Fractal LAMP: Label-Free Analysis of Fractal Precipitate for Digital Loop-Mediated Isothermal Nucleic Acid Amplification

Nucleic Acid Plate Culture: Label-Free and Naked-Eye-Based Digital Loop-Mediated Isothermal Amplification in Hydrogel with Machine Learning

Digital nucleic acid amplification enables the absolute quantification of single molecules. However, due to the ultrasmall reaction volume in the digital system (i.e., short light path), most digital systems are limited to fluorescence signals, while label-free and naked-eye readout remain challenging. In this work, we report a digital nucleic acid plate culture method for label-free, ultrasimple, and naked-eye nucleic acid analysis. As simple as the bacteria culture, the nanoconfined digital loop-mediated isothermal amplification was performed by using polyacrylamide (PAM) hydrogel as the amplification matrix. The nanoconfinement of PAM hydrogel with an ionic polymer chain can remarkably accelerate the amplification of target nucleic acids and the growth of inorganic byproducts, namely, magnesium pyrophosphate particles (MPPs). Compared to that in aqueous solutions, MPPs trapped in the hydrogel with enhanced light scattering characteristics are clearly visible to the naked eye, forming white "colony" spots that can be simply counted in a label-free and instrument-free manner. The MPPs can also be photographed by a smartphone and automatically counted by a machine-learning algorithm to realize the absolute quantification of antibiotic-resistant pathogens in diverse real samples.

Advances, challenges, and opportunities for food safety analysis in the isothermal nucleic acid amplification/CRISPR-Cas12a era

Global food safety stands out as a prominent public concern, affecting populations worldwide. The recurrent challenge of food safety incidents reveals the need for a robust inspection framework. In recent years, the integration of isothermal nucleic acid amplification with CRISPR-Cas12a techniques has emerged as a promising tool for molecular detection of food hazards, presenting next generation of biosensing for food safety detection. This paper provides a comprehensive review of the current state of research on the synergistic application of isothermal nucleic acid amplification and CRISPR-Cas12a technology in the field of food safety. This innovative combination not only enriches the analytical tools, but also improving assay performance such as sensitivity and specificity, addressing the limitations of traditional methods. The review summarized various detection methodologies by the integration of isothermal nucleic acid amplification and CRISPR-Cas12a technology for diverse food safety concerns, including pathogenic bacterium, viruses, mycotoxins, food adulteration, and genetically modified foods. Each section elucidates the specific strategies employed and highlights the advantages conferred. Furthermore, the paper discussed the challenges faced by this technology in the context of food safety, offering insightful discussions on potential solutions and future prospects.

StratoLAMP: Label-free, multiplex digital loop-mediated isothermal amplification based on visual stratification of precipitate

Multiplex, digital nucleic acid detections have important biomedical applications, but the multiplexity of existing methods is predominantly achieved using fluorescent dyes or probes, making the detection complicated and costly. Here, we present the StratoLAMP for label-free, multiplex digital loop-mediated isothermal amplification based on visual stratification of the precipitate byproduct. The StratoLAMP designates two sets of primers with different concentrations to achieve different precipitate yields when amplifying different nucleic acid targets. In the detection, deep learning image analysis is used to stratify the precipitate within each droplet and determine the encapsulated targets for nucleic acid quantification. We investigated the effect of the amplification reagents and process on the precipitate generation and optimized the assay conditions. We then implemented a deep-learning image analysis pipeline for droplet detection, achieving an overall accuracy of 94.3%. In the application, the StratoLAMP successfully achieved the simultaneous quantification of two nucleic acid targets with high accuracy. By eliminating the need for fluorescence, StratoLAMP represents a unique concept toward label-free, multiplex nucleic acid assays and an analytical tool with great cost-effectiveness.

Advanced design and applications of digital microfluidics in biomedical fields: An update of recent progress

Significant breakthroughs have been made in digital microfluidic (DMF)-based technologies over the past decades. DMF technology has attracted great interest in bioassays depending on automatic microscale liquid manipulations and complicated multi-step processing. In this review, the recent advances of DMF platforms in the biomedical field were summarized, focusing on the integrated design and applications of the DMF system. Firstly, the electrowetting-on-dielectric principle, fabrication of DMF chips, and commercialization of the DMF system were elaborated. Then, the updated droplets and magnetic beads manipulation strategies with DMF were explored. DMF-based biomedical applications were comprehensively discussed, including automated sample preparation strategies, immunoassays, molecular diagnosis, blood processing/testing, and microbe analysis. Emerging applications such as enzyme activity assessment and DNA storage were also explored. The performance of each bioassay was compared and discussed, providing insight into the novel design and applications of the DMF technology. Finally, the advantages, challenges, and future trends of DMF systems were systematically summarized, demonstrating new perspectives on the extensive applications of DMF in basic research and commercialization.

