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Biosensors for Diagnostic Applications
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Biosensors for Diagnostic Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biosensors".

Deadline for manuscript submissions: closed (15 December 2023) | Viewed by 12417

Special Issue Editors

Dr. XiaoGang Lin

E-Mail Website
Guest Editor
College of Optoelectronic Engineering, Chongqing University, Chongqing 400030, China
Interests: biosensors; biophotoelectric sensing; precision measurement; point-of-care diagnostics
Dr. Cheng Cheng

E-Mail Website
Guest Editor
School of Engineering and Computer Science, Morehead State University, Morehead, KY 40351, USA
Interests: biosensors; wearable sensors; point-of-care diagnostics; microfluidics
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Mihaela Badea

E-Mail Website
Guest Editor
Faculty of Medicine, Research Centre for Fundamental Research and Prevention Strategies in Medicine, Transilvania University of Brasov, B-dul Eroilor nr 29, 500036 Brasov, Romania
Interests: bioanalytical methods; electrochemical (bio) sensors; biochemistry; antioxidants detection; telemedicine; plant food supplements
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Early diagnosis and treatment are the holy grail of the fight against any disease. Biosensor tests have recently been recognized as promising for early screening of various diseases, especially cancer.

This Special Issue aims to put together original research and review articles on recent biosensor advances, biosensor material, sensing interface design, biosensor interface stability solutions, applications, and new challenges in the field of disease diagnostics.

Potential topics include but are not limited to:

  • Functional materials for biosensors;
  • Biosensor interfaces;
  • Biosensor fabrication;
  • DNA biosensors;
  • Aptamer sensors;
  • Immunosensors;
  • Wearable biosensors;
  • in vitro and in vivo applications.

Papers presented in the frame of the international conference “New Trends on Sensing-Monitoring-Telediagnosis for Life Sciences”—NT SMT-LS 2022 (http://www.healthfoodenviron.unitbv.ro/2022/), September 8–10, 2022, Brasov, Romania will receive a special discount of 20% if the article is accepted by at least two independent reviewers of the journal. Authors whose papers were selected for the conference will be invited to submit extended versions of their original papers and contributions (a 50% extension of the contents of the conference paper is required).

Dr. XiaoGang Lin
Dr. Cheng Cheng
Prof. Dr. Mihaela Badea
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. Sensors is an international peer-reviewed open access semimonthly 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 2600 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.

Published Papers (6 papers)

