An Internet-of-Disease System for COVID-19 Testing Using Saliva by an AI-Controlled Microfluidic ELISA Device

Polymer-Supported Graphene Sheet as a Vertically Conductive Anode of Lithium-Ion Battery

The increasing demand for electric vehicles necessitates the development of cost-effective, mass-producible, long-lasting, and highly conductive batteries. Making this kind of battery is exceedingly tricky. This study introduces an innovative fabrication technique utilizing a laser-induced graphene (LIG) approach on commercial Kapton film to create hexagonal pores. These pores form vertical conduction paths for electron and ion transportation during lithiation and delithiation, significantly enhancing conductivity. The nongraphitized portion of the Kapton film makes it a binder-less, free-standing electrode, providing mechanical stability. Various analytical techniques, including scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), Raman spectroscopy, and atomic force microscopy (AFM) are utilized to confirm the transformation of a 3D porous graphene sheet from a commercial Kapton film. Cross-sectional SEM images verify the vertical connections. The specific capacity of 581 mAh g-1 is maintained until the end, with 99% coulombic efficiency at 0.1C. This simple manufacturing method paves the pathway for future LIG-based, cost-effective, lightweight, mass-producible, long-lasting, vertically conductive electrodes for lithium-ion batteries.

Near-infrared responsive gold nanorods for highly sensitive colorimetric and photothermal lateral flow immuno-detection of SARS-CoV-2

The highly infectious characteristics of coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), highlight the necessity of sensitive and rapid nucleocapsid (N) protein-based antigen testing for early triage and epidemic management. In this study, a colorimetric and photothermal dual-mode lateral flow immunoassay (LFIA) platform for the rapid and sensitive detection of the SARS-CoV-2 N protein was developed based on gold nanorods (GNRs), which possessed tunable local surface plasma resonance (LSPR) absorption peaks from UV-visible to near-infrared (NIR). The LSPR peak was adjusted to match the NIR emission laser 808 nm by controlling the length-to-diameter ratio, which could maximize the photothermal conversion efficiency and achieve photothermal detection signal amplification. Qualitative detection of SARS-CoV-2 N protein was achieved by observing the strip color, and the limit of detection was 2 ng mL-1, while that for photothermal detection was 0.096 ng mL-1. Artificial saliva samples spiked with the N protein were analyzed with the recoveries ranging from 84.38% to 107.72%. The intra-assay and inter-assay coefficients of variation were 6.76% and 10.39%, respectively. We further evaluated the reliability of this platform by detecting 40 clinical samples collected from nasal swabs, and the results matched well with that of nucleic acid detection (87.5%). This method shows great promise in early disease diagnosis and screening.

Microneedle patch-based enzyme-linked immunosorbent assay to quantify protein biomarkers of tuberculosis

There is a clinical need for differential diagnosis of the latent versus active stages of tuberculosis (TB) disease by a simple-to-administer test. Alpha-crystallin (Acr) and early secretory antigenic target-6 (ESAT-6) are protein biomarkers associated with the latent and active stages of TB, respectively, and could be used for differential diagnosis. We therefore developed a microneedle patch (MNP) designed for application to the skin to quantify Acr and ESAT-6 in dermal interstitial fluid by enzyme-linked immunosorbent assay (ELISA). We fabricated mechanically strong microneedles made of polystyrene and coated them with capture antibodies against Acr and ESAT-6. We then optimized assay sensitivity to achieve a limit of detection of 750 pg/ml and 3,020 pg/ml for Acr and ESAT-6, respectively. This study demonstrates the feasibility of an MNP-based ELISA for differential diagnosis of latent TB disease.

Immunity testing against COVID-19 from blood by an IoT-enabled and AI-controlled multiplexed microfluidic platform

Developing herd immunity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is pivotal for changing the course of the coronavirus disease 2019 (COVID-19) pandemic. However, the uncertainty of vaccine-induced immunity development and inequitable distribution of vaccines hinders the global vaccination effort. Therefore, routine serodiagnosis and ensuring effective vaccination on a time-to-time basis are essential for developing sustainable immunity against SARS-CoV-2. Herein, an AI-driven multiplexed point-of-care testing (POCT) platform capable of utilizing a microfluidic lab-on-a-chip (LOC) device has been proposed for analyzing bodily fluid response against SARS-CoV-2. The developed platform has been successfully utilized for the quantification of SARS-CoV-2 S-protein, N-protein, IgM, and IgG from human blood samples with limits of detection (LODs) as low as 0.01, 0.02, 0.69, and 0.61 ng/mL respectively. Finally, a data-receptive web-based dashboard system has been developed and demonstrated to provide real-time, territory-specific analysis of herd immunity progress from the test results. Thus, the proposed platform could be an imperative tool for healthcare authorities to analyze and restrain ongoing COVID-19 outbreaks or similar pandemics in the future by ensuring effective immunization.

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.

Microfluidic-based technologies for diagnosis, prevention, and treatment of COVID-19: recent advances and future directions

The COVID-19 pandemic has posed significant challenges to existing healthcare systems around the world. The urgent need for the development of diagnostic and therapeutic strategies for COVID-19 has boomed the demand for new technologies that can improve current healthcare approaches, moving towards more advanced, digitalized, personalized, and patient-oriented systems. Microfluidic-based technologies involve the miniaturization of large-scale devices and laboratory-based procedures, enabling complex chemical and biological operations that are conventionally performed at the macro-scale to be carried out on the microscale or less. The advantages microfluidic systems offer such as rapid, low-cost, accurate, and on-site solutions make these tools extremely useful and effective in the fight against COVID-19. In particular, microfluidic-assisted systems are of great interest in different COVID-19-related domains, varying from direct and indirect detection of COVID-19 infections to drug and vaccine discovery and their targeted delivery. Here, we review recent advances in the use of microfluidic platforms to diagnose, treat or prevent COVID-19. We start by summarizing recent microfluidic-based diagnostic solutions applicable to COVID-19. We then highlight the key roles microfluidics play in developing COVID-19 vaccines and testing how vaccine candidates perform, with a focus on RNA-delivery technologies and nano-carriers. Next, microfluidic-based efforts devoted to assessing the efficacy of potential COVID-19 drugs, either repurposed or new, and their targeted delivery to infected sites are summarized. We conclude by providing future perspectives and research directions that are critical to effectively prevent or respond to future pandemics.

Rapid Detection of SARS-CoV-2 Variants of Concern by Genomic Surveillance Techniques

This chapter describes the application of genomic, transcriptomic, proteomic, and metabolomic methods in the study of SARS-CoV-2 variants of concern. We also describe the important role of machine learning tools to identify the most significant biomarker signatures and discuss the latest point-of-care devices that can be used to translate these findings to the physician's office or to bedside care. The main emphasis is placed on increasing our diagnostic capacity and predictability of disease outcomes to guide the most appropriate treatment strategies.