Single-molecule RNA capture-assisted droplet digital loop-mediated isothermal amplification for ultrasensitive and rapid detection of infectious pathogens

To minimize and control the transmission of infectious diseases, a sensitive, accurate, rapid, and robust assay strategy for application on-site screening is critical. Here, we report single-molecule RNA capture-assisted digital RT-LAMP (SCADL) for point-of-care testing of infectious diseases. Target RNA was captured and enriched by specific capture probes and oligonucleotide probes conjugated to magnetic beads, replacing laborious RNA extraction. Droplet generation, amplification, and the recording of results are all integrated on a microfluidic chip. In assaying commercial standard samples, quantitative results precisely corresponded to the actual concentration of samples. This method provides a limit of detection of 10 copies mL-1 for the N gene within 1 h, greatly reducing the need for skilled personnel and precision instruments. The ultrasensitivity, specificity, portability, rapidity and user-friendliness make SCADL a competitive candidate for the on-site screening of infectious diseases.

Integrated Sensing Chip for Ultrasensitive Label-Free Detection of the Products of Loop-Mediated Isothermal Amplification

Loop-mediated isothermal amplification (LAMP) is a nucleic acid amplification technique that has been widely used for the detection of pathogens in many organisms. Current LAMP-based sensors usually require the LAMP products to be labeled in order for them to be detected. Here, we present a novel label-free LAMP chip, which consists of a nanopore thin-film sensor embedded inside a LAMP reaction chamber. A fraction of LAMP primers is immobilized on the sensor surface, allowing the LAMP products to be synthesized and bound to the sensor surface via immobilized primers. After the LAMP reaction components are removed from the reaction chamber, the amplified LAMP products bound to the sensor surface give rise to significantly increased transducing signals, which can be measured by a portable optical spectrometer through an optical fiber probe. As a demonstration, we used the LAMP chip to detect the causal agent of late blight, Phytophthora infestans, which is one of the most devastating plant pathogens and poses a major threat to sustainable crop production worldwide. We show that this chip can detect as low as 1 fg/μL of P. infestans DNA in 30 min, which corresponds to an attomolar level of 1.6 × 10-6 attomole/μL and is at least 10 times more sensitive than the currently available methods. This label-free sensing technology holds great promise to open up a new avenue for ultrasensitive, highly specific, rapid, and cost-effective point-of-care diagnostics of plant, animal, human, and foodborne pathogens.

Microsystem Advances through Integration with Artificial Intelligence

Microfluidics is a rapidly growing discipline that involves studying and manipulating fluids at reduced length scale and volume, typically on the scale of micro- or nanoliters. Under the reduced length scale and larger surface-to-volume ratio, advantages of low reagent consumption, faster reaction kinetics, and more compact systems are evident in microfluidics. However, miniaturization of microfluidic chips and systems introduces challenges of stricter tolerances in designing and controlling them for interdisciplinary applications. Recent advances in artificial intelligence (AI) have brought innovation to microfluidics from design, simulation, automation, and optimization to bioanalysis and data analytics. In microfluidics, the Navier-Stokes equations, which are partial differential equations describing viscous fluid motion that in complete form are known to not have a general analytical solution, can be simplified and have fair performance through numerical approximation due to low inertia and laminar flow. Approximation using neural networks trained by rules of physical knowledge introduces a new possibility to predict the physicochemical nature. The combination of microfluidics and automation can produce large amounts of data, where features and patterns that are difficult to discern by a human can be extracted by machine learning. Therefore, integration with AI introduces the potential to revolutionize the microfluidic workflow by enabling the precision control and automation of data analysis. Deployment of smart microfluidics may be tremendously beneficial in various applications in the future, including high-throughput drug discovery, rapid point-of-care-testing (POCT), and personalized medicine. In this review, we summarize key microfluidic advances integrated with AI and discuss the outlook and possibilities of combining AI and microfluidics.

