Nano-enabled biosensing systems for intelligent healthcare: towards COVID-19 management

Artificial intelligence for personalized nanomedicine; from material selection to patient outcomes

INTRODUCTION

Artificial intelligence (AI) is changing the field of nanomedicine by exploring novel nanomaterials for developing therapies of high efficacy. AI works on larger datasets, finding sought-after nano-properties for different therapeutic aims and eventually enhancing nanomaterials' safety and effectiveness. AI leverages patient clinical and genetic data to predict outcomes, guide treatments, and optimize drug dosages and forms, enhancing benefits while minimizing side effects. AI-supported nanomedicine faces challenges like data fusion, ethics, and regulation, requiring better tools and interdisciplinary collaboration. This review highlights the importance of AI regarding patient care and urges scientists, medical professionals, and regulators to adopt AI for better outcomes.

AREAS COVERED

Personalized Nanomedicine, Material Discovery, AI-Driven Therapeutics, Data Integration, Drug Delivery, Patient Centric Care.

EXPERT OPINION

Today, AI can improve personalized health wellness through the discovery of new types of drug nanocarriers, nanomedicine of specific properties to tackle targeted medical needs, and an increment in efficacy along with safety. Nevertheless, problems such as ethical issues, data security, or unbalanced data sets need to be addressed. Potential future developments involve using AI and quantum computing together and exploring telemedicine i.e. the Internet-of-Medical-Things (IoMT) approach can enhance the quality of patient care in a personalized manner by timely decision-making.

Recent Advances in Phthalocyanine-Based Hybrid Composites for Electrochemical Biosensors

Biosensors are smart devices that convert biochemical responses to electrical signals. Designing biosensor devices with high sensitivity and selectivity is of great interest because of their wide range of functional operations. However, the major obstacles in the practical application of biosensors are their binding affinity toward biomolecules and the conversion and amplification of the interaction to various signals such as electrical, optical, gravimetric, and electrochemical signals. Additionally, the enhancement of sensitivity, limit of detection, time of response, reproducibility, and stability are considerable challenges when designing an efficient biosensor. In this regard, hybrid composites have high sensitivity, selectivity, thermal stability, and tunable electrical conductivities. The integration of phthalocyanines (Pcs) with conductive materials such as carbon nanomaterials or metal nanoparticles (MNPs) improves the electrochemical response, signal amplification, and stability of biosensors. This review explores recent advancements in hybrid Pcs for biomolecule detection. Herein, we discuss the synthetic strategies, material properties, working mechanisms, and integration methods for designing electrochemical biosensors. Finally, the challenges and future directions of hybrid Pc composites for biosensor applications are discussed.

Adjunctive Testing Using Biospectral Emission Sequencing: Bioregulatory Intelligence Technology in Parallel With the Goals of Artificial Intelligence in Medicine

The many advancements in medical technology of the last century have continually sought to improve the sensitivity of testing and the specificity of treatment of human maladies. Conventional physical and pharmaceutical treatment is largely an imprecise process, stimulating the impetus for the advancement of machine learning-enhanced artificial intelligence (AI) medical technologies. Biospectral Emission Sequencing (BES) is a bioregulatory intelligence (BI) technology already in use as an adjunct to conventional testing. Biospectral Emission Sequencing provides a functional system of dynamic real-time adjunctive testing and treatment selection. This paper discusses the parallel technologies of present and future AI and BI technologies in medicine.

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.

Synergizing Nanomaterials and Artificial Intelligence in Advanced Optical Biosensors for Precision Antimicrobial Resistance Diagnosis

Antimicrobial resistance (AMR) poses a critical global One Health concern, ensuing from unintentional and continuous exposure to antibiotics, as well as challenges in accurate contagion diagnostics. Addressing AMR requires a strategic approach that emphasizes early stage prevention through screening in clinical, environmental, farming, and livestock settings to identify nonvulnerable antimicrobial agents and the associated genes. Conventional AMR diagnostics, like antibiotic susceptibility testing, possess drawbacks, including high costs, time-consuming processes, and significant manpower requirements, underscoring the need for intelligent, prompt, and on-site diagnostic techniques. Nanoenabled artificial intelligence (AI)-supported smart optical biosensors present a potential solution by facilitating rapid point-of-care AMR detection with real-time, sensitive, and portable capabilities. This Review comprehensively explores various types of optical nanobiosensors, such as surface plasmon resonance sensors, whispering-gallery mode sensors, optical coherence tomography, interference reflection imaging sensors, surface-enhanced Raman spectroscopy, fluorescence spectroscopy, microring resonance sensors, and optical tweezer biosensors, for AMR diagnostics. By harnessing the unique advantages of these nanoenabled smart biosensors, a revolutionary paradigm shift in AMR diagnostics can be achieved, characterized by rapid results, high sensitivity, portability, and integration with Internet-of-Things (IoT) technologies. Moreover, nanoenabled optical biosensors enable personalized monitoring and on-site detection, significantly reducing turnaround time and eliminating the human resources needed for sample preservation and transportation. Their potential for holistic environmental surveillance further enhances monitoring capabilities in diverse settings, leading to improved modern-age healthcare practices and more effective management of antimicrobial treatments. Embracing these advanced diagnostic tools promises to bolster global healthcare capacity to combat AMR and safeguard One Health.

Editorial for Special Issue on Biosensors for Biomedical and Environmental Applications

A sensor is typically defined as a device able to transform a physical quantity of interest into a different kind of signal that can be easily measured and recorded [...].

Engineered two-dimensional nanomaterials based diagnostics integrated with internet of medical things (IoMT) for COVID-19

More than four years have passed since an inimitable coronavirus disease (COVID-19) pandemic hit the globe in 2019 after an uncontrolled transmission of the severe acute respiratory syndrome (SARS-CoV-2) infection. The occurrence of this highly contagious respiratory infectious disease led to chaos and mortality all over the world. The peak paradigm shift of the researchers was inclined towards the accurate and rapid detection of diseases. Since 2019, there has been a boost in the diagnostics of COVID-19 via numerous conventional diagnostic tools like RT-PCR, ELISA, etc., and advanced biosensing kits like LFIA, etc. For the same reason, the use of nanotechnology and two-dimensional nanomaterials (2DNMs) has aided in the fabrication of efficient diagnostic tools to combat COVID-19. This article discusses the engineering techniques utilized for fabricating chemically active E2DNMs that are exceptionally thin and irregular. The techniques encompass the introduction of heteroatoms, intercalation of ions, and the design of strain and defects. E2DNMs possess unique characteristics, including a substantial surface area and controllable electrical, optical, and bioactive properties. These characteristics enable the development of sophisticated diagnostic platforms for real-time biosensors with exceptional sensitivity in detecting SARS-CoV-2. Integrating the Internet of Medical Things (IoMT) with these E2DNMs-based advanced diagnostics has led to the development of portable, real-time, scalable, more accurate, and cost-effective SARS-CoV-2 diagnostic platforms. These diagnostic platforms have the potential to revolutionize SARS-CoV-2 diagnosis by making it faster, easier, and more accessible to people worldwide, thus making them ideal for resource-limited settings. These advanced IoMT diagnostic platforms may help with combating SARS-CoV-2 as well as tracking and predicting the spread of future pandemics, ultimately saving lives and mitigating their impact on global health systems.

