Search Results (11)

From acute to chronic hepatitis, cirrhosis, and hepatocellular cancer, hepatitis B infection causes a broad spectrum of liver diseases. Molecular and serological tests have been used to diagnose hepatitis B-related illnesses. Due to technology limitations, it is challenging to identify hepatitis B infection cases at an early stage, particularly in a low- and middle-income country with constrained resources. Generally, the gold-standard methods to detect hepatitis B virus (HBV) infection requires dedicated personnel, bulky, expensive equipment and reagents, and long processing times which delay the diagnosis of HBV. Thus, lateral flow assay (LFA), which is inexpensive, straightforward, portable, and operates reliably, has dominated point-of-care diagnostics. LFA consists of four parts: a sample pad where samples are dropped; a conjugate pad where labeled tags and biomarker components are combined; a nitrocellulose membrane with test and control lines for target DNA-probe DNA hybridization or antigen-antibody interaction; and a wicking pad where waste is stored. By modifying the pre-treatment during the sample preparation process or enhancing the signal of the biomarker probes on the membrane pad, the accuracy of the LFA for qualitative and quantitative analysis can be improved. In this review, we assembled the most recent developments in LFA technologies for the progress of hepatitis B infection detection. Prospects for ongoing development in this area are also covered. Full article

The illegal use of β-adrenergic agonists during livestock growth poses a threat to public health; the long-term intake of this medication can cause serious physiological side effects and even death. Therefore, rapid detection methods for β-adrenergic agonist residues on-site are required. Traditional detection methods such as liquid chromatography have limitations in terms of expensive instruments and complex operations. In contrast, paper methods are low cost, ubiquitous, and portable, which has led to them becoming the preferred detection method in recent years. Various paper-based fluidic devices have been developed to detect β-adrenergic agonist residues, including lateral flow immunoassays (LFAs) and microfluidic paper-based analytical devices (μPADs). In this review, the application of LFAs for the detection of β-agonists is summarized comprehensively, focusing on the latest advances in novel labeling and detection strategies. The use of μPADs as an analytical platform has attracted interest over the past decade due to their unique advantages and application for detecting β-adrenergic agonists, which are introduced here. Vertical flow immunoassays are also discussed for their shorter assay time and stronger multiplexing capabilities compared with LFAs. Furthermore, the development direction and prospects for the commercialization of paper-based devices are considered, shedding light on the development of point-of-care testing devices for β-adrenergic agonist residue detection. Full article

Vertical flow assays (VFAs) or flow-through assays have emerged as an alternate type of paper-based assay due to their faster detection time, larger sample volume capacity, and significantly higher multiplexing capabilities. They have been successfully employed to detect several different targets (polysaccharides, protein, and nucleic acids), although in a limited number of samples (serum, whole blood, plasma) compared to the more commonly known lateral flow assays (LFAs). The operation of a VFA relies mainly on gravity, coupled with capillary action or external force to help the sample flow through layers of stacked pads. With recent developments in this field, multiple layers of pads and signal readers have been optimized for more user-friendly operation, and VFAs have achieved a lower limit of detection for various analytes than the gold-standard methods. Thus, compared to the more widely used LFA, the VFA demonstrates certain advantages and is becoming an increasingly popular platform for obtaining qualitative and quantitative results in low-resource settings. Considering the wide application of gold nanoparticles (GNPs) in VFAs, we will mostly discuss (1) the design of GNP-based VFA along with its associated advantages/disadvantages, (2) fabrication and optimization of GNP-based VFAs for applications, and (3) the future outlook of flow-based assays for point-of-care testing (POCT) diagnostics. Full article

Paper-based analytical devices (PADs), including lateral flow assays (LFAs), dipstick assays and microfluidic PADs (μPADs), have a great impact on the healthcare realm and environmental monitoring. This is especially evident in developing countries because PADs-based point-of-care testing (POCT) enables to rapidly determine various (bio)chemical analytes in a miniaturized, cost-effective and user-friendly manner. Low sensitivity and poor specificity are the main bottlenecks associated with PADs, which limit the entry of PADs into the real-life applications. The application of nanomaterials in PADs is showing great improvement in their detection performance in terms of sensitivity, selectivity and accuracy since the nanomaterials have unique physicochemical properties. In this review, the research progress on the nanomaterial-based PADs is summarized by highlighting representative recent publications. We mainly focus on the detection principles, the sensing mechanisms of how they work and applications in disease diagnosis, environmental monitoring and food safety management. In addition, the limitations and challenges associated with the development of nanomaterial-based PADs are discussed, and further directions in this research field are proposed. Full article

