B-Cell-Epitope-Based Fluorescent Quantum Dot Biosensors for SARS-CoV-2 Enable Highly Sensitive COVID-19 Antibody Detection

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.

A novel fluorescence immunoassay for the quantitative detection of florfenicol in animal-derived foods based on ZnCdSe/ZnS quantum dot labelled antibody

Florfenicol (F), an antimicrobial agent exclusive to veterinary use within the chloramphenicol class, is extensively applied as a broad-spectrum remedy for animal diseases. Despite its efficacy, concerns arise over potential deleterious residues in animal-derived edibles, posing threats to human health. This study pioneers an innovative approach, introducing a quantum dot fluorescence-based immunoassay (FLISA) for the meticulous detection of F residues in animal-derived foods and feeds. This method demonstrates heightened sensitivity, with a detection limit of 0.3 ng/mL and a quantitative detection range of 0.6-30.4 ng/mL. Method validation, applied to diverse food sources, yields recoveries from 90.4 % to 109.7 %, featuring RSDs within 1.3 % to 8.7 %, the results showed high consistency with the national standard HPLC-MS/MS detection method. These findings underscore the method's accuracy and precision, positioning it as a promising tool for swift and reliable F residue detection, with substantial implications for fortifying food safety monitoring.

Low-Cost Biosensor Technologies for Rapid Detection of COVID-19 and Future Pandemics

Many systems have been designed for the detection of SARS-CoV-2, which is the virus that causes COVID-19. SARS-CoV-2 is readily transmitted, resulting in the rapid spread of disease in human populations. Frequent testing at the point of care (POC) is a key aspect for controlling outbreaks caused by SARS-CoV-2 and other emerging pathogens, as the early identification of infected individuals can then be followed by appropriate measures of isolation or treatment, maximizing the chances of recovery and preventing infectious spread. Diagnostic tools used for high-frequency testing should be inexpensive, provide a rapid diagnostic response without sophisticated equipment, and be amenable to manufacturing on a large scale. The application of these devices should enable large-scale data collection, help control viral transmission, and prevent disease propagation. Here we review functional nanomaterial-based optical and electrochemical biosensors for accessible POC testing for COVID-19. These biosensors incorporate nanomaterials coupled with paper-based analytical devices and other inexpensive substrates, traditional lateral flow technology (antigen and antibody immunoassays), and innovative biosensing methods. We critically discuss the advantages and disadvantages of nanobiosensor-based approaches compared to widely used technologies such as PCR, ELISA, and LAMP. Moreover, we delineate the main technological, (bio)chemical, translational, and regulatory challenges associated with developing functional and reliable biosensors, which have prevented their translation into the clinic. Finally, we highlight how nanobiosensors, given their unique advantages over existing diagnostic tests, may help in future pandemics.

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.

State-of-the-Art Smart and Intelligent Nanobiosensors for SARS-CoV-2 Diagnosis

The novel coronavirus appeared to be a milder infection initially, but the unexpected outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), commonly called COVID-19, was transmitted all over the world in late 2019 and caused a pandemic. Human health has been disastrously affected by SARS-CoV-2, which is still evolving and causing more serious concerns, leading to the innumerable loss of lives. Thus, this review provides an outline of SARS-CoV-2, of the traditional tools to diagnose SARS-CoV-2, and of the role of emerging nanomaterials with unique properties for fabricating biosensor devices to diagnose SARS-CoV-2. Smart and intelligent nanomaterial-enabled biosensors (nanobiosensors) have already proven their utility for the diagnosis of several viral infections, as various detection strategies based on nanobiosensor devices are already present, and several other methods are also being investigated by researchers for the determination of SARS-CoV-2 disease; however, considerably more is undetermined and yet to be explored. Hence, this review highlights the utility of various nanobiosensor devices for SARS-CoV-2 determination. Further, it also emphasizes the future outlook of nanobiosensing technologies for SARS-CoV-2 diagnosis.

SARS-CoV-2 Detection Methods

A fast and highly specific detection of COVID-19 infections is essential in managing the virus dissemination networks. The most relevant technologies developed for SARS-CoV-2 detection, along with their advantages and limitations, will be presented and fully explored. Additionally, some of the newest and emerging COVID-19 diagnosis tools, such as biosensing platforms, will also be introduced. Considering the extreme relevance that all these technologies assume in pandemic control, it is of the utmost relevance to have an intrinsic knowledge of the parameters that need to be taken into consideration before choosing the most adequate test for a particular situation. Moreover, the new variants of the virus and their potential impact on the detection method’s effectiveness will be discussed. In order to better manage the pandemic, it is essential to maintain continuous research into the SARS-CoV-2 genome and updated genomic surveillance at the global level. This will allow for timely detection of new mutations and viral variants, which may affect the performance of COVID-19 detection tests.