Electrochemical SARS-CoV-2 Sensing at Point-of-Care and Artificial Intelligence for Intelligent COVID-19 Management

Protein Stacking on the APTES-Functionalized Pyrochlore Bi2Ru2O7 Clusters for Ultrasensitive and Selective Immunosensing

With their unique physicochemical properties, such as metallic-like conductivity, favorable (electro)catalytic properties, electrochemical stability, and ease of functionalization, pyrochlores have found applications in various fields such as solid oxide fuel cells, batteries, thick film resistors, and temperature sensors; however, there are no reports on their application in electrochemical immunosensing. In this study, we exploited the (electro)catalytic nature and stability of the pyrochlore Bi2Ru2O7 clusters silanized with (3-aminopropyl)triethoxysilane (APTES) to demonstrate their potential for the effective stacking of functional proteins. Characterization of the clusters by XPS disclosed a dual environment of Bi, also indicating the presence of Bi2O3 alongside APTES-Bi2Ru2O7 clusters and, importantly, the predominant involvement of pyrochlore moieties in subsequent protein stacking. After stacking protein A and antibodies, the immunosensor revealed a nearly interference-free operation, high sensitivity, a detection limit of 118 fM SARS-CoV-2 spike protein, and operation in a wide examined concentration range of 10-5-10-1 μg mL-1 with an r2 of 0.98. In combination with a short incubation time of 30 min, the pyrochlore-based immunosensor provides a solid platform for future point-of-need applications.

Recent Plasmonic Gold- and Silver-Assisted Raman Spectra for Advanced SARS-CoV-2 Detection

COVID-19 has become one of the deadliest epidemics in the past years. In efforts to combat the deadly disease besides vaccines, drug therapies, and facemasks, significant focus has been on designing specific methods for the sensitive and accurate detection of SARS-CoV-2. Of these, surface-enhanced Raman scattering (SERS) is an attractive analytical tool for the identification of SARS-CoV-2. SERS is the phenomenon of enhancement of Raman intensity signals from molecular analytes anchored onto the surfaces of roughened plasmonic nanomaterials. This work gives an updated summary of plasmonic gold nanomaterials (AuNMs) and silver nanomaterials (AgNMs)-based SERS technologies to identify SARS-CoV-2. Due to extreme "hot spots" promoting higher electromagnetic fields on their surfaces, different shapes of AuNMs and AgNMs combined with Raman probes have been reviewed for enhancing Raman signals of probe molecules for quantifying the virus. It also reviews progress made recently in the design of certain specific Raman probe molecules capable of imparting characteristic SERS response/tags for SARS-CoV-2 detection.

Liposome-embedded PtCu nanozymes for improved immunoassay of accurate myocardial infarction

Herein, we developed a platinum-copper nano-enzyme-linked immunosorbent assay (NLISA) based split diagnostic platform for the ultrasensitive detection of cardiac troponin I (cTnI). The PtCu nanozyme synthesized by one-pot synthesis exhibited ultra-high peroxidase-like activity (35.17 U mg-1), which was about 4.5 times higher than that of the unmodified Pt nanozyme (8.83 U mg-1). Due to the efficient peroxidase-like activity of the copper-platinum complexed nanozyme, transduction and sequential amplification of cTnI biological signals were achieved in combination with a liposome-embedded amplification strategy. The encapsulation efficiency was calculated by introducing a liposomal bilayer model, which showed that the introduction of a single liposomal molecule could amplify the signal up to 870-fold, thus promising a high sensitivity test. Notably, the dynamic response of cTnI was in the range of 0.1-5000 pg mL-1 with an ultra-low detection limit (0.048 pg mL-1). The developed NLISA analysis system provides a new way to discover efficient and sensitive alternatives to ELISA kits, which can meet the practical needs of community healthcare testing conditions and rapid testing in hospitals.

Artificial intelligence-powered electrochemical sensor: Recent advances, challenges, and prospects

Integrating artificial intelligence (AI) with electrochemical biosensors is revolutionizing medical treatments by enhancing patient data collection and enabling the development of advanced wearable sensors for health, fitness, and environmental monitoring. Electrochemical biosensors, which detect biomarkers through electrochemical processes, are significantly more effective. The integration of artificial intelligence is adept at identifying, categorizing, characterizing, and projecting intricate data patterns. As the Internet of Things (IoT), big data, and big health technologies move from theory to practice, AI-powered biosensors offer significant opportunities for real-time disease detection and personalized healthcare. Still, they also pose challenges such as data privacy, sensor stability, and algorithmic bias. This paper highlights the critical advances in material innovation, biorecognition elements, signal transduction, data processing, and intelligent decision systems necessary for developing next-generation wearable and implantable devices. Despite existing limitations, the integration of AI into biosensor systems shows immense promise for creating future medical devices that can provide early detection and improved patient outcomes, marking a transformative step forward in healthcare technology.

Revolutionary Point-of-Care Wearable Diagnostics for Early Disease Detection and Biomarker Discovery through Intelligent Technologies

Early-stage disease detection, particularly in Point-Of-Care (POC) wearable formats, assumes pivotal role in advancing healthcare services and precision-medicine. Public benefits of early detection extend beyond cost-effectively promoting healthcare outcomes, to also include reducing the risk of comorbid diseases. Technological advancements enabling POC biomarker recognition empower discovery of new markers for various health conditions. Integration of POC wearables for biomarker detection with intelligent frameworks represents ground-breaking innovations enabling automation of operations, conducting advanced large-scale data analysis, generating predictive models, and facilitating remote and guided clinical decision-making. These advancements substantially alleviate socioeconomic burdens, creating a paradigm shift in diagnostics, and revolutionizing medical assessments and technology development. This review explores critical topics and recent progress in development of 1) POC systems and wearable solutions for early disease detection and physiological monitoring, as well as 2) discussing current trends in adoption of smart technologies within clinical settings and in developing biological assays, and ultimately 3) exploring utilities of POC systems and smart platforms for biomarker discovery. Additionally, the review explores technology translation from research labs to broader applications. It also addresses associated risks, biases, and challenges of widespread Artificial Intelligence (AI) integration in diagnostics systems, while systematically outlining potential prospects, current challenges, and opportunities.

Aspects of 6th generation sensing technology: from sensing to sense

The 6th-generation (6G) sensing technology is transforming the ways we perceive and interact with the world in real scenarios. It combines advanced materials, sophisticated algorithms, and connectivity to create intelligent, context-aware systems that can interpret and respond to environmental stimuli with unprecedented accuracy and speed. The key advancements include 1) ultra-sensitive sensors capable of detecting physical, chemical, and biological changes at low concentrations, 2) the integration of artificial intelligence (AI) and machine learning (ML) for enhanced data processing, and 3) the deployment of IoT networks with 5th-generation (5G) for seamless data transmission and real-time analysis. These cutting-edge technologies create immersive environments where devices capture data and anticipate user needs and environmental conditions. The 6G sensing technology has potential applications across sectors like point-of-care (PoC), healthcare, urban planning, and environmental monitoring. The transition from sensing to sense-making represents a paradigm shift, fostering a more intuitive, responsive, and interconnected world. The article provides a comprehensive overview of the current state and prospects of 6G sensing technology, highlighting its transformative potential and the challenges in realizing its full capabilities.

