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Emerging Applications of Label-Free Optical Biosensors

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

Deadline for manuscript submissions: 30 June 2024 | Viewed by 12715

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Special Issue Editors

Dr. Shuo Chen

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Guest Editor

College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
Interests: biomedical optical spectrosocopy; optical biosensors; raman imaging; computational optical sensing and imaging

Prof. Dr. Shangyuan Feng

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Guest Editor

Key Laboratory of OptoElectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory for Photonics Technology, Fujian Normal University, Fuzhou 350007, China
Interests: biophotonics; raman scattering; optical biosensors

Dr. Caigang Zhu

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Guest Editor

The F. Joseph Halcomb III, M.D. Department of Biomedical Engineering, University of Kentucky, 143 Graham Avenue, Lexington, KY 40506-0108, USA
Interests: optical spectroscopy; optical biosensors; optical microscopy; cancer metabolism
Special Issues, Collections and Topics in MDPI journals

Dr. Rongkang Gao

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Guest Editor

Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
Interests: optical imaging; optical biosensors; photoacoustic imaging

Special Issue Information

Dear Colleagues,

Label-free optical biosensors are a powerful tool for detecting and quantifying specific biomolecular compounds, without additional labeling or altering target biomolecules. Its distinctive advantages in terms of simplicity and rapidity of the measurement procedure have promoted its vast applications, covering biology, health care, pharmacy, food safety, agriculture and environmental monitoring. In the recent decades, there has been a large effort aiming at the development of reliable label-free optical biosensors with good performances (e.g. high precision, good stability, cost-effectiveness, high sensitivity and specificity), and great progress has been made in this research field to fulfill the growing demand on label-free optical biosensors.

This Special Issue aims to highlight the emerging applications of label-free optical biosensors, covering biological, clinical, environmental, agricultural, industrial and other related applications. All submissions with the topics related to recent and crucial insights into improvements of label-free optical biosensors, including but not limited to sensing theory, sensing materials, optical sensing system, optical signal processing and their applications, are encouraged and welcomed.

Dr. Shuo Chen
Prof. Dr. Shangyuan Feng
Dr. Caigang Zhu
Dr. Rongkang Gao
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

optical biosensors
label-free
surface plasmon resonance
optofluidics
spectroscopy
optical fiber
point-of-care devices
machine learning
diagnosis and prognosis
quality assessment and monitoring

Published Papers (5 papers)

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Research

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12 pages, 2102 KiB

Open AccessArticle

Deep Learning-Based Culture-Free Bacteria Detection in Urine Using Large-Volume Microscopy

by Rafael Iriya, Brandyn Braswell, Manni Mo, Fenni Zhang, Shelley E. Haydel and Shaopeng Wang

Biosensors 2024, 14(2), 89; https://doi.org/10.3390/bios14020089 - 5 Feb 2024

Viewed by 1437

Abstract

Bacterial infections, increasingly resistant to common antibiotics, pose a global health challenge. Traditional diagnostics often depend on slow cell culturing, leading to empirical treatments that accelerate antibiotic resistance. We present a novel large-volume microscopy (LVM) system for rapid, point-of-care bacterial detection. This system, using low magnification (1–2×), visualizes sufficient sample volumes, eliminating the need for culture-based enrichment. Employing deep neural networks, our model demonstrates superior accuracy in detecting uropathogenic Escherichia coli compared to traditional machine learning methods. Future endeavors will focus on enriching our datasets with mixed samples and a broader spectrum of uropathogens, aiming to extend the applicability of our model to clinical samples. Full article

(This article belongs to the Special Issue Emerging Applications of Label-Free Optical Biosensors)

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15 pages, 2865 KiB

Open AccessArticle

Polarized Micro-Raman Spectroscopy and 2D Convolutional Neural Network Applied to Structural Analysis and Discrimination of Breast Cancer

by Linwei Shang, Jinlan Tang, Jinjin Wu, Hui Shang, Xing Huang, Yilin Bao, Zhibing Xu, Huijie Wang and Jianhua Yin

Biosensors 2023, 13(1), 65; https://doi.org/10.3390/bios13010065 - 30 Dec 2022

Cited by 2 | Viewed by 2116

Abstract

Raman spectroscopy has been efficiently used to recognize breast cancer tissue by detecting the characteristic changes in tissue composition in cancerization. In addition to chemical composition, the change in bio-structure may be easily obtained via polarized micro-Raman spectroscopy, aiding in identifying the cancerization process and diagnosis. In this study, a polarized Raman spectral technique is employed to obtain rich structural features and, combined with deep learning technology, to achieve discrimination of breast cancer tissue. The results reconfirm that the orientation of collagen fibers changes from parallel to vertical during breast cancerization, and there are significant structural differences between cancerous and normal tissues, which is consistent with previous reports. Optical anisotropy of collagen fibers weakens in cancer tissue, which is closely related with the tumor’s progression. To distinguish breast cancer tissue, a discrimination model is established based on a two-dimensional convolutional neural network (2D-CNN), where the input is a matrix containing the Raman spectra acquired at a set of linear polarization angles varying from 0° to 360°. As a result, an average discrimination accuracy of 96.01% for test samples is achieved, better than that of the KNN classifier and 1D-CNN that are based on non-polarized Raman spectra. This study implies that polarized Raman spectroscopy combined with 2D-CNN can effectively detect changes in the structure and components of tissues, innovatively improving the identification and automatic diagnosis of breast cancer with label-free probing and analysis. Full article

