Amorphous carbon nanoparticles: a versatile label for rapid diagnostic (immuno)assays

Carbon nanoparticles (CNPs) labeled with reporter molecules can serve as signaling labels in rapid diagnostic assays as an alternative to gold, colored latex, silica, quantum dots, or up-converting phosphor nanoparticles. Detailed here is the preparation of biomolecule-labeled CNPs and examples of their use as a versatile label. CNPs can be loaded with a range of biomolecules, such as DNA, antibodies, and proteins (e.g., neutravidin or a fusion protein of neutravidin with an enzyme), and the resulting conjugates can be used to detect analytes of high or low molecular mass

Scanning-fluorescence Reader Based on Embedded System

To measure the concentration of C-reactive protein (CRP) in serum, a portable, scanning-fluorescence reader based on time-resolved fluoroimmunoassays was developed. The scanning-fluorescence reader integrates with the AD7707 converter, which performs at a high accuracy. The photosensitive diode acts as the photoelectric conversion device, an optical module based on optical fibers, which is able to concentrate the excitation light from an LED into a line-shape beam, was designed to sendand receive the optical signal. The device subsequently addresses waveform data using a gradient, smoothing, and binarization method. When the device measures the CRP fluorescence test strip, the results exhibited a good linearity (0.99998) and the CVs (coefficient of variation) were below 5%, which indicate high accuracy. At the same time the system is low cost and small size

ACS Appl Bio Mater

The lateral flow assay (LFA) is a point-of-care diagnostic test commonly available in an over-the-counter format because of its simplicity, speed, low cost, and portability. The reporter particles in these assays are among their most significant components because they perform the diagnostic readout and dictate the test's sensitivity. Today, gold nanoparticles are frequently used as reporters, but recent work focusing on photoluminescent-based reporter technologies has pushed LFAs to better performance. These efforts have focused specifically on reporters made of organic fluorophores, quantum dots, lanthanide chelates, persistent luminescent phosphors, and upconversion phosphors. In most cases, photoluminescent reporters show enhanced sensitivity compared to conventional gold nanoparticle-based assays. Here, we examine the advantages and disadvantages of these different reporters and highlight their potential benefits in LFAs. Our assessment shows that photoluminescent-based LFAs can not only reach lower detection limits than LFAs with traditional reporters, but they also can be capable of quantitative and multiplex analyte detection. As a result, the photoluminescent reporters make LFAs well-suited for medical diagnostics, the food and agricultural industry, and environmental testing.R01 AR072742/AR/NIAMS NIH HHSUnited States/R43 AI118180/AI/NIAID NIH HHSUnited States/U01 CK000512/CK/NCEZID CDC HHSUnited States/U01CK000512/ACL/ACL HHSUnited States

Lateral flow immunoassays with fluorescent reporter technologies

Lateral flow assays (LFAs) are user-friendly diagnostic test devices most commonly known from the home pregnancy tests. Since their appearance in the market in 1980’s, LFAs have become well-established and products have been developed for various applications, but the most commonly sold LFAs still have the same basic features as the early products. Compared to other rapid diagnostic test (RDT) platforms, the main benefits of LFAs include inexpensive manufacturing costs, relatively fast assay development process, and the stand-alone capability of the test to be used without any instrumentation. The analytical membrane that provides the solid support for the bioassay reagents and allows the liquids to migrate through the binder lines by capillary force is almost exclusively manufactured of nitrocellulose. As the nitrocellulose remains the most widely used material, its optical properties, mechanical robustness, and chemical stability are not optimal for the RDT development. However, the established status of the nitrocellulose membrane in the RDT industry and the continuous product development suggests that the material will remain in LFAs for years to come. Typically, in LFAs, the coloured reporter particles form visible lines on the analytical membrane depending on the presence or absence of the analyte of interest. The visible lines can be interpreted visually without any instrumentation. However, the visual assessment of the assay read-out is prone to subjectivity in interpretation and can be affected by poor lighting conditions. Moreover, the visual read-out can only be used to generate a qualitative or a semi-quantitative result. The versatility of the lateral flow technology can be improved by using efficiently quantifiable reporter technologies such as fluorescent nanoparticles. However, the drawback of pursuing high analytical sensitivity and quantitative results by fluorescent reporter is the apparent need for a reader instrument. With fluorescent reporters, the optical properties of the assay membranes and sample fluids must be considered in order to achieve minimal interference to the detection of the reporters. Autofluorescence originating from the assay materials can be avoided by using the upconverting nanoparticle (UCNP) detection technology. Nevertheless, the non-analyte specific background signal can still occur from non-specific binding of the reporter particles. The aim of the thesis is to explore the opportunities arising from the use of different fluorescent reporter particles to improve the analytical sensitivities of LFAs, and to evaluate the feasibility of fluorescent reporter particles as a substitute for common visually detectable reporters. Exploiting the increased detectability of the reporter particles to improve the assay sensitivity requires careful re-optimization of the assay conditions

Immunochromatographic diagnostic test analysis using Google Glass.