Computational Frontiers in Aptamer-Based Nanomedicine for Precision Therapeutics: A Comprehensive Review

In the rapidly evolving landscape of nanomedicine, aptamers have emerged as powerful molecular tools, demonstrating immense potential in targeted therapeutics, diagnostics, and drug delivery systems. This paper explores the computational features of aptamers in nanomedicine, highlighting their advantages over antibodies, including selectivity, low immunogenicity, and a simple production process. A comprehensive overview of the aptamer development process, specifically the Systematic Evolution of Ligands by Exponential Enrichment (SELEX) process, sheds light on the intricate methodologies behind aptamer selection. The historical evolution of aptamers and their diverse applications in nanomedicine are discussed, emphasizing their pivotal role in targeted drug delivery, precision medicine and therapeutics. Furthermore, we explore the integration of artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), Internet of Medical Things (IoMT), and nanotechnology in aptameric development, illustrating how these cutting-edge technologies are revolutionizing the selection and optimization of aptamers for tailored biomedical applications. This paper also discusses challenges in computational methods for advancing aptamers, including reliable prediction models, extensive data analysis, and multiomics data incorporation. It also addresses ethical concerns and restrictions related to AI and IoT use in aptamer research. The paper examines progress in computer simulations for nanomedicine. By elucidating the importance of aptamers, understanding their superiority over antibodies, and exploring the historical context and challenges, this review serves as a valuable resource for researchers and practitioners aiming to harness the full potential of aptamers in the rapidly evolving field of nanomedicine.

Employing nano-enabled artificial intelligence (AI)-based smart technologies for prediction, screening, and detection of cancer

Cancer has been classified as a diverse illness with a wide range of subgroups. Its early identification and prognosis, which have become a requirement of cancer research, are essential for clinical treatment. Patients have already benefited greatly from the use of artificial intelligence (AI), machine learning (ML), and deep learning (DL) algorithms in the field of healthcare. AI simulates and combines data, pre-programmed rules, and knowledge to produce predictions. Data are used to improve efficiency across several pursuits and tasks through the art of ML. DL is a larger family of ML methods based on representational learning and simulated neural networks. Support vector machines, convulsion neural networks, and artificial neural networks, among others, have been widely used in cancer research to construct prediction models that enable precise and effective decision-making. Although using these innovative methods can enhance our comprehension of how cancer progresses, further validation is required before these techniques can be used in routine clinical practice. We cover contemporary methods used in the modelling of cancer development in this article. The presented prediction models are built using a variety of guided ML approaches, as well as numerous input attributes and data collections. Early identification and cost-effective detection of cancer's progression are equally necessary for successful treatment of the disease. Smart material-based detection techniques can give end consumers a portable, affordable instrument to easily detect and monitor their health issues without the need for specialized knowledge. Owing to their cost-effectiveness, excellent sensitivity, multimodal detection capacity, and miniaturization aptitude, two-dimensional (2D) materials have a lot of prospects for clinical examination of various compounds as well as cancer biomarkers. The effectiveness of traditional devices is moving faster towards more useful techniques thanks to developments in 2D material-based biosensors/sensors. The most current developments in the design of 2D material-based biosensors/sensors-the next wave of cancer screening instruments-are also outlined in this article.

Simple, Visual, Point-of-Care SARS-CoV-2 Detection Incorporating Recombinase Polymerase Amplification and Target DNA-Protein Crosslinking Enhanced Chemiluminescence

The ongoing COVID-19 pandemic, driven by persistent SARS-CoV-2 transmission, threatens human health worldwide, underscoring the urgent need for an efficient, low-cost, rapid SARS-CoV-2 detection method. Herein, we developed a point-of-care SARS-CoV-2 detection method incorporating recombinase polymerase amplification (RPA) and DNA-protein crosslinking chemiluminescence (DPCL) (RPADPCL). RPADPCL involves the crosslinking of biotinylated double-stranded RPA DNA products with horseradish peroxidase (HRP)-labeled streptavidin (SA-HRP). Modified products are captured using SA-labeled magnetic beads, and then analyzed using a chemiluminescence detector and smartphone after the addition of a chemiluminescent substrate. Under optimal conditions, the RPADPCL limit of detection (LOD) was observed to be 6 copies (within the linear detection range of 1-300 copies) for a plasmid containing the SARS-CoV-2 N gene and 15 copies (within the linear range of 10-500 copies) for in vitro transcribed (IVT) SARS-CoV-2 RNA. The proposed method is convenient, specific, visually intuitive, easy to use, and does not require external excitation. The effective RPADPCL detection of SARS-CoV-2 in complex matrix systems was verified by testing simulated clinical samples containing 10% human saliva or a virus transfer medium (VTM) spiked with a plasmid containing a SARS-CoV-2 N gene sequence or SARS-CoV-2 IVT RNA. Consequently, this method has great potential for detecting targets in clinical samples.

Smart and emerging point of care electrochemical sensors based on nanomaterials for SARS-CoV-2 virus detection: Towards designing a future rapid diagnostic tool

In the recent years, researchers from all over the world have become interested in the fabrication of advanced and innovative electrochemical and/or biosensors for respiratory virus detection with the use of nanotechnology. These fabricated sensors demonstrated a number of benefits, including precision, affordability, accessibility, and miniaturization which makes them a promising test method for point-of-care (PoC) screening for SARS-CoV-2 viral infection. In order to comprehend the principles of electrochemical sensing and the role of various types of sensing interfaces, we comprehensively explored the underlying principles of electroanalytical methods and terminologies related to it in this review. In addition, it is addressed how to fabricate electrochemical sensing devices incorporating nanomaterials as graphene, metal/metal oxides, metal organic frameworks (MOFs), MXenes, quantum dots, and polymers. We took an effort to carefully compile current developments, advantages, drawbacks, possible solutions in nanomaterials based electrochemical sensors.

Sensing Characteristics of SARS-CoV-2 Spike Protein Using Aptamer-Functionalized Si-Based Electrolyte-Gated Field-Effect Transistor (EGT)

The sensing responses of SARS-CoV-2 spike protein using top-down-fabricated Si-based electrolyte-gated transistors (EGTs) have been investigated. An aptamer was employed as a receptor for the SARS-CoV-2 spike protein. The EGT demonstrated excellent intrinsic characteristics and higher sensitivity in the subthreshold regime compared to the linear regime. The limit of detection (LOD) was achieved as low as 0.94 pg/mL and 20 pg/mL for the current and voltage sensitivity, respectively. To analyze the sensing responses of EGT in detecting the aptamer-SARS-CoV-2 spike protein conjugate, a lumped-capacitive model with the presence of an effective dipole potential and an effective capacitance of the functionalized layer component was employed. The aptamer-functionalized EGT showed high sensitivity even in 10 mM phosphate-buffered saline (PBS) solution. These results suggest that Si-based EGTs are a highly promising method for detecting SARS-CoV-2 spike proteins.

The development of an electrochemical immunosensor utilizing chicken IgY anti-spike antibody for the detection of SARS-CoV-2

This paper introduces a novel approach for detecting the SARS-CoV-2 recombinant spike protein combining a label free electrochemical impedimetric immunosensor with the use of purified chicken IgY antibodies. The sensor employs three electrodes and is functionalized with an anti-S IgY antibody, ELISA and immunoblot assays confirmed the positive response of chicken immunized with SARS-CoV2 S antigen. The developed immunosensor is effective in detecting SARS-CoV-2 in nasopharyngeal clinical samples from suspected cases. The key advantage of this biosensor is its remarkable sensitivity, and its capability of detecting very low concentrations of the target analyte, with a detection limit of 5.65 pg/mL. This attribute makes it highly suitable for practical point-of-care (POC) applications, particularly in low analyte count clinical scenarios, without requiring amplification. Furthermore, the biosensor has a wide dynamic range of detection, spanning from 11.56 to 740 ng/mL, which makes it applicable for sample analysis in a typical clinical setting.

