The unexpected pandemic set off by the novel coronavirus (SARS-CoV2) has spread to more than 210 countries across the globe, including India. In the current pandemic situation, various steps have been taken by the Indian government to prevent and control the spread of the SARS-CoV2 infection. To date, there are no proven vaccines or effective therapeutic interventions against the virus. Current clinical management includes infection prevention and control, symptom-specific relief and supportive care. Physicians and scientists across the country have been tirelessly working on developing effective diagnostic and therapeutic strategies and to combat and control this infection. As the demand for diagnostics and therapeutics continues to rise in India and around the globe, it is essential to rapidly develop various algorithms to successfully identify and contain the virus. This review discusses the updates on the recent developments in COVID-19 diagnostics and therapeutics in India.

Since the infectious disease occurrence rate in the human community is gradually rising due to varied reasons, appropriate diagnosis and treatments are essential to control its spread. The recently discovered COVID-19 is one of the contagious diseases, which infected numerous people globally. This contagious disease is arrested by several diagnoses and handling actions. Medical image-supported diagnosis of COVID-19 infection is an approved clinical practice. This research aims to develop a new Deep Learning Method (DLM) to detect the COVID-19 infection using the chest X-ray. The proposed work implemented two methods namely, detection of COVID-19 infection using (i) a Firefly Algorithm (FA) optimized deep-features and (ii) the combined deep and machine features optimized with FA. In this work, a 5-fold cross-validation method is engaged to train and test detection methods. The performance of this system is analyzed individually resulting in the confirmation that the deep feature-based technique helps to achieve a detection accuracy of >  92% with SVM-RBF classifier and combining deep and machine features achieves >  96% accuracy with Fine KNN classifier. In the future, this technique may have potential to play a vital role in testing and validating the X-ray images collected from patients suffering from the infection diseases.

The widespread surge in COVID-19 infections has caused an overwhelming rise in the number of hospital admissions and patient deaths. Massive research efforts are underway globally to develop COVID-19 vaccines. For the newly developed vaccines, given that safety beyond the trial population and the worldwide accessibility remains to be determined, there is also an opportunity to explore repurposing the pre-existing safe vaccines like the oral polio vaccine (OPV) leveraging their potential to provide cross-protection. The plausible mechanisms by which OPV might provide partial cross-immunity against SARS-CoV-2 include inhibition of PVR-TIGITCD226 axis and stimulation of trained innate immunity. Inhibition of PVR-TIGIT-CD226 axis by OPV unleashes the immunosuppressive effects of TIGIT, thus priming the immune system against the invading pathogen. Stimulation of trained innate immunity by OPV due to metabolic reprogramming and epigenetic modifications provides partial protection. This paper reviews the literature about live-attenuated OPV as a potential source of protection against COVID-19 and highlights the need for randomized, multicentric trials in India.

The remarkable developments in neural engineering in collecting and analyzing big data have made it possible to further recognize the patient’s brain conditions through their neural recovery, reconstruction, identification, and diagnosis. As a recent science field, the convergence of signal processing and neural processing begins to emerge to work with a major amount of neuronal information for easy, long, but powerful purposes. With complex neuroscience uses, mass spectroscopy indications for brain-computer connections have proved very exciting. We concentrated on EEG-based methods in this analysis from Solutions in getting high and power solutions. Specifically, in Ecg signals’ growing field, we discuss the latest practices, scientific prospects, and CS threats. We stressed that big CS imaging techniques summarise the minimum foundation and the calculation function being used CS to interpret electrical signals. The whole researcher noted selecting an efficient recovery method, imperfect base, and measuring matrix; it will increase current Adc Brain imaging assessments’ efficiency. Finally, the possibilities and issues emerging from promoting the implementation of its application domain architecture are discussed. Research article presents 4-channel Ica in Eeg data differentiation for treated patients and studies brain functionality. A modern ICA process is developed using a mixed linear, tube, and concurrent processing elements and using alternating and triangular Systems in the brain to achieve a device design and manufactured with UMC 90nm Strong Conventional technologies.