CoID-LAMP: Color-Encoded, Intelligent Digital LAMP for Multiplex Nucleic Acid Quantification

Multiplex, digital nucleic acid tests have important biomedical applications, but existing methods mostly use fluorescent probes that are target-specific and difficult to optimize, limiting their widespread applications. Here, we report color-encoded, intelligent digital loop-mediated isothermal amplification (CoID-LAMP) for the coidentification of multiple nucleic acid targets. CoID-LAMP supplements different primer solutions with different dyes, generates primer droplets and sample droplets, and collectively pairs these two types of droplets in a microwell array device to perform LAMP. After imaging, the droplet colors were analyzed to decode the primer information, and the precipitate byproducts within droplets were detected to determine the target occupancy and calculate the concentrations. We first established an image analysis pipeline based on a deep learning algorithm for reliable droplet detection and validated the analytical performance in nucleic acid quantification. We then implemented CoID-LAMP using fluorescent dyes as the coding materials and established an 8-plex digital nucleic acid assay, confirming the reliable coding performance and the capability of multiplex nucleic acid quantification. We further implemented CoID-LAMP using brightfield dyes for a 4-plex assay, suggesting that the assay could be realized solely by brightfield imaging with minimal demand on the optics. Leveraging the advantages of droplet microfluidics in multiplexing and deep learning in intelligent image analysis, CoID-LAMP offers a useful tool for multiplex nucleic acid quantification.

Deep-dLAMP: Deep Learning-Enabled Polydisperse Emulsion-Based Digital Loop-Mediated Isothermal Amplification

Digital nucleic acid amplification tests enable absolute quantification of nucleic acids, but the generation of uniform compartments and reading of the fluorescence requires specialized instruments that are costly, limiting their widespread applications. Here, the authors report deep learning-enabled polydisperse emulsion-based digital loop-mediated isothermal amplification (deep-dLAMP) for label-free, low-cost nucleic acid quantification. deep-dLAMP performs LAMP reaction in polydisperse emulsions and uses a deep learning algorithm to segment and determine the occupancy status of each emulsion in images based on precipitated byproducts. The volume and occupancy data of the emulsions are then used to infer the nucleic acid concentration based on the Poisson distribution. deep-dLAMP can accurately predict the sizes and occupancy status of each emulsion and provide accurate measurements of nucleic acid concentrations with a limit of detection of 5.6 copies µl^-1 and a dynamic range of 37.2 to 11000 copies µl^-1 . In addition, deep-dLAMP shows robust performance under various parameters, such as the vortexing time and image qualities. Leveraging the state-of-the-art deep learning models, deep-dLAMP represents a significant advancement in digital nucleic acid tests by significantly reducing the instrument cost. We envision deep-dLAMP would be readily adopted by biomedical laboratories and be developed into a point-of-care digital nucleic acid test system.

High-throughput selection of cells based on accumulated growth and division using PicoShell particles

Production of high-energy lipids by microalgae may provide a sustainable energy source that can help tackle climate change. However, microalgae engineered to produce more lipids usually grow slowly, leading to reduced overall yields. Unfortunately, culture vessels used to select cells based on growth while maintaining high biomass production, such as well plates, water-in-oil droplet emulsions, and nanowell arrays, do not provide production-relevant environments that cells experience in scaled-up cultures (e.g., bioreactors or outdoor cultivation farms). As a result, strains that are developed in the laboratory may not exhibit the same beneficial phenotypic behavior when transferred to industrial production. Here, we introduce PicoShells, picoliter-scale porous hydrogel compartments, that enable >100,000 individual cells to be compartmentalized, cultured in production-relevant environments, and selected based on growth and bioproduct accumulation traits using standard flow cytometers. PicoShells consist of a hollow inner cavity where cells are encapsulated and a porous outer shell that allows for continuous solution exchange with the external environment. PicoShells allow for cell growth directly in culture environments, such as shaking flasks and bioreactors. We experimentally demonstrate that Chlorella sp., Saccharomyces cerevisiae, and Chinese hamster ovary cells, used for bioproduction, grow to significantly larger colony sizes in PicoShells than in water-in-oil droplet emulsions (P < 0.05). We also demonstrate that PicoShells containing faster dividing and growing Chlorella clonal colonies can be selected using a fluorescence-activated cell sorter and regrown. Using the PicoShell process, we select a Chlorella population that accumulates chlorophyll 8% faster than does an unselected population after a single selection cycle.