Impact of nanotechnology on conventional and artificial intelligence-based biosensing strategies for the detection of viruses

Recent years have witnessed the emergence of several viruses and other pathogens. Some of these infectious diseases have spread globally, resulting in pandemics. Although biosensors of various types have been utilized for virus detection, their limited sensitivity remains an issue. Therefore, the development of better diagnostic tools that facilitate the more efficient detection of viruses and other pathogens has become important. Nanotechnology has been recognized as a powerful tool for the detection of viruses, and it is expected to change the landscape of virus detection and analysis. Recently, nanomaterials have gained enormous attention for their value in improving biosensor performance owing to their high surface-to-volume ratio and quantum size effects. This article reviews the impact of nanotechnology on the design, development, and performance of sensors for the detection of viruses. Special attention has been paid to nanoscale materials, various types of nanobiosensors, the internet of medical things, and artificial intelligence-based viral diagnostic techniques.

Galvanic Displacement Reaction Enabled Specific and Sensitive Detection of Bacteria with a Digital Photocorrosion GaAs/AlGaAs Biosensor

The conjugation of ionic gold with bacterial antibodies makes it possible to induce a specific interaction between targeted bacteria and the surface of a GaAs/AlGaAs biochip. The process of immobilization is based on a galvanic displacement reaction (GDR) involving electron transfer between GaAs and Au3+ ions that leads to the formation of a Au-Ga alloy anchoring bacteria to the biochip surface. The GDR-based immobilization of Escherichia coli on biochips comprising a stack of GaAs/AlGaAs nanolayers (dGaAs = 12 nm, dAlGaAs = 10 nm) was confirmed by X-ray photoelectron spectroscopy and atomic force microscopy-based infrared experiments. We report the successful application of this approach for highly sensitive detection of E. coli with a digital photocorrosion (DIP) biosensor. The photoluminescence (PL) monitored DIP of GaAs/AlGaAs nanolayers results in the formation of a PL intensity maximum whose temporal appearance depends on the electric charge transfer between bacteria and the biochip. The formation of a robust bacteria-biochip interface achieved with the GDR process allowed us to observe the role of bacteria on the temporal position of a PL intensity maximum related to the etching of two pairs of GaAs/AlGaAs nanolayers extending up to 24 nm below the biochip surface. We demonstrate the attractive detection of E. coli at 250 CFU/mL, and we discuss the potential of this approach for designing a family of biosensors addressing the quasi-continuous monitoring of a water environment for the presence of pathogenic bacteria.

Efficient trapping and destruction of SARS-CoV-2 using PECO-assisted Molekule air purifiers in the laboratory and real-world settings

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is transmitted human-to-human via aerosols and air-borne droplets. Therefore, capturing and destroying viruses from indoor premises are essential to reduce the probability of human exposure and virus transmission. While the heating, ventilation, and air conditioning (HVAC) systems help in reducing the indoor viral load, a targeted approach is required to effectively remove SARS-CoV-2 from indoor air to address human exposure concerns. The present study demonstrates efficient trapping and destruction of SARS-CoV-2 via nano-enabled filter technology using the UV-A-stimulated photoelectrochemical oxidation (PECO) process. Aerosols containing SARS-CoV-2 were generated by nebulization inside an air-controlled test chamber where an air purifier (Air Mini+) was placed. The study demonstrated the efficient removal of SARS-CoV-2 (99.98 %) from the test chamber in less than two minutes and PECO-assisted destruction (over 99%) on the filtration media in 1 h. Furthermore, in a real-world scenario, the Molekule Air-Pro air purifier removed SARS-CoV-2 (a negative RT-qPCR result post-running the filter device) from the circulating air in a COVID-19 testing facility. Overall, the ability of two FDA-approved class II medical devices, Molekule Air-Mini+ and Air-Pro air purifiers, to remove and destroy SARS-CoV-2 in indoor settings was successfully demonstrated. The study indicates that as the "tripledemic" of COVID-19, influenza, and respiratory syncytial virus (RSV) overwhelm the healthcare facilities in the USA, the use of a portable air filtration device will help contain the spread of the viruses in close door facilities, such as in schools and daycare facilities.

Advances in miniaturized nanosensing platforms for analysis of pathogenic bacteria and viruses

Pathogenic bacteria and viruses are the main causes of infectious diseases all over the world. Early diagnosis of such infectious diseases is a critical step in management of their spread and treatment of the infection in its early stages. Therefore, the innovation of smart sensing platforms for point-of-care diagnosis of life-threatening infectious diseases such as COVID-19 is a prerequisite to isolate the patients and provide them with suitable treatment strategies. The developed diagnostic sensors should be highly sensitive, specific, ultrafast, portable, cheap, label-free, and selective. In recent years, different nanosensors have been developed for the detection of bacterial and viral pathogens. We focus here on label-free miniaturized nanosensing platforms that were efficiently applied for pathogenic detection in biological matrices. Such devices include nanopore sensors and nanostructure-integrated lab-on-a-chip sensors that are characterized by portability, simplicity, cost-effectiveness, and ultrafast analysis because they avoid the time-consuming sample preparation steps. Furthermore, nanopore-based sensors could afford single-molecule counting of viruses in biological specimens, yielding high-sensitivity and high-accuracy detection. Moreover, non-invasive nanosensors that are capable of detecting volatile organic compounds emitted from the diseased organ to the skin, urine, or exhaled breath were also reviewed. The merits and applications of all these nanosensors for analysis of pathogenic bacteria and viruses in biological matrices will be discussed in detail, emphasizing the importance of artificial intelligence in advancing specific nanosensors.

Effect of Ambient Environment on Laser Reduction of Graphene Oxide for Applications in Electrochemical Sensing

Electrochemical sensors play an important role in a variety of applications. With the potential for enhanced performance, much of the focus has been on developing nanomaterials, in particular graphene, for such sensors. Recent work has looked towards laser scribing technology for the reduction of graphene oxide as an easy and cost-effective option for sensor fabrication. This work looks to develop this approach by assessing the quality of sensors produced with the effect of different ambient atmospheres during the laser scribing process. The graphene oxide was reduced using a laser writing system in a range of atmospheres and sensors characterised with Raman spectroscopy, XPS and cyclic voltammetry. Although providing a slightly higher defect density, sensors fabricated under argon and nitrogen atmospheres exhibited the highest average electron transfer rates of approximately 2 × 10-3 cms-1. Issues of sensor reproducibility using this approach are discussed.

Point-of-Care Devices for Viral Detection: COVID-19 Pandemic and Beyond

The pandemic of COVID-19 and its widespread transmission have made us realize the importance of early, quick diagnostic tests for facilitating effective cure and management. The primary obstacles encountered were accurately distinguishing COVID-19 from other illnesses including the flu, common cold, etc. While the polymerase chain reaction technique is a robust technique for the determination of SARS-CoV-2 in patients of COVID-19, there arises a high demand for affordable, quick, user-friendly, and precise point-of-care (POC) diagnostic in therapeutic settings. The necessity for available tests with rapid outcomes spurred the advancement of POC tests that are characterized by speed, automation, and high precision and accuracy. Paper-based POC devices have gained increasing interest in recent years because of rapid, low-cost detection without requiring external instruments. At present, microfluidic paper-based analysis devices have garnered public attention and accelerated the development of such POCT for efficient multistep assays. In the current review, our focus will be on the fabrication of detection modules for SARS-CoV-2. Here, we have included a discussion on various strategies for the detection of viral moieties. The compilation of these strategies would offer comprehensive insight into the detection of the causative agent preparedness for future pandemics. We also provide a descriptive outline for paper-based diagnostic platforms, involving the determination mechanisms, as well as a commercial kit for COVID-19 as well as their outlook.

