Analyte Quantity Detection from Lateral Flow Assay Using a Smartphone

A portable, integrated microfluidics for rapid and sensitive diagnosis of Streptococcus agalactiae in resource-limited environments

Streptococcus agalactiae (Group B Streptococcus, GBS) has been the leading cause of infections in newborns. Rapid and accurate diagnosis of GBS in pregnant women is a deterministic strategy to prevent newborn infection. Conventional detection methods based on nucleic acid amplification assay have been applied in GBS diagnosis in central laboratories, with demonstrated high sensitivity. However, their heavy dependence on instrumentation and trained technicians forms remarkable obstacles to GBS detection in wide scenarios, including self-testing, and bedside-/community-screening. Furthermore, the structures of GBS bring about extra challenges to the nucleic acid extraction and purification. Novel GBS diagnosis platforms integrating sample processing, amplification, and read-out, are highly desired in clinical. Here, we report a portable, integrated microfluidics that enables rapid extraction of DNA from sampling swabs (<10 min), power-free DNA amplification (<30 min), and simple read-out in GBS detection. The platform works without an external pump, achieving rapid and highly efficient DNA extraction from clinical samples, with a significantly reduced time from 6 h to less than 50 min. Systematic clinical tests based on 47 patient samples validated the high performance of the platform, highlighted with a low limit of detection (LOD, 103 copies/ml), high sensitivity (100%), and specificity (100%). Head-to-head comparisons showed that the device improved the LOD by an order of magnitude than the traditional PCR method, showing a simple yet powerful POCT platform for home-/community-based testing towards GBS (and other pathogens) prevention in remote areas.

Advancing diagnostic efficacy using a computer vision-assisted lateral flow assay for influenza and SARS-CoV-2 detection

Lateral flow assays (LFAs) have emerged as indispensable tools for point-of-care testing during the pandemic era. However, the interpretation of results through unassisted visual inspection by untrained individuals poses inherent limitations. In our study, we propose a novel approach that combines computer vision (CV) and lightweight machine learning (ML) to overcome these limitations and significantly enhance the performance of LFAs. By incorporating CV-assisted analysis into the LFA assay, we achieved a remarkable three-fold improvement in analytical sensitivity for detecting Influenza A and for SARS-CoV-2 detection. The obtained R2 values reached approximately 0.95, respectively, demonstrating the effectiveness of our approach. Moreover, the integration of CV techniques with LFAs resulted in a substantial amplification of the colorimetric signal specifically for COVID-19 positive patient samples. Our proposed approach, which incorporates a simple machine learning algorithm, provides substantial enhancements in assay sensitivity, improving diagnostic efficacy and accessibility of point-of-care testing without requiring significant additional resources. Moreover, the simplicity of the machine learning algorithm enables its standalone use on a mobile phone, further enhancing its practicality for point-of-care testing.

Lateral Flow Assay: A Summary of Recent Progress for Improving Assay Performance

Lateral flow tests are one of the most important types of paper-based point-of-care (POCT) diagnostic tools. It shows great potential as an implement for improving the rapid screening and management of infections in global pandemics or other potential health disorders by using minimally expert staff in locations where no sophisticated laboratory services are accessible. They can detect different types of biomarkers in various biological samples and provide the results in a little time at a low price. An important challenge regarding conventional LFAs is increasing their sensitivity and specificity. There are two main approaches to increase sensitivity and specificity, including assay improvement and target enrichment. Assay improvement comprises the assay optimization and signal amplification techniques. In this study, a summarize of various sensitivity and specificity enhancement strategies with an objective evaluation are presented, such as detection element immobilization, capillary flow rate adjusting, label evolution, sample extraction and enrichment, etc. and also the key findings in improving the LFA performance and solving their limitations are discussed along with numerous examples.

A smartphone digital image colorimetric method based on nanoparticles for determination of lamotrigine

Aim: A colorimetric approach for quantification of lamotrigine using spectrophotometric and smartphone image analysis is described in this study. Methods: For full optimization and validation procedures, UV-visible spectroscopy was used, and image analysis was carried out with the help of an app (PhotoMetrix PRO®). Then, as a multivariate calibration method, parallel factor analysis was used for data analysis. Results: The results demonstrated the capacity of these methods to estimate lamotrigine concentrations in the range of 0.1-7.0 μg.ml-1 in exhaled breath condensate, indicating the value of using digital images and smartphone applications in combination with chemometric tools. Conclusion: The image analysis can be superior for its fast and reliable lamotrigine analysis in biological samples.

