Quantitative and rapid detection of C-reactive protein using quantum dot-based lateral flow test strip

Wu, Ruili; Zhou, Shuai; Chen, Ting; Li, Jinjie; Shen, Huaibin; Chai, Yujuan; Li, Lin Song

doi:10.1016/j.aca.2017.12.031

Cited by 75 publications

(40 citation statements)

References 38 publications

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“…To date, several kinds of aqueous QD‐based biological detection techniques have been developed . Recently, our group has obtained aqueous high‐quality CdSe core/shell QDs via amphiphilic polymer (polymaleic acid n ‐hexadecanol ester, PMAH) coating technique and also adapted CdSe QD‐based lateral flow immunoassay (LFIA) for qualitative and quantitative detection of human chorionic gonadotropin (HCG), procalcitonin (PCT), influenza A virus, and C‐reactive protein . But only traditional Cd‐based QDs have been widely developed in biomedical fields, especially for CdSe and CdTe related core/shell QDs .…”

Section: Introductionmentioning

confidence: 99%

Preparation of Highly Stable and Photoluminescent Cadmium‐Free InP/GaP/ZnS Core/Shell Quantum Dots and Application to Quantitative Immunoassay

et al. 2020

Part & Part Syst Charact

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Indium phosphide (InP) quantum dots (QDs) are ideal substitutes for widely used cadmium‐based QDs and have great application prospects in biological fields due to their environmentally benign properties and human safety. However, the synthesis of InP core/shell QDs with biocompatibility, high quantum yield (QY), uniform particle size, and high stability is still a challenging subject. Herein, high quality (QY up to 72%) thick shell InP/GaP/ZnS core/shell QDs (12.8 ± 1.4 nm) are synthesized using multiple injections of shell precursor and extension of shell growth time, with GaP serving as the intermediate layer and 1‐octanethiol acting as the new S source. The thick shell InP/GaP/ZnS core/shell QDs still keep high QY and photostability after transfer into water. InP/GaP/ZnS core/shell QDs as fluorescence labels to establish QD‐based fluorescence‐linked immunosorbent assay (QD‐FLISA) for quantitative detection of C‐reactive protein (CRP), and a calibration curve is established between fluorescence intensity and CRP concentrations (range: 1–800 ng mL−1, correlation coefficient: R2 = 0.9992). The limit of detection is 2.9 ng mL−1, which increases twofold compared to previously reported cadmium‐free QD‐based immunoassays. Thus, InP/GaP/ZnS core/shell QDs as a great promise fluorescence labeling material, provide a new route for cadmium‐free sensitive and specific immunoassays in biomedical fields.

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Section: Introductionmentioning

confidence: 99%

Preparation of Highly Stable and Photoluminescent Cadmium‐Free InP/GaP/ZnS Core/Shell Quantum Dots and Application to Quantitative Immunoassay

et al. 2020

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“…Our blind testing results yielded an average coefficient of variation (CV) of 11.2% and a coefficient of determination (R 2 ) of 0.95 over an analytical measurement range of 0 mg/L to 10 mg/L. It is important to note that although there is no FDA-approved POC hsCRP sensor, various systems have been demonstrated in the literature [40][41][42][43][44] . However, the tests which report accurate quantification in the high-sensitivity range employ fluorescent-based chemical assays and benchtop readers to overcome the performance limits of their traditional colorimetric counterparts.…”

Section: Introductionmentioning

confidence: 85%

Deep Learning-Enabled Point-of-Care Sensing Using Multiplexed Paper-Based Sensors