Reviewing methods of deep learning for diagnosing COVID-19, its variants and synergistic medicine combinations

The COVID-19 pandemic has necessitated the development of reliable diagnostic methods for accurately detecting the novel coronavirus and its variants. Deep learning (DL) techniques have shown promising potential as screening tools for COVID-19 detection. In this study, we explore the realistic development of DL-driven COVID-19 detection methods and focus on the fully automatic framework using available resources, which can effectively investigate various coronavirus variants through modalities. We conducted an exploration and comparison of several diagnostic techniques that are widely used and globally validated for the detection of COVID-19. Furthermore, we explore review-based studies that provide detailed information on synergistic medicine combinations for the treatment of COVID-19. We recommend DL methods that effectively reduce time, cost, and complexity, providing valuable guidance for utilizing available synergistic combinations in clinical and research settings. This study also highlights the implication of innovative diagnostic technical and instrumental strategies, exploring public datasets, and investigating synergistic medicines using optimised DL rules. By summarizing these findings, we aim to assist future researchers in their endeavours by providing a comprehensive overview of the implication of DL techniques in COVID-19 detection and treatment. Integrating DL methods with various diagnostic approaches holds great promise in improving the accuracy and efficiency of COVID-19 diagnostics, thus contributing to effective control and management of the ongoing pandemic.

Biopolymers Used for Receptor Immobilization for Nickel-Detection Biosensors in Food

Food is humans' main source of nickel intake, which is responsible for the prevalence of allergic contact dermatitis and other pathological afflictions. While robust, the classical methods for nickel detection-atomic absorption spectrometry and inductively coupled plasma mass spectrometry-are expensive and laborious; in contrast, modern methods that utilize sensors-of which most are electrochemical-have rapid run times, are cost-effective, and are easily assembled. Here, we describe the use of four biopolymers (alginate, agar, chitosan, and carrageenan) for receptor immobilization on biosensors to detect nickel ions and use an optimization approach with three biopolymer concentrations to assay analytical performance profiles. We measured the total performance of screen-printed carbon electrodes immobilized with the biopolymer-sensor combinations using cyclic voltammetry (CV). Voltammetric behavior favored the carrageenan biosensor, based on performance characteristics measured using CV, with sensitivities of 2.68 (for 1% biopolymer concentration) and 2.08 (for 0.5% biopolymer concentration). Our results indicated that among the four biopolymer combinations, carrageenan with urease affixed to screen-printed electrodes was effective at coupling for nickel detection.

Advancements in SARS-CoV-2 Testing: Enhancing Accessibility through Machine Learning-Enhanced Biosensors

The COVID-19 pandemic highlighted the importance of widespread testing for SARS-CoV-2, leading to the development of various new testing methods. However, traditional invasive sampling methods can be uncomfortable and even painful, creating barriers to testing accessibility. In this article, we explore how machine learning-enhanced biosensors can enable non-invasive sampling for SARS-CoV-2 testing, revolutionizing the way we detect and monitor the virus. By detecting and measuring specific biomarkers in body fluids or other samples, these biosensors can provide accurate and accessible testing options that do not require invasive procedures. We provide examples of how these biosensors can be used for non-invasive SARS-CoV-2 testing, such as saliva-based testing. We also discuss the potential impact of non-invasive testing on accessibility and accuracy of testing. Finally, we discuss potential limitations or biases associated with the machine learning algorithms used to improve the biosensors and explore future directions in the field of machine learning-enhanced biosensors for SARS-CoV-2 testing, considering their potential impact on global healthcare and disease control.

COVID-19 associated thyroid dysfunction and other comorbidities and its management using phytochemical-based therapeutics: a natural way

The present severe acute respiratory syndrome-2 (SARS-CoV-2) mediated Coronavirus pandemic (COVID-19) and post-COVID-19 complications affect human life drastically. Patients who have been cured of COVID-19 infection are now experiencing post-COVID-19 associated comorbidities, which have increased mortality rates. The SARS-CoV-2 infection distresses the lungs, kidneys, gastrointestinal tract, and various endocrine glands, including the thyroid. The emergence of variants which includes Omicron (B.1.1.529) and its lineages threaten the world severely. Among different therapeutic approaches, phytochemical-based therapeutics are not only cost-effective but also have lesser side effects. Recently a plethora of studies have shown the therapeutic efficacy of various phytochemicals for the treatment of COVID-19. Besides this, various phytochemicals have been found efficacious in treating several inflammatory diseases, including thyroid-related anomalies. The method of the phytochemical formulation is quick and facile and the raw materials for such herbal preparations are approved worldwide for human use against certain disease conditions. Owing to the advantages of phytochemicals, this review primarily discusses the COVID-19-related thyroid dysfunction and the role of key phytochemicals to deal with thyroid anomaly and post-COVID-19 complications. Further, this review shed light on the mechanism via which COVID-19 and its related complication affect organ function of the body, along with the mechanistic insight into the way by which phytochemicals could help to cure post-COVID-19 complications in thyroid patients. Considering the advantages offered by phytochemicals as a safer and cost-effective medication they can be potentially used to combat COVID-19-associated comorbidities.

Optical Biosensors for the Diagnosis of COVID-19 and Other Viruses-A Review

The sudden outbreak of the COVID-19 pandemic led to a huge concern globally because of the astounding increase in mortality rates worldwide. The medical imaging computed tomography technique, whole-genome sequencing, and electron microscopy are the methods generally used for the screening and identification of the SARS-CoV-2 virus. The main aim of this review is to emphasize the capabilities of various optical techniques to facilitate not only the timely and effective diagnosis of the virus but also to apply its potential toward therapy in the field of virology. This review paper categorizes the potential optical biosensors into the three main categories, spectroscopic-, nanomaterial-, and interferometry-based approaches, used for detecting various types of viruses, including SARS-CoV-2. Various classifications of spectroscopic techniques such as Raman spectroscopy, near-infrared spectroscopy, and fluorescence spectroscopy are discussed in the first part. The second aspect highlights advances related to nanomaterial-based optical biosensors, while the third part describes various optical interferometric biosensors used for the detection of viruses. The tremendous progress made by lab-on-a-chip technology in conjunction with smartphones for improving the point-of-care and portability features of the optical biosensors is also discussed. Finally, the review discusses the emergence of artificial intelligence and its applications in the field of bio-photonics and medical imaging for the diagnosis of COVID-19. The review concludes by providing insights into the future perspectives of optical techniques in the effective diagnosis of viruses.

A Novel COVID-19 Diagnostic System Using Biosensor Incorporated Artificial Intelligence Technique

COVID-19, continually developing and raising increasingly significant issues, has impacted human health and caused countless deaths. It is an infectious disease with a high incidence and mortality rate. The spread of the disease is also a significant threat to human health, especially in the developing world. This study suggests a method called shuffle shepherd optimization-based generalized deep convolutional fuzzy network (SSO-GDCFN) to diagnose the COVID-19 disease state, types, and recovered categories. The results show that the accuracy of the proposed method is as high as 99.99%; similarly, precision is 99.98%; sensitivity/recall is 100%; specificity is 95%; kappa is 0.965%; AUC is 0.88%; and MSE is less than 0.07% as well as 25 s. Moreover, the performance of the suggested method has been confirmed by comparison of the simulation results from the proposed approach with those from several traditional techniques. The experimental findings demonstrate strong performance and high accuracy for categorizing COVID-19 stages with minimal reclassifications over the conventional methods.

A surface molecularly imprinted electrochemical biosensor for the detection of SARS-CoV-2 spike protein by using Cu7S4-Au as built-in probe

Sensitive detection of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) spike protein (S protein) is of significant clinical importance in the diagnosis of COVID-19 pandemic. In this work, a surface molecularly imprinted (SMI) electrochemical biosensor is fabricated for the detection of SARS-CoV-2 S protein. Cu₇S₄-Au is used as the built-in probe and modified on the surface of a screen-printed carbon electrode (SPCE). 4-Mercaptophenylboric acid (4-MPBA) is anchored to the surface of the Cu₇S₄-Au through Au-SH bonds, which can be used for the immobilization of the SARS-CoV-2 S protein template through boronate ester bonds. After that, 3-aminophenylboronic acid (3-APBA) is electropolymerized on the electrode surface and used as the molecularly imprinted polymers (MIPs). The SMI electrochemical biosensor is obtained after the elution of the SARS-CoV-2 S protein template with an acidic solution by the dissociation of the boronate ester bonds, which can be utilized for sensitive detection of the SARS-CoV-2 S protein. The developed SMI electrochemical biosensor displays high specificity, reproducibility and stability, which might be a potential and promising candidate for the clinical diagnosis of COVID-19.