Proof-of-Concept: Smartphone- and Cloud-Based Artificial Intelligence Quantitative Analysis System (SCAISY) for SARS-CoV-2-Specific IgG Antibody Lateral Flow Assays

Smartphone-based point-of-care testing (POCT) is rapidly emerging as an alternative to traditional screening and laboratory testing, particularly in resource-limited settings. In this proof-of-concept study, we present a smartphone- and cloud-based artificial intelligence quantitative analysis system (SCAISY) for relative quantification of SARS-CoV-2-specific IgG antibody lateral flow assays that enables rapid evaluation (<60 s) of test strips. By capturing an image with a smartphone camera, SCAISY quantitatively analyzes antibody levels and provides results to the user. We analyzed changes in antibody levels over time in more than 248 individuals, including vaccine type, number of doses, and infection status, with a standard deviation of less than 10%. We also tracked antibody levels in six participants before and after SARS-CoV-2 infection. Finally, we examined the effects of lighting conditions, camera angle, and smartphone type to ensure consistency and reproducibility. We found that images acquired between 45° and 90° provided accurate results with a small standard deviation and that all illumination conditions provided essentially identical results within the standard deviation. A statistically significant correlation was observed (Spearman correlation coefficient: 0.59, p = 0.008; Pearson correlation coefficient: 0.56, p = 0.012) between the OD450 values of the enzyme-linked immunosorbent assay and the antibody levels obtained by SCAISY. This study suggests that SCAISY is a simple and powerful tool for real-time public health surveillance, enabling the acceleration of quantifying SARS-CoV-2-specific antibodies generated by either vaccination or infection and tracking of personal immunity levels.

Sample-to-answer platform for the clinical evaluation of COVID-19 using a deep learning-assisted smartphone-based assay

Since many lateral flow assays (LFA) are tested daily, the improvement in accuracy can greatly impact individual patient care and public health. However, current self-testing for COVID-19 detection suffers from low accuracy, mainly due to the LFA sensitivity and reading ambiguities. Here, we present deep learning-assisted smartphone-based LFA (SMART^AI-LFA) diagnostics to provide accurate decisions with higher sensitivity. Combining clinical data learning and two-step algorithms enables a cradle-free on-site assay with higher accuracy than the untrained individuals and human experts via blind tests of clinical data (n = 1500). We acquired 98% accuracy across 135 smartphone application-based clinical tests with different users/smartphones. Furthermore, with more low-titer tests, we observed that the accuracy of SMART^AI-LFA was maintained at over 99% while there was a significant decrease in human accuracy, indicating the reliable performance of SMART^AI-LFA. We envision a smartphone-based SMART^AI-LFA that allows continuously enhanced performance by adding clinical tests and satisfies the new criterion for digitalized real-time diagnostics.

Fluorophore-encapsulated nanobeads for on-site, rapid, and sensitive lateral flow assay

Since December 2019, the rapid and sensitive detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a priority for public health. Although the lateral flow assay (LFA) sensor has emerged as a rapid and on-site SARS-CoV-2 detection technique, the conventional approach of using gold nanoparticles for the signaling probe had limitations in increasing the sensitivity of the sensor. Herein, our newly suggested methodology to improve the performance of the LFA system could amplify the sensor signal with a facile fabrication method by concentrating fluorescent organic molecules. A large Stokes shift fluorophore (single benzene) was encapsulated into polystyrene nanobeads to enhance the fluorescence intensity of the probe for LFA sensor, which was detected on the test line with a longpass filter under ultraviolet light irradiation. This approach provides comparatively high sensitivity with the limit of detection of 1 ng mL^-1 for the SARS-CoV-2 spike protein and a fast detection process, which takes less than 20 min. Furthermore, our sensor showed higher performance than gold nanoparticle-based commercial rapid diagnostics test kits in clinical tests, proving that this approach is more suitable and reliable for the sensitive and rapid detection of viruses, bacteria, and other hazardous materials.