Automation and Computerization of (Bio)sensing Systems

Sensing systems necessitate automation to reduce human effort, increase reproducibility, and enable remote sensing. In this perspective, we highlight different types of sensing systems with elements of automation, which are based on flow injection and sequential injection analysis, microfluidics, robotics, and other prototypes addressing specific real-world problems. Finally, we discuss the role of computer technology in sensing systems. Automated flow injection and sequential injection techniques offer precise and efficient sample handling and dependable outcomes. They enable continuous analysis of numerous samples, boosting throughput, and saving time and resources. They enhance safety by minimizing contact with hazardous chemicals. Microfluidic systems are enhanced by automation to enable precise control of parameters and increase of analysis speed. Robotic sampling and sample preparation platforms excel in precise execution of intricate, repetitive tasks such as sample handling, dilution, and transfer. These platforms enhance efficiency by multitasking, use minimal sample volumes, and they seamlessly integrate with analytical instruments. Other sensor prototypes utilize mechanical devices and computer technology to address real-world issues, offering efficient, accurate, and economical real-time solutions for analyte identification and quantification in remote areas. Computer technology is crucial in modern sensing systems, enabling data acquisition, signal processing, real-time analysis, and data storage. Machine learning and artificial intelligence enhance predictions from the sensor data, supporting the Internet of Things with efficient data management.

Impact of nanotechnology at heterogeneous interphases @ Sustainability

The 21st century information and communication industries have played the pivotal role of bio-sensing technologies, refining privacy policies for human performance, facilitating scientific innovation, shaping e-governance, and reinforcing public confidence using nanotechnology. Human body is a thermodynamic heat engine in providing effective mechanical work as a function of psyche, conventional fuel transformation into enriched protein meal, and balancing of work-life fulcrum. The triboelectric effect of rubbing surfaces, interfaces, and interphases is invincible from the large field of the planet to nanodomains.

Global Challenges After a Global Challenge: Lessons Learned from the COVID-19 Pandemic

Coronavirus disease 2019 (COVID-19) has affected not only individual lives but also the world and global systems, both natural and human-made. Besides millions of deaths and environmental challenges, the rapid spread of the infection and its very high socioeconomic impact have affected healthcare, economic status and wealth, and mental health across the globe. To better appreciate the pandemic's influence, multidisciplinary and interdisciplinary approaches are needed. In this chapter, world-leading scientists from different backgrounds share collectively their views about the pandemic's footprint and discuss challenges that face the international community.

Reduction of Biosensor False Responses and Time Delay Using Dynamic Response and Theory-Guided Machine Learning

Here, we provide a new methodology for reducing false results and time delay of biosensors, which are barriers to industrial, healthcare, military, and consumer applications. We show that integrating machine learning with domain knowledge in biosensing can complement and improve the biosensor accuracy and speed relative to the performance achieved by traditional regression analysis of a standard curve based on the biosensor steady-state response. The methodology was validated by rapid and accurate quantification of microRNA across the nanomolar to femtomolar range using the dynamic response of cantilever biosensors. Theory-guided feature engineering improved the performance and efficiency of several classification models relative to the performance achieved using traditional feature engineering methods (TSFRESH). In addition to the entire dynamic response, the technique enabled rapid and accurate quantification of the target analyte concentration and false-positive and false-negative results using the initial transient response, thereby reducing the required data acquisition time (i.e., time delay). We show that model explainability can be achieved by combining theory-guided feature engineering and feature importance analysis. The performance of multiple classifiers using both TSFRESH- and theory-based features from the biosensor's initial transient response was similar to that achieved using the entire dynamic response with data augmentation. We also show that the methodology can guide design of experiments for high-performance biosensing applications, specifically, the selection of data acquisition parameters (e.g., time) based on potential application-dependent performance thresholds. This work provides an example of the opportunities for improving biosensor performance, such as reducing biosensor false results and time delay, using explainable machine learning models supervised by domain knowledge in biosensing.

Bionanotechnology and bioMEMS (BNM): state-of-the-art applications, opportunities, and challenges

The development of micro- and nanotechnology for biomedical applications has defined the cutting edge of medical technology for over three decades, as advancements in fabrication technology developed originally in the semiconductor industry have been applied to solving ever-more complex problems in medicine and biology. These technologies are ideally suited to interfacing with life sciences, since they are on the scale lengths as cells (microns) and biomacromolecules (nanometers). In this paper, we review the state of the art in bionanotechnology and bioMEMS (collectively BNM), including developments and challenges in the areas of BNM, such as microfluidic organ-on-chip devices, oral drug delivery, emerging technologies for managing infectious diseases, 3D printed microfluidic devices, AC electrokinetics, flexible MEMS devices, implantable microdevices, paper-based microfluidic platforms for cellular analysis, and wearable sensors for point-of-care testing.

Intelligent Health: Progress and Benefit of Artificial Intelligence in Sensing-Based Monitoring and Disease Diagnosis

Technology has progressed and allows people to go further in multiple fields related to social issues. Medicine cannot be the exception, especially nowadays, when the COVID-19 pandemic has accelerated the use of technology to continue living meaningfully, but mainly in giving consideration to people who remain confined at home with health issues. Our research question is: how can artificial intelligence (AI) translated into technological devices be used to identify health issues, improve people's health, or prevent severe patient damage? Our work hypothesis is that technology has improved so much during the last decades that Medicine cannot remain apart from this progress. It must integrate technology into treatments so proper communication between intelligent devices and human bodies could better prevent health issues and even correct those already manifested. Consequently, we will answer: what has been the progress of Medicine using intelligent sensor-based devices? Which of those devices are the most used in medical practices? Which is the most benefited population, and what do physicians currently use this technology for? Could sensor-based monitoring and disease diagnosis represent a difference in how the medical praxis takes place nowadays, favouring prevention as opposed to healing?

Recent Advances in Quantum Dot-Based Lateral Flow Immunoassays for the Rapid, Point-of-Care Diagnosis of COVID-19

The COVID-19 pandemic has spurred demand for efficient and rapid diagnostic tools that can be deployed at point of care to quickly identify infected individuals. Existing detection methods are time consuming and they lack sensitivity. Point-of-care testing (POCT) has emerged as a promising alternative due to its user-friendliness, rapidity, and high specificity and sensitivity. Such tests can be conveniently conducted at the patient's bedside. Immunodiagnostic methods that offer the rapid identification of positive cases are urgently required. Quantum dots (QDs), known for their multimodal properties, have shown potential in terms of combating or inhibiting the COVID-19 virus. When coupled with specific antibodies, QDs enable the highly sensitive detection of viral antigens in patient samples. Conventional lateral flow immunoassays (LFAs) have been widely used for diagnostic testing due to their simplicity, low cost, and portability. However, they often lack the sensitivity required to accurately detect low viral loads. Quantum dot (QD)-based lateral flow immunoassays have emerged as a promising alternative, offering significant advancements in sensitivity and specificity. Moreover, the lateral flow immunoassay (LFIA) method, which fulfils POCT standards, has gained popularity in diagnosing COVID-19. This review focuses on recent advancements in QD-based LFIA for rapid POCT COVID-19 diagnosis. Strategies to enhance sensitivity using QDs are explored, and the underlying principles of LFIA are elucidated. The benefits of using the QD-based LFIA as a POCT method are highlighted, and its published performance in COVID-19 diagnostics is examined. Overall, the integration of quantum dots with LFIA holds immense promise in terms of revolutionizing COVID-19 detection, treatment, and prevention, offering a convenient and effective approach to combat the pandemic.