Internet-of-medical-things integrated point-of-care biosensing devices for infectious diseases: Toward better preparedness for futuristic pandemics

Microbial pathogens have threatened the world due to their pathogenicity and ability to spread in communities. The conventional laboratory-based diagnostics of microbes such as bacteria and viruses need bulky expensive experimental instruments and skilled personnel which limits their usage in resource-limited settings. The biosensors-based point-of-care (POC) diagnostics have shown huge potential to detect microbial pathogens in a faster, cost-effective, and user-friendly manner. The use of various transducers such as electrochemical and optical along with microfluidic integrated biosensors further enhances the sensitivity and selectivity of detection. Additionally, microfluidic-based biosensors offer the advantages of multiplexed detection of analyte and the ability to deal with nanoliters volume of fluid in an integrated portable platform. In the present review, we discussed the design and fabrication of POCT devices for the detection of microbial pathogens which include bacteria, viruses, fungi, and parasites. The electrochemical techniques and current advances in this field in terms of integrated electrochemical platforms that include mainly microfluidic- based approaches and smartphone and Internet-of-things (IoT) and Internet-of-Medical-Things (IoMT) integrated systems have been highlighted. Further, the availability of commercial biosensors for the detection of microbial pathogens will be briefed. In the end, the challenges while fabrication of POC biosensors and expected future advances in the field of biosensing have been discussed. The integrated biosensor-based platforms with the IoT/IoMT usually collect the data to track the community spread of infectious diseases which would be beneficial in terms of better preparedness for current and futuristic pandemics and is expected to prevent social and economic losses.

Emerging trends in point-of-care biosensing strategies for molecular architectures and antibodies of SARS-CoV-2

COVID-19, a highly contagious viral infection caused by the occurrence of severe acute respiratory syndrome coronavirus (SARS-CoV-2), has turned out to be a viral pandemic then ravaged many countries worldwide. In the recent years, point-of-care (POC) biosensors combined with state-of-the-art bioreceptors, and transducing systems enabled the development of novel diagnostic tools for rapid and reliable detection of biomarkers associated with SARS-CoV-2. The present review thoroughly summarises and discusses various biosensing strategies developed for probing SARS-CoV-2 molecular architectures (viral genome, S Protein, M protein, E protein, N protein and non-structural proteins) and antibodies as a potential diagnostic tool for COVID-19. This review discusses the various structural components of SARS-CoV-2, their binding regions and the bioreceptors used for recognizing the structural components. The various types of clinical specimens investigated for rapid and POC detection of SARS-CoV-2 is also highlighted. The importance of nanotechnology and artificial intelligence (AI) approaches in improving the biosensor performance for real-time and reagent-free monitoring the biomarkers of SARS-CoV-2 is also summarized. This review also encompasses existing practical challenges and prospects for developing new POC biosensors for clinical monitoring of COVID-19.

Bibliometric analysis of the use of artificial intelligence in COVID-19 based on scientific studies

Background and Aims

One such strategy is citation analysis used by researchers for research planning an article referred to by another article receives a "citation." By using bibliometric analysis, the development of research areas and authors' influence can be investigated. The current study aimed to identify and analyze the characteristics of 100 highly cited articles on the use of artificial intelligence concerning COVID-19.

Methods

On July 27, 2022, this database was searched using the keywords "artificial intelligence" and "COVID-19" in the topic. After extensive searching, all retrieved articles were sorted by the number of citations, and 100 highly cited articles were included based on the number of citations. The following data were extracted: year of publication, type of study, name of journal, country, number of citations, language, and keywords.

Results

The average number of citations for 100 highly cited articles was 138.54. The top three cited articles with 745, 596, and 549 citations. The top 100 articles were all in English and were published in 2020 and 2021. China was the most prolific country with 19 articles, followed by the United States with 15 articles and India with 10 articles.

Conclusion

The current bibliometric analysis demonstrated the significant growth of the use of artificial intelligence for COVID-19. Using these results, research priorities are more clearly defined, and researchers can focus on hot topics.

Magnetic biosensors for identification of SARS-CoV-2, Influenza, HIV, and Ebola viruses: a review

Infectious diseases such as novel coronavirus (SARS-CoV-2), Influenza, HIV, Ebola, etc kill many people around the world every year (SARS-CoV-2 in 2019, Ebola in 2013, HIV in 1980, Influenza in 1918). For example, SARS-CoV-2 has plagued higher than 317 000 000 people around the world from December 2019 to January 13, 2022. Some infectious diseases do not yet have not a proper vaccine, drug, therapeutic, and/or detection method, which makes rapid identification and definitive treatments the main challenges. Different device techniques have been used to detect infectious diseases. However, in recent years, magnetic materials have emerged as active sensors/biosensors for detecting viral, bacterial, and plasmids agents. In this review, the recent applications of magnetic materials in biosensors for infectious viruses detection have been discussed. Also, this work addresses the future trends and perspectives of magnetic biosensors.

Superior possibilities and upcoming horizons for nanoscience in COVID-19: noteworthy approach for effective diagnostics and management of SARS-CoV-2 outbreak

The outbreak of COVID-19 has caused great havoc and affected many parts of the world. It has imposed a great challenge to the medical and health fraternity with its ability to continue mutating and increasing the transmission rate. Some challenges include the availability of current knowledge of active drugs against the virus, mode of delivery of the medicaments, its diagnosis, which are relatively limited and do not suffice for further prognosis. One recently developed drug delivery system called nanoparticles is currently being utilized in combating COVID-19. This article highlights the existing methods for diagnosis of COVID-19 such as computed tomography scan, reverse transcription-polymerase chain reaction, nucleic acid sequencing, immunoassay, point-of-care test, detection from breath, nanotechnology-based bio-sensors, viral antigen detection, microfluidic device, magnetic nanosensor, magnetic resonance platform and internet-of-things biosensors. The latest detection strategy based on nanotechnology, biosensor, is said to produce satisfactory results in recognizing SARS-CoV-2 virus. It also highlights the successes in the research and development of COVID-19 treatments and vaccines that are already in use. In addition, there are a number of nanovaccines and nanomedicines currently in clinical trials that have the potential to target COVID-19.

A Comprehensive Overview of Sensors Applications for the Diagnosis of SARS-CoV-2 and of Drugs Used in its Treatment

During the COVID-19 process, determination-based analytical chemistry studies have had a major place at every stage. Many analytical techniques have been used in both diagnostic studies and drug analysis. Among these, electrochemical sensors are frequently preferred due to their high sensitivity, selectivity, short analysis time, reliability, ease of sample preparation, and low use of organic solvents. For the determination of drugs used in the SARS-CoV-2, such as favipiravir, molnupiravir, ribavirin, etc., electrochemical (nano)sensors are widely used in both pharmaceutical and biological samples. Diagnosis is the most critical step in the management of the disease, and electrochemical sensor tools are widely preferred for this purpose. Diagnostic electrochemical sensor tools can be biosensor-, nano biosensor-, or MIP-based sensors and utilize a wide variety of analytes such as viral proteins, viral RNA, antibodies, etc. This review overviews the sensor applications in SARS-CoV-2 in terms of diagnosis and determination of drugs by evaluating the most recent studies in the literature. In this way, it is aimed to compile the developments so far by shedding light on the most recent studies and giving ideas to researchers for future studies.