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Research

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11 pages, 2306 KiB  
Article
ACEK Biosensor for the Minute-Scale Quantification of Breast Cancer ctDNA
by Ke Wang, Xiaogang Lin, Maoxiao Zhang, Mengjie Yang, Xiang Shi, Mingna Xie and Yang Luo
Sensors 2024, 24(2), 547; https://doi.org/10.3390/s24020547 - 15 Jan 2024
Viewed by 937
Abstract
Circulating tumor DNA (ctDNA) appears as a valuable liquid biopsy biomarker in the early diagnosis, treatment, and prognosis of cancer. Here, a biosensing method derived from the AC electrokinetics (ACEK) effect was constructed in this study for the simple, efficient, and rapid method [...] Read more.
Circulating tumor DNA (ctDNA) appears as a valuable liquid biopsy biomarker in the early diagnosis, treatment, and prognosis of cancer. Here, a biosensing method derived from the AC electrokinetics (ACEK) effect was constructed in this study for the simple, efficient, and rapid method of detection of ctDNA. In the proof-of-concept experiment, ctDNA from the PIK3CA E542K mutant in breast cancer was quantified by detecting a normalized capacitance change rate using a forked-finger gold electrode as the sensing electrode in combination with the ACEK effect. We compared two formats for the construction of the approach by employing varied immobilization strategies; one is to immobilize the DNA capture probe on the electrode surface by Au–S bonding, while the other immobilizes the probe on a self-assembled membrane on the electrode surface by amide bonding. Both formats demonstrated ultrafast detection speed by completing the ctDNA quantification within 1 min and a linear range of 10 fM–10 pM was observed. Meanwhile, the immobilization via the self-assembled membrane yielded improved stability, sensitivity, and specificity than its Au–S bonding counterpart. A detection limit of 1.94 fM was eventually achieved using the optimized approach. This research provides a label-free and minute-scale universal method for the detection of various malignant tumors. The ctDNA biosensors based on the ACEK effect improved according to the probe type or electrode structure and have potential applications in tumor drug efficacy prediction, drug resistance monitoring, screening of high-risk groups, differential diagnosis, monitoring of tiny residual lesions, and prognosis determination. Full article
(This article belongs to the Special Issue Biosensors for Diagnostic Applications)
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10 pages, 1230 KiB  
Article
An Array SPRi Biosensor for the Determination of Follicle-Stimulating Hormone in Blood Plasma
by Anna Sankiewicz, Beata Zelazowska-Rutkowska, Zenon Lukaszewski, Adam Hermanowicz and Ewa Gorodkiewicz
Sensors 2023, 23(24), 9686; https://doi.org/10.3390/s23249686 - 7 Dec 2023
Viewed by 818
Abstract
Follicle-stimulating hormone (FSH) regulates the development, growth, pubertal maturation and reproductive processes of the human body. The determination of serous FSH concentration is significant as an alternative to testicular biopsy in the case of boys suffering from cryptorchidism after orchidopexy, and as a [...] Read more.
Follicle-stimulating hormone (FSH) regulates the development, growth, pubertal maturation and reproductive processes of the human body. The determination of serous FSH concentration is significant as an alternative to testicular biopsy in the case of boys suffering from cryptorchidism after orchidopexy, and as a means of determining the menopausal stage in women. The aim of this investigation is to develop a specific array surface plasmon resonance imaging (SPRi) biosensor for the determination of FSH in body liquids such as blood plasma, obtaining sufficient sensitivity to determine FSH at levels characteristic for that hormone in blood plasma, without any signal enhancement. The biosensor consists of a mouse monoclonal anti-FSH antibody attached to the gold surface of a chip via a cysteamine linker. Its linear response range is from 0.08 mIU mL−1 (LOQ) to 20 mIU mL−1, and well covers most of the range of FSH activities found in blood without dilution. The precision of measurement is between 3.2% and 13.1% for model samples, and between 3.7% and 5.6% for spiked plasma samples. Recoveries are in the range from 94% to 108%. The biosensor has good selectivity, and is validated by comparison with ECLE, with good agreement of the results Full article
(This article belongs to the Special Issue Biosensors for Diagnostic Applications)
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13 pages, 624 KiB  
Article
Central Arterial Dynamic Evaluation from Peripheral Blood Pressure Waveforms Using CycleGAN: An In Silico Approach
by Nicolas Aguirre, Leandro J. Cymberknop, Edith Grall-Maës, Eugenia Ipar and Ricardo L. Armentano
Sensors 2023, 23(3), 1559; https://doi.org/10.3390/s23031559 - 1 Feb 2023
Viewed by 1549
Abstract
Arterial stiffness is a major condition related to many cardiovascular diseases. Traditional approaches in the assessment of arterial stiffness supported by machine learning techniques are limited to the pulse wave velocity (PWV) estimation based on pressure signals from the peripheral arteries. Nevertheless, arterial [...] Read more.
Arterial stiffness is a major condition related to many cardiovascular diseases. Traditional approaches in the assessment of arterial stiffness supported by machine learning techniques are limited to the pulse wave velocity (PWV) estimation based on pressure signals from the peripheral arteries. Nevertheless, arterial stiffness can be assessed based on the pressure–strain relationship by analyzing its hysteresis loop. In this work, the capacity of deep learning models based on generative adversarial networks (GANs) to transfer pressure signals from the peripheral arterial region to pressure and area signals located in the central arterial region is explored. The studied signals are from a public and validated virtual database. Compared to other works in which the assessment of arterial stiffness was performed via PWV, in the present work the pressure–strain hysteresis loop is reconstructed and evaluated in terms of classical machine learning metrics and clinical parameters. Least-square GAN (LSGAN) and Wasserstein GAN with gradient penalty (WGAN-GP) adversarial losses are compared, yielding better results with LSGAN. LSGAN mean ± standard deviation of error for pressure and area pulse waveforms are 0.8 ± 0.4 mmHg and 0.1 ± 0.1 cm2, respectively. Regarding the pressure–strain elastic modulus, it is achieved a mean absolute percentage error of 6.5 ± 5.1%. GAN-based deep learning models can recover the pressure–strain loop of central arteries while observing pressure signals from peripheral arteries. Full article
(This article belongs to the Special Issue Biosensors for Diagnostic Applications)
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13 pages, 3436 KiB  
Article
Detection of Diabetic Retinopathy Using Extracted 3D Features from OCT Images
by Mahmoud Elgafi, Ahmed Sharafeldeen, Ahmed Elnakib, Ahmed Elgarayhi, Norah S. Alghamdi, Mohammed Sallah and Ayman El-Baz
Sensors 2022, 22(20), 7833; https://doi.org/10.3390/s22207833 - 15 Oct 2022
Cited by 19 | Viewed by 2037
Abstract
Diabetic retinopathy (DR) is a major health problem that can lead to vision loss if not treated early. In this study, a three-step system for DR detection utilizing optical coherence tomography (OCT) is presented. First, the proposed system segments the retinal layers from [...] Read more.
Diabetic retinopathy (DR) is a major health problem that can lead to vision loss if not treated early. In this study, a three-step system for DR detection utilizing optical coherence tomography (OCT) is presented. First, the proposed system segments the retinal layers from the input OCT images. Second, 3D features are extracted from each retinal layer that include the first-order reflectivity and the 3D thickness of the individual OCT layers. Finally, backpropagation neural networks are used to classify OCT images. Experimental studies on 188 cases confirm the advantages of the proposed system over related methods, achieving an accuracy of 96.81%, using the leave-one-subject-out (LOSO) cross-validation. These outcomes show the potential of the suggested method for DR detection using OCT images. Full article
(This article belongs to the Special Issue Biosensors for Diagnostic Applications)
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Review

