Identification of key differentially expressed genes in SARS-CoV-2 using RNA-seq analysis with a systems biology approach

COVID-19 is associated with dysregulation of several genes and signaling pathways. Based on the importance of expression profiling in identification of the pathogenesis of COVID-19 and proposing novel therapies for this disorder, we have employed an in silico approach to find differentially expressed genes between COVID-19 patients and healthy controls and their relevance with cellular functions and signaling pathways. We obtained 630 DEmRNAs, including 486 down-regulated DEGs (such as CCL3 and RSAD2) and 144 up-regulated DEGs (such as RHO and IQCA1L), and 15 DElncRNAs, including 9 down-regulated DElncRNAs (such as PELATON and LINC01506) and 6 up-regulated DElncRNAs (such as AJUBA-DT and FALEC). The PPI network of DEGs showed the presence of a number immune-related genes such as those coding for HLA molecules and interferon regulatory factors. Taken together, these results highlight the importance of immune-related genes and pathways in the pathogenesis of COVID-19 and suggest novel targets for treatment of this disorder.

Identification of key differentially expressed genes in SARS-CoV-2 using RNA-seq analysis with a systems biology approach.

COVID-19 is associated with dysregulation of several genes and signaling pathways. Based on the importance of expression profiling in identification of the pathogenesis of COVID-19 and proposing novel therapies for this disorder, we have employed an in silico approach to find differentially expressed genes between COVID-19 patients and healthy controls and their relevance with cellular functions and signaling pathways. We obtained 630 DEmRNAs, including 486 down-regulated DEGs (such as CCL3 and RSAD2) and 144 up-regulated DEGs (such as RHO and IQCA1L), and 15 DElncRNAs, including 9 down-regulated DElncRNAs (such as PELATON and LINC01506) and 6 up-regulated DElncRNAs (such as AJUBA-DT and FALEC). The PPI network of DEGs showed the presence of a number immune-related genes such as those coding for HLA molecules and interferon regulatory factors. Taken together, these results highlight the importance of immune-related genes and pathways in the pathogenesis of COVID-19 and suggest novel targets for treatment of this disorder.

A Concise Review on Dysregulation of LINC00665 in Cancers.

Long Intergenic Non-Protein Coding RNA 665 (LINC00665) is an RNA gene located on the minus strand of chromosome 19. This lncRNA acts as a competing endogenous RNA for miR-4458, miR-379-5p, miR-551b-5p, miR-3619-5p, miR-424-5p, miR-9-5p, miR-214-3p, miR-126-5p, miR-149-3p, miR-379-5p, miR-665, miR-34a-5p, miR-186-5p, miR-138-5p, miR-181c-5p, miR-98, miR-195-5p, miR-224-5p, miR-3619, miR-708, miR-101, miR-1224-5p, miR-34a-5p, and miR-142-5p. Via influencing expression of these miRNAs, it can enhance expression of a number of oncogenes. Moreover, LINC00665 can influence activity of Wnt/ß-Catenin, TGF-ß, MAPK1, NF-κB, ERK, and PI3K/AKT signaling. Function of this lncRNA has been assessed through gain-of-function tests and/or loss-of-function studies. Furthermore, diverse research groups have evaluated its expression levels in tissue samples using microarray and RT-qPCR techniques. In this manuscript, we have summarized the results of these studies and categorized them in three sections, i.e., cell line studies, animal studies, and investigations in clinical samples.

Rational Design of a Hybrid Peptide against Severe Acute Respiratory Syndrome Coronavirus 2 Using Melittin and Angiotensin-Converting Enzyme 2 as Pharmaceutical Agents.