Self-directed molecular diagnostics (SdMDx) system for COVID-19 via one-pot processing

Rapid, sensitive, and specific detection of the severe acute respiratory syndrome coronavirus (SARS-CoV)- 2 during early infection is pivotal in controlling the spread and pathological progression of Coronavirus Disease 2019 (COVID-19). Thus, highly accurate, affordable, and scalable point-of-care (POC) diagnostic technologies are necessary. Herein, we developed a rapid and efficient self-directed molecular diagnostic (SdMDx) system for SARS-CoV-2. This system combines the sample preparation step, including virus enrichment and extraction processes, which involve dimethyl suberimidate dihydrochloride and diatomaceous earth functionalized with 3-aminopropyl(diethoxy)methylsilane, and the detection step using loop-mediated isothermal amplification-lateral flow assay (LAMP-LFA). Using the SdMDx system, SARS-CoV-2 could be detected within 47 min by hand without the need for any larger instruments. The SdMDx system enabled detection as low as 0.05 PFU in the culture fluid of SARS-CoV-2-infected VeroE6 cells. We validated the accuracy of the SdMDx system on 38 clinical nasopharyngeal specimens. The clinical utility of the SdMDx system for targeting the S gene of SARS-CoV-2 showed 94.4% sensitivity and 100% specificity. This system is more sensitive than antigen and antibody assays, and it minimizes the use of complicated processes and reduces contamination risks. Accordingly, we demonstrated that the SdMDx system enables a rapid, accurate, simple, efficient, and inexpensive detection of SARS-CoV-2 at home, in emergency facilities, and in low-resource sites as a pre-screening platform and POC testing through self-operation and self-diagnosis.

Development of a rapid and ultra-sensitive RNA:DNA hybrid immunocapture based biosensor for visual detection of SARS-CoV-2 RNA

The Development of reliable and field-compatible detection methods is essential to monitoring and controlling the spread of any global pandemic. We herein report a novel anti-RNA:DNA hybrid (anti-RDH) antibody-based biosensor for visual, colorimetric lateral flow assay, using gold nanoparticles, coupled with transcription-mediated-isothermal-RNA-amplification (TMIRA) for specific and sensitive detection of viral RNA. We have demonstrated its utility for SARS-CoV-2 RNA detection. This technique, which we have named RDH-LFA (anti-RNA:DNA hybrid antibody-based lateral flow assay), exploits anti-RDH antibody for immunocapture of viral RNA hybridized with specific DNA probes in lateral flow assay. This method uses biotinylated-oligonucleotides (DNAB) specific to SARS-CoV-2 RNA (vRNA) to generate a vRNA-DNAB hybrid. The biotin-tagged vRNA-DNAB hybrid molecules bind to streptavidin conjugated with gold nanoparticles. This hybrid complex is trapped by the anti-RDH antibody immobilized on the nitrocellulose membrane resulting in pink color signal leading to visual naked-eye detection in 1 minute. Combining RDH-LFA with isothermal RNA amplification (TMIRA) significantly improves the sensitivity (LOD:10 copies/µl) with a total turnaround time of an hour. More importantly, RDH-LFA coupled with the TMIRA method showed 96.6% sensitivity and 100% specificity for clinical samples when compared to a commercial gold standard reverse-transcription quantitative polymerase-chain-reaction assay. Thus, the present study reports a rapid, sensitive, specific, and simple method for visual detection of viral RNA, which can be used at the point-of-care without requiring sophisticated instrumentation.

Highly Sensitive Interdigitated Capacitive Humidity Sensors Based on Sponge-Like Nanoporous PVDF/LiCl Composite for Real-Time Monitoring

In this study, a sponge-like poly(vinylidene fluoride) (PVDF)/lithium chloride (LiCl) nanocomposite-entrenched interdigitated capacitive (IDC) sensor was developed for real-time humidity-sensing applications. Here, we demonstrated a sponge-like nanoporous structure ranging from 200 nm to 2 μm size holes, the PVDF/LiCl structure fabricated on an interdigitated capacitor (IDC) electrode functioning as a high-performance sensor because of the presence of ionized LiCl. The nanoporous PVDF/LiCl composite-based humidity sensor exhibited a high sensitivity of 12.6 nF/% relative humidity (RH), a linearity of 0.990, and a low hysteresis of 2.6% in the range of 25-95% RH. The composite film exhibited a response time of 17.7 s, a recovery time of 21 s, and an intensified increase of 8.02 nF/s (a decrease of 6.7 nF/s). The sensor designed demonstrates ultra-high sensing characteristics with 10 times higher sensitivity, i.e., 12.678.96 pF/%RH as compared to other polymer-based composite humidity sensors. Owing to the sensing performance and portability, the proposed nanoporous PVDF/LiCl composite-based IDC sensor is expected to be a promising platform for a wide range of humidity-sensing applications, including real-time breath monitoring and non-contact sensing.

Towards hospital-on-chip supported by 2D MXenes-based 5th generation intelligent biosensors

Existing public health emergencies due to fatal/infectious diseases such as coronavirus disease (COVID-19) and monkeypox have raised the paradigm of 5th generation portable intelligent and multifunctional biosensors embedded on a single chip. The state-of-the-art 5th generation biosensors are concerned with integrating advanced functional materials with controllable physicochemical attributes and optimal machine processability. In this direction, 2D metal carbides and nitrides (MXenes), owing to their enhanced effective surface area, tunable physicochemical properties, and rich surface functionalities, have shown promising performances in biosensing flatlands. Moreover, their hybridization with diversified nanomaterials caters to their associated challenges for the commercialization of stability due to restacking and oxidation. MXenes and its hybrid biosensors have demonstrated intelligent and lab-on-chip prospects for determining diverse biomarkers/pathogens related to fatal and infectious diseases. Recently, on-site detection has been clubbed with solution-on-chip MXenes by interfacing biosensors with modern-age technologies, including 5G communication, internet-of-medical-things (IoMT), artificial intelligence (AI), and data clouding to progress toward hospital-on-chip (HOC) modules. This review comprehensively summarizes the state-of-the-art MXene fabrication, advancements in physicochemical properties to architect biosensors, and the progress of MXene-based lab-on-chip biosensors toward HOC solutions. Besides, it discusses sustainable aspects, practical challenges and alternative solutions associated with these modules to develop personalized and remote healthcare solutions for every individual in the world.

Machine Learning-Assisted Real-Time Polymerase Chain Reaction and High-Resolution Melt Analysis for SARS-CoV-2 Variant Identification

Since the declaration of COVID-19 as a pandemic in early 2020, multiple variants of the severe acute respiratory syndrome-related coronavirus (SARS-CoV-2) have been detected. The emergence of multiple variants has raised concerns due to their impact on public health. Therefore, it is crucial to distinguish between different viral variants. Here, we developed a machine learning web-based application for SARS-CoV-2 variant identification via duplex real-time polymerase chain reaction (PCR) coupled with high-resolution melt (qPCR-HRM) analysis. As a proof-of-concept, we investigated the platform's ability to identify the Alpha, Delta, and wild-type strains using two sets of primers. The duplex qPCR-HRM could identify the two variants reliably in as low as 100 copies/μL. Finally, the platform was validated with 167 nasopharyngeal swab samples, which gave a sensitivity of 95.2%. This work demonstrates the potential for use as automated, cost-effective, and large-scale viral variant surveillance.

