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Biosensors
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Advanced Surface Plasmon Resonance Sensor and Its Application
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Advanced Surface Plasmon Resonance Sensor and Its Application

A special issue of Biosensors (ISSN 2079-6374). This special issue belongs to the section "Optical and Photonic Biosensors".

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 13244

Special Issue Editors

Prof. Dr. Chengjun Huang

E-Mail Website
Guest Editor
e-Health Electronics Center, Institute of Microelectronics of the Chinese Academy of Sciences, Beijing 100029, China
Interests: MEMS, micro/nano sensors, actuators, and systems; microfluidics and lab on a chip, biomedical microdevices and systems; BT-IT; semiconductor chips for life science and healthcare
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Jian Ye

E-Mail Website
Guest Editor
School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
Interests: plasmonic nanomaterials and Raman spectroscopy for biomedical applications

Special Issue Information

Dear Colleagues,

The main topic of this Special Issue concerns a surface plasmon resonance (SPR) sensor for a specific chemical (or set of chemicals) and biomolecules analysis in different fields, which cause serious global concerns regarding healthcare, food quality, food safety and pollution. In this context, this Special Issue aims to gather original articles and reviews showing research advances, innovative applications, new challenges and future perspectives of SPR sensors in important areas, such as health, biomedicine, and environmental fields.

SPR sensor is one of the most advanced and unique optical transduction methods for the label-free and real-time detecting of biological species at a molecular level; it uses an optical approach to measure a change in the refractive index unit of target sensing media. The topics that can be explored for this Special Issue include SPR sensing with different couplers: optical prism, grating, optical fiber and optical waveguides. Additionally, localized SPR sensors and LSPR-enhanced Raman and fluoresecence sensors based on nanostructures can also be addressed. This Special Issue contains SPR sensors, which are capable of detecting changes in the resonant angle, wavelength and phase shift. Furthermore, novel SPR sensing techniques, e.g., surface plasmon resonance microscopy, which detects the discrete nature of molecules with a high sensitivity and high resolution, can be studied. In this Special Issue, innovative research on various new SPR sensors are welcome, which are achieved by improving their function with a combination of SPR technology and microelectronic technology, optical fiber technology, nanotechnology, electrochemistry, photoacoustic spectroscopy, solar thermal spectrometry, gene recombination technology, bio-film technology, bionic technology, etc.

Prof. Dr. Chengjun Huang
Prof. Dr. Jian Ye
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biosensors is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Kretschmann-based SPR sensor
  • fiber SPR sensor
  • optical waveguide SPR sensor
  • SPR microscopy
  • LSPR sensor
  • gas SPR sensor
  • micro-array sensors
  • advanced bio-marker for SPR sensor
  • surface-enhanced Raman scattering sensor
  • surface-enhanced fluorescence sensor
  • biomelecular interactions
  • virus detection

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Published Papers (4 papers)

