Dual-phase nanoplasmonic sensing platform for monitoring blood protein adsorption and its coagulation in vitro

Tan, Yayin; Zeng, Bin; Ye, Xiangyi; Zhou, Jianhua

doi:10.1016/j.snb.2022.132240

Cited by 3 publications

(2 citation statements)

References 33 publications

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“…[5] The dependence between the light scattering spectrum and the local environment near nanostructures allows wide applications in high-sensitive and real-time tasks. [6] Due to these unique properties, metasurface-based plasmonic molecular detection has emerged as an analytic technique in gaseous chemicals, [7][8][9] biomolecules, [10,11] environmental pollutants, [12,13] etc. [14,15] However, achieving the requirements for detecting trace amounts of attached substances with spectroscopic characterization sensors, which rely on spectral changes in resonances caused by the presence of target substances, can be challenging.…”

Section: Introductionmentioning

confidence: 99%

Deep Learning‐Assisted Molecular Classification and Concentration Prediction by Imaging of a Large‐Area Metasurface with Spatially Gradient Geometry

Yang,

Wen,

et al. 2023

Advanced Intelligent Systems

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Classifying and quantifying small molecules on‐site with a rapid and cost‐effective operation are essential for pharmaceutical manufacturing, healthcare, hazardous risk control, and other applications. However, traditional molecular detection and identification methods like chromatography often involve expensive and bulky equipment and are required to be operated by trained professionals, which severely hinders the further development of small molecule‐based applications. Herein, a novel molecular detection platform is introduced by imaging a spatial gradient metasurface consisting of millions of different unique atoms and following with deep learning modeling to classify and quantify small molecules from mixed solutions accurately. The metasurface has a circular gradient geometry, which changes its transmittance intensity pattern based on the surrounding molecules under narrow‐band illumination. A convolutional neural network trained on the monochromatic images of the metasurface is employed. The results demonstrate a recognition rate of 96.88% for classification and a mean absolute error of 16.23% for quantification. This novel platform enables label‐free, sensitive, and rapid molecular classification and quantification, which opens a new avenue for small molecule classification and quantification and enables possibilities for real‐time, on‐site, and label‐free applications, including environmental monitoring, drug screening, and early diagnosis.

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Section: Introductionmentioning

confidence: 99%

Deep Learning‐Assisted Molecular Classification and Concentration Prediction by Imaging of a Large‐Area Metasurface with Spatially Gradient Geometry

Yang,

Wen,

et al. 2023

Advanced Intelligent Systems

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“…Their interaction resulted in a gradual increase in the fluorescence intensity of the detection probe with increasing influenza virus concentration [20]. In addition, nanoparticle-based SPR sensors have been widely used in various fields such as cancer diagnosis, virus detection, molecular response, and environmental monitoring due to their high sensitivity and specificity [21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Research on Dual-Technology Fusion Biosensor Chip Based on RNA Virus Medical Detection

Zhu

Xie

2022

Micromachines

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In recent years, the emergence of COVID-19 and other epidemics caused by RNA(ribonucleic acid)-type genetic viruses has aroused the close attention of governments around the world on emergency response to public safety and health emergencies. In this paper, an electrodeless biosensing detection chip for RNA virus medical detection is designed using quartz crystal microbalance technology and local surface plasmon resonance technology. The plasmonic resonance characteristic in the nanostructures of gold nanorods-quartz substrates with different parameters and the surface potential distribution of the quartz crystal microbalance sensing chip were studied by COMSOL finite element simulation software. The results show that the arrangement structure and spacing of gold nanorod dimers greatly affect the local surface plasmon resonance of nanorods, which in turn affects the detection results of biomolecules. Moreover, high concentrations of “hot spots” are distributed between both ends and the gap of the gold nanorod dimer, which reflects the strong hybridization of the multiple resonance modes of the nanoparticles. In addition, by simulating and calculating the surface potential distribution of the electrode area and non-electrode area of the biosensor chip, it was found that the biosensor chip with these two areas can enhance the piezoelectric effect of the quartz chip. Under the same simulation conditions, the biochip with a completely electrodeless structure showed a better sensing performance. The sensor chip combining QCM and LSPR can reduce the influence of the metal electrode on the quartz wafer to improve the sensitivity and accuracy of detection. Considering the significant influence of the gold nanorod dimer plasma resonance mode and the significant advantages of the electrodeless biosensor chip, an electrodeless biosensor combining these two technologies is proposed for RNA virus detection and screening, which has potential applications in biomolecular measurement and other related fields.

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A Polyphenol–Metal Network of Propyl Gallate Gallium/Hafnium Oxide on Polyimide Fibers for Facilitating Ligament–Bone Healing

Xie,

Zhang,

Zhou

et al. 2024

Adv. Fiber Mater.

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Dual-phase nanoplasmonic sensing platform for monitoring blood protein adsorption and its coagulation in vitro

Cited by 3 publications

References 33 publications

Deep Learning‐Assisted Molecular Classification and Concentration Prediction by Imaging of a Large‐Area Metasurface with Spatially Gradient Geometry

Deep Learning‐Assisted Molecular Classification and Concentration Prediction by Imaging of a Large‐Area Metasurface with Spatially Gradient Geometry

Research on Dual-Technology Fusion Biosensor Chip Based on RNA Virus Medical Detection

A Polyphenol–Metal Network of Propyl Gallate Gallium/Hafnium Oxide on Polyimide Fibers for Facilitating Ligament–Bone Healing

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