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Biosensors
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High-Efficiency Surface-Enhanced Raman Scattering Biosensing
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High-Efficiency Surface-Enhanced Raman Scattering Biosensing

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

Deadline for manuscript submissions: 25 June 2024 | Viewed by 13491

Special Issue Editors

Dr. Giovanna Palermo

E-Mail Website
Guest Editor
1. Department of Physics, NLHT-Lab, University of Calabria, Via Ponte P. Bucci, Cubo 33C, 87036 Rende, Cosenza, Italy
2. CNR NANOTEC-Institute of Nanotechnology, Via Ponte P. Bucci, Cubo 33C, 87036 Rende, Cosenza, Italy
Interests: biosensing; nanostructures; metasurface; metamaterials; plasmonics; modeling and characterization of biosensors; nanomaterial-based biosensors
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Giuseppe Strangi

E-Mail Website
Guest Editor
1. Department of Physics, Case Western Reserve University, 10600 Euclid Avenue, Cleveland, OH 44106, USA
2. Department of Physics, University of Calabria, 87036 Rende, CS, Italy
Interests: soft-condensed matter; nanoscience; biosensing; spectroscopy; nonlinear optics; nanophotonics

Special Issue Information

Dear Colleagues,

The development of biosensors with high sensitivity and selectively is increasingly becoming crucial in medical and clinical research for detecting extremely low concentrations of low-molecular-weight molecules relevant to diseases such as cancer and infectious diseases. To radically improve early diagnosis, the progression of the disease and the evaluation of the efficacy of drug therapy, it is necessary to have biosensors characterized by a high level of sensitivity, specificity and accuracy for the recognition of both nucleic acids and proteins. A strong contribution in this context is represented by the development of high-efficiency surface-enhanced Raman scattering (SERS) biosensors. This Special Issue aims to present the most recent studies on the progress achieved in the development, design, modeling, implementation and characterization of high-efficiency SERS biosensors.

Dr. Giovanna Palermo
Prof. Dr. Giuseppe Strangi
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 2700 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

  • biosensing
  • SERS
  • Raman
  • metasurface
  • metamaterials
  • plasmonics
  • electromagnetic enhancement

Published Papers (6 papers)

