Aptamer-based lateral flow assay on-site biosensors.

The lateral flow assay (LFA) is a widely used paper-based on-site biosensor that can detect target analytes and obtain test results in several minutes. Generally, antibodies are utilized as the biorecognition molecules in the LFA. However, antibodies selected using an in vivo process not only may risk killing the animal hosts and causing errors between different batches but also their range is restricted by the refrigerated conditions used to store them. To avoid these limitations, aptamers screened by an in vitro process have been studied as biorecognition molecules in LFAs. Based on the sandwich or competitive format, the aptamer-based LFA can accomplish on-site detection of target analytes. Since aptamers have a distinctive ability to undergo conformational changes, the adsorption-desorption format has also been exploited to detect target analytes in aptamer-based LFAs. This paper reviews developments in aptamer-based LFAs in the last three years for the detection of target analytes. Three formats of aptamer-based LFAs, i.e., sandwich, competitive, and adsorption-desorption, are described in detail. Based on these formats, signal amplification strategies and multiplexed detection are discussed in order to provide an overview of aptamer-based LFAs for on-site detection of target analytes. In addition, the potential commercialization and future perspectives of aptamer-based LFAs for rapid detection of SARS-CoV-2 are given to support the COVID-19 pandemic.

5G-enabled ultra-sensitive fluorescence sensor for proactive prognosis of COVID-19.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading around the globe since December 2019. There is an urgent need to develop sensitive and online methods for on-site diagnosing and monitoring of suspected COVID-19 patients. With the huge development of Internet of Things (IoT), the impact of Internet of Medical Things (IoMT) provides an impressive solution to this problem. In this paper, we proposed a 5G-enabled fluorescence sensor for quantitative detection of spike protein and nucleocapsid protein of SARS-CoV-2 by using mesoporous silica encapsulated up-conversion nanoparticles (UCNPs@mSiO2) labeled lateral flow immunoassay (LFIA). The sensor can detect spike protein (SP) with a detection of limit (LOD) 1.6 ng/mL and nucleocapsid protein (NP) with an LOD of 2.2 ng/mL. The feasibility of the sensor in clinical use was further demonstrated by utilizing virus culture as real clinical samples. Moreover, the proposed fluorescence sensor is IoMT enabled, which is accessible to edge hardware devices (personal computers, 5G smartphones, IPTV, etc.) through Bluetooth. Medical data can be transmitted to the fog layer of the network and 5G cloud server with ultra-low latency and high reliably for edge computing and big data analysis. Furthermore, a COVID-19 monitoring module working with the proposed the system is developed on a smartphone application (App), which endows patients and their families to record their medical data and daily conditions remotely, releasing the burdens of going to central hospitals. We believe that the proposed system will be highly practical in the future treatment and prevention of COVID-19 and other mass infectious diseases.

Anti-SARS-CoV-2 IgG and IgM detection with a GMR based LFIA system.

Since December 2019, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused millions of deaths and seriously threatened the safety of human life; indeed, this situation is worsening and many people are infected with the new coronavirus every day. Therefore, it is very important to understand patients' degree of infection and infection history through antibody testing. Such information is useful also for the government and hospitals to formulate reasonable prevention policies and treatment plans. In this paper, we develop a lateral flow immunoassay (LFIA) method based on superparamagnetic nanoparticles (SMNPs) and a giant magnetoresistance (GMR) sensing system for the simultaneously quantitative detection of anti-SARS-CoV-2 immunoglobulin M (IgM) and G (IgG). A simple and time-effective co-precipitation method was utilized to prepare the SMNPs, which have good dispersibility and magnetic property, with an average diameter of 68 nm. The Internet of Medical Things-supported GMR could transmit medical data to a smartphone through the Bluetooth protocol, making patient information available for medical staff. The proposed GMR system, based on SMNP-supported LFIA, has an outstanding advantage in cost-effectiveness and time-efficiency, and is easy to operate. We believe that the suggested GMR based LFIA system will be very useful for medical staff to analyze and to preserve as a record of infection in COVID-19 patients.