Over the past decades, paper-based lateral flow immunoassays (LFIAs) have been extensively developed for rapid, facile, and low-cost detection of a wide array of target analytes in a point-of-care manner. Conventional home pregnancy tests are the most significant example of LFAs, which detect elevated concentrations of human chorionic gonadotrophin (hCG) in body fluids to identify early pregnancy. In this work, we have upgraded these platforms to a higher version by developing a customized microfluidic paper-based analytical device (μPAD), as the new generation of paper-based point-of-care platforms, for colorimetric immunosensing. This will offer a cost-efficient and environmentally friendly alternative platform for paper-based immunosensing, eliminating the need for nitrocellulose (NC) membrane as the substrate material. The performance of the developed platform is demonstrated by detection of hCG (as a model case) in urine samples and subsequently indicating positive or negative pregnancy. A dual-functional silane-based composite was used to treat filter paper in order to enhance the colorimetric signal intensity in the detection zones of μPADs. In addition, microfluidic pathways were designed in a manner to provide the desired regulated fluid flow, generating sufficient incubation time (delays) at the designated detection zones, and consequently enhancing the obtained signal intensity. The presented approaches allow to overcome the existing limitations of μPADs in immunosensing and will broaden their applicability to a wider range of assays. Although, the application of the developed hCG μPAD assay is mainly in qualitative (i.e., positive or negative) detection of pregnancy, the semi-quantitative measurement of hCG was also investigated, indicating the viability of this assay for sensitive detection of the target hCG analyte within the related physiological range (i.e., 10–500 ng/mL) with a LOD value down to 10 ng/mL. Full article

In this paper, a novel and ultrasensitive lateral flow assay (LFA) based on aptamer–magnetic separation, and multifold Au nanoparticles (AuNPs) was developed for visual detecting Salmonella enterica ser. Typhimurium (S. Typhimurium). The method realized magnetic enrichment and signal transduction via magnetic separation and achieved signal amplification through hybridizing AuNPs–capture probes and AuNPs–amplification probes to form multifold AuNPs. Two different thiolated single-strand DNA (ssDNA) on the AuNPs–capture probe played different roles. One was combined with the AuNPs–amplification probe on the conjugate pad to achieve enhanced signals. The other was connected to transduction ssDNA1 released by aptamer–magnetic capture of S. Typhimurium, and captured by the T-line, forming a positive signal. This method had an excellent linear relationship ranging from 8.6 × 10² CFU/mL to 8.6 × 10⁷ CFU/mL with the limit of detection (LOD) as low as 8.6 × 10⁰ CFU/mL in pure culture. In actual samples, the visual LOD was 4.1 × 10² CFU/mL, which did not carry out nucleic acid amplification and pre-enrichment, increasing three orders of magnitudes than unenhanced assays with single–dose AuNPs and no magnetic separation. Furthermore, the system showed high specificity, having no reaction with other nontarget strains. This visual signal amplificated system would be a potential platform for ultrasensitive monitoring S. Typhimurium in milk samples. Full article

In this work, a simple and rapid method based on the lateral flow assay (LFA) has been developed for the detection of dual antibiotics. To achieve the quantitative assay and to reduce the non-specific adsorption, an internal system has been developed. A non-specific DNA was exploited as an internal standard and could be recognized by the DNA marker that was coated at the internal line. Two different kinds of aptamers were applied to recognize ampicillin (AMP) and kanamycin (KAM), and the distance between the detection line and conjugate pad was then optimized. Under the optimum conditions, the quantitative assays of AMP (R² = 0.984) and KAM (R² = 0.990) were achieved with dynamic ranges of 0.50 to 500.0 ng/L, and of 0.50 to 1000.0 ng/L, respectively. The LOQs of AMP and KAM were 0.06 ng/L and 0.015 ng/L, respectively. Finally, the proposed method has been successfully applied to analyze aquaculture water, tap water, and lake water, and hospital wastewater, indicating the established method could be used to monitor the environment. Full article