Background: Management of severe acute respiratory syndrome coronavirus 2 in humans depends on the availability of vaccines or effective drugs. Studies have shown that angiotensin-converting enzyme 2 (ACE2) is responsible for binding the viral spike glycoproteins to human cells. Melittin from the bee venom of Apis melifera is a peptide with antimicrobial activities. Materials and Methods: In this study, important amino acid residues of ACE2 interacting with spike glycoproteins of the virus were described based on the ACE2-spike-glycoprotein interface. This has been previously analyzed by Robson in crystal structures of the receptors and ligands. Flexible linkers and 31 amino acid residues from N-terminal of ACE2 as coronavirus spike binding domains (SBDs) were added to 17 N-terminal amino acids of melittin (the hydrophobic motif) to construct a hybrid peptide or M-ACE2SBD. Then, secondary and tertiary structures of the peptide were predicted. Results: Docking of the hybrid peptide and coronavirus SBDs was carried out as well. Previous studies showed that toxicity and hemolytic activity of the melittin hydrophobic motif decreased in comparison to native melittin due to the lack of peptide binding to the exposed anionic lipids of the human cell membranes and hence the novel peptide can be recommended as an appropriate drug for clinical uses. Conclusion: This study has hypothesized that 17 N-terminal amino acids of the mutant melittin used in M-ACE2SBD design are potentially hydrophobic and attached coronavirus-2 through lipid envelope of the virus.

Evaluation of human error in workers of an Iranian copper mine during the COVID-19 pandemic using the CREAM.

BACKGROUND: The outbreak of COVID-19 has adversely affected both global economy and public health around the world. These effects have also been observed in many workplaces, including mines. OBJECTIVE: This study aimed to examine the human error of copper miners during the pandemic. METHOD: This descriptive-analytical, cross-sectional study was performed on 192 workers of a copper mine in Iran.. For this, occupation tasks were firstly analyzed using the Hierarchical Task Analysis (HTA), and then the human error in different subunits was assessed using the basic Cognitive Reliability and Error Analysis Method (CREAM). The prevalence of COVID-19 among miners was determined by assessing positive PCR test records. RESULTS: The probability of human error in the operational subunits including mining, crushing, processing, and support subunits was estimated to be 0.0056, 0.056, 0.0315, and 0.0177, respectively. All three operational units were found to be in the scrambling control mode. The support unit was determined to be in the tactical control mode. Approximately 50% of all workers had been infected with COVID-19, with the highest prevalence in support units. CONCLUSION: The results suggest that during the COVID-19 pandemic, copper miners are at higher risk of human error induced by poor working conditions. Therefore, it is recommended to employ some management strategies such as promotion of safety, health monitoring, and adopting supportive measures to control occupational stresses and therefore the probability of human error in the mine's operational units.

EfficientMask-Net for face authentication in the era of COVID-19 pandemic.

Today, we are facing the COVID-19 pandemic. Accordingly, properly wearing face masks has become vital as an effective way to prevent the rapid spread of COVID-19. This research develops an Efficient Mask-Net method for low-power devices, such as mobile and embedding models with low-memory requirements. The method identifies face mask-wearing conditions in two different schemes: I. Correctly Face Mask (CFM), Incorrectly Face Mask (IFM), and Not Face Mask (NFM) wearing; II. Uncovered Chin IFM, Uncovered Nose IFM, and Uncovered Nose and Mouth IFM. The proposed method can also be helpful to unmask the face for face authentication based on unconstrained 2D facial images in the wild. In this study, deep convolutional neural networks (CNNs) were employed as feature extractors. Then, deep features were fed to a recently proposed large margin piecewise linear (LMPL) classifier. In the experimental study, lightweight and very powerful mobile implementation of CNN models were evaluated, where the novel "EffientNetb0" deep feature extractor with LMPL classifier outperformed well-known end-to-end CNN models, as well as conventional image classification methods. It achieved high accuracies of 99.53 and 99.64% in fulfilling the two mentioned tasks, respectively.

Expression analysis of IFNAR1 and TYK2 transcripts in COVID-19 patients.

As a member of JAK family of non-receptor tyrosine kinases, TYK2 has a crucial role in regulation of immune responses. This protein has a crucial role in constant expression of IFNAR1 on surface of cells and initiation of type I IFN signaling. In the current study, we measured expression of IFNAR1 and TYK2 levels in venous blood samples of COVID-19 patients and matched controls. TYK2 was significantly down-regulated in male patients compared with male controls (RME = 0.34, P value = 0.03). Though, levels of TYK2 were not different between female cases and female controls, or between ICU-admitted and non-ICU-admitted cases. Expression of IFNAR1 was not different either between COVID-19 cases and controls or between patients required ICU admission and non-ICU-admitted cases. However, none of these transcripts can properly diffrentiate COVID-19 cases from controls or separate patients based on disease severity. The current study proposes down-regulation of TYK2 as a molecular mechanism for incapacity of SARS-CoV-2 in induction of a competent IFN response.