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Research

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13 pages, 5145 KiB  
Article
The Label-Free Detection and Identification of SARS-CoV-2 Using Surface-Enhanced Raman Spectroscopy and Principal Component Analysis
by Lu Zhou, Ambra Vestri, Valentina Marchesano, Massimo Rippa, Domenico Sagnelli, Gerardo Picazio, Giovanna Fusco, Jiaguang Han, Jun Zhou and Lucia Petti
Biosensors 2023, 13(12), 1014; https://doi.org/10.3390/bios13121014 - 05 Dec 2023
Cited by 2 | Viewed by 1527
Abstract
The World Health Organization (WHO) declared in a May 2023 announcement that the COVID-19 illness is no longer categorized as a Public Health Emergency of International Concern (PHEIC); nevertheless, it is still considered an actual threat to world health, social welfare and economic [...] Read more.
The World Health Organization (WHO) declared in a May 2023 announcement that the COVID-19 illness is no longer categorized as a Public Health Emergency of International Concern (PHEIC); nevertheless, it is still considered an actual threat to world health, social welfare and economic stability. Consequently, the development of a convenient, reliable and affordable approach for detecting and identifying SARS-CoV-2 and its emerging new variants is crucial. The fingerprint and signal amplification characteristics of surface-enhanced Raman spectroscopy (SERS) could serve as an assay scheme for SARS-CoV-2. Here, we report a machine learning-based label-free SERS technique for the rapid and accurate detection and identification of SARS-CoV-2. The SERS spectra collected from samples of four types of coronaviruses on gold nanoparticles film, fabricated using a Langmuir–Blodgett self-assembly, can provide more spectroscopic signatures of the viruses and exhibit low limits of detection (<100 TCID50/mL or even <10 TCID50/mL). Furthermore, the key Raman bands of the SERS spectra were systematically captured by principal component analysis (PCA), which effectively distinguished SARS-CoV-2 and its variant from other coronaviruses. These results demonstrate that the combined use of SERS technology and PCA analysis has great potential for the rapid analysis and discrimination of multiple viruses and even newly emerging viruses without the need for a virus-specific probe. Full article
(This article belongs to the Special Issue High-Efficiency Surface-Enhanced Raman Scattering Biosensing)
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11 pages, 4584 KiB  
Article
Effect of the Combination of Gold Nanoparticles and Polyelectrolyte Layers on SERS Measurements
by Antonello Nucera, Rossella Grillo, Carmen Rizzuto, Riccardo Cristoforo Barberi, Marco Castriota, Thomas Bürgi, Roberto Caputo and Giovanna Palermo
Biosensors 2022, 12(10), 895; https://doi.org/10.3390/bios12100895 - 19 Oct 2022
Cited by 4 | Viewed by 1605
Abstract
In this study, polyelectrolyte (PE) layers are deposited on substrates made by glass covered with an array of gold nanoparticles (GNPs). In particular, the samples studied have 0 PE layers (GGPE0), 3 PE layers (GGPE3), 11 PE layers (GGPE [...] Read more.
In this study, polyelectrolyte (PE) layers are deposited on substrates made by glass covered with an array of gold nanoparticles (GNPs). In particular, the samples studied have 0 PE layers (GGPE0), 3 PE layers (GGPE3), 11 PE layers (GGPE11), and 21 PE layers (GGPE21). All samples have been studied by micro-Raman spectroscopy. An acetic acid solution (10% v/v) has been used as a standard solution in order to investigate the SERS effect induced by different numbers of PE layers in each sample. The Surface Enhancement Raman Spectroscopy (SERS) effect correlating to the number of PE layers deposited on the samples has been shown. This effect is explained in terms of an increase in the interaction between the photon of the laser source and the plasmonic band of the GNPs due to a change of the permittivity of the surrounding medium around the GNPs. The trends of the ratios of the intensities of the Raman bands of the acetic acid solution (acetic acid and water molecules) on the band at 1098 cm−1 ascribed to the substrates increase, and the number of PE layers increases. Full article
(This article belongs to the Special Issue High-Efficiency Surface-Enhanced Raman Scattering Biosensing)
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12 pages, 5210 KiB  
Communication
Detection of 3,4-Methylene Dioxy Amphetamine in Urine by Magnetically Improved Surface-Enhanced Raman Scattering Sensing Strategy
by Yue Wang, Xinyan Teng, Jiaying Cao, Yilei Fan, Xinling Liu, Xiaoyu Guo, Yu Xu, Ying Wen and Haifeng Yang
Biosensors 2022, 12(9), 711; https://doi.org/10.3390/bios12090711 - 02 Sep 2022
Cited by 2 | Viewed by 1824
Abstract
Abuse of illicit drugs has become a major issue of global concern. As a synthetic amphetamine analog, 3,4-Methylene Dioxy Amphetamine (MDA) causes serotonergic neurotoxicity, posing a serious risk to human health. In this work, a two-dimensional substrate of ITO/Au is fabricated by transferring [...] Read more.
Abuse of illicit drugs has become a major issue of global concern. As a synthetic amphetamine analog, 3,4-Methylene Dioxy Amphetamine (MDA) causes serotonergic neurotoxicity, posing a serious risk to human health. In this work, a two-dimensional substrate of ITO/Au is fabricated by transferring Au nanoparticle film onto indium–tin oxide glass (ITO). By magnetic inducing assembly of Fe3O4@Au onto ITO/Au, a sandwich-based, surface-enhanced Raman scattering (SERS) detection strategy is designed. Through the use of an external magnet, the MDA is retained in the region of hot spots formed between Fe3O4@Au and ITO/Au; as a result, the SERS sensitivity for MDA is superior compared to other methods, lowering the limit of detection (LOD) to 0.0685 ng/mL and attaining a corresponding linear dynamic detection range of 5–105 ng/mL. As an actual application, this magnetically improved SERS sensing strategy is successfully applied to distinguish MDA in urine at trace level, which is beneficial to clinical and forensic monitors. Full article
(This article belongs to the Special Issue High-Efficiency Surface-Enhanced Raman Scattering Biosensing)
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13 pages, 2658 KiB  
Article
A Machine Learning Framework for Detecting COVID-19 Infection Using Surface-Enhanced Raman Scattering
by Eloghosa Ikponmwoba, Okezzi Ukorigho, Parikshit Moitra, Dipanjan Pan, Manas Ranjan Gartia and Opeoluwa Owoyele
Biosensors 2022, 12(8), 589; https://doi.org/10.3390/bios12080589 - 02 Aug 2022
Cited by 6 | Viewed by 2409
Abstract
In this study, we explored machine learning approaches for predictive diagnosis using surface-enhanced Raman scattering (SERS), applied to the detection of COVID-19 infection in biological samples. To do this, we utilized SERS data collected from 20 patients at the University of Maryland Baltimore [...] Read more.
In this study, we explored machine learning approaches for predictive diagnosis using surface-enhanced Raman scattering (SERS), applied to the detection of COVID-19 infection in biological samples. To do this, we utilized SERS data collected from 20 patients at the University of Maryland Baltimore School of Medicine. As a preprocessing step, the positive-negative labels are obtained using Polymerase Chain Reaction (PCR) testing. First, we compared the performance of linear and nonlinear dimensionality techniques for projecting the high-dimensional Raman spectra to a low-dimensional space where a smaller number of variables defines each sample. The appropriate number of reduced features used was obtained by comparing the mean accuracy from a 10-fold cross-validation. Finally, we employed Gaussian process (GP) classification, a probabilistic machine learning approach, to correctly predict the occurrence of a negative or positive sample as a function of the low-dimensional space variables. As opposed to providing rigid class labels, the GP classifier provides a probability (ranging from zero to one) that a given sample is positive or negative. In practice, the proposed framework can be used to provide high-throughput rapid testing, and a follow-up PCR can be used for confirmation in cases where the model’s uncertainty is unacceptably high. Full article
(This article belongs to the Special Issue High-Efficiency Surface-Enhanced Raman Scattering Biosensing)
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14 pages, 4384 KiB  
Article
Ultra-Sensitive, Rapid and On-Site Sensing Harmful Ingredients Used in Aquaculture with Magnetic Fluid SERS
by Meizhen Zhang, Jingru Liao, Xianming Kong, Qian Yu, Miao Zhang and Alan X. Wang
Biosensors 2022, 12(3), 169; https://doi.org/10.3390/bios12030169 - 09 Mar 2022
Cited by 5 | Viewed by 2713
Abstract
The integration of surface-enhanced Raman scattering (SERS) spectroscopy with magnetic fluid provides significant utility in point-of-care (POC) testing applications. Bifunctional magnetic–plasmonic composites have been widely employed as SERS substrates. In this study, a simple and cost-effective approach was developed to synthesize magnetic–plasmonic SERS [...] Read more.
The integration of surface-enhanced Raman scattering (SERS) spectroscopy with magnetic fluid provides significant utility in point-of-care (POC) testing applications. Bifunctional magnetic–plasmonic composites have been widely employed as SERS substrates. In this study, a simple and cost-effective approach was developed to synthesize magnetic–plasmonic SERS substrates by decorating silver nanoparticles onto magnetic Fe3O4 nanoparticles (AgMNPs), which function both as SERS-active substrates and magnetic fluid particles. The strong magnetic responsivity from AgMNPs can isolate, concentrate, and detect target analytes from the irregular surface of fish skin rapidly. We fabricate a microfluid chip with three sample reservoirs that confine AgMNPs into ever smaller volumes under an applied magnetic field, which enhances the SERS signal and improves the detection limit by two orders of magnitude. The magnetic fluid POC sensor successfully detected malachite green from fish with excellent selectivity and high sensitivity down to the picomolar level. This work achieves a label-free, non-destructive optical sensing approach with promising potential for the detection of various harmful ingredients in food or the environment. Full article
(This article belongs to the Special Issue High-Efficiency Surface-Enhanced Raman Scattering Biosensing)
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Review