Advances in Diagnostic Approaches and Therapeutic Management in Bovine Mastitis

Mastitis causes huge economic losses to dairy farmers worldwide, which largely negatively affects the quality and quantity of milk. Mastitis decreases overall milk production, degrades milk quality, increases milk losses because of milk being discarded, and increases overall production costs due to higher treatment and labour costs and premature culling. This review article discusses mastitis with respect to its clinical epidemiology, the pathogens involved, economic losses, and basic and advanced diagnostic tools that have been used in recent times to diagnose mastitis effectively. There is an increasing focus on the application of novel therapeutic approaches as an alternative to conventional antibiotic therapy because of the decreasing effectiveness of antibiotics, emergence of antibiotic-resistant bacteria, issue of antibiotic residues in the food chain, food safety issues, and environmental impacts. This article also discussed nanoparticles'/chitosan's roles in antibiotic-resistant strains and ethno-veterinary practices for mastitis treatment in dairy cattle.

Integration of IoT-Enabled Technologies and Artificial Intelligence (AI) for Smart City Scenario: Recent Advancements and Future Trends

As the global population grows, and urbanization becomes more prevalent, cities often struggle to provide convenient, secure, and sustainable lifestyles due to the lack of necessary smart technologies. Fortunately, the Internet of Things (IoT) has emerged as a solution to this challenge by connecting physical objects using electronics, sensors, software, and communication networks. This has transformed smart city infrastructures, introducing various technologies that enhance sustainability, productivity, and comfort for urban dwellers. By leveraging Artificial Intelligence (AI) to analyze the vast amount of IoT data available, new opportunities are emerging to design and manage futuristic smart cities. In this review article, we provide an overview of smart cities, defining their characteristics and exploring the architecture of IoT. A detailed analysis of various wireless communication technologies employed in smart city applications is presented, with extensive research conducted to determine the most appropriate communication technologies for specific use cases. The article also sheds light on different AI algorithms and their suitability for smart city applications. Furthermore, the integration of IoT and AI in smart city scenarios is discussed, emphasizing the potential contributions of 5G networks coupled with AI in advancing modern urban environments. This article contributes to the existing literature by highlighting the tremendous opportunities presented by integrating IoT and AI, paving the way for the development of smart cities that significantly enhance the quality of life for urban dwellers while promoting sustainability and productivity. By exploring the potential of IoT, AI, and their integration, this review article provides valuable insights into the future of smart cities, demonstrating how these technologies can positively impact urban environments and the well-being of their inhabitants.

Smart Graphene-Based Electrochemical Nanobiosensor for Clinical Diagnosis: Review

The technological improvement in the field of physics, chemistry, electronics, nanotechnology, biology, and molecular biology has contributed to the development of various electrochemical biosensors with a broad range of applications in healthcare settings, food control and monitoring, and environmental monitoring. In the past, conventional biosensors that have employed bioreceptors, such as enzymes, antibodies, Nucleic Acid (NA), etc., and used different transduction methods such as optical, thermal, electrochemical, electrical and magnetic detection, have been developed. Yet, with all the progresses made so far, these biosensors are clouded with many challenges, such as interference with undesirable compound, low sensitivity, specificity, selectivity, and longer processing time. In order to address these challenges, there is high need for developing novel, fast, highly sensitive biosensors with high accuracy and specificity. Scientists explore these gaps by incorporating nanoparticles (NPs) and nanocomposites (NCs) to enhance the desired properties. Graphene nanostructures have emerged as one of the ideal materials for biosensing technology due to their excellent dispersity, ease of functionalization, physiochemical properties, optical properties, good electrical conductivity, etc. The Integration of the Internet of Medical Things (IoMT) in the development of biosensors has the potential to improve diagnosis and treatment of diseases through early diagnosis and on time monitoring. The outcome of this comprehensive review will be useful to understand the significant role of graphene-based electrochemical biosensor integrated with Artificial Intelligence AI and IoMT for clinical diagnostics. The review is further extended to cover open research issues and future aspects of biosensing technology for diagnosis and management of clinical diseases and performance evaluation based on Linear Range (LR) and Limit of Detection (LOD) within the ranges of Micromolar µM (10^-6), Nanomolar nM (10^-9), Picomolar pM (10^-12), femtomolar fM (10^-15), and attomolar aM (10^-18).

Functional Fiber Materials to Smart Fiber Devices

The development of fiber materials has accompanied the evolution of human civilization for centuries. Recent advances in materials science and chemistry offered fibers new applications with various functions, including energy harvesting, energy storing, displaying, health monitoring and treating, and computing. The unique one-dimensional shape of fiber devices endows them advantages to work as human-interfaced electronics due to the small size, lightweight, flexibility, and feasibility for integration into large-scale textile systems. In this review, we first present a discussion of the basics of fiber materials and the design principles of fiber devices, followed by a comprehensive analysis on recently developed fiber devices. Finally, we provide the current challenges facing this field and give an outlook on future research directions. With novel fiber devices and new applications continuing to be discovered after two decades of research, we envision that new fiber devices could have an important impact on our life in the near future.

The emerging significance of nanomedicine-based approaches to fighting COVID-19 variants of concern: A perspective on the nanotechnology’s role in COVID-19 diagnosis and treatment

COVID-19, one of the worst-hit pandemics, has quickly spread like fire across nations with very high mortality rates. Researchers all around the globe are making consistent efforts to address the main challenges faced due to COVID-19 infection including prompt diagnosis and therapeutics to reduce mortality. Conventional medical technology does not effectively contain the havoc caused by deadly COVID-19. This signals a crucial mandate for innovative and novel interventions in diagnostics and therapeutics to combat this ongoing pandemic and counter its successor or disease if it were ever to arise. The expeditious solutions can spring from promising areas such as nanomedicine and nanotechnology. Nanomedicine is a dominant tool that has a huge potential to alleviate the disease burden by providing nanoparticle-based vaccines and carriers. Nanotechnology encompasses multidisciplinary aspects including artificial intelligence, chemistry, biology, material science, physical science, and medicine. Nanoparticles offer many advantages compared to larger particles, including better magnetic properties and a multiplied surface-to-volume ratio. Given this, the present review focuses on promising nanomedicine-based solutions to combat COVID-19 and their utility to control a broad range of pathogens and viruses, along with understanding their role in the therapy, diagnosis, and prevention of COVID-19. Various studies, reports, and recent research and development from the nanotechnology perspective are discussed in this article.