Ballard

Joung²,

Goncharov³

et al. 2019

Preprint

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ABSTRACTWe present a deep learning-based framework to design and quantify point-of-care sensors. As its proof-of-concept and use-case, we demonstrated a low-cost and rapid paper-based vertical flow assay (VFA) for high sensitivity C-Reactive Protein (hsCRP) testing, a common medical test used for quantifying the degree of inflammation in patients at risk of cardio-vascular disease (CVD). A machine learning-based sensor design framework was developed for two key tasks: (1) to determine an optimal configuration of immunoreaction spots and conditions, spatially-multiplexed on a paper-based sensing membrane, and (2) to accurately infer the target analyte concentration based on the signals of the optimal VFA configuration. Using a custom-designed mobile-phone based VFA reader, a clinical study was performed with 85 human serum samples to characterize the quantification accuracy around the clinically defined cutoffs for CVD risk stratification. Results from blindly-tested VFAs indicate a competitive coefficient of variation of 11.2% with a linearity of R2 = 0.95; in addition to the success in the high-sensitivity CRP range (i.e., 0-10 mg/L), our results further demonstrate a mitigation of the hook-effect at higher CRP concentrations due to the incorporation of antigen capture spots within the multiplexed sensing membrane of the VFA. This paper-based computational VFA that is powered by deep learning could expand access to CVD health screening, and the presented machine learning-enabled sensing framework can be broadly used to design cost-effective and mobile sensors for various point-of-care diagnostics applications.

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“…Currently, most research efforts are focused on signal amplification, which has been quite successful at improving PAD sensitivity. For example, nanoparticle-based approaches, including use of gold nanoparticles [40], carbon nanopartides [41], and quantum dots [42], as well as chemiluminescence [43] have all been used to improve PAD based immunoassay sensitivity to levels comparable with a large-scale instrument like ELISA and mass spectrometry. In terms of enhancing effective immunobinding at ultralow analyte concentration, an ideal technique should be capable of on-board depletion of abundant proteins to reduce their interference on immunobinding of the desired target, and should further be able to elevate concentration of the desired target before immunocapture.…”

Section: Discussionmentioning

confidence: 99%

Paper-based cascade cationic isotachophoresis: Multiplex detection of cardiac markers

Guo

Schlecht

et al. 2019

Talanta

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Paper-based analytical devices (PADs) are widely used in point-of-care testing (POCT) as they are cost-effective, simple and straightforward. However, poor sensitivity hinders their use in detecting diseases with low abundance biomarkers. The poor detection limit of PADs is mainly attributed to the low concentration of analytes, and the complexity of biological fluid, leading to insufficient interactions between analytes and capture antibodies. This study aims to overcome these difficulties by developing a paper-based cationic isotachophoresis (ITP) approach for simultaneously detecting pico-molar levels of two essential cardiac protein markers: acidic troponin T (cTnT) and basic troponin I (cTnI) spiked into human serum samples. The approach utilizes 3-aminopropyltrimethoxysilane (APTMS) treated glass fiber papers with decreasing cross-sectional area assembled on a 3D printed cartridge device. Our results showed that in the presence of cTnT monoclonal antibody (mAb), fluorescently labeled cTnI and cTnT could be effectively enriched in cationic ITP. Each individual target was captured subsequently by a test line in the detection zone where the capture mAb was immobilized. Detailed analysis suggests that the technology is capable of simultaneous on-board depletion of abundant plasma proteins and enrichment of cTnI/cTnT by ~1300-fold with a sensitivity of 0.6pmol/L for cTnT and a sensitivity of 1.5 pmol/L for cTnI in less than 6 min. The results demonstrate the potential of this technology for rapid, ultrasensitive and cost-effective analysis of multiplex protein markers in clinical serum samples at point of care.

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Quantitative and rapid detection of C-reactive protein using quantum dot-based lateral flow test strip

Cited by 75 publications

References 38 publications

Preparation of Highly Stable and Photoluminescent Cadmium‐Free InP/GaP/ZnS Core/Shell Quantum Dots and Application to Quantitative Immunoassay

Preparation of Highly Stable and Photoluminescent Cadmium‐Free InP/GaP/ZnS Core/Shell Quantum Dots and Application to Quantitative Immunoassay

Deep Learning-Enabled Point-of-Care Sensing Using Multiplexed Paper-Based Sensors

Paper-based cascade cationic isotachophoresis: Multiplex detection of cardiac markers

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