New approach in SARS-CoV-2 surveillance using biosensor technology: a review

Enhancing the understanding of SARS-CoV-2 protein with structure and detection methods: An integrative review

As the rapid and accurate screening of infectious diseases can provide meaningful information for outbreak prevention and control, as well as owing to the existing limitations of the polymerase chain reaction (PCR), it is imperative to have new and validated detection techniques for SARS-CoV-2. Therefore, the rationale for outlining the techniques used to detect SARS-CoV-2 proteins and performing a comprehensive comparison to serve as a practical benchmark for future identification of similar viral proteins is clear. This review highlights the urgent need to strengthen pandemic preparedness by emphasizing the importance of integrated measures. These include improved tools for pathogen characterization, optimized societal precautions, the establishment of early warning systems, and the deployment of highly sensitive diagnostics for effective surveillance, triage, and resource management. Additionally, with an improved understanding of the virus' protein structure, considerable advances in targeted detection, treatment, and prevention strategies are expected to greatly improve our ability to respond to future outbreaks.

Hierarchical Nanobiosensors at the End of the SARS-CoV-2 Pandemic

Nanostructures have played a key role in the development of different techniques to attack severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Some applications include masks, vaccines, and biosensors. The latter are of great interest for detecting diseases since some of their features allowed us to find specific markers in secretion samples such as saliva, blood, and even tears. Herein, we highlight how hierarchical nanoparticles integrated into two or more low-dimensional materials present outstanding advantages that are attractive for photonic biosensing using their nanoscale functions. The potential of nanohybrids with their superlative mechanical characteristics together with their optical and optoelectronic properties is discussed. The progress in the scientific research focused on using nanoparticles for biosensing a variety of viruses has become a medical milestone in recent years, and has laid the groundwork for future disease treatments. This perspective analyzes the crucial information about the use of hierarchical nanostructures in biosensing for the prevention, treatment, and mitigation of SARS-CoV-2 effects.

Wearable biosensors for human health: A bibliometric analysis from 2007 to 2022

Objective

This study aimed to determine the status of scientific production on biosensor usage for human health monitoring.

Methods

We used bibliometrics based on the data and metadata retrieved from the Web of Science between 2007 and 2022. Articles unrelated to health and medicine were excluded. The databases were processed using the VOSviewer software and auxiliary spreadsheets. Data extraction yielded 275 articles published in 161 journals, mainly concentrated on 13 journals and 881 keywords plus.

Results

The keywords plus of high occurrences were estimated at 27, with seven to 30 occurrences. From the 1595 identified authors, 125 were consistently connected in the coauthorship network in the total set and were grouped into nine clusters. Using Lotka's law, we identified 24 prolific authors, and Hirsch index analysis revealed that 45 articles were cited more than 45 times. Crosses were identified between 17 articles in the Hirsch index and 17 prolific authors, highlighting the presence of a large set of prolific authors from various interconnected clusters, a triad, and a solitary prolific author.

Conclusion

An exponential trend was observed in biosensor research for health monitoring, identifying areas of innovation, collaboration, and technological challenges that can guide future research on this topic.

Laser nanostructured gold biosensor for proto-oncogene detection

The advancement of biosensor research has been a primary driving force in the continuing progress of modern medical science. While traditional nanofabrication methods have long been the foundation of biosensor research, recent years have seen a shift in the field of nanofabrication towards laser-based techniques. Here we report a gold-based biosensor, with a limit of detection (LoD) 3.18 µM, developed using environmentally friendly Laser Ablation Synthesis in Liquid (LASiS) and Confined Atmospheric Pulsed-laser (CAP) deposition techniques for the first time. The sensors were able detect a DNA fragment corresponding to the longest unpaired sequence of the c-Myc gene, indicating their potential for detecting such fragments in the ctDNA signature of various cancers. The LoD of the developed novel biosensor highlights its reliability and sensitivity as an analytical platform. The reproducibility of the sensor was examined via the production and testing of 200 sensors with the same fabrication methodology. This work offers a scalable, and green approach to fabricating viable biosensors capable of detecting clinically relevant oncogenic targets.