Exploiting machine learning for bestowing intelligence to microfluidics

Intelligent microfluidics is an emerging cross-discipline research area formed by combining microfluidics with machine learning. It uses the advantages of microfluidics, such as high throughput and controllability, and the powerful data processing capabilities of machine learning, resulting in improved systems in biotechnology and chemistry. Compared to traditional microfluidics using manual analysis methods, intelligent microfluidics needs less human intervention, and results in a more user-friendly experience with faster processing. There is a paucity of literature reviewing this burgeoning and highly promising cross-discipline. Therefore, we herein comprehensively and systematically summarize several aspects of microfluidic applications enabled by machine learning. We list the types of microfluidics used in intelligent microfluidic applications over the last five years, as well as the machine learning algorithms and the hardware used for training. We also present the most recent advances in key technologies, developments, challenges, and the emerging opportunities created by intelligent microfluidics.

Microfluidic Biosensor for Rapid Nucleic Acid Quantitation Based on Hyperspectral Interferometric Amplicon-Complex Analysis

Nucleic acid detection plays a vital role in both biomedical research and clinical medicine. The temperature circulation changes of the widely used polymerase chain reaction technique are time-consuming and technically challenging for system development. Recombinase polymerase amplification (RPA) is an isothermal method for rapid nucleic acid detection. However, current RPA amplicon detection methods are complicated and expensive and easily generate false positives, restricting the promotion of RPA techniques. In this work, a hyperspectral interferometric amplicon-complex quantitation method is presented, combined with asymmetric dipole complex strategy optical scattering analysis. GelRed dye was utilized to form amplicon-complex particles, and the Fourier domain spectrum computation contributed to complex scattering quantitation. With this method, a supporting microfluidic chip and automatic system were developed to achieve integrated, rapid, quantitative, and miniscule nucleic acid detection. The Plasmodium falciparum dhfr gene was utilized as an example for targeted nucleic acid quantitation and single nucleotide polymorphism detection. The total reaction time was decreased to merely 20 min, and the limit of detection was only 3.17 ng/μL. The minimum measurable concentration of target was 1.68 copies/μL, 31.67 times more sensitive than turbidity detection, and the single reaction chamber was only 9.33 μL. No scattering increase occurred for template-free control, and thus, false positives caused by primer dimers and nonspecific products could be avoided. The experimental results prove that the provided method and system can detect single-base mutations in the dhfr gene and is a reasonable technique for rapid, automatic, and low-cost nucleic acid detection.

Recent advances in detection technologies for COVID-19

Corona Virus Disease 2019 (COVID-19) is a highly infectious respiratory illness that was caused by the SARS-CoV-2. It spread around the world in just a few months and became a worldwide pandemic. Quick and accurate diagnosis of infected patients is very important for controlling transmission. In addition to the commonly used Real-time reverse-transcription polymerase chain reaction (RT-PCR) detection techniques, other diagnostic techniques are also emerging endlessly. This article reviews the current diagnostic methods for COVID-19 and discusses their advantages and disadvantages. It provides an important reference for the diagnosis of COVID-19.

Counting of enzymatically amplified affinity reactions in hydrogel particle-templated drops

Counting of numerous compartmentalized enzymatic reactions underlies quantitative and high sensitivity immunodiagnostic assays. However, digital enzyme-linked immunosorbent assays (ELISA) require specialized instruments which have slowed adoption in research and clinical labs. We present a lab-on-a-particle solution to digital counting of thousands of single enzymatic reactions. Hydrogel particles are used to bind enzymes and template the formation of droplets that compartmentalize reactions with simple pipetting steps. These hydrogel particles can be made at a high throughput, stored, and used during the assay to create ∼500 000 compartments within 2 minutes. These particles can also be dried and rehydrated with sample, amplifying the sensitivity of the assay by driving affinity interactions on the hydrogel surface. We demonstrate digital counting of β-galactosidase enzyme at a femtomolar detection limit with a dynamic range of 3 orders of magnitude using standard benchtop equipment and experiment techniques. This approach can faciliate the development of digital ELISAs with reduced need for specialized microfluidic devices, instruments, or imaging systems.