Recent Advances in Biosensors for Detection of COVID-19 and Other Viruses

This century has introduced very deadly, dangerous, and infectious diseases to humankind such as the influenza virus, Ebola virus, Zika virus, and the most infectious SARS-CoV-2 commonly known as COVID-19 and have caused epidemics and pandemics across the globe. For some of these diseases, proper medications, and vaccinations are missing and the early detection of these viruses will be critical to saving the patients. And even the vaccines are available for COVID-19, the new variants of COVID-19 such as Delta, and Omicron are spreading at large. The available virus detection techniques take a long time, are costly, and complex and some of them generates false negative or false positive that might cost patients their lives. The biosensor technique is one of the best qualified to address this difficult challenge. In this systematic review, we have summarized recent advancements in biosensor-based detection of these pandemic viruses including COVID-19. Biosensors are emerging as efficient and economical analytical diagnostic instruments for early-stage illness detection. They are highly suitable for applications related to healthcare, wearable electronics, safety, environment, military, and agriculture. We strongly believe that these insights will aid in the study and development of a new generation of adaptable virus biosensors for fellow researchers.

Cancer bioimaging using dual mode luminescence of graphene/FA-ZnO nanocomposite based on novel green technique

Graphene based nanomaterials are explored in the field of cancer bioimaging and biomedical science and engineering. The luminescent nanostructures with a low toxicity and high photostability can be used as probes in bioimaging applications. This work is aimed to prepare graphene/folic acid-zinc oxide (GN/FA-ZnO) nanocomposite with dual-mode emissions (down-conversion and up-conversion) to be used in cancer bioimaging. The dual mode emissions offer long luminescence lifetime, multicolor emissions detected by the naked eyes after excitation and narrow band absorption and emission spectra. ZnO nanospheres and nanorods structures were prepared using co-precipitation technique and were conjugated with FA to separate the bulk graphite layers electrostatically into GN. The optical, morphological, surface charge and structural properties of the prepared nanostructures were investigated and discussed using different characterization techniques such as UV-visible spectroscopy, photoluminescence (PL) spectroscopy, scanning electron microscope (SEM), high resolution transmission electron microscope (HRTEM), Zeta potential, Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), X-ray powder diffraction (XRD), and Fourier transform infrared (FTIR). GN/FA-ZnO nanocomposites were injected into Swiss albino mice implanted with Ehrlich Tumor and the bioimaging was investigated using photon imager and digital camera. The results showed clear fluorescence and confirmed that the green design of GN/FA-ZnO nanocomposite with targeting behavior was capable of selective bioimaging of the tumor. This study presented a novel dual mode emission nanocomposite for tumor targeting and is a promising strategy for the fabrication of a new design of spectral encoding.

Achieving broad availability of SARS-CoV-2 detections via smartphone-based analysis

With the development of COVID-19, widely available tests are in great demand. Naked-eye SARS-CoV-2 test kits have recently been developed as home tests, but their sensitivity and accuracy are sometimes limited. Smartphones can convert various signals into digital information, potentially improving the sensitivity and accuracy of these home tests. Herein, we summarize smartphone-based detections for SARS-CoV-2. Optical detections of non-nucleic acids using various sensors and portable imaging systems, as well as nucleic acid analyses based on LAMP, CRISP, CATCH, and biosensors are discussed. Furthermore, different electrochemical detections were compared. We show results obtained using relatively complex equipment, complicated programming procedures, or custom smartphone apps, and describe methods for obtaining information with only simple setups and free software on smartphones. Then, the combined costs of typical smartphone-based detections are evaluated. Finally, the prospect of improving smartphone-based strategies to achieve broad availability of SARS-CoV-2 detection is proposed.

Role of Wearable Sensing Technology to Manage Long COVID

Long COVID consequences have changed the perception towards disease management, and it is moving towards personal healthcare monitoring. In this regard, wearable devices have revolutionized the personal healthcare sector to track and monitor physiological parameters of the human body continuously. This would be largely beneficial for early detection (asymptomatic and pre-symptomatic cases of COVID-19), live patient conditions, and long COVID monitoring (COVID recovered patients and healthy individuals) for better COVID-19 management. There are multitude of wearable devices that can observe various human body parameters for remotely monitoring patients and self-monitoring mode for individuals. Smart watches, smart tattoos, rings, smart facemasks, nano-patches, etc., have emerged as the monitoring devices for key physiological parameters, such as body temperature, respiration rate, heart rate, oxygen level, etc. This review includes long COVID challenges for frequent monitoring of biometrics and its possible solution with wearable device technologies for diagnosis and post-therapy of diseases.

Needs, Challenges and Countermeasures of SARS-CoV-2 Surveillance in Cold-Chain Foods and Packaging to Prevent Possible COVID-19 Resurgence: A Perspective from Advanced Detections

The pandemic caused by SARS-CoV-2 has a huge impact on the global economy. SARS-CoV-2 could possibly and potentially be transmitted to humans through cold-chain foods and packaging (namely good-to-human), although it mainly depends on a human-to-human route. It is imperative to develop countermeasures to cope with the spread of viruses and fulfil effective surveillance of cold-chain foods and packaging. This review outlined SARS-CoV-2-related cold-chain food incidents and current methods for detecting SARS-CoV-2. Then the needs, challenges and practicable countermeasures for SARS-CoV-2 detection, specifically for cold-chain foods and packaging, were underlined. In fact, currently established detection methods for SARS-CoV-2 are mostly used for humans; thus, these may not be ideally applied to cold-chain foods directly. Therefore, it creates a need to develop novel methods and low-cost, automatic, mini-sized devices specifically for cold-chain foods and packaging. The review intended to draw people's attention to the possible spread of SARS-CoV-2 with cold-chain foods and proposed perspectives for futuristic cold-chain foods monitoring during the pandemic.

AI-Assisted Fusion of Scanning Electrochemical Microscopy Images Using Novel Soft Probe

Scanning electrochemical microscopy (SECM) is one of the scanning probe techniques that has attracted considerable attention because of its ability to interrogate surface morphology or electrochemical reactivity. However, the quality of SECM images generally depends on the sizes of the electrodes and many uncontrollable factors. Furthermore, manipulating fragile glass ultramicroelectrodes and blurred images sometimes frustrate researchers. To overcome the challenges of modern SECM, we developed novel soft gold probes and then established the AI-assisted methodology for image fusion. A novel gold microelectrode probe with high softness was developed to scan fragile samples. The distribution of EGFR (protein biomarker) in oral cancer was investigated. Then, we fused the optical microscopic and SECM images to enhance the image quality using Matlab software. However, thousands of fused images were generated by changing the parameters for image fusion, which is annoying for researchers. Thus, a deep learning model was built to select the best-fused images according to the contrast and clarity of the fused images. Therefore, the quality of the SECM images was improved using a novel soft probe and combining the image fusion technique. In the future, a new scanning probe with AI-assisted fused SECM image processing may be interpreted more preciously and contribute to the early detection of cancers.

SARS-CoV-2 airborne transmission: a review of risk factors and possible preventative measures using air purifiers

The rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the resulting worldwide death toll have prompted worries regarding its transmission mechanisms. Direct, indirect, and droplet modes are the basic mechanisms of transmission. SARS-CoV-2 spreads by respiratory droplets (size range >10 μm size ranges), aerosols (5 μm), airborne, and particulate matter. The rapid transmission of SARS-CoV-2 is due to the involvement of tiny indoor air particulate matter (PM_2.5), which functions as a vector. SARS-CoV-2 is more contagious in the indoor environment where particulate matter floats for a longer period and greater distances. Extended residence time in the environment raises the risk of SARS-CoV-2 entering the lower respiratory tract, which may cause serious infection and possibly death. To decrease viral transmission in the indoor environment, it is essential to catch and kill the SARS-CoV-2 virus and maintain virus-free air, which will significantly reduce viral exposure concerns. Therefore, effective air filters with anti-viral, anti-bacterial, and anti-air-pollutant characteristics are gaining popularity recently. It is essential to develop cost-effective materials based on nanoparticles and metal-organic frameworks in order to lower the risk of airborne transmission in developing countries. A diverse range of materials play an important role in the manufacturing of effective air filters. We have summarized in this review article the basic concepts of the transmission routes of SARS-CoV-2 virus and precautionary measures using air purifiers with efficient materials-based air filters for the indoor environment. The performance of air-filter materials, challenges and alternative approaches, and future perspectives are also presented. We believe that air purifiers fabricated with highly efficient materials can control various air pollutants and prevent upcoming pandemics.