Immunochromatographic enhancement strategy for SARS-CoV-2 detection based on nanotechnology

The global outbreak of coronavirus disease 2019 (COVID-19) has been catastrophic to both human health and social development. Therefore, developing highly reliable and sensitive point-of-care testing (POCT) for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a priority. Among all available POCTs, the lateral flow immunoassay (LFIA, also known as immunochromatography) has proved to be effective due to its accuracy, portability, convenience, and speed. In areas with a scarcity of laboratory resources and medical personnel, the LFIA provides an affordable option for the diagnosis of COVID-19. This review offers a comprehensive overview of methods for improving the sensitivity of SARS-CoV-2 detection using immunochromatography based on nanotechnology, sorted according to the different detection targets (antigens, antibodies, and nucleic acids). It also looks into the performance and properties of the various sensitivity enhancement strategies, before delving into the remaining challenges in COVID-19 diagnosis through LFIA. Ultimately, it seeks to provide helpful guidance in selecting an appropriate strategy for SARS-CoV-2 immunochromatographic detection based on nanotechnology.

Machine Learning Techniques for Effective Pathogen Detection Based on Resonant Biosensors

We describe a machine learning (ML) approach to processing the signals collected from a COVID-19 optical-based detector. Multilayer perceptron (MLP) and support vector machine (SVM) were used to process both the raw data and the feature engineering data, and high performance for the qualitative detection of the SARS-CoV-2 virus with concentration down to 1 TCID50/mL was achieved. Valid detection experiments contained 486 negative and 108 positive samples, and control experiments, in which biosensors without antibody functionalization were used to detect SARS-CoV-2, contained 36 negative samples and 732 positive samples. The data distribution patterns of the valid and control detection dataset, based on T-distributed stochastic neighbor embedding (t-SNE), were used to study the distinguishability between positive and negative samples and explain the ML prediction performance. This work demonstrates that ML can be a generalized effective approach to process the signals and the datasets of biosensors dependent on resonant modes as biosensing mechanism.

Sensitivity-enhanced nanoplasmonic biosensor using direct immobilization of two engineered nanobodies for SARS-CoV-2 spike receptor-binding domain detection

Sensitive, rapid, and easy-to-implement biosensors are critical in responding to highly contagious and fast-spreading severe acute respiratory syndrome coronavirus (SARS-CoV-2) mutations, enabling early infection screening for appropriate isolation and treatment measures to prevent the spread of the virus. Based on the sensing principle of localized surface plasmon resonance (LSPR) and nanobody immunological techniques, an enhanced sensitivity nanoplasmonic biosensor was developed to quantify the SARS-CoV-2 spike receptor-binding domain (RBD) in serum within 30 min. The lowest concentration in the linear range can be detected down to 0.01 ng/mL by direct immobilization of two engineered nanobodies. Both the sensor fabrication process and immune strategy are facile and inexpensive, with the potential for large-scale application. The designed nanoplasmonic biosensor achieved excellent specificity and sensitivity for SARS-CoV-2 spike RBD, providing a potential option for accurate early screening of the novel coronavirus disease 2019 (COVID-19).

Molecular mechanisms and cellular functions of liquid-liquid phase separation during antiviral immune responses

Spatiotemporal separation of cellular components is vital to ensure biochemical processes. Membrane-bound organelles such as mitochondria and nuclei play a major role in isolating intracellular components, while membraneless organelles (MLOs) are accumulatively uncovered via liquid-liquid phase separation (LLPS) to mediate cellular spatiotemporal organization. MLOs orchestrate various key cellular processes, including protein localization, supramolecular assembly, gene expression, and signal transduction. During viral infection, LLPS not only participates in viral replication but also contributes to host antiviral immune responses. Therefore, a more comprehensive understanding of the roles of LLPS in virus infection may open up new avenues for treating viral infectious diseases. In this review, we focus on the antiviral defense mechanisms of LLPS in innate immunity and discuss the involvement of LLPS during viral replication and immune evasion escape, as well as the strategy of targeting LLPS to treat viral infectious diseases.

Looking Forward: The Role of Academic Researchers in Building Sustainable Wastewater Surveillance Programs

BACKGROUND

In just over 2 years, tracking the COVID-19 pandemic through wastewater surveillance advanced from early reports of successful SARS-CoV-2 RNA detection in untreated wastewater to implementation of programs in at least 60 countries. Early wastewater monitoring efforts primarily originated in research laboratories and are now transitioning into more formal surveillance programs run in commercial and public health laboratories. A major challenge in this progression has been to simultaneously optimize methods and build scientific consensus while implementing surveillance programs, particularly during the rapidly changing landscape of the pandemic. Translating wastewater surveillance results for effective use by public health agencies also remains a key objective for the field.

