Biosensing Advances in Lateral Flow Assays (LFA)

A special issue of Biosensors (ISSN 2079-6374). This special issue belongs to the section "Biosensor Materials".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 2927

Special Issue Editor


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Guest Editor

Special Issue Information

Dear Colleagues,

As low-cost, simple, rapid, and portable detection devices, lateral flow assays (LFAs) are popular in biomedicine, agriculture, food, and environmental sciences for detecting the target analyte(s) in complex mixtures. Perhaps the most commonly used LFA is the single-step test to detect hCG in urine. The recent COVID-19 pandemic has resulted in considerable developments in LFAs for home testing, small ambulatory care settings, remote areas, etc.  However, the improvement and further development of established LFA technologies are required to enhance detection sensitivity and selectivity.  Ongoing research is needed to address the three key weaknesses of LFAs; therefore, this SI calls for papers (research or critical review) that address key challenges and opportunities to advance the development of LFAs. The SI inspires papers that cover the following topics:

Novel recognition molecules—Beyond antibodies and nucleic acids, this Special Issue is interested in other recognition molecules, e.g., molecular imprinting polymers.

Improved detection schemes—To date, the detection format of several commercial LFAs is still based on colloidal gold as a label because of its intense color for visualization. However, the detection sensitivity is still insufficient for the earlier detection of some cancer biomarkers or viral infections. The SI is interested in other more sensitive detection schemes based on fluorescent dyes, magnetic or paramagnetic components, and nanomaterials, e.g., quantum dots, thermal contrast, and laser- or light-emitting diodes (LEDs). Of interest is the use of latex, which can be produced in multiple colors for multiplex assays to discriminate numerous detection lines.

LFA sensitivity can also be augmented by smart readers, including smartphones that can differentiate slight signal alterations through non-specific binding and amplify the detection sensitivity significantly over conventional visualization.

Although the detection sensitivity of LFAs can be increased by the extraction/preconcentration of the target analyte, the added step requires several washing cycles and is more prone to error. Thus, this user-unfriendly method is not considered in this SI. 

Multiple assays—LFAs that can test multiple analytes simultaneously under the same conditions. The device in an array format has test lines for different analytes. Multiplexing is important for the analysis of different pathogens, viruses, antigens/antibodies, and pollutants in biological and environmental samples. 

Prof. Dr. John H. T. Luong
Guest Editor

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Keywords

  • antibody
  • nucleic acid
  • molecular imprinted polymer
  • point-of-care testing
  • multiplexed assay

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Published Papers (2 papers)

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Research

19 pages, 1818 KiB  
Article
Enhancing Sensitivity of Point-of-Care Thyroid Diagnosis via Computational Analysis of Lateral Flow Assay Images Using Novel Textural Features and Hybrid-AI Models
by Towfeeq Fairooz, Sara E. McNamee, Dewar Finlay, Kok Yew Ng and James McLaughlin
Biosensors 2024, 14(12), 611; https://doi.org/10.3390/bios14120611 - 13 Dec 2024
Viewed by 1137
Abstract
Lateral flow assays are widely used in point-of-care diagnostics but face challenges in sensitivity and accuracy when detecting low analyte concentrations, such as thyroid-stimulating hormone biomarkers. This study aims to enhance assay performance by leveraging textural features and hybrid artificial intelligence models. A [...] Read more.
Lateral flow assays are widely used in point-of-care diagnostics but face challenges in sensitivity and accuracy when detecting low analyte concentrations, such as thyroid-stimulating hormone biomarkers. This study aims to enhance assay performance by leveraging textural features and hybrid artificial intelligence models. A modified Gray-Level Co-occurrence Matrix, termed the Averaged Horizontal Multiple Offsets Gray-Level Co-occurrence Matrix, was utilised to compute the textural features of the biosensor assay images. Significant textural features were selected for further analysis. A deep learning Convolutional Neural Network model was employed to extract features from these textural features. Both traditional machine learning models and hybrid artificial intelligence models, which combine Convolutional Neural Network features with traditional algorithms, were used to categorise these textural features based on the thyroid-stimulating hormone concentration levels. The proposed method achieved accuracy levels exceeding 95%. This pioneering study highlights the utility of textural aspects of assay images for accurate predictive disease modelling, offering promising advancements in diagnostics and management within biomedical research. Full article
(This article belongs to the Special Issue Biosensing Advances in Lateral Flow Assays (LFA))
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13 pages, 1683 KiB  
Article
Enhanced Analytical Performance in CYFRA 21-1 Detection Using Lateral Flow Assay with Magnetic Bioconjugates: Integration and Comparison of Magnetic and Optical Registration
by Artemiy M. Skirda, Alexey V. Orlov, Juri A. Malkerov, Sergey L. Znoyko, Alexandra S. Rakitina and Petr I. Nikitin
Biosensors 2024, 14(12), 607; https://doi.org/10.3390/bios14120607 - 11 Dec 2024
Viewed by 1404
Abstract
A novel approach to developing lateral flow assays (LFAs) for the detection of CYFRA 21-1 (cytokeratin 19 fragment, a molecular biomarker for epithelial-origin cancers) is proposed. Magnetic bioconjugates (MBCs) were employed in combination with advanced optical and magnetic tools to optimize assay conditions. [...] Read more.
A novel approach to developing lateral flow assays (LFAs) for the detection of CYFRA 21-1 (cytokeratin 19 fragment, a molecular biomarker for epithelial-origin cancers) is proposed. Magnetic bioconjugates (MBCs) were employed in combination with advanced optical and magnetic tools to optimize assay conditions. The approach integrates such techniques as label-free spectral-phase interferometry, colorimetric detection, and ultrasensitive magnetometry using the magnetic particle quantification (MPQ) technique. For the first time in LFA applications, the MPQ-based and colorimetry-based detection methods were compared side by side, and superior analytical performance was demonstrated. The limit of detection (LOD) of 0.9 pg/mL was achieved using MPQ, and 2.9 pg/mL with optical detection. This study has demonstrated that MPQ provides elimination of signal saturation, higher sensitivity (slope of the calibration curve), and a 19-fold wider dynamic range of detected signals. Both optical and magnetic detection results are comparable to the best laboratory-based tests with the added benefits of a 20-min assay duration and the LFA format convenience. The assay effectiveness was validated in human serum and artificial saliva, and high recovery rates were observed. The proposed approach offers rapid and reliable detection of molecular biomarkers and holds significant potential for point-of-care diagnostics, particularly in resource-limited settings. Full article
(This article belongs to the Special Issue Biosensing Advances in Lateral Flow Assays (LFA))
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