Moving toward smart biomedical sensing

The development of novel biomedical sensors as highly promising devices/tools in early diagnosis and therapy monitoring of many diseases and disorders has recently witnessed unprecedented growth; more and faster than ever. Nonetheless, on the eve of Industry 5.0 and by learning from defects of current sensors in smart diagnostics of pandemics, there is still a long way to go to achieve the ideal biomedical sensors capable of meeting the growing needs and expectations for smart biomedical/diagnostic sensing through eHealth systems. Herein, an overview is provided to highlight the importance and necessity of an inevitable transition in the era of digital health/Healthcare 4.0 towards smart biomedical/diagnostic sensing and how to approach it via new digital technologies including Internet of Things (IoT), artificial intelligence, IoT gateways (smartphones, readers), etc. This review will bring together the different types of smartphone/reader-based biomedical sensors, which have been employing for a wide variety of optical/electrical/electrochemical biosensing applications and paving the way for future eHealth diagnostic devices by moving towards smart biomedical sensing. Here, alongside highlighting the characteristics/criteria that should be met by the developed sensors towards smart biomedical sensing, the challenging issues ahead are delineated along with a comprehensive outlook on this extremely necessary field.

Double Competitive Immunodetection of Small Analyte: Realization for Highly Sensitive Lateral Flow Immunoassay of Chloramphenicol

A new scheme of reagents interaction for lateral flow immunoassay (LFIA) is proposed, which combines the features of competitive and sandwich assay and provides highly sensitive detection of low-molecular-weight analytes. Namely, the antigen in the sample interferes with the formation of the antibody (on the membrane)–hapten-protein–antibody (on the nanoparticle-marker) complex, competing with hapten-protein conjugate in both reactions. The proposed scheme was modelled using COPASI software, with a prediction of limit of detection (LOD) decrease by one order of magnitude compared to the standard competitive LFIA. This feature was experimentally confirmed for the detection of chloramphenicol (CAP) in honey. When tested in spiked honey, the visual LOD was 50 ng/mL for the common scheme and 5 ng/mL for the proposed scheme. Instrumental LOD was 300 pg/mL (1.2 µg/kg in conversion per sample weight of honey) in the standard scheme and 20 pg/mL (80 ng/kg in conversion per sample weight of honey) in the proposed scheme.

Paper-based genetic assays with bioconjugated gold nanorods and an automated readout pipeline

Paper-based biosensors featuring immunoconjugated gold nanoparticles have gained extraordinary momentum in recent times as the platform of choice in key cases of field applications, including the so-called rapid antigen tests for SARS-CoV-2. Here, we propose a revision of this format, one that may leverage on the most recent advances in materials science and data processing. In particular, we target an amplifiable DNA rather than a protein analyte, and we replace gold nanospheres with anisotropic nanorods, which are intrinsically brighter by a factor of ~ 10, and multiplexable. By comparison with a gold-standard method for dot-blot readout with digoxigenin, we show that gold nanorods entail much faster and easier processing, at the cost of a higher limit of detection (from below 1 to 10 ppm in the case of plasmid DNA containing a target transgene, in our current setup). In addition, we test a complete workflow to acquire and process photographs of dot-blot membranes with custom-made hardware and regression tools, as a strategy to gain more analytical sensitivity and potential for quantification. A leave-one-out approach for training and validation with as few as 36 sample instances already improves the limit of detection reached by the naked eye by a factor around 2. Taken together, we conjecture that the synergistic combination of new materials and innovative tools for data processing may bring the analytical sensitivity of paper-based biosensors to approach the level of lab-grade molecular tests.

Highly portable quantitative screening test for prostate-specific antigen at point of care