Statistical energy minimization theory for systems of drop-carrier particles

Drop-carrier particles (DCPs) are solid microparticles designed to capture uniform microscale drops of a target solution without using costly microfluidic equipment and techniques. DCPs are useful for automated and high-throughput biological assays and reactions, as well as single-cell analyses. Surface energy minimization provides a theoretical prediction for the volume distribution in pairwise droplet splitting, showing good agreement with macroscale experiments. We develop a probabilistic pairwise interaction model for a system of such DCPs exchanging fluid volume to minimize surface energy. This leads to a theory for the number of pairwise interactions of DCPs needed to reach a uniform volume distribution. Heterogeneous mixtures of DCPs with different sized particles require fewer interactions to reach a minimum energy distribution for the system. We optimize the DCP geometry for minimal required target solution and uniformity in droplet volume.

Hairpin DNA-Mediated isothermal amplification (HDMIA) techniques for nucleic acid testing

Nucleic acid detection is of great importance in a variety of areas, from life science and clinical diagnosis to environmental monitoring and food safety. Unfortunately, nucleic acid targets are always found in trace amounts and their response signals are difficult to be detected. Amplification mechanisms are then practically needed to either duplicate nucleic acid targets or enhance the detection signals. Polymerase chain reaction (PCR) is one of the most popular and powerful techniques for nucleic acid analysis. But the requirement of costly devices for precise thermo-cycling procedures in PCR has severely hampered the wide applications of PCR. Fortunately, isothermal molecular reactions have emerged as promising alternatives. The past decade has witnessed significant progress in the research of isothermal molecular reactions utilizing hairpin DNA probes (HDPs). Based on the nucleic acid strand interaction mechanisms, the hairpin DNA-mediated isothermal amplification (HDMIA) techniques can be mainly divided into three categories: strand assembly reactions, strand decomposition reactions, and strand creation reactions. In this review, we introduce the basics of HDMIA methods, including the sensing principles, the basic and advanced designs, and their wide applications, especially those benefiting from the utilization of G-quadruplexes and nanomaterials during the past decade. We also discuss the current challenges encountered, highlight the potential solutions, and point out the possible future directions in this prosperous research area.

Fluorometric Paper-Based, Loop-Mediated Isothermal Amplification Devices for Quantitative Point-of-Care Detection of Methicillin-Resistant Staphylococcus aureus (MRSA)

Loop-mediated isothermal amplification (LAMP) has been widely used to detect many infectious diseases. However, minor inconveniences during the steps of adding reaction ingredients and lack of simple color results hinder point-of-care detection. We therefore invented a fluorometric paper-based LAMP by incorporating LAMP reagents, including a biotinylated primer, onto a cellulose membrane paper, with a simple DNA fluorescent dye incubation that demonstrated rapid and accurate results parallel to quantitative polymerase chain reaction (qPCR) methods. This technology allows for instant paper strip detection of methicillin-resistant Staphylococcus aureus (MRSA) in the laboratory and clinical samples. MRSA represents a major public health problem as it can cause infections in different parts of the human body and yet is resistant to commonly used antibiotics. In this study, we optimized LAMP reaction ingredients and incubation conditions following a central composite design (CCD) that yielded the shortest reaction time with high sensitivity. These CCD components and conditions were used to construct the paper-based LAMP reaction by immobilizing the biotinylated primer and the rest of the LAMP reagents to produce the ready-to-use MRSA diagnostic device. Our paper-based LAMP device could detect as low as 10 ag (equivalent to 1 copy) of the MRSA gene mecA within 36-43 min, was evaluated using both laboratory (individual cultures of MRSA and non-MRSA bacteria) and clinical blood samples to be 100% specific and sensitive compared to qPCR results, and had 35 day stability under 25 °C storage. Furthermore, the color readout allows for quantitation of MRSA copies. Hence, this device is applicable for point-of-care MRSA detection.

