Smart healthcare: A prospective future medical approach for COVID-19.

COVID-19 has greatly affected human life for over 3 years. In this review, we focus on smart healthcare solutions that address major requirements for coping with the COVID-19 pandemic, including (1) the continuous monitoring of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), (2) patient stratification with distinct short-term outcomes (e.g. mild or severe diseases) and long-term outcomes (e.g. long COVID), and (3) adherence to medication and treatments for patients with COVID-19. Smart healthcare often utilizes medical artificial intelligence (AI) and cloud computing and integrates cutting-edge biological and optoelectronic techniques. These are valuable technologies for addressing the unmet needs in the management of COVID. By leveraging deep/machine learning (DL/ML) capabilities and big data, medical AI can perform precise prognosis predictions and provide reliable suggestions for physicians' decision-making. Through the assistance of the Internet of Medical Things (IoMT), which encompasses wearable devices, smartphone apps, Internet-based drug delivery systems, and telemedicine technologies, the status of mild cases can be continuously monitored and medications provided at home without the need for hospital care. In cases that develop into severe cases, emergency feedback can be provided through the hospital for rapid treatment. Smart healthcare can possibly prevent the development of severe COVID-19 cases and therefore lower the burden on intensive care units.

SARS-CoV-2 vaccines in children and adolescents: Can immunization prevent hospitalization?

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants of concern can infect people of all ages and can cause severe diseases in children, such as encephalitis, which require intensive care. Therefore, vaccines are urgently required to prevent severe disease in all age groups. We reviewed the safety and efficacy profiles of mRNA vaccines-BNT162b2 and mRNA-1273-demonstrated by clinical trials or observed in the real world. mRNA-1273 is effective in preventing SARS-CoV-2 infection in preschool children (6 months-6 years old). Both BNT162b2 and mRNA-1273 are effective in preventing SARS-CoV-2 infection in school-aged children and adolescents, thereby preventing post-coronavirus disease (COVID) conditions. The common side effects of vaccination are pain at the injection site, fatigue, and headache. Myocarditis and pericarditis are uncommon. Monitoring post-vaccination troponin levels may help prevent severe cardiac events. The SARS-CoV-2 coronavirus mutates its genome to overcome the herd immunity provided by mass vaccinations; therefore, we may need to develop new generations of vaccines, such as those using viral nucleocapsid proteins as antigens. In conclusion, the mRNA vaccines are generally safe and effective in preventing severe diseases and hospitalization among children and adolescents.

Low compositions of human toll-like receptor 7/8-stimulating RNA motifs in the MERS-CoV, SARS-CoV and SARS-CoV-2 genomes imply a substantial ability to evade human innate immunity.

BACKGROUND: The innate immune system especially Toll-like receptor (TLR) 7/8 and the interferon pathway, constitutes an important first line of defense against single-stranded RNA viruses. However, large-scale, systematic comparisons of the TLR 7/8-stimulating potential of genomic RNAs of single-stranded RNA viruses are rare. In this study, a computational method to evaluate the human TLR 7/8-stimulating ability of single-stranded RNA virus genomes based on their human TLR 7/8-stimulating trimer compositions was used to analyze 1,002 human coronavirus genomes. RESULTS: The human TLR 7/8-stimulating potential of coronavirus genomic (positive strand) RNAs followed the order of NL63-CoV > HKU1-CoV >229E-CoV ≅ OC63-CoV > SARS-CoV-2 > MERS-CoV > SARS-CoV. These results suggest that among these coronaviruses, MERS-CoV, SARS-CoV and SARS-CoV-2 may have a higher ability to evade the human TLR 7/8-mediated innate immune response. Analysis with a logistic regression equation derived from human coronavirus data revealed that most of the 1,762 coronavirus genomic (positive strand) RNAs isolated from bats, camels, cats, civets, dogs and birds exhibited weak human TLR 7/8-stimulating potential equivalent to that of the MERS-CoV, SARS-CoV and SARS-CoV-2 genomic RNAs. CONCLUSIONS: Prediction of the human TLR 7/8-stimulating potential of viral genomic RNAs may be useful for surveillance of emerging coronaviruses from nonhuman mammalian hosts.

Composition of human-specific slow codons and slow di-codons in SARS-CoV and 2019-nCoV are lower than other coronaviruses suggesting a faster protein synthesis rate of SARS-CoV and 2019-nCoV.

Translation of a genetic codon without a cognate tRNA gene is affected by both the cognate tRNA availability and the interaction with non-cognate isoacceptor tRNAs. Moreover, two consecutive slow codons (slow di-codons) lead to a much slower translation rate. Calculating the composition of host specific slow codons and slow di-codons in the viral protein coding sequences can predict the order of viral protein synthesis rates between different virus strains. Comparison of human-specific slow codon and slow di-codon compositions in the genomes of 590 coronaviruses infect humans revealed that the protein synthetic rates of 2019 novel coronavirus (2019-nCoV) and severe acute respiratory syndrome-related coronavirus (SARS-CoV) may be much faster than other coronaviruses infect humans. Analysis of host-specific slow codon and di-codon compositions provides links between viral genomic sequences and capability of virus replication in host cells that may be useful for surveillance of the transmission potential of novel viruses.