Prostate cancer (PCa) is the second most diagnosed cancer among men. Targeted PCa screening may decrease PCa-specific mortality. Prostate-specific antigen (PSA) is the most reliable and widely accepted tumor biomarker for screening and monitoring PCa status. However, in many settings, quantification of serum PSA requires access to centralized laboratories. In this study, we describe a proof-of-concept rapid test combined with a highly portable Cube^™ reader for quantification of total PSA from a drop of serum within 20 min. We demonstrated the application of gold nanoshells as a label for lateral flow assay with significant increase in the measured colorimetric signal intensity to achieve five times lower detection limit when compared to the traditionally used 40 nm gold nanosphere labels, without a need for any additional signal amplification steps. We first optimized and evaluated the performance of the assay with commercially available total PSA calibrators. For initial validation with commercially available ACCESS Hybritech PSA calibrator, a detection range of 0.5-150 ng/mL was achieved. We compared the performance of our total PSA test with IMMULITE analyzer for quantification of total PSA in archived human serum samples. On preliminary testing with archived serums samples and comparison with IMMULITE total PSA assay, a correlation of 0.95 (p < .0001) was observed. The highly portable quantitative screening test for PSA described in this study has the potential to make PCa screening more accessible where diagnostic labs and automated immunoassay systems are not available, to reduce therapeutic turnaround time, to streamline clinical care, and to direct patient care for both initial screening and for post-treatment monitoring of patients.

A Cross-Disciplinary View of Testing and Bioinformatic Analysis of SARS-CoV-2 and Other Human Respiratory Viruses in Pandemic Settings

The SARS-Coronavirus-2 (SARS-CoV-2) infectious disease, COVID-19, has spread rapidly, resulting in a global pandemic with significant mortality. The combination of early diagnosis via rapid screening, contact tracing, social distancing and quarantine has helped to control the pandemic. The absence of real time response and diagnosis is a crucial technology shortfall and is a key reason why current contact tracing methods are inadequate to control spread. In contrast, current information technology combined with a new generation of near-real time tests offers consumer-engaged smartphone-based "lab-in-a-phone" internet-of-things (IoT) connected devices that provide increased pandemic monitoring. This review brings together key aspects required to create an entire global diagnostic ecosystem. Cross-disciplinary understanding and integration of both mechanisms and technologies for effective detection, incidence mapping and disease containment in near real-time is summarized. Available measures to monitor and/or sterilize surfaces, next-generation laboratory and smartphone-based diagnostic approaches can be brought together and networked for instant global monitoring that informs Public Health policy. Cloud-based analysis enabling real-time mapping will enable future pandemic control, drive the suppression and elimination of disease spread, saving millions of lives globally. A new paradigm is introduced - scaled and multiple diagnostics for mapping and spreading of a pandemic rather than traditional accumulation of individual measurements. This can do away with the need for ultra-precise and ultra-accurate analysis by taking mass measurements that can relax tolerances and build resilience through networked analytics and informatics, the basis for novel swarm diagnostics. These include addressing ethical standards, local, national and international collaborative engagement, multidisciplinary and analytical measurements and standards, and data handling and storage protocols.

Recurrence monitoring for ovarian cancer using a cell phone-integrated paper device to measure the ovarian cancer biomarker HE4/CRE ratio in urine

Ovarian cancer has a poor cure rate and rates of relapse are high. Current recurrence detection is limited by non-specific methods such as blood testing and ultrasound. Based on reports that human epididymis four (HE4) / creatinine (CRE) ratios found in urine are elevated in ovarian cancers, we have developed a paper-based device that combines lateral flow technology and cell phone analysis to quantitatively measure HE4/CRE. Surrogate samples were used to test the performance over clinically expected HE4/CRE ratios. For HE4/CRE ratios of 2 to 47, the percent error was found to be 16.0% on average whether measured by a flatbed scanner or cell phone. There was not a significant difference between the results from the cell phone or scanner. Based on published studies, error in this method was less than the difference required to detect recurrence. This promising new tool, with further development, could be used at home or in low-resource settings to provide timely detection of ovarian cancer recurrence.

Potential of Point-of-Care and At-Home Assessment of Immune Status via Rapid Cytokine Detection and Questionnaire-Based Anamnesis