Recently, demand for handwriting recognition, such as automation of mail sorting, license plate recognition, and electronic memo pads, has exponentially increased in various industrial fields. In addition, in the image recognition field, methods using artificial convolutional neural networks, which show outstanding performance, have been applied to handwriting recognition. However, owing to the diversity of recognition application fields, the number of dimensions in the learning and reasoning processes is increasing. To solve this problem, a principal component analysis (PCA) technique is used for dimensionality reduction. However, PCA is likely to increase the accuracy loss due to data compression. Therefore, in this paper, we propose a line-segment feature analysis (LFA) algorithm for input dimensionality reduction in handwritten text recognition. This proposed algorithm extracts the line segment information, constituting the image of input data, and assigns a unique value to each segment using 3 × 3 and 5 × 5 filters. Using the unique values to identify the number of line segments and adding them up, a 1-D vector with a size of 512 is created. This vector is used as input to machine-learning. For the performance evaluation of the method, the Extending Modified National Institute of Standards and Technology (EMNIST) database was used. In the evaluation, PCA showed 96.6% and 93.86% accuracy with k-nearest neighbors (KNN) and support vector machine (SVM), respectively, while LFA showed 97.5% and 98.9% accuracy with KNN and SVM, respectively. Full article

Lateral flow assay (LFA) technology has recently received interest in the biochemical field since it is simple, low-cost, and rapid, while conventional laboratory test procedures are complicated, expensive, and time-consuming. In this paper, we propose a robust smartphone-based analyte detection method that estimates the amount of analyte on an LFA strip using a smartphone camera. The proposed method can maintain high estimation accuracy under various illumination conditions without additional devices, unlike conventional methods. The robustness and simplicity of the proposed method are enabled by novel image processing and machine learning techniques. For the performance analysis, we applied the proposed method to LFA strips where the target analyte is albumin protein of human serum. We use two sets of training LFA strips and one set of testing LFA strips. Here, each set consists of five strips having different quantities of albumin—10 femtograms, 100 femtograms, 1 picogram, 10 picograms, and 100 picograms. A linear regression analysis approximates the analyte quantity, and then machine learning classifier, support vector machine (SVM), which is trained by the regression results, classifies the analyte quantity on the LFA strip in an optimal way. Experimental results show that the proposed smartphone application can detect the quantity of albumin protein on a test LFA set with 98% accuracy, on average, in real time. Full article

The following article summarizes United States Patent Application No. US20180052155A1, titled ‘Assay Devices and Methods’ (filed 16 August 2016, published 22 February 2018). While lateral flow assays (LFAs) have revolutionized point-of-care diagnostics by enabling accurate, inexpensive, and rapid detection of biomarkers, they typically do not provide quantitative results. Hence, there is a significant need for quantitative assays at the point of care. This patent summary describes a novel method of chronometric biomarker quantitation via enzymatic degradation of a metastable gelatin-based biomatrix, principally suited for use in paper-based microfluidic devices (microPADs). This new quantitation mechanism was designed to meet the ASSURED criteria for point-of-care diagnostic devices laid forth by the World Health Organization and may ultimately provide increased access to healthcare, at a significantly reduced cost, around the world. Full article

Immunochromatographic or lateral flow assays (LFAs) are inexpensive, easy to use, point-of-care medical diagnostic tests that are found in arenas ranging from a doctor’s office in Manhattan to a rural medical clinic in low resource settings. The simplicity in the LFA itself belies the complex task of optimization required to make the test sensitive, rapid and easy to use. Currently, the manufacturers develop LFAs by empirical optimization of material components (e.g., analytical membranes, conjugate pads and sample pads), biological reagents (e.g., antibodies, blocking reagents and buffers) and the design of delivery geometry. In this paper, we will review conventional optimization and then focus on the latter and outline analytical tools, such as dynamic light scattering and optical biosensors, as well as methods, such as microfluidic flow design and mechanistic models. We are applying these tools to find non-obvious optima of lateral flow assays for improved sensitivity, specificity and manufacturing robustness. Full article