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.

COVID-19 diagnostics: Molecular biology to nanomaterials

The SARS-CoV-2 pandemic has claimed around 6.4 million lives worldwide. The disease symptoms range from mild flu-like infection to life-threatening complications. The widespread infection demands rapid, simple, and accurate diagnosis. Currently used methods include molecular biology-based approaches that consist of conventional amplification by RT-PCR, isothermal amplification-based techniques such as RT-LAMP, and gene editing tools like CRISPR-Cas. Other methods include immunological detection including ELISA, lateral flow immunoassay, chemiluminescence, etc. Radiological-based approaches are also being used. Despite good analytical performance of these current methods, there is an unmet need for less costly and simpler tests that may be performed at point of care. Accordingly, nanomaterial-based testing has been extensively pursued. In this review, we discuss the currently used diagnostic techniques for SARS-CoV-2, their usefulness, and limitations. In addition, nanoparticle-based approaches have been highlighted as another potential means of detection. The review provides a deep insight into the current diagnostic methods and future trends to combat this deadly menace.

Nucleotide detection mechanism and comparison based on low-dimensional materials: A review

The recent pandemic has led to the fabrication of new nucleic acid sensors that can detect infinitesimal limits immediately and effectively. Therefore, various techniques have been demonstrated using low-dimensional materials that exhibit ultrahigh detection and accuracy. Numerous detection approaches have been reported, and new methods for impulse sensing are being explored. All ongoing research converges at one unique point, that is, an impetus: the enhanced limit of detection of sensors. There are several reviews on the detection of viruses and other proteins related to disease control point of care; however, to the best of our knowledge, none summarizes the various nucleotide sensors and describes their limits of detection and mechanisms. To understand the far-reaching impact of this discipline, we briefly discussed conventional and nanomaterial-based sensors, and then proposed the feature prospects of these devices. Two types of sensing mechanisms were further divided into their sub-branches: polymerase chain reaction and photospectrometric-based sensors. The nanomaterial-based sensor was further subdivided into optical and electrical sensors. The optical sensors included fluorescence (FL), surface plasmon resonance (SPR), colorimetric, and surface-enhanced Raman scattering (SERS), while electrical sensors included electrochemical luminescence (ECL), microfluidic chip, and field-effect transistor (FET). A synopsis of sensing materials, mechanisms, detection limits, and ranges has been provided. The sensing mechanism and materials used were discussed for each category in terms of length, collectively forming a fusing platform to highlight the ultrahigh detection technique of nucleotide sensors. We discussed potential trends in improving the fabrication of nucleotide nanosensors based on low-dimensional materials. In this area, particular aspects, including sensitivity, detection mechanism, stability, and challenges, were addressed. The optimization of the sensing performance and selection of the best sensor were concluded. Recent trends in the atomic-scale simulation of the development of Deoxyribonucleic acid (DNA) sensors using 2D materials were highlighted. A critical overview of the challenges and opportunities of deoxyribonucleic acid sensors was explored, and progress made in deoxyribonucleic acid detection over the past decade with a family of deoxyribonucleic acid sensors was described. Areas in which further research is needed were included in the future scope.

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.

Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review

Despite the fact that COVID-19 is no longer a global pandemic due to development and integration of different technologies for the diagnosis and treatment of the disease, technological advancement in the field of molecular biology, electronics, computer science, artificial intelligence, Internet of Things, nanotechnology, etc. has led to the development of molecular approaches and computer aided diagnosis for the detection of COVID-19. This study provides a holistic approach on COVID-19 detection based on (1) molecular diagnosis which includes RT-PCR, antigen-antibody, and CRISPR-based biosensors and (2) computer aided detection based on AI-driven models which include deep learning and transfer learning approach. The review also provide comparison between these two emerging technologies and open research issues for the development of smart-IoMT-enabled platforms for the detection of COVID-19.

Computer vision enabled funnel adapted sensing tube (FAST) for power-free and pipette-free nucleic acid detection

A simple, portable, and low-cost microfluidic system-funnel adapted sensing tube (FAST) is developed as an integrated, power-free, and pipette-free biosensor for viral nucleic acids. This FAST chip consists of four reaction chambers separated by carbon fiber rods, and the reagents in each chamber are transferred and mixed by manually removing the rods. Rather than using electrical heaters, only a hand warmer pouch is used for an isothermal recombinase polymerase amplification (RPA) and CRISPR-Cas12a reaction. The signal produced by the RPA-CRISPR reaction is observed by the naked eye using an inexpensive flashlight as a light source. The FAST chip is fabricated using water-soluble polyvinyl alcohol (PVA) as a sacrificial core, which is simple and environmentally friendly. Using a SARS-CoV-2 fragment as a target, a ∼10 fM (6 × 10³ copies per μL) detection limit is achieved. To generalize standard optical readout for individuals without training, a linear kernel algorithm is created, showing an accuracy of ∼100% for identifying both positive and negative samples in FAST. This power-free, pipette-free, disposable, and simple device will be a promising tool for nucleic acid diagnostics in either clinics or low-resource settings.

Outlook of various diagnostics and nanodiagnostic techniques for COVID-19

The sudden outbreak of the coronavirus disease 2019 (COVID-19) pandemic has brought to the fore the existing threat of disease-causing pathogens that affect public health all over the world. It has left the best healthcare systems struggling to contain the spread of disease and its consequences. Under challenging circumstances, several innovative technologies have emerged that facilitated quicker diagnosis and treatment. Nanodiagnostic devices are biosensing platforms developed using nanomaterials such as nanoparticles, nanotubes, nanowires, etc. These devices have the edge over conventional techniques such as reverse transcription-polymerase chain reaction (RT-PCR) because of their ease of use, quicker analysis, possible miniaturization, and scope for use in point-of-care (POC) treatment. This review discusses the techniques currently used for COVID-19 diagnosis, emphasizing nanotechnology-based diagnostic devices. The commercialized nanodiagnostic devices in various research and development stages are also reviewed. The advantages of nanodiagnostic devices over other techniques are discussed, along with their limitations. Additionally, the important implications of the utility of nanodiagnostic devices in COVID-19, their prospects for future development for use in clinical and POC settings, and personalized healthcare are also discussed.

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.

Trends in artificial intelligence in nursing: Impacts on nursing management

OBJECTIVE

To investigate the academic use of artificial intelligence (AI) in nursing.

BACKGROUND

A bibliometric analysis combined with the VOSviewer software quantification method has been utilized for a literature analysis. In recent years, this approach has attracted the interest of scholars in various research fields. Thus far, there is no publication using bibliometric analysis combined with the VOSviewer software to analyse the applications of AI in nursing.

