COVID-19 Diagnosis: A Comprehensive Review of the RT-qPCR Method for Detection of SARS-CoV-2.

The world is grappling with the coronavirus disease 2019 (COVID-19) pandemic, the causative agent of which is severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 symptoms are similar to the common cold, including fever, sore throat, cough, muscle and chest pain, brain fog, dyspnoea, anosmia, ageusia, and headache. The manifestation of the disease can vary from being asymptomatic to severe life-threatening conditions warranting hospitalization and ventilation support. Furthermore, the emergence of mutecated variants of concern (VOCs) is paramount to the devastating effect of the pandemic. This highly contagious virus and its emergent variants challenge the available advanced viral diagnostic methods for high-accuracy testing with faster result yields. This review is to shed light on the natural history, pathology, molecular biology, and efficient diagnostic methods of COVID-19, detecting SARS-CoV-2 in collected samples. We reviewed the gold standard RT-qPCR method for COVID-19 diagnosis to confer a better understanding and application to combat the COVID-19 pandemic. This comprehensive review may further develop awareness about the management of the COVID-19 pandemic.

COVID-19 Diagnosis: A Comprehensive Review of the RT-qPCR Method for Detection of SARS-CoV-2

The world is grappling with the coronavirus disease 2019 (COVID-19) pandemic, the causative agent of which is severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 symptoms are similar to the common cold, including fever, sore throat, cough, muscle and chest pain, brain fog, dyspnoea, anosmia, ageusia, and headache. The manifestation of the disease can vary from being asymptomatic to severe life-threatening conditions warranting hospitalization and ventilation support. Furthermore, the emergence of mutecated variants of concern (VOCs) is paramount to the devastating effect of the pandemic. This highly contagious virus and its emergent variants challenge the available advanced viral diagnostic methods for high-accuracy testing with faster result yields. This review is to shed light on the natural history, pathology, molecular biology, and efficient diagnostic methods of COVID-19, detecting SARS-CoV-2 in collected samples. We reviewed the gold standard RT-qPCR method for COVID-19 diagnosis to confer a better understanding and application to combat the COVID-19 pandemic. This comprehensive review may further develop awareness about the management of the COVID-19 pandemic.

Psychiatric comorbidity in clinically stable COVID-19 patients.

Aims: To identify prevalence of psychiatric comorbidity in clinically stable COVID-19 patients. Materials and Methods: A cross-sectional single point observational study was conducted among clinically stable 72 COVID-19 infected patients. Psychiatric comorbidity was assessed with the help of DSM-5 Self-Rated Level 1 CCSM-Adult scale. Results: The prevalence of psychiatric comorbidity was 76.4% (n = 55). Depression was the most common diagnosis in 44.44% (n = 32) followed by anxiety (34.72%, n = 25), somatic symptoms (26.39%, n = 19), sleep problems (23.61%, n = 17). Around 45 .83 % (n = 33) patients considered COVID-19 infection as potentially life-threatening and 23.62% (n=17) patients experienced discrimination and stigma after being diagnosed with COVID-19 infection. Using binary logistic regression, physical symptoms was identified as a risk factor for psychiatric comorbidity. Conclusion: Our study provides evidence of a significant impact of COVID-19 infection on mental health in COVID-19 patients.

LSTM-Based Emotion Detection Using Physiological Signals: IoT Framework for Healthcare and Distance Learning in COVID-19.

Human emotions are strongly coupled with physical and mental health of any individual. While emotions exbibit complex physiological and biological phenomenon, yet studies reveal that physiological signals can be used as an indirect measure of emotions. In unprecedented circumstances alike the coronavirus (Covid-19) outbreak, a remote Internet of Things (IoT) enabled solution, coupled with AI can interpret and communicate emotions to serve substantially in healthcare and related fields. This work proposes an integrated IoT framework that enables wireless communication of physiological signals to data processing hub where long short-term memory (LSTM)-based emotion recognition is performed. The proposed framework offers real-time communication and recognition of emotions that enables health monitoring and distance learning support amidst pandemics. In this study, the achieved results are very promising. In the proposed IoT protocols (TS-MAC and R-MAC), ultralow latency of 1 ms is achieved. R-MAC also offers improved reliability in comparison to state of the art. In addition, the proposed deep learning scheme offers high performance ([Formula: see text]-score) of 95%. The achieved results in communications and AI match the interdependency requirements of deep learning and IoT frameworks, thus ensuring the suitability of proposed work in distance learning, student engagement, healthcare, emotion support, and general wellbeing.

Structure-guided T cell vaccine design for SARS-CoV-2 variants and sarbecoviruses.