(This article belongs to the Special Issue Emerging Applications of Label-Free Optical Biosensors)

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11 pages, 1902 KiB

Open AccessArticle

Micro-Raman Analysis of Sperm Cells on Glass Slide: Potential Label-Free Assessment of Sperm DNA toward Clinical Applications

by Shengrong Du, Qun Zhang, Haohao Guan, Guannan Chen, Sisi Wang, Yan Sun, Yuling Li, Rong Chen, Youwu He and Zufang Huang

Biosensors 2022, 12(11), 1051; https://doi.org/10.3390/bios12111051 - 21 Nov 2022

Cited by 1 | Viewed by 1762

Abstract

Routine assessment of sperm DNA integrity involves the time-consuming and complex process of staining sperm chromatin. Here, we report a Raman spectroscopy method combined with extended multiplicative signal correction (EMSC) for the extraction of characteristic fingerprints of DNA-intact and DNA-damaged sperm cells directly on glass slides. Raman results of sperm cell DNA integrity on glass substrates were validated one-to-one with clinical sperm cell staining. Although the overall Raman spectral pattern showed considerable similarity between DNA-damaged and DNA-intact sperm cells, differences in specific Raman spectral responses were observed. We then employed and compared multivariate statistical analysis based on principal component analysis-linear discriminant analysis (PCA-LDA) and partial least-squares-discriminant analysis (PLS-DA), and the classifications were validated by leave-one-out-cross-validation (LOOCV) and k-fold cross-validation methods. In comparison, the PLS-DA model showed relatively better results in terms of diagnostic sensitivity, specificity, and the classification rate between the sperm DNA damaged group and the DNA intact group. Our results demonstrate the potential of Raman based label-free DNA assessment of sperm cell on glass substrates as a simple method toward clinical applications. Full article

(This article belongs to the Special Issue Emerging Applications of Label-Free Optical Biosensors)

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Review

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38 pages, 7385 KiB

Open AccessReview

Molecular Fingerprint Detection Using Raman and Infrared Spectroscopy Technologies for Cancer Detection: A Progress Review

by Shuyan Zhang, Yi Qi, Sonia Peng Hwee Tan, Renzhe Bi and Malini Olivo

Biosensors 2023, 13(5), 557; https://doi.org/10.3390/bios13050557 - 18 May 2023

Cited by 14 | Viewed by 3512

Abstract

Molecular vibrations play a crucial role in physical chemistry and biochemistry, and Raman and infrared spectroscopy are the two most used techniques for vibrational spectroscopy. These techniques provide unique fingerprints of the molecules in a sample, which can be used to identify the chemical bonds, functional groups, and structures of the molecules. In this review article, recent research and development activities for molecular fingerprint detection using Raman and infrared spectroscopy are discussed, with a focus on identifying specific biomolecules and studying the chemical composition of biological samples for cancer diagnosis applications. The working principle and instrumentation of each technique are also discussed for a better understanding of the analytical versatility of vibrational spectroscopy. Raman spectroscopy is an invaluable tool for studying molecules and their interactions, and its use is likely to continue to grow in the future. Research has demonstrated that Raman spectroscopy is capable of accurately diagnosing various types of cancer, making it a valuable alternative to traditional diagnostic methods such as endoscopy. Infrared spectroscopy can provide complementary information to Raman spectroscopy and detect a wide range of biomolecules at low concentrations, even in complex biological samples. The article concludes with a comparison of the techniques and insights into future directions. Full article

(This article belongs to the Special Issue Emerging Applications of Label-Free Optical Biosensors)

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27 pages, 6797 KiB

Open AccessEditor’s ChoiceReview

Applications of Optical Fiber in Label-Free Biosensors and Bioimaging: A Review

by Baocheng Li, Ruochong Zhang, Renzhe Bi and Malini Olivo

Biosensors 2023, 13(1), 64; https://doi.org/10.3390/bios13010064 - 30 Dec 2022

Cited by 7 | Viewed by 2644

Abstract

Biosensing and bioimaging are essential in understanding biological and pathological processes in a living system, for example, in detecting and understanding certain diseases. Optical fiber has made remarkable contributions to the biosensing and bioimaging areas due to its unique advantages of compact size, immunity to electromagnetic interference, biocompatibility, fast response, etc. This review paper will present an overview of seven common types of optical fiber biosensors and optical fiber-based ultrasound detection in photoacoustic imaging (PAI) and the applications of these technologies in biosensing and bioimaging areas. Of course, there are many types of optical fiber biosensors. Still, this paper will review the most common ones: optical fiber grating, surface plasmon resonance, Sagnac interferometer, Mach–Zehnder interferometer, Michelson interferometer, Fabry–Perot Interferometer, lossy mode resonance, and surface-enhanced Raman scattering. Furthermore, different optical fiber techniques for detecting ultrasound in PAI are summarized. Finally, the main challenges and future development direction are briefly discussed. Full article

(This article belongs to the Special Issue Emerging Applications of Label-Free Optical Biosensors)

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