Harnessing the Natural Toxic Metabolites in COVID-19.

SARS-CoV-2 is a novel coronavirus and the cause of the recent pandemic; it is an enveloped ß-coronavirus. SARS-CoV-2 appear in the Wuhan City of China for the first time and outspread worldwide quickly. Due to its person-to-person fast transmission, COVID-19 is becoming a global problem. SARS-CoV-2 enter into cells by using ACE2 receptors that are numerous in the lungs and finally can cause acute respiratory distress syndrome (ARDS). Dry cough, sore throat, fever, body pain, headache, GIT discomfort, diarrhoea, and fatigue are some of the COVID-19 symptoms. There is no definite and certain treatment for disease caused by SARS-CoV-2 till now. Some pharmacological effects of toxins, toxoids, and venoms have been proven, and their effects on some diseases have been evaluated. This study aimed to investigate the role of toxins, toxoids, and venom in the pathophysiology of COVID-19 disease.

COVID-19 pandemic: Insights into genetic susceptibility to SARS-CoV-2 and host genes implications on virus spread, disease severity and outcomes.

The outbreak of the newly emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) all over the world has caused global public health emergencies, international concern and economic crises. The systemic SARS-CoV-2 disease (COVID-19) can lead to death through causing unrestrained cytokines-storm and subsequent pulmonary shutdown among the elderly and patients with pre-existing comorbidities. Additionally, in comparison with poor nations without primary health care services, in developed countries with advanced healthcare system we can witness higher number of infections per one million people. In this review, we summarize the latest studies on genes associated with SARS-CoV-2 pathogenesis and propose possible mechanisms of the virus replication cycle and its triggered signaling pathways to encourage researchers to investigate genetic and immune profiles of the disease and try strategies for its treatment. Our review shows that immune response in people with different genetic background might vary as African and then Asian populations have lowest number of affected cases compared with European and American nations. Considering SARS-CoV-2 pathogenesis, we put forward some potentially important genetic gateways to COVID-19 infection including genes involved in the entry and replication of SARS-CoV-2 and the regulation of host immune response which might represent explanation for its spread, severity, and morality. Finally, we suggest that genetic alterations within these gateways could be critical factors in influencing geographical discrepancies of the virus, so it is essential to fully study them and design appropriated and reliable therapeutic agents against COVID-19.

Abnormal Transcript Levels of Cytokines Among Iranian COVID-19 Patients.

The pandemic caused by severe acute respiratory syndrome coronavirus 2 and the related disorder i.e. "coronavirus disease 2019" (COVID-19) has encouraged researchers to unravel the molecular mechanism of disease severity. Several lines of evidence support the impact of "cytokine storm" in the pathogenesis of severe forms of the disorder. We aimed to assess expression levels of nine cytokine coding genes in COVID-19 patients admitted in a hospital. We collected clinical data of patients from their medical reports. Then, we assessed expression of genes using real-time PCR. Expression levels of IFN-G, IL-2, IL-4, IL-6, IL-17, TGF-B, IL-8, and IL-1B were significantly higher in COVID-19 patients compared with healthy controls and in both female and male patients compared with sex-matched controls. However, expression level of TNF-A was not different between COVID-19 patients and healthy controls. Expression of none of these cytokines was different between ICU-admitted patients and other patients except for IL-6 whose expression was lower in the former group compared with the latter (ratio of means = 0.33, P value = 4.82E-02). Then, we assessed diagnostic power of cytokine coding genes in differentiating between COVID-19 patients and controls. The area under curve (AUC) values ranged from 0.94 for IFN-G to 1.0 for IL-2 and IL-1B. After combining the transcript levels of all cytokines, AUC, sensitivity, and specificity values reached 100%, 100%, and 99%, respectively. For differentiation between ICU-admitted patients and other patients, IL-4 with AUC value of 0.68 had the best diagnostic power among cytokine coding genes. Expression of none of cytokine coding genes was correlated with the available clinical/demographic data including age, gender, ICU admission, or erythrocyte sedimentation rate (ESR)/C-reactive protein (CRP) levels. This study provides further evidence for contribution of "cytokine storm" in the pathobiology of moderate/severe forms of COVID-19.