Monitoring the immune system's status has emerged as an urgent demand in critical health conditions. The circulating cytokine levels in the blood reflect a thorough insight into the immune system status. Indeed, measuring one cytokine may deliver more information equivalent to detecting multiple diseases at a time. However, if the reported cytokine levels are interpreted with considering lifestyle and any comorbid health conditions for the individual, this will promote a more precise assessment of the immune status. Therefore, this study addresses the most recent advanced assays that deliver rapid, accurate measuring of the cytokine levels in human blood, focusing on add-on potentials for point-of-care (PoC) or personal at-home usage, and investigates existing health questionnaires as supportive assessment tools that collect all necessary information for the concrete analysis of the measured cytokine levels. We introduced a ten-dimensional featuring of cytokine measurement assays. We found 15 rapid cytokine assays with assay time less than 1 h; some could operate on unprocessed blood samples, while others are mature commercial products available in the market. In addition, we retrieved several health questionnaires that addressed various health conditions such as chronic diseases and psychological issues. Then, we present a machine learning-based solution to determine what makes the immune system fit. To this end, we discuss how to employ topic modeling for deriving the definition of immune fitness automatically from literature. Finally, we propose a prototype model to assess the fitness of the immune system through leveraging the derived definition of the immune fitness, the cytokine measurements delivered by a rapid PoC immunoassay, and the complementary information collected by the health questionnaire about other health factors. In conclusion, we discovered various advanced rapid cytokine detection technologies that are promising candidates for point-of-care or at-home usage; if paired with a health status questionnaire, the assessment of the immune system status becomes solid and we demonstrated potentials for promoting the assessment tool with data mining techniques.

A Semi-Quantitative Isothermal Diagnostic Assay Utilizing Competitive Amplification

Quantitative diagnostics that are rapid, inexpensive, sensitive, robust, and field-deployable are needed to contain the spread of infectious diseases and inform treatment strategies. While current gold-standard techniques are highly sensitive and quantitative, they are slow and require expensive equipment. Conversely, current rapid field-deployable assays available provide essentially binary information about the presence of the target analyte, not a quantitative measure of concentration. Here, we report the development of a molecular diagnostic test [quantitative recombinase polymerase amplification (qRPA)] that utilizes competitive amplification during a recombinase polymerase amplification (RPA) assay to provide semi-quantitative information on a target nucleic acid. We demonstrate that qRPA can quantify DNA, RNA, and viral titers in HIV and COVID-19 patient samples and that it is more robust to environmental perturbations than traditional RPA. These features make qRPA potentially useful for at-home testing to monitor the progress of viral infections or other diseases.

COVID-19 Biomarkers and Advanced Sensing Technologies for Point-of-Care (POC) Diagnosis

COVID-19, also known as SARS-CoV-2 is a novel, respiratory virus currently plaguing humanity. Genetically, at its core, it is a single-strand positive-sense RNA virus. It is a beta-type Coronavirus and is distinct in its structure and binding mechanism compared to other types of coronaviruses. Testing for the virus remains a challenge due to the small market available for at-home detection. Currently, there are three main types of tests for biomarker detection: viral, antigen and antibody. Reverse Transcription-Polymerase Chain Reaction (RT-PCR) remains the gold standard for viral testing. However, the lack of quantitative detection and turnaround time for results are drawbacks. This manuscript focuses on recent advances in COVID-19 detection that have lower limits of detection and faster response times than RT-PCR testing. The advancements in sensing platforms have amplified the detection levels and provided real-time results for SARS-CoV-2 spike protein detection with limits as low as 1 fg/mL in the Graphene Field Effect Transistor (FET) sensor. Additionally, using multiple biomarkers, detection levels can achieve a specificity and sensitivity level comparable to that of PCR testing. Proper biomarker selection coupled with nano sensing detection platforms are key in the widespread use of Point of Care (POC) diagnosis in COVID-19 detection.

Commercially available rapid diagnostic tests for the detection of high priority pathogens: status and challenges

The ongoing COVID-19 pandemic has shown the importance of having analytical devices that allow a simple, fast, and robust detection of pathogens which cause epidemics and pandemics. The information these devices can collect is crucial for health authorities to make effective decisions to contain the disease's advance. The World Health Organization published a list of primary pathogens that have raised concern as potential causes of future pandemics. Unfortunately, there are no rapid diagnostic tests commercially available and approved by the regulatory bodies to detect most of the pathogens listed by the WHO. This report describes these pathogens, the available detection methods, and highlights areas where more attention is needed to produce rapid diagnostic tests for future pandemic surveillance.