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Research

14 pages, 3255 KiB  
Article
A Novel SPR Immunosensor Based on Dual Signal Amplification Strategy for Detection of SARS-CoV-2 Nucleocapsid Protein
by Lirui Fan, Bin Du, Fubin Pei, Wei Hu, Shasha Feng, Bing Liu, Zhaoyang Tong, Wenyuan Tan and Xihui Mu
Biosensors 2023, 13(5), 549; https://doi.org/10.3390/bios13050549 - 15 May 2023
Cited by 8 | Viewed by 2334
Abstract
Since the global outbreak of coronavirus disease 2019 (COVID-19), it has spread rapidly around the world. The nucleocapsid (N) protein is one of the most abundant SARS-CoV-2 proteins. Therefore, a sensitive and effective detection method for SARS-CoV-2 N protein is the focus of [...] Read more.
Since the global outbreak of coronavirus disease 2019 (COVID-19), it has spread rapidly around the world. The nucleocapsid (N) protein is one of the most abundant SARS-CoV-2 proteins. Therefore, a sensitive and effective detection method for SARS-CoV-2 N protein is the focus of research. Here, we developed a surface plasmon resonance (SPR) biosensor based on the dual signal-amplification strategy of Au@Ag@Au nanoparticles (NPs) and graphene oxide (GO). Additionally, a sandwich immunoassay was utilized to sensitively and efficiently detect SARS-CoV-2 N protein. On the one hand, Au@Ag@Au NPs have a high refractive index and the capability to electromagnetically couple with the plasma waves propagating on the surface of gold film, which are harnessed for amplifying the SPR response signal. On the other hand, GO, which has the large specific surface area and the abundant oxygen-containing functional groups, could provide unique light absorption bands that can enhance plasmonic coupling to further amplify the SPR response signal. The proposed biosensor could efficiently detect SARS-CoV-2 N protein for 15 min and the detection limit for SARS-CoV-2 N protein was 0.083 ng/mL, with a linear range of 0.1 ng/mL~1000 ng/mL. This novel method can meet the analytical requirements of artificial saliva simulated samples, and the developed biosensor had a good anti-interference capability. Full article
(This article belongs to the Special Issue Advanced Surface Plasmon Resonance Sensor and Its Application)
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16 pages, 4053 KiB  
Article
Real-Time Ellipsometric Surface Plasmon Resonance Sensor Using Polarization Camera May Provide the Ultimate Detection Limit
by Nipun Vashistha, Marwan J. Abuleil, Anand M. Shrivastav, Aabha Bajaj and Ibrahim Abdulhalim
Biosensors 2023, 13(2), 173; https://doi.org/10.3390/bios13020173 - 22 Jan 2023
Cited by 8 | Viewed by 3677
Abstract
Ellipsometric Surface Plasmon Resonance (SPR) sensors are known for their relatively simple optical configuration compared to interferometric and optical heterodyne phase interrogation techniques. However, most of the previously explored ellipsometric SPR sensors based on intensity measurements are limited by their real-time applications because [...] Read more.
Ellipsometric Surface Plasmon Resonance (SPR) sensors are known for their relatively simple optical configuration compared to interferometric and optical heterodyne phase interrogation techniques. However, most of the previously explored ellipsometric SPR sensors based on intensity measurements are limited by their real-time applications because phase or polarization shifts are conducted serially. Here we present an ellipsometric SPR sensor based on a Kretschmann–Raether (KR) diverging beam configuration and a pixelated microgrid polarization camera. The proposed methodology has the advantage of real-time and higher precision sensing applications. The short-term stability of the measurement using the ellipsometric parameters tanψ and cos(Δ) is found to be superior over direct SPR or intensity measurements, particularly with fluctuating sources such as laser diodes. Refractive index and dynamic change measurements in real-time are presented together with Bovine Serum Albumin (BSA)–anti-BSA antibody binding to demonstrate the potential of the developed sensor for biological sensing applications with a resolution of sub-nM and down to pM with additional optimization. The analysis shows that this approach may provide the ultimate detection limit for SPR sensors. Full article
(This article belongs to the Special Issue Advanced Surface Plasmon Resonance Sensor and Its Application)
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11 pages, 3038 KiB  
Article
Ingenious Fabrication of Ag-Filled Porous Anodic Alumina Films as Powerful SERS Substrates for Efficient Detection of Biological and Organic Molecules
by Chih-Yi Liu, Rahul Ram, Rahim Bakash Kolaru, Anindya Sundar Jana, Annada Sankar Sadhu, Cheng-Shane Chu, Yi-Nan Lin, Bhola Nath Pal, Shih-Hsin Chang and Sajal Biring
Biosensors 2022, 12(10), 807; https://doi.org/10.3390/bios12100807 - 29 Sep 2022
Cited by 14 | Viewed by 3261
Abstract
Surface-enhanced Raman scattering (SERS) has been widely used to effectively detect various biological and organic molecules. This detection method needs analytes adsorbed onto a specific metal nanostructure, e.g., Ag-nanoparticles. A substrate containing such a structure (called SERS substrate) is user-friendly for people implementing [...] Read more.
Surface-enhanced Raman scattering (SERS) has been widely used to effectively detect various biological and organic molecules. This detection method needs analytes adsorbed onto a specific metal nanostructure, e.g., Ag-nanoparticles. A substrate containing such a structure (called SERS substrate) is user-friendly for people implementing the adsorption and subsequent SERS detection. Here, we report on powerful SERS substrates based on efficient fabrication of Ag-filled anodic aluminum oxide (AAO) films. The films contain many nanopores with small as-grown inter-pore gap of 15 nm. The substrates are created by electrochemically depositing silver into nanopores without an additional pore widening process, which is usually needed for conventional two-step AAO fabrication. The created substrates contain well-separated Ag-nanoparticles with quite a small inter-particle gap and a high number density (2.5 × 1010 cm−2). We use one-step anodization together with omitting additional pore widening to improve the throughput of substrate fabrication. Such substrates provide a low concentration detection limit of 10−11 M and high SERS enhancement factor of 1 × 106 for rhodamine 6G (R6G). The effective detection of biological and organic molecules by the substrate is demonstrated with analytes of adenine, glucose, R6G, eosin Y, and methylene blue. These results allow us to take one step further toward the successful commercialization of AAO-based SERS substrates. Full article
(This article belongs to the Special Issue Advanced Surface Plasmon Resonance Sensor and Its Application)
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15 pages, 7263 KiB  
Article
HCTNet: A Hybrid ConvNet-Transformer Network for Retinal Optical Coherence Tomography Image Classification
by Zongqing Ma, Qiaoxue Xie, Pinxue Xie, Fan Fan, Xinxiao Gao and Jiang Zhu
Biosensors 2022, 12(7), 542; https://doi.org/10.3390/bios12070542 - 20 Jul 2022
Cited by 22 | Viewed by 3119
Abstract
Automatic and accurate optical coherence tomography (OCT) image classification is of great significance to computer-assisted diagnosis of retinal disease. In this study, we propose a hybrid ConvNet-Transformer network (HCTNet) and verify the feasibility of a Transformer-based method for retinal OCT image classification. The [...] Read more.
Automatic and accurate optical coherence tomography (OCT) image classification is of great significance to computer-assisted diagnosis of retinal disease. In this study, we propose a hybrid ConvNet-Transformer network (HCTNet) and verify the feasibility of a Transformer-based method for retinal OCT image classification. The HCTNet first utilizes a low-level feature extraction module based on the residual dense block to generate low-level features for facilitating the network training. Then, two parallel branches of the Transformer and the ConvNet are designed to exploit the global and local context of the OCT images. Finally, a feature fusion module based on an adaptive re-weighting mechanism is employed to combine the extracted global and local features for predicting the category of OCT images in the testing datasets. The HCTNet combines the advantage of the convolutional neural network in extracting local features and the advantage of the vision Transformer in establishing long-range dependencies. A verification on two public retinal OCT datasets shows that our HCTNet method achieves an overall accuracy of 91.56% and 86.18%, respectively, outperforming the pure ViT and several ConvNet-based classification methods. Full article
(This article belongs to the Special Issue Advanced Surface Plasmon Resonance Sensor and Its Application)
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