Evaluation of Lactocare® Synbiotic Administration on the Serum Electrolytes and Trace Elements Levels in Psoriasis Patients: a Randomized, Double-Blind, Placebo-Controlled Clinical Trial Study.

BACKGROUND: Despite the exact etiopathogenesis of psoriasis remains unknown, the increasing or decreasing of some trace elements and oxidative stress status are considered to play a role. In this study, the effect of Lactocare® synbiotic on the serum levels of trace elements including Zn, Cu, Mg, Na, Fe, P, Ca, and K in the patients with mild to moderate psoriasis was investigated. METHODS: Sixty-four patients with mild to moderate psoriasis were included. Patients were randomly divided into treatment (n═32) and control (n═32) groups. The treatment group received Lactocare® and the control group received a placebo (two times daily for 12 weeks). Eight patients from the intervention group and 18 patients from the control group discontinued the study because of the recent COVID-19 condition. For routine trace element analysis, the blood samples were collected from all patients at the baseline as well as week 12 post-treatment. The serum was then isolated and the serum levels of trace elements including Fe, K, Ca, Mg, P, Zn, Na, and Cu were measured using an automatic electrolyte analyzer. For confirmation of the effect of Lactocare® on the alteration of serum levels of trace elements, intra-group analysis was performed at two interval times: baseline and week 12 post-treatment. RESULTS: The serum levels of K, P, and Ca in the placebo group were significantly higher than that of the treatment group at baseline. Serum levels of Zn and Ca were significantly higher in the treatment group compared to the placebo group at week 12 post-treatment. Moreover, a significantly lower serum level of K, P, and Ca in the treatment group at the baseline compared to the placebo group was compensated on week 12 post-treatment. Intra-group analysis in the treatment group showed that the serum levels of Fe, Ca, Mg, P, Zn, and Na was significantly increased at week 12 post-treatment compared to baseline levels. Whereas, intra-group analysis in the control group showed only Ca has a significant difference between baseline and week 12 post-treatment. CONCLUSION: The serum levels of Fe, Zn, P, Mg, Ca, and Na are increased significantly 12 weeks after oral administration of Lactocare® in psoriatic patients. The serum level of Fe and Cu is affected by sex at pre- and post-treatment. This study supports the concept that Lactocare® exerts beneficial effects in the gastrointestinal tract to improve mineral absorption in psoriatic patients.

Application of machine learning in the prediction of COVID-19 daily new cases: A scoping review.

COVID-19 has produced a global pandemic affecting all over of the world. Prediction of the rate of COVID-19 spread and modeling of its course have critical impact on both health system and policy makers. Indeed, policy making depends on judgments formed by the prediction models to propose new strategies and to measure the efficiency of the imposed policies. Based on the nonlinear and complex nature of this disorder and difficulties in estimation of virus transmission features using traditional epidemic models, artificial intelligence methods have been applied for prediction of its spread. Based on the importance of machine and deep learning approaches in the estimation of COVID-19 spreading trend, in the present study, we review studies which used these strategies to predict the number of new cases of COVID-19. Adaptive neuro-fuzzy inference system, long short-term memory, recurrent neural network and multilayer perceptron are among the mostly used strategies in this regard. We compared the performance of several machine learning methods in prediction of COVID-19 spread. Root means squared error (RMSE), mean absolute error (MAE), R2 coefficient of determination (R2), and mean absolute percentage error (MAPE) parameters were selected as performance measures for comparison of the accuracy of models. R2 values have ranged from 0.64 to 1 for artificial neural network (ANN) and Bidirectional long short-term memory (LSTM), respectively. Adaptive neuro-fuzzy inference system (ANFIS), Autoregressive Integrated Moving Average (ARIMA) and Multilayer perceptron (MLP) have also have R2 values near 1. ARIMA and LSTM had the highest MAPE values. Collectively, these models are capable of identification of learning parameters that affect dissimilarities in COVID-19 spread across various regions or populations, combining numerous intervention methods and implementing what-if scenarios by integrating data from diseases having analogous trends with COVID-19. Therefore, application of these methods would help in precise policy making to design the most appropriate interventions and avoid non-efficient restrictions.