Enhancing the Sensitivity of Lateral Flow Immunoassay by Magnetic Enrichment Using Multifunctional Nanocomposite Probes

For lateral flow immunoassay (LFIA), it is an important challenge to enhance the detection sensitivity to the same level as polymerase chain reaction or enzyme-linked immunosorbent assay to make LFIA pervasive in the field of on-site environmental analysis. We recently demonstrated that the LFIA sensitivity is dramatically enhanced by using Pt-nanoparticle-latex nanocomposite beads (Pt-P2VPs) as probes for the detection of the influenza A (H1N1) antigen compared with using conventional Au colloids as probes. Here, to further enhance the LFIA sensitivity using Pt-P2VPs, superparamagnetic iron oxide nanoparticles (SPIONs) were chemically conjugated to Pt-P2VPs (Pt-P2VP@SPION) to give them magnetic separation capability (enrichment and/or purification). To investigate the effect of magnetic enrichment on the LFIA sensitivity in a sandwich format, the C-reactive protein (CRP) was chosen as a model analyte and anti-CRP antibody (CRPAb)-conjugated Pt-P2VP@SPION (Pt-P2VP@SPION-CRPAb) beads were used as probes. The visual limit of detection (LOD) of LFIA was successfully lowered by increasing the magnetic enrichment factor φ. The minimum LOD under the present experimental conditions was 0.08 ng/mL for φ = 40, which is 26-fold lower than that of the standard Au-nanoparticle-based LFIA. In theory, the LOD can be unlimitedly decreased by just increasing φ. However, the times required for both the antigen-antibody binding reaction and magnetic separation dramatically increase with φ. We also propose solutions to overcome this drawback.

Aptamers as the powerhouse of dot blot assays

Dot blot assays have always been associated with antibodies as the main molecular recognition element, which are widely employed in a myriad of diagnostic applications. With the rising of aptamers as the equivalent molecular recognition elements of antibodies, dot blot assays are also one of the diagnostic avenues that should be scrutinized for their amenability with aptamers as the potential surrogates of antibodies. In this review, the stepwise procedures of an aptamer-based dot blot assays are underscored before reviewing the existing aptamer-based dot blot assays developed so far. Most of the applications center on monitoring the progress of SELEX and as the validatory assays to assess the potency of aptamer candidates. For the purpose of diagnostics, the current effort is still languid and as such possible suggestions to galvanize the move to spur the aptamer-based dot blot assays to a point-of-care arena are discussed.

Has the Flood Entered the Basement? A Systematic Literature Review about Machine Learning in Laboratory Medicine

This article presents a systematic literature review that expands and updates a previous review on the application of machine learning to laboratory medicine. We used Scopus and PubMed to collect, select and analyse the papers published from 2017 to the present in order to highlight the main studies that have applied machine learning techniques to haematochemical parameters and to review their diagnostic and prognostic performance. In doing so, we aim to address the question we asked three years ago about the potential of these techniques in laboratory medicine and the need to leverage a tool that was still under-utilised at that time.

Development of lateral flow assay based on anti-IBDV IgY for the rapid detection of Gumboro disease in poultry

The poultry industry faces serious problems against infectious diseases, including Gumboro, which is caused by contagious bursal disease virus (IBDV). IBDV infects the bursa of Fabricius (BF), a lymphoid organ for controlling the B-cell maturation. Thus, it can trigger the secondary infection's vulnerability, leading to the high mortality and morbidity of the chicken. Moreover, managing the Gumboro post-outbreaks also requires considerable time and costs. Besides vaccination programs, the early detection of IBDV is vital as an outbreak control strategy. The most popular diagnostic tool is a lateral flow immunoassay or a rapid test that meets ASSURED (Affordable, Sensitive, Specific, User-friendly, Rapid and Robust, Equipment-free, and Deliverable to end-users) criteria. In this study, the lateral flow immunoassay was successfully developed based on anti-IBDV IgY as the bio receptor. Anti-IBDV IgY was successfully isolated from Isa Brown's egg yolk. The detection system showed an acceptable affinity against the inactivated IBDV sample (1.5 × 10³ TCID₅₀). In addition, it did not react with avian influenza and Newcastle disease viruses, demonstrating a good specificity of the test.