METHOD

A bibliometric analysis methodology was used to search for relevant articles published between 1984 and March 2022. Six databases, Embase, Scopus, PubMed, CINAHL, WoS and MEDLINE, were included to identify relevant studies, and data such as the year of publication, journals, country, institutional source, field and keywords were analysed.

RESULTS

Most relevant articles were published from institutions in the United States. The League of European Research Universities has published most research studies that use AI and nursing. Scholars have mainly focused on nursing, medical informatics, computer science AI, healthcare sciences services and physics particles fields. Commonly used keywords were machine learning, care, AI, natural language processing, prediction and nurse.

CONCLUSION

Research articles were mainly published in Nurse Education Today. Research topics such as AI-assisted medical recording and medical decision making were also identified. According to this study, AI in nursing has the potential to attract more attention from researchers and nursing managers. Additional high-quality research beyond the scope of medical education, as well as on cross-domain collaboration, is warranted to explore the acceptability and effective implementation of AI technologies.

IMPLICATIONS FOR NURSING MANAGEMENT

This study provides scholars and nursing managers with structured information regarding the use of AI in nursing based on scientific and technological developments across different fields and institutions. The application of AI can improve nursing management, nursing quality, safety management and team communication, as well as encourage future international collaboration.

Exploring nanoselenium to tackle mutated SARS-CoV-2 for efficient COVID-19 management

Despite ongoing public health measures and increasing vaccination rates, deaths and disease severity caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its new emergent variants continue to threaten the health of people around the world. Therefore, there is an urgent need to develop novel strategies for research, diagnosis, treatment, and government policies to combat the variant strains of SARS-CoV-2. Since the state-of-the-art COVID-19 pandemic, the role of selenium in dealing with COVID-19 disease has been widely discussed due to its importance as an essential micronutrient. This review aims at providing all antiviral activities of nanoselenium (Nano-Se) ever explored using different methods in the literature. We systematically summarize the studied antiviral activities of Nano-Se required to project it as an efficient antiviral system as a function of shape, size, and synthesis method. The outcomes of this article not only introduce Nano-Se to the scientific community but also motivate scholars to adopt Nano-Se to tackle any serious virus such as mutated SARS-CoV-2 to achieve an effective antiviral activity in a desired manner.

Nanomaterials-based sensors for the detection of COVID-19: A review

With the threat of increasing SARS-CoV-2 cases looming in front of us and no effective and safest vaccine available to curb this pandemic disease due to its sprouting variants, many countries have undergone a lockdown 2.0 or planning a lockdown 3.0. This has upstretched an unprecedented demand to develop rapid, sensitive, and highly selective diagnostic devices that can quickly detect coronavirus (COVID-19). Traditional techniques like polymerase chain reaction have proven to be time-inefficient, expensive, labor intensive, and impracticable in remote settings. This shifts the attention to alternative biosensing devices that can be successfully used to sense the COVID-19 infection and curb the spread of coronavirus cases. Among these, nanomaterial-based biosensors hold immense potential for rapid coronavirus detection because of their noninvasive and susceptible, as well as selective properties that have the potential to give real-time results at an economical cost. These diagnostic devices can be used for mass COVID-19 detection to understand the rapid progression of the infection and give better-suited therapies. This review provides an overview of existing and potential nanomaterial-based biosensors that can be used for rapid SARS-CoV-2 diagnostics. Novel biosensors employing different detection mechanisms are also highlighted in different sections of this review. Practical tools and techniques required to develop such biosensors to make them reliable and portable have also been discussed in the article. Finally, the review is concluded by presenting the current challenges and future perspectives of nanomaterial-based biosensors in SARS-CoV-2 diagnostics.

Emerging technologies for combating pandemics

INTRODUCTION

Covid-19, alongside previous pandemics, has highlighted the need for the continued development of technologies that are at our disposal. Emerging technologies are those that show true promise in achieving such a goal and have begun to form sturdy independent research areas. Technological advances in healthcare must continually develop to ensure that the world is prepared for any future diseases that may ensue. As such, a strategic review into 39 manuscripts since 2019 has been conducted to determine the prominence of emerging technologies since the beginning of the Covid-19 pandemic.

AREAS COVERED

Relating to their use in a pandemic state, additive manufacturing (AM), biofabrication, microfluidics, biomedical microelectromechanical systems (BioMEMS), and artificial intelligence (AI) are described. Applications over the past 2-3 years, as well as future developments, are considered throughout.

EXPERT OPINION

All the technologies mentioned in this review are sure to develop further, having shown their importance and value during the covid-19 pandemic. As research continues within the area, their efficacy will increase to the point where it likely will become gold standard for pandemic control. Combining certain technologies mentioned has also proved to have had great success in improving the final results obtained.

Evaluating and mitigating clinical samples matrix effects on TX-TL cell-free performance

Cell-free biosensors are promising tools for medical diagnostics, yet their performance can be affected by matrix effects arising from the sample itself or from external components. Here we systematically evaluate the performance and robustness of cell-free systems in serum, plasma, urine, and saliva using two reporter systems, sfGFP and luciferase. In all cases, clinical samples have a strong inhibitory effect. Of the different inhibitors, only RNase inhibitor mitigated matrix effects. However, we found that the recovery potential of RNase inhibitor was partially muted by interference from glycerol contained in the commercial buffer. We solved this issue by designing a strain producing an RNase inhibitor protein requiring no additional step in extract preparation. Furthermore, our new extract yielded higher reporter levels than previous conditions and tempered interpatient variability associated with matrix effects. This systematic evaluation and improvements of cell-free system robustness unified across many types of clinical samples is a significant step towards developing cell-free diagnostics for a wide range of conditions.

Toward smart diagnosis of pandemic infectious diseases using wastewater-based epidemiology

COVID-19 outbreak revealed fundamental weaknesses of current diagnostic systems, particularly in prediction and subsequently prevention of pandemic infectious diseases (PIDs). Among PIDs detection methods, wastewater-based epidemiology (WBE) has been demonstrated to be a favorable mean for estimation of community-wide health. Besides, by going beyond purely sensing usages of WBE, it can be efficiently exploited in Healthcare 4.0/5.0 for surveillance, monitoring, control, and above all prediction and prevention, thereby, resulting in smart sensing and management of potential outbreaks/epidemics/pandemics. Herein, an overview of WBE sensors for PIDs is presented. The philosophy behind the smart diagnosis of PIDs using WBE with the help of digital technologies is then discussed, as well as their characteristics to be met. Analytical techniques that are pushing the frontiers of smart sensing and have a high potential to be used in the smart diagnosis of PIDs via WBE are surveyed. In this context, we underscore key challenges ahead and provide recommendations for implementing and moving faster toward smart diagnostics.