We demonstrate a Google Glass-based rapid diagnostic test (RDT) reader platform capable of qualitative and quantitative measurements of various lateral flow immunochromatographic assays and similar biomedical diagnostics tests. Using a custom-written Glass application and without any external hardware attachments, one or more RDTs labeled with Quick Response (QR) code identifiers are simultaneously imaged using the built-in camera of the Google Glass that is based on a hands-free and voice-controlled interface and digitally transmitted to a server for digital processing. The acquired JPEG images are automatically processed to locate all the RDTs and, for each RDT, to produce a quantitative diagnostic result, which is returned to the Google Glass (i.e., the user) and also stored on a central server along with the RDT image, QR code, and other related information (e.g., demographic data). The same server also provides a dynamic spatiotemporal map and real-time statistics for uploaded RDT results accessible through Internet browsers. We tested this Google Glass-based diagnostic platform using qualitative (i.e., yes/no) human immunodeficiency virus (HIV) and quantitative prostate-specific antigen (PSA) tests. For the quantitative RDTs, we measured activated tests at various concentrations ranging from 0 to 200 ng/mL for free and total PSA. This wearable RDT reader platform running on Google Glass combines a hands-free sensing and image capture interface with powerful servers running our custom image processing codes, and it can be quite useful for real-time spatiotemporal tracking of various diseases and personal medical conditions, providing a valuable tool for epidemiology and mobile health

A hybrid EKF and switching PSO algorithm for joint state and parameter estimation of lateral flow immunoassay models

This is the post-print version of the Article. The official published can be accessed from the link below - Copyright @ 2012 IEEEIn this paper, a hybrid extended Kalman filter (EKF) and switching particle swarm optimization (SPSO) algorithm is proposed for jointly estimating both the parameters and states of the lateral flow immunoassay model through available short time-series measurement. Our proposed method generalizes the well-known EKF algorithm by imposing physical constraints on the system states. Note that the state constraints are encountered very often in practice that give rise to considerable difficulties in system analysis and design. The main purpose of this paper is to handle the dynamic modeling problem with state constraints by combining the extended Kalman filtering and constrained optimization algorithms via the maximization probability method. More specifically, a recently developed SPSO algorithm is used to cope with the constrained optimization problem by converting it into an unconstrained optimization one through adding a penalty term to the objective function. The proposed algorithm is then employed to simultaneously identify the parameters and states of a lateral flow immunoassay model. It is shown that the proposed algorithm gives much improved performance over the traditional EKF method.This work was supported in part by the International Science and Technology Cooperation Project of China under Grant 2009DFA32050, Natural Science Foundation of China under Grants 61104041, International Science and Technology Cooperation Project of Fujian Province of China under Grant 2009I0016

Upconverting Phosphor Technology: Exceptional Photoluminescent Properties Light Up Homogeneous Bioanalytical Assays

The aim of the present study was to demonstrate the wide applicability of the novel photoluminescent labels called upconverting phosphors (UCPs) in proximity-based bioanalytical assays. The exceptional features of the lanthanide-doped inorganic UCP compounds stem from their capability for photon upconversion resulting in anti-Stokes photoluminescence at visible wavelengths under near-infrared (NIR) excitation. Major limitations related to conventional photoluminescent labels are avoided, rendering the UCPs a competitive next-generation label technology. First, the background luminescence is minimized due to total elimination of autofluorescence. Consequently, improvements in detectability are expected. Second, at the long wavelengths (>600 nm) used for exciting and detecting the UCPs, the transmittance of sample matrixes is significantly greater in comparison with shorter wavelengths. Colored samples are no longer an obstacle to the luminescence measurement, and more flexibility is allowed even in homogeneous assay concepts, where the sample matrix remains present during the entire analysis procedure, including label detection. To transform a UCP particle into a biocompatible label suitable for bioanalytical assays, it must be colloidal in an aqueous environment and covered with biomolecules capable of recognizing the analyte molecule. At the beginning of this study, only UCP bulk material was available, and it was necessary to process the material to submicrometer-sized particles prior to use. Later, the ground UCPs, with irregular shape, wide size-distribution and heterogeneous luminescence properties, were substituted by a smaller-sized spherical UCP material. The surface functionalization of the UCPs was realized by producing a thin hydrophilic coating. Polymer adsorption on the UCP surface is a simple way to introduce functional groups for bioconjugation purposes, but possible stability issues encouraged us to optimize an optional silica-encapsulation method which produces a coating that is not detached in storage or assay conditions. An extremely thin monolayer around the UCPs was pursued due to their intended use as short-distance energy donors, and much attention was paid to controlling the thickness of the coating. The performance of the UCP technology was evaluated in three different homogeneous resonance energy transfer-based bioanalytical assays: a competitive ligand binding assay, a hybridization assay for nucleic acid detection and an enzyme activity assay. To complete the list, a competitive immunoassay has been published previously. Our systematic investigation showed that a nonradiative energy transfer mechanism is indeed involved, when a UCP and an acceptor fluorophore are brought into close proximity in aqueous suspension. This process is the basis for the above-mentioned homogeneous assays, in which the distance between the fluorescent species depends on a specific biomolecular binding event. According to the studies, the submicrometer-sized UCP labels allow versatile proximity-based bioanalysis with low detection limits (a low-nanomolar concentration for biotin, 0.01 U for benzonase enzyme, 0.35 nM for target DNA sequence).Siirretty Doriast

