The rampant spread of COVID-19 and the worldwide prevalence of infected cases demand a rapid, simple, and cost-effective Point of Care Test (PoCT) for the accurate diagnosis of this pandemic. The most common molecular tests approved by regulatory bodies across the world for COVID-19 diagnosis are based on Polymerase Chain Reaction (PCR). While PCR-based tests are highly sensitive, specific, and remarkably reliable, they have many limitations ranging from the requirement of sophisticated laboratories, need of skilled personnel, use of complex protocol, long wait times for results, and an overall high cost per test. These limitations have inspired researchers to search for alternative diagnostic methods that are fast, economical, and executable in low-resource laboratory settings. The discovery of Loop-mediated isothermal Amplification (LAMP) has provided a reliable substitute platform for the accurate detection of low copy number nucleic acids in the diagnosis of several viral diseases, including epidemics like Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS). At present, a cocktail of LAMP assay reagents along with reverse transcriptase enzyme (Reverse Transcription LAMP, RT-LAMP) can be a robust solution for the rapid and cost-effective diagnosis for COVID-19, particularly in developing, and low-income countries. In summary, the development of RT-LAMP based diagnostic tools in a paper/strip format or the integration of this method into a microfluidic platform such as a Lab-on-a-chip may revolutionize the concept of PoCT for COVID-19 diagnosis. This review discusses the principle, technology and past research underpinning the success for using this method for diagnosing MERS and SARS, in addition to ongoing research, and the prominent prospect of RT-LAMP in the context of COVID-19 diagnosis.

Heart attack is one of the leading causes of human death worldwide. Every year, about 610,000 people die of heart attack in the United States alone—that is one in every four deaths—but there are well understood early symptoms of heart attack that could be used to greatly help in saving many lives and minimizing damages by detecting and reporting at an early stage. On the other hand, every year, about 2.35 million people get injured or disabled from road accidents. Unexpectedly, many of these fatal accidents happen due to the heart attack of drivers that leads to the loss of control of the vehicle. The current work proposes the development of a wearable system for real-time detection and warning of heart attacks in drivers, which could be enormously helpful in reducing road accidents. The system consists of two subsystems that communicate wirelessly using Bluetooth technology, namely, a wearable sensor subsystem and an intelligent heart attack detection and warning subsystem. The sensor subsystem records the electrical activity of the heart from the chest area to produce electrocardiogram (ECG) trace and send that to the other portable decision-making subsystem where the symptoms of heart attack are detected. We evaluated the performance of dry electrodes and different electrode configurations and measured overall power consumption of the system. Linear classification and several machine algorithms were trained and tested for real-time application. It was observed that the linear classification algorithm was not able to detect heart attack in noisy data, whereas the support vector machine (SVM) algorithm with polynomial kernel with extended time–frequency features using extended modified B-distribution (EMBD) showed highest accuracy and was able to detect 97.4% and 96.3% of ST-elevation myocardial infarction (STEMI) and non-ST-elevation MI (NSTEMI), respectively. The proposed system can therefore help in reducing the loss of lives from the growing number of road accidents all over the world.

Silver nanoparticles (AgNPs) synthesized from plant extracts are widely used for the cure of many diseases from fever to cancers. Keeping in view the medicinal value of AgNPs, here we report a cost-effective phytochemical method for the biosynthesis of silver nanoparticles from Ajuga bracteosa. A. bracteosa is an important medicinal plant used to cure fever, appetite-loss, and cancer. Silver-nanoparticles were prepared from the aqueous extract of the plant. The methanolic extract of A. bracteosa (ABMF) was separated and n-hexane (ABHF) and chloroform (ABCF) fractions were obtained from the methanolic crude extract. The AgNPs were characterized by UV-Visible spectrophotometer, FTIR, XRD, and TEM. The total phenolic contents (TPC) and total flavonoid contents (TFC) in different fractions were determined and compared with AgNPs. The medicinal value of ABMF, ABHF, ABCF, and AgNPs was evaluated by antibacterial, antioxidant, anti-inflammatory, and cytotoxicity bioassays. The UV-visible spectrum showed a peak at 484 nm while FTIR results suggested strong capping of phytochemicals on AgNPs which was confirmed by a high amount of TPC and TFC. XRD analysis depicted a high degree of crystallinity and smaller size of AgNPs. TEM results showed spherical shaped AgNPs of size range 50 ± 12 nm. The biosynthesized AgNPs showed better antibacterial activity than plant extract fractions. Similarly, AgNPs have shown better antioxidant, cytotoxicity against cancer cell lines in-vitro, and anti-inflammatory activity in-vivo than a plant extract. The great medicinal value of A. bracteosa might be due to the presence of pharmacologically active phytochemicals such as diterpenoids, neo-clerodane flavonol glycosides, ergosterol, iridoid glycosides, phytoecdysones, and other polyphenols. These phytochemicals surround the silver nanoparticles during green synthesis and therefore, this capping of phytochemicals over silver nanoparticles results in enhanced biomedical applications of plant extracts.