Optical scanner for immunoassays with up-converting phosphorescent labels

Algorithms for immunochromatographic assay: review and impact on future application

Lateral flow immunoassay (LFIA) is a critical choice for applications of point-of-care testing (POCT) in clinical and laboratory environments because of its excellent features and versatility. To obtain authentic values of analyte concentrations and reliable detection results, the relevant research has featured the application of a diversity of methods of mathematical analysis to technical analysis to allow for use with a small quantity of data. Accordingly, a number of signal and image processing strategies have also emerged for the application of gold immunochromatographic and fluorescent strips to improve sensitivity and overcome the limitations of correlative hardware systems. Instead of traditional methods to solve the problem, researchers nowadays are interested in machine learning and its more powerful variant, deep learning technology, for LFIA detection. This review emphasizes different models for the POCT of accurate labels as well as signal processing strategies that use artificial intelligence and machine learning. We focus on the analytical mechanism, procedural flow, and the results of the assay, and conclude by summarizing the advantages and limitations of each algorithm. We also discuss the potential for application of and directions of future research on LFIA technology when combined with Artificial Intelligence and deep learning.

Sensors and bioassays powered by upconverting materials

In recent years, considerable efforts have been done to better understand the peculiar emission properties of upconverting materials due to their widespread applications in different and important technological fields such as upconversion-based photoactivated cancer therapies, photoactivated drug-delivery, magnetic resonance imaging contrast agents, bioimaging. However, one of the most promising applications of upconverting materials concerns the field of sensing, due to their unique emission properties. In fact, the minimal autofluorescence, blinking, photo-bleaching, and high photostability makes them an excellent alternative to organic dyes or quantum dots. This article reviews the state-of-the-art, design, and sensing strategies of upconversion-based sensing platforms, with special attention to upconverting nanoparticles, as well as how the incorporation of these materials into pre-existing diagnostic tests and bioassays have improved their capabilities for the detection of different kinds of analytes.

Spectral and mathematical evaluation of electromyography signals for clinical use

The surface electromyography (SEMG) is a complicated biomedical signal, generated during voluntary or involuntary muscle activities and these muscle activities are always controlled by the nervous system. In this paper, the processing and analysis of SEMG signals at multiple muscle points for different operations were carried out. Myoelectric signals were detected using designed acquisition setup which consists of an instrumentation amplifier, filter circuit, an amplifier with gain adjustment. Further, Labview[Formula: see text]-based data programming code was used to record SEMG signals for independent activities. The whole system consists of bipolar noninvasive electrodes, signal acquisition protocols and signal conditioning at different levels. This work uses recorded SEMG signals generated by biceps and triceps muscles for four different arm activities. Feature extraction was done on the recorded signal for investigating the voluntary muscular contraction relationship for exercising statistic measured index method to evaluate distance between two independent groups by directly addressing the quality of signal in separability class for different arm movements. Thereafter repeated factorial analysis of variance technique was implemented to evaluate the effectiveness of processed signal. From these results, it demonstrates that the proposed method can be used as SEMG feature evaluation index.

A Novel Automatic Rapid Diagnostic Test Reader Platform

A novel automatic Rapid Diagnostic Test (RDT) reader platform is designed to analyze and diagnose target disease by using existing consumer cameras of a laptop-computer or a tablet. The RDT reader is useable with numerous lateral immunochromatographic assays and similar biomedical tests. The system has two different components, which are 3D-printed, low-cost, tiny, and compact stand and a decision program named RDT-AutoReader 2.0. The program takes the image of RDT, crops the region of interest (ROI), and extracts the features from the control end test lines to classify the results as invalid, positive, or negative. All related patient's personal information, image of ROI, and the e-report are digitally saved and transferred to the related clinician. Condition of the patient and the progress of the disease can be monitored by using the saved data. The reader platform has been tested by taking image from used cassette RDTs of rotavirus (RtV)/adenovirus (AdV) and lateral flow strip RDTs of Helicobacter pylori (H. pylori) before discarding them. The created RDT reader can also supply real-time statistics of various illnesses by using databases and Internet. This can help to inhibit propagation of contagious diseases and to increase readiness against epidemic diseases worldwide.

