Coronavirus new variants: the mutations cause and the effect on the treatment and vaccination

Using Association Rules to Obtain Sets of Prevalent Symptoms throughout the COVID-19 Pandemic: An Analysis of Similarities between Cases of COVID-19 and Unspecified SARS in São Paulo-Brazil

The efficient recognition of symptoms in viral infections holds promise for swift and precise diagnosis, thus mitigating health implications and the potential recurrence of infections. COVID-19 presents unique challenges due to various factors influencing diagnosis, especially regarding disease symptoms that closely resemble those of other viral diseases, including other strains of SARS, thus impacting the identification of useful and meaningful symptom patterns as they emerge in infections. Therefore, this study proposes an association rule mining approach, utilising the Apriori algorithm to analyse the similarities between individuals with confirmed SARS-CoV-2 diagnosis and those with unspecified SARS diagnosis. The objective is to investigate, through symptom rules, the presence of COVID-19 patterns among individuals initially not diagnosed with the disease. Experiments were conducted using cases from Brazilian SARS datasets for São Paulo State. Initially, reporting percentage similarities of symptoms in both groups were analysed. Subsequently, the top ten rules from each group were compared. Finally, a search for the top five most frequently occurring positive rules among the unspecified ones, and vice versa, was conducted to identify identical rules, with a particular focus on the presence of positive rules among the rules of individuals initially diagnosed with unspecified SARS.

Analysis of Conocurvone, Ganoderic acid A and Oleuropein molecules against the main protease molecule of COVID-19 by in silico approaches: Molecular dynamics docking studies

Traditional medicines against COVID-19 have taken important outbreaks evidenced by multiple cases, controlled clinical research, and randomized clinical trials. Furthermore, the design and chemical synthesis of protease inhibitors, one of the latest therapeutic approaches for virus infection, is to search for enzyme inhibitors in herbal compounds to achieve a minimal amount of side-effect medications. Hence, the present study aimed to screen some naturally derived biomolecules with anti-microbial properties (anti-HIV, antimalarial, and anti-SARS) against COVID-19 by targeting coronavirus main protease via molecular docking and simulations. Docking was performed using SwissDock and Autodock4, while molecular dynamics simulations were performed by the GROMACS-2019 version. The results showed that Oleuropein, Ganoderic acid A, and conocurvone exhibit inhibitory actions against the new COVID-19 proteases. These molecules may disrupt the infection process since they were demonstrated to bind at the coronavirus major protease's active site, affording them potential leads for further research against COVID-19.

Evaluating Time Influence over Performance of Machine-Learning-Based Diagnosis: A Case Study of COVID-19 Pandemic in Brazil

Efficiently recognising severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) symptoms enables a quick and accurate diagnosis to be made, and helps in mitigating the spread of the coronavirus disease 2019. However, the emergence of new variants has caused constant changes in the symptoms associate with COVID-19. These constant changes directly impact the performance of machine-learning-based diagnose. In this context, considering the impact of these changes in symptoms over time is necessary for accurate diagnoses. Thus, in this study, we propose a machine-learning-based approach for diagnosing COVID-19 that considers the importance of time in model predictions. Our approach analyses the performance of XGBoost using two different time-based strategies for model training: month-to-month and accumulated strategies. The model was evaluated using known metrics: accuracy, precision, and recall. Furthermore, to explain the impact of feature changes on model prediction, feature importance was measured using the SHAP technique, an XAI technique. We obtained very interesting results: considering time when creating a COVID-19 diagnostic prediction model is advantageous.

Coronavirus disease 2019 (COVID-19) update: From metabolic reprogramming to immunometabolism

The field of immunometabolism investigates and describes the effects of metabolic rewiring in immune cells throughout activation and the fates of these cells. Recently, it has been appreciated that immunometabolism plays an essential role in the progression of viral infections, cancer, and autoimmune diseases. Regarding COVID‐19, the aberrant immune response underlying the progression of diseases establishes two major respiratory pathologies, including acute respiratory distress syndrome (ARDS) or pneumonia‐induced acute lung injury (ALI). Both innate and adaptive immunity (T cell‐based) were impaired in the course of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection. Current findings have deciphered that macrophages (innate immune cells) are involved in the inflammatory response seen in COVID‐19. It has been demonstrated that immune system cells can change metabolic reprogramming in some conditions, including autoimmune diseases, cancer, and infectious disease, including COVID‐19. The growing findings on metabolic reprogramming in COVID‐19 allow an exploration of metabolites with immunomodulatory properties as future therapies to combat this hyperinflammatory response. The elucidation of the exact role and mechanism underlying this metabolic reprograming in immune cells could help apply more precise approaches to initial diagnosis, prognosis, and in‐hospital therapy. This report discusses the latest findings from COVID‐19 on host metabolic reprogramming and immunometabolic responses.