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24 pages, 3887 KiB  
Review
Emerging Methods in Biosensing of Immunoglobin G—A Review
by Tehmina Azam, Syed Hassan Bukhari, Usman Liaqat and Waheed Miran
Sensors 2023, 23(2), 676; https://doi.org/10.3390/s23020676 - 6 Jan 2023
Cited by 3 | Viewed by 2811
Abstract
Human antibodies are produced due to the activation of immune system components upon exposure to an external agent or antigen. Human antibody G, or immunoglobin G (IgG), accounts for 75% of total serum antibody content. IgG controls several infections by eradicating disease-causing pathogens [...] Read more.
Human antibodies are produced due to the activation of immune system components upon exposure to an external agent or antigen. Human antibody G, or immunoglobin G (IgG), accounts for 75% of total serum antibody content. IgG controls several infections by eradicating disease-causing pathogens from the body through complementary interactions with toxins. Additionally, IgG is an important diagnostic tool for certain pathological conditions, such as autoimmune hepatitis, hepatitis B virus (HBV), chickenpox and MMR (measles, mumps, and rubella), and coronavirus-induced disease 19 (COVID-19). As an important biomarker, IgG has sparked interest in conducting research to produce robust, sensitive, selective, and economical biosensors for its detection. To date, researchers have used different strategies and explored various materials from macro- to nanoscale to be used in IgG biosensing. In this review, emerging biosensors for IgG detection have been reviewed along with their detection limits, especially electrochemical biosensors that, when coupled with nanomaterials, can help to achieve the characteristics of a reliable IgG biosensor. Furthermore, this review can assist scientists in developing strategies for future research not only for IgG biosensors but also for the development of other biosensing systems for diverse targets. Full article
(This article belongs to the Special Issue Biosensors for Diagnostic Applications)
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24 pages, 4504 KiB  
Review
Aptamer-Based Technologies for Parasite Detection
by Noah Emerson Brosseau, Isabelle Vallée, Anne Mayer-Scholl, Momar Ndao and Grégory Karadjian
Sensors 2023, 23(2), 562; https://doi.org/10.3390/s23020562 - 4 Jan 2023
Cited by 6 | Viewed by 3471
Abstract
Centuries of scientific breakthroughs have brought us closer to understanding and managing the spread of parasitic diseases. Despite ongoing technological advancements in the detection, treatment, and control of parasitic illnesses, their effects on animal and human health remain a major concern worldwide. Aptamers [...] Read more.
Centuries of scientific breakthroughs have brought us closer to understanding and managing the spread of parasitic diseases. Despite ongoing technological advancements in the detection, treatment, and control of parasitic illnesses, their effects on animal and human health remain a major concern worldwide. Aptamers are single-stranded oligonucleotides whose unique three-dimensional structures enable them to interact with high specificity and affinity to a wide range of targets. In recent decades, aptamers have emerged as attractive alternatives to antibodies as therapeutic and diagnostic agents. Due to their superior stability, reusability, and modifiability, aptamers have proven to be effective bioreceptors for the detection of toxins, contaminants, biomarkers, whole cells, pathogens, and others. As such, they have been integrated into a variety of electrochemical, fluorescence, and optical biosensors to effectively detect whole parasites and their proteins. This review offers a summary of the various types of parasite-specific aptamer-based biosensors, their general mechanisms and their performance. Full article
(This article belongs to the Special Issue Biosensors for Diagnostic Applications)
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