Simplified formats of modern biosensors: 60 years of using immunochromatographic test systems in laboratory diagnostics

Immunochromatographic test systems known to foreign laboratory diagnostic experts as lateral flow immunoassay (LFIA) are simplified tape formats of modern biosensors. For 60 years, they have been widely used for the rapid detection of target molecules (ligands) in biosubstrates and the diagnosis of many diseases and conditions. The growing popularity of these test systems for providing medical care or diagnostics in developing countries, medical facilities, in emergency situations, as well as for individual home use by patients while monitoring their health are the main factors contributing to the continuous development and improvement of these methods, the emergence of a new generation of formats. The attractiveness and popularity of these fast, easy-to-use, inexpensive and portable diagnostic tools is associated primarily with their high analytical sensitivity and specificity, as well as the ease of interpretation of the results. These qualities have passed the test of time, and today LFIA test systems are fully consistent with the modern world concept of «point-of-care testing», finding wide application not only in medicine, but also in ecology, veterinary medicine, and agriculture. This review will highlight the modern principles of designing the most widely used formats of immunochromatographic test systems for clinical laboratory diagnostics, summarize the main advantages and disadvantages of the method, as well as current achievements and prospects of LFIA technology. Modern innovations aimed at improving the analytical characteristics of LFIA technology are interesting, promising and can bring additional benefits to immunochromatographic platforms that have gained popularity and attractiveness for six decades.

Unraveling the Hook Effect: A Comprehensive Study of High Antigen Concentration Effects in Sandwich Lateral Flow Immunoassays

Sandwich lateral flow immunoassays (LFIAs) are limited at high antigen concentrations by the hook effect, leading to a contradictory decrease in the test line (T) intensity and false-negative results. The hook effect is mainly associated with the loss of T, and research focuses on minimizing this effect. Nevertheless, the control line (C) intensity is also affected at higher analyte concentrations, undesirably influencing the T/C ratio in LFIA readers. The main aim of this work is to identify and understand these high antigen concentration effects in order to develop ubiquitous strategies to interpret and mitigate such effects. Four complementary experiments were performed: performance assessment of three different allergen LFIAs (two for hazelnut, one for peanut) over 0.075-3500 ppm, LFIAs with C only, surface plasmon resonance (SPR) binding experiments on the immobilized control antibody, and smartphone video recording of LFIAs during their development. As antigen concentrations increase, the C signal decreases before the T signal does, suggesting that distinct mechanisms underlie these intensity reductions. Reduced binding at the C occurred even in the absence of T, so the upfront T does not explain the loss of C. SPR confirmed that the C antibody favors binding with free labeled antibody compared with a labeled antibody-analyte complex, indicating that in antigen excess, binding is reduced at C before T. Finally, a smartphone-based video method was developed for dynamically monitoring the LFIA development in real time to distinguish between different concentration-dependent effects. Digitally analyzing the data allows clear differentiation of highly positive samples and false-negative samples and can indicate whether the LFIA is in the dynamic working range or at critically high concentrations. The aim of this work is to identify and understand such high antigen concentration effects in order to develop ubiquitous strategies to interpret and mitigate such effects.

Six decades of lateral flow immunoassay: from determining metabolic markers to diagnosing COVID-19

Technologies based on lateral flow immunoassay (LFIA), known in some countries of the world as immunochromatographic tests, have been successfully used for the last six decades in diagnostics of many diseases and conditions as they allow rapid detection of molecular ligands in biosubstrates. The popularity of these diagnostic platforms is constantly increasing in healthcare facilities, particularly those facing limited budgets and time, as well as in household use for individual health monitoring. The advantages of these low-cost devices over modern laboratory-based analyzers come from their availability, opportunity of rapid detection, and ease of use. The attractiveness of these portable diagnostic tools is associated primarily with their high analytical sensitivity and specificity, as well as with the easy visual readout of results. These qualities explain the growing popularity of LFIA in developing countries, when applied at small hospitals, in emergency situations where screening and monitoring health condition is crucially important, and as well as for self-testing of patients. These tools have passed the test of time, and now LFIA test systems are fully consistent with the world's modern concept of ‘point-of-care testing’, finding a wide range of applications not only in human medicine, but also in ecology, veterinary medicine, and agriculture. The extensive opportunities provided by LFIA contribute to the continuous development and improvement of this technology and to the creation of new-generation formats. This review will highlight the modern principles of design of the most widely used formats of test-systems for clinical laboratory diagnostics, summarize the main advantages and disadvantages of the method, as well as the current achievements and prospects of the LFIA technology. The latest innovations are aimed at improving the analytical performance of LFIA platforms for the diagnosis of bacterial and viral infections, including COVID-19.