OBJECTIVES

We examined the evolution of wastewater surveillance to identify model collaborations and effective partnerships that have created rapid and sustained success. We propose needed areas of research and key roles academic researchers can play in the framework of wastewater surveillance to aid in the transition from early monitoring efforts to more formalized programs within the public health system.

DISCUSSION

Although wastewater surveillance has rapidly developed as a useful public health tool for tracking COVID-19, there remain technical challenges and open scientific questions that academic researchers are equipped to address. This includes validating methodology and backfilling important knowledge gaps, such as fate and transport of surveillance targets and epidemiological links to wastewater concentrations. Our experience in initiating and implementing wastewater surveillance programs in the United States has allowed us to reflect on key barriers and draw useful lessons on how to promote synergy between different areas of expertise. As wastewater surveillance programs are formalized, the working relationships developed between academic researchers, commercial and public health laboratories, and data users should promote knowledge co-development. We believe active involvement of academic researchers will contribute to building robust surveillance programs that will ultimately provide new insights into population health. https://doi.org/10.1289/EHP11519.

Prostate-Specific Antigen Monitoring Using Nano Zinc(II) Metal-Organic Framework-Based Optical Biosensor

BACKGROUND

The prostate-specific antigen (PSA) is an important cancer biomarker that is commonly utilized in the diagnosis of prostate cancer. The development of a PSA determination technique that is rapid, simple, and inexpensive, in addition to highly accurate, sensitive, and selective, remains a formidable obstacle.

METHODS

In this study, we developed a practical biosensor based on Zn(II) metal-organic framework nanoparticles (Zn-MOFs-NPs). Many spectroscopic and microanalytical tools are used to determine the structure, morphology, and physicochemical properties of the prepared MOF.

RESULTS

According to the results, Zn-MOFs-NPs are sensitive to PSA, selective to an extremely greater extent, and stable in terms of chemical composition. Furthermore, the Zn-MOFs-NPs did not exhibit any interferences from other common analytes that might cause interference. The detection limit for PSA was calculated and was 0.145 fg/mL throughout a wide linear concentration range (0.1 fg/mL-20 pg/mL).

CONCLUSIONS

Zn-MOFs-NPs were successfully used as a growing biosensor for the monitoring and measurement of PSA in biological real samples.

A Closed-Loop Approach to Fight Coronavirus: Early Detection and Subsequent Treatment

The recent COVID-19 pandemic has caused tremendous damage to the social economy and people's health. Some major issues fighting COVID-19 include early and accurate diagnosis and the shortage of ventilator machines for critical patients. In this manuscript, we describe a novel solution to deal with COVID-19: portable biosensing and wearable photoacoustic imaging for early and accurate diagnosis of infection and magnetic neuromodulation or minimally invasive electrical stimulation to replace traditional ventilation. The solution is a closed-loop system in that the three modules are integrated together and form a loop to cover all-phase strategies for fighting COVID-19. The proposed technique can guarantee ubiquitous and onsite detection, and an electrical hypoglossal stimulator can be more effective in helping severe patients and reducing complications caused by ventilators.

A Framework for Biosensors Assisted by Multiphoton Effects and Machine Learning

The ability to interpret information through automatic sensors is one of the most important pillars of modern technology. In particular, the potential of biosensors has been used to evaluate biological information of living organisms, and to detect danger or predict urgent situations in a battlefield, as in the invasion of SARS-CoV-2 in this era. This work is devoted to describing a panoramic overview of optical biosensors that can be improved by the assistance of nonlinear optics and machine learning methods. Optical biosensors have demonstrated their effectiveness in detecting a diverse range of viruses. Specifically, the SARS-CoV-2 virus has generated disturbance all over the world, and biosensors have emerged as a key for providing an analysis based on physical and chemical phenomena. In this perspective, we highlight how multiphoton interactions can be responsible for an enhancement in sensibility exhibited by biosensors. The nonlinear optical effects open up a series of options to expand the applications of optical biosensors. Nonlinearities together with computer tools are suitable for the identification of complex low-dimensional agents. Machine learning methods can approximate functions to reveal patterns in the detection of dynamic objects in the human body and determine viruses, harmful entities, or strange kinetics in cells.