Artificial Intelligence (AI) and Internet of Medical Things (IoMT) Assisted Biomedical Systems for Intelligent Healthcare

Artificial intelligence (AI) is a modern approach based on computer science that develops programs and algorithms to make devices intelligent and efficient for performing tasks that usually require skilled human intelligence. AI involves various subsets, including machine learning (ML), deep learning (DL), conventional neural networks, fuzzy logic, and speech recognition, with unique capabilities and functionalities that can improve the performances of modern medical sciences. Such intelligent systems simplify human intervention in clinical diagnosis, medical imaging, and decision-making ability. In the same era, the Internet of Medical Things (IoMT) emerges as a next-generation bio-analytical tool that combines network-linked biomedical devices with a software application for advancing human health. In this review, we discuss the importance of AI in improving the capabilities of IoMT and point-of-care (POC) devices used in advanced healthcare sectors such as cardiac measurement, cancer diagnosis, and diabetes management. The role of AI in supporting advanced robotic surgeries developed for advanced biomedical applications is also discussed in this article. The position and importance of AI in improving the functionality, detection accuracy, decision-making ability of IoMT devices, and evaluation of associated risks assessment is discussed carefully and critically in this review. This review also encompasses the technological and engineering challenges and prospects for AI-based cloud-integrated personalized IoMT devices for designing efficient POC biomedical systems suitable for next-generation intelligent healthcare.

OMICRON: Virology, immunopathogenesis, and laboratory diagnosis

Since its emersion, coronavirus disease 2019 (COVID-19) has been a significant global dilemma. Several mutations in the severe acute respiratory virus (SARS-Co-2) genome has given rise to different variants with various levels of transmissibility, severity and mortality. Up until November 2021, the variants of concern declared by the World Health Organization were Alpha, Beta, Delta and Gamma. Since then, a novel variant named Omicron (B.1.1.529) has been developed. BA.1, BA.1.1, BA.2 and BA.3 are four known subvariants of Omicron. The Omicron variant involves new mutations in its spike protein, most of which are in its receptor binding site, and increase its transmissibility and decrease its antibody and vaccine response. Understanding the virology and mutations of Omicron is necessary for developing diagnostic and therapeutic methods. Moreover, important issues, such as the risk of re-infection, the response to different kinds of vaccines, the need for a booster vaccine dose and the increased risk of Omicron infection in pediatrics, need to be addressed. In this article, we provide an overview of the biological and immunopathological properties of Omicron and its subvariants, its clinical signs and symptoms, Omicron and pediatrics, vaccines against Omicron, re-infection with Omicron, diagnostic approaches and specific challenges of Omicron in the successful control and management of the rapid global spread of this variant.

Immunoassay platform with surface-enhanced resonance Raman scattering for detecting trace levels of SARS-CoV-2 spike protein

The early diagnosis of Coronavirus disease (COVID-19) requires either an accurate detection of genetic material or a sensitive detection of viral proteins. In this work, we designed an immunoassay platform for detecting trace levels of SARS-CoV-2 spike (S) protein. It is based on surface-enhanced resonance Raman scattering (SERRS) of methylene blue (MB) adsorbed onto spherical gold nanoparticles (AuNPs) and coated with a 6 nm silica shell. The latter shell in the SERRS nanoprobe prevented aggregation and permitted functionalization with SARS-CoV-2 antibodies. Specificity of the immunoassay was achieved by combining this functionalization with antibody immobilization on the cover slides that served as the platform support. Different concentrations of SARS-CoV-2 antigen could be distinguished and the lack of influence of interferents was confirmed by treating SERRS data with the multidimensional projection technique Sammon's mapping. With SERRS using a laser line at 633 nm, the lowest concentration of spike protein detected was 10 pg/mL, achieving a limit of detection (LOD) of 0.046 ng/mL (0.60 pM). This value is comparable to the lowest concentrations in the plasma of COVID-19 patients at the onset of symptoms, thus indicating that the SERRS immunoassay platform may be employed for early diagnosis.

Utilizing Electrochemical-Based Sensing Approaches for the Detection of SARS-CoV-2 in Clinical Samples: A Review

The development of precise and efficient diagnostic tools enables early treatment and proper isolation of infected individuals, hence limiting the spread of coronavirus disease 2019 (COVID-19). The standard diagnostic tests used by healthcare workers to diagnose severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection have some limitations, including longer detection time, the need for qualified individuals, and the use of sophisticated bench-top equipment, which limit their use for rapid SARS-CoV-2 assessment. Advances in sensor technology have renewed the interest in electrochemical biosensors miniaturization, which provide improved diagnostic qualities such as rapid response, simplicity of operation, portability, and readiness for on-site screening of infection. This review gives a condensed overview of the current electrochemical sensing platform strategies for SARS-CoV-2 detection in clinical samples. The fundamentals of fabricating electrochemical biosensors, such as the chosen electrode materials, electrochemical transducing techniques, and sensitive biorecognition molecules, are thoroughly discussed in this paper. Furthermore, we summarised electrochemical biosensors detection strategies and their analytical performance on diverse clinical samples, including saliva, blood, and nasopharyngeal swab. Finally, we address the employment of miniaturized electrochemical biosensors integrated with microfluidic technology in viral electrochemical biosensors, emphasizing its potential for on-site diagnostics applications.

Innovations and Challenges in Electroanalytical Tools for Rapid Biosurveillance of SARS-CoV-2

Since the onset of the coronavirus disease 2019 (COVID-19) pandemic, preventive social paradigms and vaccine development have undergone serious renovations, which drastically reduced the viral spread and increased collective immunity. Although the technological advancements in diagnostic systems for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) detection are groundbreaking, the lack of sensitive, robust, and consumer-end point-of-care (POC) devices with smartphone connectivity are conspicuously felt. Despite its revolutionary impact on biotechnology and molecular diagnostics, the reverse transcription polymerase chain reaction technique as the gold standard in COVID-19 diagnosis is not suitable for rapid testing. Today's POC tests are dominated by the lateral flow assay technique, with inadequate sensitivity and lack of internet connectivity. Herein, the biosensing advancements in Internet of Things (IoT)-integrated electroanalytical tools as superior POC devices for SARS-CoV-2 detection will be demonstrated. Meanwhile, the impeding factors pivotal for the successful deployment of such novel bioanalytical devices, including the incongruous standards, redundant guidelines, and the limitations of IoT modules will be discussed.

Advances in Nanomaterial-Based Platforms to Combat COVID-19: Diagnostics, Preventions, Therapeutics, and Vaccine Developments

The COVID-19 pandemic caused by the SARS-CoV-2, a ribonucleic acid (RNA) virus that emerged less than two years ago but has caused nearly 6.1 million deaths to date. Recently developed variants of the SARS-CoV-2 virus have been shown to be more potent and expanded at a faster rate. Until now, there is no specific and effective treatment for SARS-CoV-2 in terms of reliable and sustainable recovery. Precaution, prevention, and vaccinations are the only ways to keep the pandemic situation under control. Medical and scientific professionals are now focusing on the repurposing of previous technology and trying to develop more fruitful methodologies to detect the presence of viruses, treat the patients, precautionary items, and vaccine developments. Nanomedicine or nanobased platforms can play a crucial role in these fronts. Researchers are working on many effective approaches by nanosized particles to combat SARS-CoV-2. The role of a nanobased platform to combat SARS-CoV-2 is extremely diverse (i.e., mark to personal protective suit, rapid diagnostic tool to targeted treatment, and vaccine developments). Although there are many theoretical possibilities of a nanobased platform to combat SARS-CoV-2, until now there is an inadequate number of research targeting SARS-CoV-2 to explore such scenarios. This unique mini-review aims to compile and elaborate on the recent advances of nanobased approaches from prevention, diagnostics, treatment to vaccine developments against SARS-CoV-2, and associated challenges.