Assessment of ACE1 variants and ACE1/ACE2 expression in COVID-19 patients.

Contribution of the renin-angiotensinogen system in the risk of COVID-19 and related complications have been assessed by several groups. However, the results are not consistent. We examined levels of ACE1 and ACE2 in the circulation of two groups of COVID-19 patients (ICU-admitted and general ward-admitted patients) compared with healthy controls. We also genotyped two polymorphisms in ACE1 gene (the ACE1-I/D polymorphism rs1799752 and rs4359) to appraise their association with expression levels of ACE1 and ACE2. Expression level of ACE1 was significantly higher in ICU patients compared with non-ICU patients (P value = 0.02). However, its expression was not significantly different between total COVID-19 patients and total controls (P value = 0.34). ACE2 expression was not different ether between two groups of COVID-19 patients (P value = 0.12) or between total COVID-19 patients and total controls (P value = 0.79). While distribution of rs1799752 and rs4359 alleles was similar between study groups, genotype frequencies of rs1799752 were differently distributed among total COVID-19 patients and controls (P value = 0.00001). Moreover, genotypes of the other polymorphism tended to be distinctively distributed among these two groups (P value = 0.06). In the total population of patients and controls, different ACE1 mRNA levels were observed among carriers of different rs1799752 genotypes; of note, ID genotype carriers showed a higher expression of ACE1 compared with II genotype carriers (P = 0.01). ACE1 polymorphisms might affect risk of COVID-19 and expression of ACE transcripts.

A large margin piecewise linear classifier with fusion of deep features in the diagnosis of COVID-19.

The world has experienced epidemics of coronavirus infections several times over the last two decades. Recent studies have shown that using medical imaging techniques can be useful in developing an automatic computer-aided diagnosis system to detect pandemic diseases with high accuracy at an early stage. In this study, a large margin piecewise linear classifier was developed to diagnose COVID-19 compared to a wide range of viral pneumonia, including SARS and MERS, using chest x-ray images. In the proposed method, a preprocessing pipeline was employed. Moreover, deep pre- and post-rectified linear unit (ReLU) features were extracted using the well-known VGG-Net19, which was fine-tuned to optimize transfer learning. Afterward, the canonical correlation analysis was performed for feature fusion, and fused deep features were passed into the LMPL classifier. The introduced method reached the highest performance in comparison with related state-of-the-art methods for two different schemes (normal, COVID-19, and typical viral pneumonia) and (COVID-19, SARS, and MERS pneumonia) with 99.39% and 98.86% classification accuracy, respectively.

Angiotensin converting enzyme: A review on expression profile and its association with human disorders with special focus on SARS-CoV-2 infection

Angiotensin-converting enzyme (ACE) and its homologue, ACE2, have been mostly associated with hypertensive disorder. However, recent pandemia of SARS-CoV-2 has put these proteins at the center of attention, as this virus has been shown to exploit ACE2 protein to enter cells. Clear difference in the response of affected patients to this virus has urged researchers to find the molecular basis and pathophysiology of the cell response to this virus. Different levels of expression and function of ACE proteins, underlying disorders, consumption of certain medications and the existence of certain genomic variants within ACE genes are possible explanations for the observed difference in the response of individuals to the SARS-CoV-2 infection. In the current review, we discuss the putative mechanisms for this observation.

Exploring the Role of Heavy Metals and Their Derivatives on the Pathophysiology of COVID-19.

Many aspects of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its disease, COVID-19, have been studied to determine its properties, transmission mechanisms, and pathology. These efforts are aimed at identifying potential approaches to control or treat the disease. Early treatment of novel SARS-CoV-2 infection to minimize symptom progression has minimal evidence; however, many researchers and firms are working on vaccines, and only a few vaccines exist. COVID-19 is affected by several heavy metals and their nanoparticles. We investigated the effects of heavy metals and heavy metal nanoparticles on SARS-CoV-2 and their roles in COVID-19 pathogenesis. AgNPs, AuNPs, gold-silver hybrid NPs, copper nanoparticles, zinc oxide, vanadium, gallium, bismuth, titanium, palladium, silver grafted graphene oxide, and some quantum dots were tested to see if they could minimize the severity or duration of symptoms in patients with SARS-CoV-2 infection when compared to standard therapy.