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants that escape convalescent and vaccine-induced antibody responses has renewed focus on the development of broadly protective T-cell-based vaccines. Here, we apply structure-based network analysis and assessments of HLA class I peptide stability to define mutationally constrained CD8+ T cell epitopes across the SARS-CoV-2 proteome. Highly networked residues are conserved temporally among circulating variants and sarbecoviruses and disproportionately impair spike pseudotyped lentivirus infectivity when mutated. Evaluation of HLA class I stabilizing activity for 18 globally prevalent alleles identifies CD8+ T cell epitopes within highly networked regions with limited mutational frequencies in circulating SARS-CoV-2 variants and deep-sequenced primary isolates. Moreover, these epitopes elicit demonstrable CD8+ T cell reactivity in convalescent individuals but reduced recognition in recipients of mRNA-based vaccines. These data thereby elucidate key mutationally constrained regions and immunogenic epitopes in the SARS-CoV-2 proteome for a global T-cell-based vaccine against emerging variants and SARS-like coronaviruses.

Loss of Bcl-6-Expressing T Follicular Helper Cells and Germinal Centers in COVID-19.

Humoral responses in coronavirus disease 2019 (COVID-19) are often of limited durability, as seen with other human coronavirus epidemics. To address the underlying etiology, we examined post mortem thoracic lymph nodes and spleens in acute SARS-CoV-2 infection and observed the absence of germinal centers and a striking reduction in Bcl-6+ germinal center B cells but preservation of AID+ B cells. Absence of germinal centers correlated with an early specific block in Bcl-6+ TFH cell differentiation together with an increase in T-bet+ TH1 cells and aberrant extra-follicular TNF-α accumulation. Parallel peripheral blood studies revealed loss of transitional and follicular B cells in severe disease and accumulation of SARS-CoV-2-specific "disease-related" B cell populations. These data identify defective Bcl-6+ TFH cell generation and dysregulated humoral immune induction early in COVID-19 disease, providing a mechanistic explanation for the limited durability of antibody responses in coronavirus infections, and suggest that achieving herd immunity through natural infection may be difficult.

The Loss of Bcl-6 Expressing T Follicular Helper Cells and the Absence of Germinal Centers in COVID-19.

Humoral responses in COVID-19 disease are often of limited durability, as seen with other human coronavirus epidemics. To address the underlying etiology, we examined postmortem thoracic lymph nodes and spleens in acute SARS-CoV-2 infection and observed the absence of germinal centers, a striking reduction in Bcl-6+ germinal center B cells but preservation of AID+ B cells. Absence of germinal centers correlated with an early specific block in Bcl-6+TFH cell differentiation together with an increase in T-bet+TH1 cells and aberrant extra-follicular TNF-a accumulation.  Parallel peripheral blood studies revealed loss of transitional and follicular B cells in severe disease and accumulation of SARS-CoV-2-specific "disease-related" B cell populations. These data identify defective Bcl-6+TFH cell generation and dysregulated humoral immune induction early in COVID-19 disease, providing a mechanistic explanation for the limited durability of antibody responses in coronavirus infections and suggest that achieving herd immunity through natural infection may be difficult. Funding: This work was supported by NIH U19 AI110495 to SP, NIH R01 AI146779 to AGS, NIH R01AI137057 and DP2DA042422 to DL, BMH was supported by NIGMS T32 GM007753, TMC was supported by T32 AI007245. Funding for these studies from the Massachusetts Consortium of Pathogen Readiness, the Mark and Lisa Schwartz Foundation and Enid Schwartz is also acknowledged. Conflict of Interest: None. Ethical Approval: This study was performed with the approval of the Institutional Review Boards at the Massachusetts General Hospital and the Brigham and Women's Hospital.

S2 subunit of SARS-nCoV-2 interacts with tumor suppressor protein p53 and BRCA: an in silico study.

Novel coronavirus disease 2019 (COVID-19) is the biggest threat to human being globally. The first case was identified in a patient with flu symptoms along with severe acute respiratory syndrome in Wuhan, China in December 2019 and now it has spread in more than 200 countries. COVID-19 is more lethal in the elderly and people with an underlying condition such as asthma, cancer, diabetes. Here we performed bioinformatic analysis to investigate the interaction of S2 subunit protein of SARS-nCoV-2 of novel coronavirus with tumor suppressor proteins p53 and BRCA-1/2. In this short communication we report the interaction between S2 subunit proteins with tumor suppressor proteins for the first time. This preliminary result will open up a new direction to investigate the effect of a novel coronavirus in cancer patients.

Novel Coronavirus (nCoV): a Bitter Old Enemy in a New Avatar.

Currently, pandemic coronavirus disease 2019 (COVID-19) is the biggest threat to all human beings globally. Till June 8, 2020, it has infected 6,931,000 people and caused 400,857 deaths worldwide. The first case was identified in a patient with influenza-like symptoms along with severe acute respiratory syndrome in Wuhan, China, in December 2019 and now it has spread in more than 200 countries. Since there is no approved cure for this disease until now, there is a lot of mass fear, apprehensions, and questions globally regarding (i) genetic origin and history of the novel coronavirus, (ii) what are the first-line therapies for those who contract this disease, and (iii) what could be the potential vaccine targets. In this short review, we have tried to address these queries in the simplest manner and compiled the history of previous coronaviruses, recent developments in the COVID-19 research, potential future therapeutics, and possible targets to cure the disease.