Introduction to In Vitro Diagnostic Devices

Healthcare investment keeps on increasing substantially in recent years. Such investment has also focused on fighting major diseases, enabled by the novel invention of cost-effective and valid drug development for treatment and side effect reduction, along with improved vector control. In addition, the demand for diagnostics that is essential in determining prognosis, identifying disease stages, monitoring treatment, and assessing the spreading as health services has expanded. Molecular-based diagnostics is critical for prevention, identification, and treatment of disease. Current laboratory analyses support correct diagnosis in over 70 % of all diseases and can be used to aid the continuous monitoring of drug therapy. However, classic diagnostic technologies are not completely well suited to meeting the expanded testing requirement because they rely on complicated sample purification and sophisticated instruments which are labor-intensive, timely, and expensive and require well-trained operators. One of the main challenges for industry is to develop fast, relatively accurate, easy-to-use, and inexpensive devices. In addition to the improved efficiency in laboratory diagnostics, there has been a trend toward a more decentralized diagnostics which occurs directly at patients’ bedside, in outpatient clinics, or at the sites of accidents, so-called point-of-care (POC) systems. The concept of POC testing is mainly for the patient, so short turnaround time, minimum sample preparation, reagent storage and transferring, user-friendly analytical instruments, and digital or visible quantitative or semiquantitative single readout are required. POC test is a great option of potential in vitro diagnostics (IVD) for resource-limited settings. It is clear that on-site or minimum sample preparation and on-chip storage limit the delays that caused by transport and preparation of clinical samples. Shorter turnaround time leads to rapid clinical decision-making and may save fatal consequences. No previous knowledge in sample analysis should be required, so elders can perform the tests at home with minimum training to improve health outcome. Lateral-flow immunoassay (LFIA) devices, for example, which were originally proposed in the 1980s, remain popular largely because of their design simplicity. The purpose of this article is to introduce readers with basic information regarding the LFIA approach that we think the most representative product of IVD test for solving global health issues.

Lanthanide-doped upconversion nano-bioprobes: electronic structures, optical properties, and biodetection

The latest advances in lanthanide-doped upconversion nanoparticles were comprehensively reviewed, which covers from their fundamental photophysics to biodetection.

Persistent luminescence strontium aluminate nanoparticles as reporters in lateral flow assays

Demand for highly sensitive, robust diagnostics and environmental monitoring methods has led to extensive research in improving reporter technologies. Inorganic phosphorescent materials exhibiting persistent luminescence are commonly found in electroluminescent displays and glowing paints but are not widely used as reporters in diagnostic assays. Persistent luminescence nanoparticles (PLNPs) offer advantages over conventional photoluminescent probes, including the potential for enhanced sensitivity by collecting time-resolved measurements or images with decreased background autofluorescence while eliminating the need for expensive optical hardware, superior resistance to photobleaching, amenability to quantitation, and facile bioconjugation schemes. We isolated rare-earth doped strontium aluminate PLNPs from larger-particle commercial materials by wet milling and differential sedimentation and water-stabilized the particles by silica encapsulation using a modified Stöber process. Surface treatment with aldehyde silane followed by reductive amination with heterobifunctional amine-poly(ethylene glycol)-carboxyl allowed covalent attachment of proteins to the particles using standard carbodiimide chemistry. NeutrAvidin PLNPs were used in lateral flow assays (LFAs) with biotinylated lysozyme as a model analyte in buffer and monoclonal anti-lysozyme HyHEL-5 antibodies at the test line. Preliminary experiments revealed a limit of detection below 100 pg/mL using the NeutrAvidin PLNPs, which was approximately an order of magnitude more sensitive than colloidal gold.

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

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.

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 robust dry reagent lateral flow assay for diagnosis of active schistosomiasis by detection of Schistosoma circulating anodic antigen

An earlier reported laboratory assay, performed in The Netherlands, to diagnose Schistosoma infections by detection of the parasite antigen CAA in serum was converted to a more user-friendly format with dry reagents. The improved assay requires less equipment and allows storage and worldwide shipping at ambient temperature. Evaluation of the new assay format was carried out by local staff at Ampath Laboratories, South Africa. The lateral flow (LF) based assay utilized fluorescent ultrasensitive up-converting phosphor (UCP) reporter particles, to be read by a portable reader (UPlink) that was also provided to the laboratory. Over a period of 18 months, about 2000 clinical samples were analyzed prospectively in parallel with a routinely carried out CAA-ELISA. LF test results and ELISA data correlated very well at CAA concentrations above 300 pg/mL serum. At lower concentrations the UCP-LF test indicates a better performance than the ELISA. The UCP-LF strips can be stored as a permanent record as the UCP label does not fade. At the end of the 18 months testing period, LF strips were shipped back to The Netherlands where scan results obtained in South Africa were validated with different UCP scanning equipment including a novel, custom developed, small lightweight UCP strip reader (UCP-Quant), well suited for testing in low resource settings.

