Nanomaterials
                smartphone, dual-modality imaging, lateral flow strip, quantitative detection

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