Identification of nonlinear lateral flow immunoassay state-space models via particle filter approach

This is the post-print of the Article. The official published version can be accessed from the link below - Copyright @ 2012 IEEEIn this paper, the particle filtering approach is used, together with the kernel smoothing method, to identify the state-space model for the lateral flow immunoassay through available but short time-series measurement. The lateral flow immunoassay model is viewed as a nonlinear dynamic stochastic model consisting of the equations for the biochemical reaction system as well as the measurement output. The renowned extended Kalman filter is chosen as the importance density of the particle filter for the purpose of modeling the nonlinear lateral flow immunoassay. By using the developed particle filter, both the states and parameters of the nonlinear state-space model can be identified simultaneously. The identified model is of fundamental significance for the development of lateral flow immunoassay quantification. It is shown that the proposed particle filtering approach works well for modeling the lateral flow immunoassay.This work was supported in part by the International Science and Technology Cooperation Project of China under Grant 2009DFA32050, Natural Science Foundation of China under Grants 61104041, International Science and Technology Cooperation Project of Fujian Province of China under Grant 2009I0016

Image-based quantitative analysis of gold immunochromatographic strip via cellular neural network approach

"(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works."Gold immunochromatographic strip assay provides a rapid, simple, single-copy and on-site way to detect the presence or absence of the target analyte. This paper aims to develop a method for accurately segmenting the test line and control line of the gold immunochromatographic strip (GICS) image for quantitatively determining the trace concentrations in the specimen, which can lead to more functional information than the traditional qualitative or semi-quantitative strip assay. The canny operator as well as the mathematical morphology method is used to detect and extract the GICS reading-window. Then, the test line and control line of the GICS reading-window are segmented by the cellular neural network (CNN) algorithm, where the template parameters of the CNN are designed by the switching particle swarm optimization (SPSO) algorithm for improving the performance of the CNN. It is shown that the SPSO-based CNN offers a robust method for accurately segmenting the test and control lines, and therefore serves as a novel image methodology for the interpretation of GICS. Furthermore, quantitative comparison is carried out among four algorithms in terms of the peak signal-to-noise ratio. It is concluded that the proposed CNN algorithm gives higher accuracy and the CNN is capable of parallelism and analog very-large-scale integration implementation within a remarkably efficient time

Rapid Daignostic Lateral Flow Strip Test Reader

Non-invasive rapid diagnostic tests (RDT) are commonly used to detect some kind of viruses or bacteria instead of invasive methods. Helicobacter pylori (H. Pylori) which causes gastric cancer, peptic ulcer, gastritis, mucosa-associated lymphoid tissue lymphoma diseases can be detected easily with lateral flow strip (LFS) that is one of the RDT types. The tests are evaluated whether there are control line and test line at the region of interest (ROI) by users or microbiology technicians manually. Once the test line is tentative, despite the test must be reported positive, it can be resulted as negative incorrectly. This incorrect diagnose causes incorrect treatment planning. In this work, to mitigate this problem which will be able to occur by human based, an automatic LFS-RDT reading system is developed. The computer laptop based system firstly takes image utilizing the holders that are designed with 3D printer. Whether the test have the control-test lines or not are carried out by image processing techniques straightforwardly. After feature extraction from line areas, k-NN classification method is used to evaluate the test results automatically. 100 LFS-RDTs are tested and observed that all results are correct. The system is found quite useful and approved as a second reader by medical technicians