Evaluation of expression of VDR-associated lncRNAs in COVID-19 patients.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has been shown to cause serious health problems among them is the Acute Respiratory Distress syndrome (ARDS). Vitamin D receptor (VDR) signaling possibly partakes in the pathophysiology of this devastating complication. METHODS: In the current project, we have appraised expression levels of VDR, CYP27B1 and a number of associated lncRNAs in the circulation of COVID-19 patients versus healthy subjects using real-time PCR method. RESULTS: Expression of SNHG6 was considerably lower in COVID-19 patients compared with control subjects (Ratio of mean expression (RME) = 0.22, P value = 7.04E-05) and in both female and male COVID-19 patients compared with sex-matched unaffected individuals (RME = 0.32, P value = 0.04 and RME = 0.16, P value = 0.000679683, respectively). However, its expression was similar among ICU-hospitalized and non-ICU patients. Similarly, expression of SNHG16 was lower in in COVID-19 patients compared with controls (RME = 0.20, P value = 5.94E-05) and in both female and male patients compared with sex-matched controls (RME = 0.32, P value = 0.04 and RME = 0.14, P value = 0.000496435, respectively) with no significant difference among ICU-hospitalized and non-ICU hospitalized patients. Expression of VDR was lower in COVID-19 patients compared with controls (RME = 0.42, P value = 0.04) and in male patients compared with male controls (RME = 0.27, P value = 0.02). Yet, expression of VDR was statistically similar between female subgroups and between ICU-hospitalized and non-ICU hospitalized patients. Expression levels CYP27B, Linc00511 and Linc00346 were similar among COVID-19 patients and healthy subjects or between their subgroups. Significant correlations have been detected between expression levels of VDR, CYP27B and SNHG6, SNHG16, Linc00511 and Linc00346 lncRNAs both among COVID-19 patients and among healthy controls with the most significant ones being SNHG6 and SNHG16 (r = 0.74, P value = 3.26e-17 and r = 0.81, P = 1.54e-22, respectively). CONCLUSION: Combination of transcript levels of VDR, CYP27B and SNHG6, SNHG16, Linc00511 and Linc00346 could differentiate patients from controls with AUC = 0.76, sensitivity = 0.62 and specificity = 0.81. The current data potentiate SNHG6, SNHG16 and VDR as possible contributors in COVID-19 infection but not in the severity of ARDS.

Microalgae: therapeutic potentials and applications.

Recently, special attention has been paid to marine origin compounds such as carbohydrates, peptides, lipids, and carotenoids, which are extracted from microalgae and have anticancer, anti-inflammatory, antimicrobial (e.g., anti-COVID-19 activity), and antioxidant properties in biomedicine and pharmaceutical biotechnology. In addition, these photosynthetic marine microorganisms have several applications in biotechnology and are suitable hosts for the production of recombinant proteins/peptides, such as monoclonal antibodies and vaccines. Silica-based nanoparticles obtained from diatoms (a microalgae group) are used as drug delivery carriers owing to their biodegradability, easy functionalization, low cost, and simple features compared to synthetics, which make these agents proper alternatives for synthetic silica nanoparticles. Therefore, diatom-based nanoparticles are a viable option for the delivery of anti-cancer drugs and reducing the side-effects of cancer chemotherapy.

Application of Machine Learning in Diagnosis of COVID-19 Through X-Ray and CT Images: A Scoping Review.

Coronavirus disease, first detected in late 2019 (COVID-19), has spread fast throughout the world, leading to high mortality. This condition can be diagnosed using RT-PCR technique on nasopharyngeal and throat swabs with sensitivity values ranging from 30 to 70%. However, chest CT scans and X-ray images have been reported to have sensitivity values of 98 and 69%, respectively. The application of machine learning methods on CT and X-ray images has facilitated the accurate diagnosis of COVID-19. In this study, we reviewed studies which used machine and deep learning methods on chest X-ray images and CT scans for COVID-19 diagnosis and compared their performance. The accuracy of these methods ranged from 76% to more than 99%, indicating the applicability of machine and deep learning methods in the clinical diagnosis of COVID-19.