SARS-CoV-2 triggering autoimmune diseases

Autoimmunity, hyperstimulation of the immune system, can be caused by a variety of reasons. Viruses are thought to be important environmental elements that contribute to the development of autoimmune antibodies. It seems that viruses cause autoimmunity with mechanisms such as molecular mimicry, bystander activation of T cells, transient immunosuppression, and inflammation, which has also been seen in post-Covid-19 autoimmunity. Infection of respiratory epithelium by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) dysregulates the immune response, triggers both innate and acquired immunity that led to the immune system's hyperactivation, excessive cytokine secretion known as “cytokine storm,” and finally acute respiratory distress syndrome (ARDS) associated with high mortality. Any factor in the body that triggers chronic inflammation can contribute to autoimmune disease, which has been documented during the Covid-19 pandemic. It has been observed that some patients produce autoantibody and autoreactive CD4⁺ and CD8⁺ T cells, leading to the loss of self-tolerance. However, there is a scarcity of evidence defining the precise molecular interaction between the virus and the immune system to elicit autoreactivity. Here, we present a review of the relevant immunological findings in Covid-19 and the current reports of autoimmune disease associated with the disease.

The impact of lymphoid memory cells in different ages of COVID-19 patients

Coronaviruses are highly pathogenic and transmissible viruses. The SARS-CoV-2 virus that emerged in December 2019 is increasingly recognized as a serious, worldwide public health concern. Respiratory infections and the hyper-inflammatory response induced by SARS-CoV-2 play a key role in disease severity and death in infected COVID-19 patients. However, much uncertainty still exists about the pathogenesis and various effects of COVID-19 on immune system. It seems that memory T cells can reduce the severity of COVID-19 infection by inducing a protective immune response. Memory T cells along with protective antibodies are the main defenses and also protective barrier against recurrent COVID-19 infection. The role of Memory T cells varies in different ages and the severity of COVID-19 infection varies between children, adults and the elderly. Furthermore, the aim of this review is to evaluate the role of memory cells in mild, moderate and severe infected COVID-19 patients with different ages.

Computational screening of camostat and related compounds against human TMPRSS2: A Potential Treatment of COVID-19

The global coronavirus pandemic has burdened the human population with mass fatalities and disastrous socio-economic consequences. The frequent occurrence of these new variants has fueled the already prevailing challenge. There is still a necessity for highly effective small molecular agents to prevent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Here, we targeted the human transmembrane surface protease TMPRSS2, which is essential for proteolytic activation of SARS-CoV-2. Camostat is a well-known inhibitor of serine proteases and an effective TMPRSS2 inhibitor. A virtual library of camostat-like compounds was computationally screened against the catalytic site of TMPRSS2. Following a sequential in-depth molecular docking and dynamics simulation, we report the compounds that exhibited promising efficacy against TMPRSS2. The molecular docking and MM/PBSA free energy calculation study indicates these compounds carry excellent binding affinity against TMPRSS2 and found them more effective than camostat. The study will open doors for the effective treatment of coronavirus disease 2019.

Chronic myeloid leukemia stem cells: targeting therapeutic implications

Chronic myeloid leukemia (CML) is a clonal myeloproliferative neoplasm driven by BCR-ABL1 oncoprotein, which plays a pivotal role in CML pathology, diagnosis, and treatment as confirmed by the success of tyrosine kinase inhibitor (TKI) therapy. Despite advances in the development of more potent tyrosine kinase inhibitors, some mechanisms particularly in terms of CML leukemic stem cell (CML LSC) lead to intrinsic or acquired therapy resistance, relapse, and disease progression. In fact, the maintenance CML LSCs in patients who are resistance to TKI therapy indicates the role of CML LSCs in resistance to therapy through survival mechanisms that are not completely dependent on BCR-ABL activity. Targeting therapeutic approaches aim to eradicate CML LSCs through characterization and targeting genetic alteration and molecular pathways involving in CML LSC survival in a favorable leukemic microenvironment and resistance to apoptosis, with the hope of providing a functional cure. In other words, it is possible to develop the combination therapy of TKs with drugs targeting genes or molecules more specifically, which is required for survival mechanisms of CML LSCs, while sparing normal HSCs for clinical benefits along with TKIs.

Immunotherapy of multisystem inflammatory syndrome in children (MIS-C) following COVID-19 through mesenchymal stem cells

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new type of coronavirus causing coronavirus 2019 (COVID-19) that was first observed in Wuhan, China, in Dec. 2019. An inflammatory immune response targeting children appeared during the pandemic, which was associated with COVID-19 named multisystem inflammatory syndrome in children (MIS-C). Characteristics of MIS-C include the classic inflammation findings, multi-organ dysfunction, and fever as the cardinal feature. Up to now, no specific therapy has been identified for MIS-C. Currently, considerable progress has been obtained in the MIS-C treatment by cell therapy, specially Mesenchymal stem cells (MSCs). Unique properties have been reported for MSCs, such as various resources for purification of cell, high proliferation, self-renewal, non-invasive procedure, tissue regenerator, multidirectional differentiation, and immunosuppression. As indicated by a recent clinical research, MSCs have the ability of reducing disease inflammation and severity in children with MIS-C. In the present review study, the benefits and characteristics of MSCs and exosomes are discussed for treating patients with MIS-C.