CONCLUSION

The dry format UCP-LF assay was shown to provide a robust and easy to use format for rapid testing of CAA antigen in serum. It performed at least as good as the ELISA with respect to sensitivity and specificity, and was found to be superior with respect to speed and simplicity of use. Worldwide shipping at ambient temperature of the assay reagents, and the availability of small scanners to analyze the CAA UCP-LF strip, are two major steps towards point-of-care (POC) applications in remote and resource poor environments to accurately identify low (30 pg CAA/mL serum; equivalent to about 10 worm pairs) to heavy Schistosoma infections.

Integrated rapid-diagnostic-test reader platform on a cellphone

We demonstrate a cellphone-based rapid-diagnostic-test (RDT) reader platform that can work with various lateral flow immuno-chromatographic assays and similar tests to sense the presence of a target analyte in a sample. This compact and cost-effective digital RDT reader, weighing only ~65 g, mechanically attaches to the existing camera unit of a cellphone, where various types of RDTs can be inserted to be imaged in reflection or transmission modes under light-emitting diode (LED)-based illumination. Captured raw images of these tests are then digitally processed (within less than 0.2 s per image) through a smart application running on the cellphone for validation of the RDT, as well as for automated reading of its diagnostic result. The same smart application then transmits the resulting data, together with the RDT images and other related information (e.g., demographic data), to a central server, which presents the diagnostic results on a world map through geo-tagging. This dynamic spatio-temporal map of various RDT results can then be viewed and shared using internet browsers or through the same cellphone application. We tested this platform using malaria, tuberculosis (TB) and HIV RDTs by installing it on both Android-based smartphones and an iPhone. Providing real-time spatio-temporal statistics for the prevalence of various infectious diseases, this smart RDT reader platform running on cellphones might assist healthcare professionals and policymakers to track emerging epidemics worldwide and help epidemic preparedness.

A Portable Analyzer for Pouch-Actuated, Immunoassay Cassettes

A portable, small footprint, light, general purpose analyzer (processor) to control the flow in immunoassay cassettes and to facilitate the detection of test results is described. The durable analyzer accepts disposable cassettes that contain pouches and reaction chambers for various unit operations such as hydration of dry reagents, stirring, and incubation. The analyzer includes individually controlled, linear actuators to compress the pouches in the cassette, which facilitates the pumping and mixing of sample and reagents, and to close diaphragm-based valves for flow control. The same types of actuators are used to compress pouches and actuate valves. The analyzer also houses a compact OEM scanner/reader to excite fluorescence and detect emission from labels. The analyzer is hydraulically isolated from the cassette, reducing the possibility of cross-contamination. The analyzer facilitates programmable, automated execution of a sequence of operations such as pumping and valving in a timely fashion, reducing the level of expertise required from the operator and the possibility for errors. The analyzer's design is modular and expandable to accommodate cassettes of various complexities and additional functionalities. In this paper, the utility of the analyzer has been demonstrated with the execution of a simple, consecutive, lateral flow assay of a model biological system and the test results were detected with up converting phosphor labels that are excited at infrared frequencies and emit in the visible spectrum.

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

In 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.

Luminescent chemical sensing, biosensing, and screening using upconverting nanoparticles

Upconverting nanoparticles (UCNPs) display the unique property of converting near-infrared light (with wavelengths of typically 800-1,000 nm) into visible luminescence. Following a short introduction into the mechanisms leading to the effect, the main classes of materials used are discussed. We then review the state of the art of using UCNPs: (1) to label biomolecules such as antibodies and (synthetic) oligomers for use in affinity assay and flow assays; (2) to act as nanolamps whose emission intensity is modulated by chemical indicators, thus leading to a novel kind of chemical sensors; and (3), to act as donors in luminescence resonance energy transfer in chemical sensors and biosensors.

The science of neural interface systems

The ultimate goal of neural interface research is to create links between the nervous system and the outside world either by stimulating or by recording from neural tissue to treat or assist people with sensory, motor, or other disabilities of neural function. Although electrical stimulation systems have already reached widespread clinical application, neural interfaces that record neural signals to decipher movement intentions are only now beginning to develop into clinically viable systems to help paralyzed people. We begin by reviewing state-of-the-art research and early-stage clinical recording systems and focus on systems that record single-unit action potentials. We then address the potential for neural interface research to enhance basic scientific understanding of brain function by offering unique insights in neural coding and representation, plasticity, brain-behavior relations, and the neurobiology of disease. Finally, we discuss technical and scientific challenges faced by these systems before they are widely adopted by severely motor-disabled patients.