Jump to: Research

21 pages, 4267 KiB  
Review
Recent Progress in the Application of Metal Organic Frameworks in Surface-Enhanced Raman Scattering Detection
by Haojia Qin, Shuai Zhao, Huaping Gong, Zhi Yu, Qiang Chen, Pei Liang and De Zhang
Biosensors 2023, 13(4), 479; https://doi.org/10.3390/bios13040479 - 16 Apr 2023
Cited by 3 | Viewed by 2240
Abstract
Metal–organic framework (MOF) compounds are centered on metal ions or metal ion clusters, forming lattices with a highly ordered periodic porous network structure by connecting organic ligands. As MOFs have the advantages of high porosity, large specific surface area, controllable pore size, etc., [...] Read more.
Metal–organic framework (MOF) compounds are centered on metal ions or metal ion clusters, forming lattices with a highly ordered periodic porous network structure by connecting organic ligands. As MOFs have the advantages of high porosity, large specific surface area, controllable pore size, etc., they are widely used in gas storage, catalysis, adsorption, separation and other fields. SERS substrate based on MOFs can not only improve the sensitivity of SERS analysis but also solve the problem of easy aggregation of substrate nanoparticles. By combining MOFs with SERS, SERS performance is further improved, and tremendous research progress has been made in recent years. In this review, three methods of preparing MOF-based SERS substrates are introduced, and the latest applications of MOF-based SERS substrates in biosensors, the environment, gases and medical treatments are discussed. Finally, the current status and prospects of MOF-based SERS analysis are summarized. Full article
(This article belongs to the Special Issue High-Efficiency Surface-Enhanced Raman Scattering Biosensing)
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