Point-of-care COVID-19 testing: colorimetric diagnosis using rapid and ultra-sensitive ramified rolling circle amplification

In this paper, we report a molecular diagnostic system—combining a colorimetric probe (RHthio-CuSO₄) for pyrophosphate sensing and isothermal gene amplification (ramified rolling circle amplification)—that operates with high selectivity and sensitivity for clinical point-of-care diagnosis of SARS-CoV-2. During the polymerase phase of the DNA amplification process, pyrophosphate was released from the nucleotide triphosphate as a side product, which was then sensed by our RHthio-CuSO₄ probe with a visible color change. This simple colorimetric diagnostic system allowed highly sensitive (1.13 copies/reaction) detection of clinical SARS-CoV-2 within 1 h, while also displaying high selectivity, as evidenced by its discrimination of two respiratory viral genomes (human rhino virus and respiratory syncytial virus) from that of SARS-CoV-2. All of the reactions in this system were performed at a single temperature, with positive identification being made by the naked eye, without requiring any instrumentation. The high sensitivity and selectivity, short detection time (1 h), simple treatment (one-pot reaction), isothermal amplification, and colorimetric detection together satisfy the requirements for clinical point-of-care detection of SARS-CoV-2. Therefore, we believe that this combination of a colorimetric probe and isothermal amplification will be useful for point-of-care testing to prevent the propagation of COVID-19.

Telehealth and Artificial Intelligence Insights into Healthcare during the COVID-19 Pandemic

Soon after the coronavirus disease 2019 pandemic was proclaimed, digital health services were widely adopted to respond to this public health emergency, including comprehensive monitoring technologies, telehealth, creative diagnostic, and therapeutic decision-making methods. The World Health Organization suggested that artificial intelligence might be a valuable way of dealing with the crisis. Artificial intelligence is an essential technology of the fourth industrial revolution that is a critical nonmedical intervention for overcoming the present global health crisis, developing next-generation pandemic preparation, and regaining resilience. While artificial intelligence has much potential, it raises fundamental privacy, transparency, and safety concerns. This study seeks to address these issues and looks forward to an intelligent healthcare future based on best practices and lessons learned by employing telehealth and artificial intelligence during the COVID-19 pandemic.

Investigating the current environmental situation in the Middle East and North Africa (MENA) region during the third wave of COVID-19 pandemic: urban vs. rural context

BACKGROUND

Coronavirus 2019 (COVID-19) pandemic led to a massive global socio-economic tragedy that has impacted the ecosystem. This paper aims to contextualize urban and rural environmental situations during the COVID-19 pandemic in the Middle East and North Africa (MENA) Region.

RESULTS

An online survey was conducted, 6770 participants were included in the final analysis, and 64% were females. The majority of the participants were urban citizens (74%). Over 50% of the urban residents significantly (p < 0.001) reported a reduction in noise, gathering in tourist areas, and gathering in malls and restaurants. Concerning the pollutants, most urban and rural areas have reported an increase in masks thrown in streets (69.49% vs. 73.22%, resp.; p = 0.003). Plastic bags and hospital waste also increased significantly with the same p-value of < 0.001 in urban areas compared with rural ones. The multifactorial logistic model for urban resident predictors achieved acceptable discrimination (AUROC = 0.633) according to age, crowdedness, noise and few pollutants.

CONCLUSION

The COVID-19 pandemic had a beneficial impact on the environment and at the same time, various challenges regarding plastic and medical wastes are rising which requires environmental interventions.

Recent Advances in Metal-Organic Framework-Based Electrochemical Biosensing Applications

In the face of complex environments, considerable effort has been made to accomplish sensitive, accurate and highly-effective detection of target analytes. Given the versatility of metal clusters and ligands, high porosity and large specific surface area, metal–organic framework (MOF) provides researchers with prospective solutions for the construction of biosensing platforms. Combined with the benefits of electrochemistry method such as fast response, low cost and simple operation, the untapped applications of MOF for biosensors are worthy to be exploited. Therefore, this review briefly summarizes the preparation methods of electroactive MOF, including synthesize with electroactive ligands/metal ions, functionalization of MOF with biomolecules and modification for MOF composites. Moreover, recent biosensing applications are highlighted in terms of small biomolecules, biomacromolecules, and pathogenic cells. We conclude with a discussion of future challenges and prospects in the field. It aims to offer researchers inspiration to address the issues appropriately in further investigations.