Therapeutic significance of nano- and biosensor technology in combating SARS-CoV-2: a review

The diagnosis of novel coronavirus (COVID-19) has gained the spotlight of the world's scientific community since December 2019 and it remains an important issue due to the emergence of novel variants around the globe. Early diagnosis of coronavirus is captious to prevent and hard to control. This pandemic can be eradicated by implementing suppressing strategies which can lead to better outcomes and more lives being saved. Therefore, the analysis showed that COVID-19 can only be managed by adopting public health measures, such as testing, isolation and social distancing. Much work has been done to diagnose coronavirus. Various testing technologies have been developed, opted and modified for rapid and accurate detection. The advanced molecular diagnosis relies on the detection of SARS-CoV-2 as it has been considered the main causative agent of this pandemic. Studies have shown that several molecular tests are considered essential for the confirmation of coronavirus infection. Various serology-based tests are also used in the detection and diagnosis of coronavirus including point-of-care assays and high-throughput enzyme immunoassays that aid in the diagnosis of COVID-19. Both these assays are time-consuming and have less diagnostic accuracy. Nanotechnology has the potential to develop new strategies to combat COVID-19 by developing diagnostics and therapeutics. In this review, we have focused on the nanotechnology-based detection techniques including nanoparticles and biosensors to obstruct the spread of SARS-CoV-2.

Advanced materials used in wearable health care devices and medical textiles in the battle against coronavirus (COVID-19): A review

The novel coronavirus disease (COVID-19) has generated great confusion around the world, affecting people's lives and producing a large number of deaths. The development of portable and wearable devices is of great importance in several fields such as point-of-care medical applications and environmental monitoring. Wearable devices with an ability to collect various types of physiological records are progressively becoming incorporated into everyday life of people. Physiological indicators are essential health indicators and their monitoring could efficiently enable early discovery of disease. This would also help decrease the number of extra severe health problems, in disease avoidance, and lower the overall public sector health cost. Protective clothing is nowadays a main part of textiles classified as technical or industrial textiles. Protective clothing aims to protect its wearer from the harsh environmental impacts that may result in injury or death. Providing protection for the common population has also been taken seriously considering the anticipated disaster due to virus attacks. This review highlights the properties of the materials that are used in wearable health care device and medical textiles.

Construction of a binder-free non-enzymatic glucose sensor based on Cu@Ni core-shell nanoparticles anchored on 3D chiral carbon nanocoils-nickel foam hierarchical scaffold

Bimetallic nanostructures composited with carbonaceous materials are the potential contenders for quantitative glucose measurement owing to their unique nanostructures, high biomimetic activity, synergistic effects, good conductivity and chemical stability. In the present work, chemical vapors deposition technique has been employed to grow 3D carbon nanocoils (CNCs) with a chiral morphology on hierarchical macroporous nickel foam (NF) to get a CNCs/NF scaffold. Following, bimetallic Cu@Ni core-shell nanoparticles (CSNPs) are effectively coupled with this scaffold through a facile solvothermal route in order to fabricate a binder-free novel Cu@Ni CSNPs/CNCs/NF hybrid nanostructure. The constructed free-standing 3D hierarchical composite electrode guarantees highly efficient glucose redox activity due to core-shell synergistic effects, enhanced electrochemical active surface area, excellent electrochemical stability, improved conductivity with better ion diffusivity and accelerated reaction kinetics. Being a non-enzymatic glucose sensor, this electrode achieves highly swift response time of 0.1 s, ultra-high sensitivity of 6905 μA mM^-1 cm^-2, low limit of detection of 0.03 μM along with potential selectivity and good storage stability. Moreover, the proposed sensor is also tested successfully for the determination of glucose concentration in human serum samples under good recovery ranging from 96.6 to 102.1 %. The 3D Cu@Ni CSNPs/CNCs/NF composite electrode with unprecedented catalytic performance can be utilized as an ideal biomimetic catalyst in the field of non-enzymatic glucose sensing.

Green syntheses of graphene and its applications in internet of things (IoT)-a status review

Internet of Things (IoT) is a trending technological field that converts any physical object into a communicable smarter one by converging the physical world with the digital world. This innovative technology connects the device to the internet and provides a platform to collect real-time data, cloud storage, and analyze the collected data to trigger smart actions from a remote location via remote notifications, etc. Because of its wide-ranging applications, this technology can be integrated into almost all the industries. Another trending field with tremendous opportunities is Nanotechnology, which provides many benefits in several areas of life, and helps to improve many technological and industrial sectors. So, integration of IoT and Nanotechnology can bring about the very important field of Internet of Nanothings (IoNT), which can re-shape the communication industry. For that, data (collected from trillions of nanosensors, connected to billions of devices) would be the 'ultimate truth', which could be generated from highly efficient nanosensors, fabricated from various novel nanomaterials, one of which is graphene, the so-called 'wonder material' of the 21st century. Therefore, graphene-assisted IoT/IoNT platforms may revolutionize the communication technologies around the globe. In this article, a status review of the smart applications of graphene in the IoT sector is presented. Firstly, various green synthesis of graphene for sustainable development is elucidated, followed by its applications in various nanosensors, detectors, actuators, memory, and nano-communication devices. Also, the future market prospects are discussed to converge various emerging concepts like machine learning, fog/edge computing, artificial intelligence, big data, and blockchain, with the graphene-assisted IoT field to bring about the concept of 'all-round connectivity in every sphere possible'.

Nanotechnology-Assisted Metered-Dose Inhalers (MDIs) for High-Performance Pulmonary Drug Delivery Applications

PURPOSE

Respiratory disorders pose a major threat to the morbidity and mortality to public health. Here we reviewed the nanotechnology based pulmonary drug delivery using metered dose inhalers.

METHODS

Major respiratory diseases such as chronic obstructive pulmonary diseases (COPD), asthma, acute lower respiratory tract infections, tuberculosis (TB) and lung cancer. At present, common treatments for respiratory disorders include surgery, radiation, immunotherapy, and chemotherapy or a combination. The major challenge is development of systemic delivery of the chemotherapeutic agents to the respiratory system. Conventional delivery of chemotherapy has various limitation and adverse side effected. Hence, targeted, and systemic delivery need to be developed. Towards this direction nanotechnology, based controlled, targeted, and systemic drug delivery systems are potential candidate to enhance therapeutic efficacy with minimum side effect. Among different route of administration, pulmonary delivery has unique benefits such as circumvents first pass hepatic metabolism and reduces dose and side effects.