High-throughput functional profiling of single adherent cells via hydrogel drop-screen

Single-adherent-cell phenotyping on an extracellular matrix (ECM) is essential to determine cellular biological functions, such as morphological adaptations and biomolecule secretions, correlated to medical treatments and metastasis, yet there is no available platform for such high-throughput screening. Here, a novel hydrogel drop-screen device was developed to rapidly measure large-scale single-cell morphologies and multiple secretions on substrates for phenotype profiling. Single cells were first anchored to microfluidically fabricated gelatin particles providing mechanical stimulations similar to those from ECM in vivo. The cellular morphologies were then examined by quantifying the amount of cytoskeleton expressed on the particles. With droplet encapsulation, adherent single-cell multiplexed secretion analysis of a disintegrin and metalloproteinases (ADAMs) and matrix metalloproteinases (MMPs) was conducted at a throughput of ∼102 cells per second, revealing distinct functional heterogeneities associated with extracellular mechanical stimulations. The level of cell heterogeneity increased with increasing substrate stuffiness. Moreover, because of the promising screening capability, a database related to both nontumorigenic and tumorigenic breast cells (MCF10A, MCF-7, and MDA-MB-231) was constructed. The respective cell distributions and heterogeneities based on the morphologies and secreted bioindicators, such as MMP-2, MMP-3, MMP-9, and ADAM-8, were measured and found to correspond to the progress of tumor metastasis.

Fabrication of 3D concentric amphiphilic microparticles to form uniform nanoliter reaction volumes for amplified affinity assays

Reactions performed in uniform microscale volumes have enabled numerous applications in the analysis of rare entities (e.g. cells and molecules). Here, highly monodisperse aqueous droplets are formed by simply mixing microscale multi-material particles, consisting of concentric hydrophobic outer and hydrophilic inner layers, with oil and water. The particles are manufactured in batch using a 3D printed device to co-flow four concentric streams of polymer precursors which are polymerized with UV light. The cross-sectional shapes of the particles are altered by microfluidic nozzle design in the 3D printed device. Once a particle encapsulates an aqueous volume, each "dropicle" provides uniform compartmentalization and customizable shape-coding for each sample volume to enable multiplexing of uniform reactions in a scalable manner. We implement an enzymatically-amplified immunoassay using the dropicle system, yielding a detection limit of <1 pM with a dynamic range of at least 3 orders of magnitude. Multiplexing using two types of shape-coded particles was demonstrated without cross talk, laying a foundation for democratized single-entity assays.

Multiplex Digital MicroRNA Detection Using Cross-Inhibitory DNA Circuits

Ubiquitous post-transcriptional regulators in eukaryotes, microRNAs are currently emerging as promising biomarkers of physiological and pathological processes. Multiplex and digital detection of microRNAs represents a major challenge toward the use of microRNA signatures in clinical settings. The classical reverse transcription polymerase chain reaction quantification approach has important limitations because of the need for thermocycling and a reverse transcription step. Simpler, isothermal alternatives have been proposed, yet none could be adapted in both a digital and multiplex format. This is either because of a lack of sensitivity that forbids single molecule detection or molecular cross-talk reactions that are responsible for nonspecific amplification. Building on an ultrasensitive isothermal amplification mechanism, we present a strategy to suppress cross-talk reactions, allowing for robust isothermal and multiplex detection of microRNA targets. Our approach relies on target-specific DNA circuits interconnected with DNA-encoded inhibitors that repress nonspecific signal amplification. We demonstrate the one-step, isothermal, digital, and simultaneous quantification of various pairs of important microRNA targets.

Current and Perspective Diagnostic Techniques for COVID-19

Since late December 2019, the coronavirus pandemic (COVID-19; previously known as 2019-nCoV) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been surging rapidly around the world. With more than 1,700,000 confirmed cases, the world faces an unprecedented economic, social, and health impact. The early, rapid, sensitive, and accurate diagnosis of viral infection provides rapid responses for public health surveillance, prevention, and control of contagious diffusion. More than 30% of the confirmed cases are asymptomatic, and the high false-negative rate (FNR) of a single assay requires the development of novel diagnostic techniques, combinative approaches, sampling from different locations, and consecutive detection. The recurrence of discharged patients indicates the need for long-term monitoring and tracking. Diagnostic and therapeutic methods are evolving with a deeper understanding of virus pathology and the potential for relapse. In this Review, a comprehensive summary and comparison of different SARS-CoV-2 diagnostic methods are provided for researchers and clinicians to develop appropriate strategies for the timely and effective detection of SARS-CoV-2. The survey of current biosensors and diagnostic devices for viral nucleic acids, proteins, and particles and chest tomography will provide insight into the development of novel perspective techniques for the diagnosis of COVID-19.