Ultrarapid and ultrasensitive detection of SARS-CoV-2 antibodies in COVID-19 patients via a 3D-printed nanomaterial-based biosensing platform

Rapid detection of antibodies during infection and after vaccination is critical for the control of infectious outbreaks, understanding immune response, and evaluating vaccine efficacy. In this manuscript, we evaluate a simple ultrarapid test for SARS-CoV-2 antibodies in COVID-19 patients, which gives quantitative results (i.e., antibody concentration) in 10-12 s using a previously reported nanomaterial-based three-dimensional (3D)-printed biosensing platform. This platform consists of a micropillar array electrode fabricated via 3D printing of aerosolized gold nanoparticles and coated with nanoflakes of graphene and specific SARS-CoV-2 antigens, including spike S1, S1 receptor-binding domain (RBD) and nucleocapsid (N). The sensor works on the principle of electrochemical transduction, where the change of sensor impedance is realized by the interactions between the viral proteins attached to the sensor electrode surface and the antibodies. The three sensors were used to test samples from 17 COVID-19 patients and 3 patients without COVID-19. Unlike other serological tests, the 3D sensors quantitatively detected antibodies at a concentration as low as picomole within 10-12 s in human plasma samples. We found that the studied COVID-19 patients had higher concentrations of antibodies to spike proteins (RBD and S1) than to the N protein. These results demonstrate the enormous potential of the rapid antibody test platform for understanding patients' immunity, disease epidemiology and vaccine efficacy, and facilitating the control and prevention of infectious epidemics.

Emerging 0D, 1D, 2D, and 3D nanostructures for efficient point-of-care biosensing

The recent COVID-19 infection outbreak has raised the demand for rapid, highly sensitive POC biosensing technology for intelligent health and wellness. In this direction, efforts are being made to explore high-performance nano-systems for developing novel sensing technologies capable of functioning at point-of-care (POC) applications for quick diagnosis, data acquisition, and disease management. A combination of nanostructures [i.e., 0D (nanoparticles & quantum dots), 1D (nanorods, nanofibers, nanopillars, & nanowires), 2D (nanosheets, nanoplates, nanopores) & 3D nanomaterials (nanocomposites and complex hierarchical structures)], biosensing prototype, and micro-electronics makes biosensing suitable for early diagnosis, detection & prevention of life-threatening diseases. However, a knowledge gap associated with the potential of 0D, 1D, 2D, and 3D nanostructures for the design and development of efficient POC sensing is yet to be explored carefully and critically. With this focus, this review highlights the latest engineered 0D, 1D, 2D, and 3D nanomaterials for developing next-generation miniaturized, portable POC biosensors development to achieve high sensitivity with potential integration with the internet of medical things (IoMT, for miniaturization and data collection, security, and sharing), artificial intelligence (AI, for desired analytics), etc. for better diagnosis and disease management at the personalized level.

Biopolymer-based electrospun fibers in electrochemical devices: versatile platform for energy, environment, and health monitoring

Electrochemical power tools are regarded as essential keys in a world that is becoming increasingly reliant on fossil fuels in order to meet the challenges of rapidly depleting fossil fuel supplies. Additionally, due to the industrialization of societies and the growth of diseases, the need for sensitive, reliable, inexpensive, and portable sensors and biosensors for noninvasive monitoring of human health and environmental pollution is felt more than ever before. In recent decades, electrospun fibers have emerged as promising candidates for the fabrication of highly efficient electrochemical devices, such as actuators, batteries, fuel cells, supercapacitors, and biosensors. Meanwhile, the use of synthetic polymers in the fabrication of versatile electrochemical devices has raised environmental concerns, leading to an increase in the quest for natural polymers. Natural polymers are primarily derived from microorganisms and plants. Despite the challenges of processing bio-based electrospun fibers, employing natural nanofibers in the fabrication of electrochemical devices has garnered tremendous attention in recent years. Here, various natural polymers and the strategies employed to fabricate various electrospun biopolymers are briefly covered. The recent advances and research strategies used to apply the bio-based electrospun membranes in different electrochemical devices are carefully summarized, along with the scopes in various advanced technologies. A comprehensive and critical discussion about the use of biopolymer-based electrospun fibers as the potential alternative to non-renewable ones in future technologies is briefly highlighted. This review will serve as a field opening platform for using different biopolymer-based electrospun fibers to advance the electrochemical device-based renewable and sustainable technologies, which will be of high interest to a large community. Accordingly, future studies should focus on feasible and cost-effective extraction of biopolymers from natural resources as well as fabrication of high-performance nanofibrous biopolymer-based components applicable in various electrochemical devices.

Strong anti-viral nano biocide based on Ag/ZnO modified by amodiaquine as an antibacterial and antiviral composite

In this paper, we synthesized Ag/ZnO composite colloidal nanoparticles and the surface of nanoparticles was improved by amodiaquine ligand. The synthesized nanoparticles were characterized using the XRD diffraction pattern, FT-IR Spectroscopy, TEM image, and UV-Vis spectroscopy. The antibacterial, antifungal, and antiviral effects of the synthesized colloid were examined on E.coli, Staphylococcus aureus, Pseudomonas aeruginosa, and Enterococcus hirae bacteria, and Candida Albicans and form spore aspergillus fungi, also influenza, herpes simplex, and covid 19 viruses. The results indicate more than 7 log removal of the bacteria, fungi, and viruses by synthesized colloid with a concentration of 15 μg/L (Ag)/50 µg/ml (ZnO). This removal for covid 19 virus is from 3.2 × 10⁸ numbers to 21 viruses within 30 s. Also, irritation and toxicity tests of the synthesized colloid show harmless effects on human cells and tissues. These colloidal nanoparticles were used as mouthwash solution and their clinical tests were done on 500 people infected by the coronavirus. The results indicate that by washing their mouth and nose three times on day all patients got healthy at different times depending on the depth of the disease. Almost all people with no signs of infection and using this solution as a mouthwash didn't infect by the virus during the study.

Application of Nanotechnology in COVID-19 Infection: Findings and Limitations

There is an urgent need to address the global mortality of the COVID-19 pandemic, as it reached 6.3 million as of July 2022. As such, the experts recommended the mass diagnosis of SARS-CoV-2 infection at an early stage using nanotechnology-based sensitive diagnostic approaches. The development of nanobiosensors for Point-of-Care (POC) sampling of COVID-19 could ensure mass detection without the need for sophisticated laboratories or expert personnel. The use of Artificial Intelligence (AI) techniques for POC detection was also proposed. In addition, the utilization of various antiviral nanomaterials such as Silver Nanoparticles (AgNPs) for the development of masks for personal protection mitigates viral transmission. Nowadays, nano-assisted vaccines have been approved for emergency use, but their safety and effectiveness in the mutant strain of the SARS-CoV-2 virus remain challenging. Methodology: Updated literature was sourced from various research indexing databases such as PubMed, SCOPUS, Science Direct, Research Gate and Google Scholars. Result: We presented the concept of novel nanotechnology researched discovery, including nano-devices, electrochemical biosensing, nano-assisted vaccine, and nanomedicines, for use in recent times, which could be a formidable step for future management of COVID-19.