RESULTS

Respiratory disorders pose a major threat to the morbidity and mortality to public health globally. Pulmonary delivery can be achieved through various drug delivery devices such as nebulizers, dry powder inhalers, and metered dose inhalers. Among them, metered dose inhalers are the most interesting and first choice of clinician over others. This review focused on nanotechnology based pulmonary drug delivery using metered dose inhalers. This report focused on delivery of various types of therapeutics using nanocarriers such as polymeric nanoparticles and micelles, dendrimers, lipid nanocarriers such as liposomes, solid lipid nanostructures and nanostructured lipid carriers, and other using metered dose inhalers discussed comprehensively. This report provides insight about the effect of parameters of MDI such as co-solvent, propellants, actuators shape, nozzle diameters, and jet lengths, and respiratory flow rate, and particle size of co-suspension of drug on aerodynamics and lung deposition of formulation. This review also provided the insight about various metered dose inhalers market scenario and digital metered dose inhalers.

CONCLUSION

This report concluded the clinical potential of metered dose inhalers, summary of current progress and future perspectives towards the smart digital metered dose inhalers development.

An encodable multiplex microsphere-phase amplification sensing platform detects SARS-CoV-2 mutations

SARS-CoV-2 variants of concern (VOCs) contain several single-nucleotide variants (SNVs) at key sites in the receptor-binding region (RBD) that enhance infectivity and transmission, as well as cause immune escape, resulting in an aggravation of the coronavirus disease 2019 (COVID-19) pandemic. Emerging VOCs have sparked the need for a diagnostic method capable of simultaneously monitoring these SNVs. To date, no highly sensitive, efficient clinical tool exists to monitor SNVs simultaneously. Here, an encodable multiplex microsphere-phase amplification (MMPA) sensing platform that combines primer-coded microsphere technology with dual fluorescence decoding strategy to detect SARS-CoV-2 RNA and simultaneously identify 10 key SNVs in the RBD. MMPA limits the amplification refractory mutation system PCR (ARMS-PCR) reaction for specific target sequence to the surface of a microsphere with specific fluorescence coding. This effectively solves the problem of non-specific amplification among primers and probes in multiplex PCR. For signal detection, specific fluorescence codes inside microspheres are used to determine the corresponding relationship between the microspheres and the SNV sites, while the report probes hybridized with PCR products are used to detect the microsphere amplification intensity. The MMPA platform offers a lower SARS-CoV-2 RNA detection limit of 28 copies/reaction, the ability to detect a respiratory pathogen panel without cross-reactivity, and a SNV analysis accuracy level comparable to that of sequencing. Moreover, this super-multiple parallel SNVs detection method enables a timely updating of the panel of detected SNVs that accompanies changing VOCs, and presents a clinical availability that traditional sequencing methods do not.

The impact of medical cyber–physical systems on healthcare service delivery

Purpose

The pandemic has reinforced the need for revamping the healthcare service delivery systems around the world to meet the increased challenges of modern-day illnesses. The use of medical cyber–physical system (MCPS) in the healthcare is one of the means of transforming the landscape of the traditional healthcare service delivery system. The purpose of this study is to critically examine the impact of MCPS on the quality of healthcare service delivery.

Design/methodology/approach

This paper uses an evidence-based approach, the authors have conducted a systematic literature review to study the impact of MCPS on healthcare service delivery. Fifty-four articles were thematically examined to study the impact of MCPS on eight characteristics of the healthcare service delivery proposed by the world health organisation.

Findings

The study proposes support that MCPS will positively impact (1) comprehensiveness, (2) accessibility, (3) coverage, (4) continuity, (5) quality, (6) person-centredness, (7) coordination, (8) accountability and (9) efficiency dimension of the healthcare service delivery. The study further draws nine propositions to support the impact of MCPS on the healthcare service delivery.

Practical implications

This study can be used by stakeholders as a guide point while using MCPS in healthcare service delivery systems. Besides, healthcare managers can use this study to understand the performance of their healthcare system. This study can further be used for designing effective strategies for deploying MCPS to be effective and efficient in each of the dimensions of healthcare service delivery.

Originality/value

The previous studies have focussed on technology aspects of MCPS and none of them critically analysed the impact on healthcare service delivery. This is the first literature review carried out to understand the impact of MCPS on the nine dimensions of healthcare service delivery proposed by WHO. This study provides improved thematic awareness of the resulting body of knowledge, allowing the field of MCPS and healthcare service delivery to progress in a more informed and multidisciplinary manner.

Translation of aptamers toward clinical diagnosis and commercialization

The dominance of antibodies in diagnostics has gradually changed following the discovery of aptamers in the early 1990s. Aptamers offer inherent advantages over traditional antibodies, including higher specificity, higher affinity, smaller size, greater stability, ease of manufacture, and low immunogenicity, rendering them the best candidates for point-of-care testing (POCT). In the past 20 years, the research community and pharmaceutical companies have made great efforts to promote the development of aptamer technology. Macugen® (pegaptanib) was the first aptamer drug approved by the US Food and Drug Administration (FDA), and various aptamer-based diagnostics show great promise in preclinical research and clinical trials. In this review, we introduce recent literature, ongoing clinical trials, commercial reagents of aptamer-based diagnostics, discuss the FDA regulatory mechanisms, and highlight the prospects and challenges in translating these studies into viable clinical diagnostic tools.

Recent Progress in Graphene- and Related Carbon-Nanomaterial-based Electrochemical Biosensors for Early Disease Detection

Graphene- and carbon-based nanomaterials are key materials to develop advanced biosensors for the sensitive detection of many biomarkers owing to their unique properties. Biosensors have attracted increasing interest because they allow efficacious, sensitive, selective, rapid, and low-cost diagnosis. Biosensors are analytical devices based on receptors for the process of detection and transducers for response measuring. Biosensors can be based on electrochemical, piezoelectric, thermal, and optical transduction mechanisms. Early virus identification provides critical information about potentially effective and selective therapies, extends the therapeutic window, and thereby reduces morbidity. The sensitivity and selectivity of graphene can be amended via functionalizing it or conjoining it with further materials. Amendment of the optical and electrical features of the hybrid structure by introducing appropriate functional groups or counterparts is especially appealing for quick and easy-to-use virus detection. Various techniques for the electrochemical detection of viruses depending on antigen-antibody interactions or DNA hybridization are discussed in this work, and the reasons behind using graphene and related carbon nanomaterials for the fabrication are presented and discussed. We review the existing state-of-the-art directions of graphene-based classifications for detecting DNA, protein, and hormone biomarkers and summarize the use of the different biosensors to detect several diseases, like cancer, Alzheimer's disease, and diabetes, to sense numerous viruses, including SARS-CoV-2, human immunodeficiency virus, rotavirus, Zika virus, and hepatitis B virus, and to detect the recent pandemic virus COVID-19. The general concepts, mechanisms of action, benefits, and disadvantages of advanced virus biosensors are discussed to afford beneficial evidence of the creation and manufacture of innovative virus biosensors. We emphasize that graphene-based nanomaterials are ideal candidates for electrochemical biosensor engineering due to their special and tunable physicochemical properties.