Designing a Multi-epitope Vaccine against the SARS-CoV-2 Variant Based on an Immunoinformatics Approach.

BACKGROUND: SARS-CoV-2 is a life-threatening virus in the world. Scientific evidence indicates that this pathogen will emerge again in the future. Although the current vaccines have a pivotal role in the control of this pathogen, the emergence of new variants has a negative impact on their effectiveness. OBJECTIVE: Therefore, it is urgent to consider the protective and safe vaccine against all sub-coronavirus species and variants based on the conserved region of the virus. Multi-epitope peptide vaccine (MEV), comprised of immune-dominant epitopes, is designed by immunoinformatic tools and it is a promising strategy against infectious diseases. METHODS: Spike glycoprotein and nucleocapsid proteins from all coronavirus species and variants were aligned and the conserved region was selected. Antigenicity, toxicity, and allergenicity of epitopes were checked by a proper server. To robust the immunity of the multi-epitope vaccine, cholera toxin b (CTB) and three HTL epitopes of tetanus toxin fragment C (TTFrC) were linked at the N-terminal and C-terminal of the construct, respectively. Selected epitopes with MHC molecules and the designed vaccines with Toll-like receptors (TLR-2 and TLR-4) were docked and analyzed. The immunological and physicochemical properties of the designed vaccine were evaluated. The immune responses to the designed vaccine were simulated. Furthermore, molecular dynamic simulations were performed to study the stability and interaction of the MEV-TLRs complexes during simulation time by NAMD (Nanoscale molecular dynamic) software. Finally, the codon of the designed vaccine was optimized according to Saccharomyces boulardii. RESULTS: The conserved regions of spike glycoprotein and nucleocapsid protein were gathered. Then, safe and antigenic epitopes were selected. The population coverage of the designed vaccine was 74.83%. The instability index indicated that the designed multi-epitope was stable (38.61). The binding affinity of the designed vaccine to TLR2 and TLR4 was -11.4 and -11.1, respectively. The designed vaccine could induce humoral and cellular immunity. CONCLUSION: In silico analysis showed that the designed vaccine is a protective multi-epitope vaccine against SARS-CoV-2 variants.

The psychological toll of the COVID-19 pandemic on dental care providers in Iran: A multicenter cross-sectional study.

Background/Purpose: The COVID-19 pandemic affects social and psychological resources. Healthcare workers, especially dental personnel, are more at risk for mental issues due to anxiety, pressure, and frustration. This study assessed mental health outcomes during the COVID-19 epidemic among Iranian dental care providers, focusing on insomnia, anxiety, depression, and posttraumatic stress disorder (PTSD). Methods: In this multicenter cross-sectional survey, the Insomnia Severity Index, the Hospital Anxiety and Depression Scale, and the Global Psychotrauma Screening were masured. Six hundred thirty-eight dental care providers (dental specialists, general dentists, dental hygienists, dental assistants, and dental students) from different parts of Iran (Tehran, Shiraz, Tabriz, and Mashhad) were investigated by the stratified sampling method. The univariate analysis was incorporated as independent in binary logistic regression models to analyze the data. In this study, the significance level was set at 0.05. Results: Among all the participants, 42.8% were dental students or residents, 21.9% were general or specialist dentists, 18.7% were dental assistants, and 16.6% were nonclinicians. The prevalence of insomnia, anxiety, and depression was 31.3%, 40.8%, and 54.9%, respectively. The frequency of participants in the low, moderate, and high levels of PTSD resulting from LCA 56.6%, 33.7%, and 9.7%, respectively. Conclusions: This study found a significant frequency of mental health issues among Iranian dentists. Females, participants whose relatives have COVID-19, and those with a higher workload were more likely to develop mental health symptoms. As mental problems among dental professionals might affect the quality of patient care, diagnostic, supportive, and therapeutic interventions should be taken.

Olfactory system measurements in COVID-19: a systematic review and meta-analysis.

PURPOSE: The neurotropism of SARS-CoV-2 and the consequential damage to the olfactory system have been proposed as one of the possible underlying causes of olfactory dysfunction in COVID-19. We aimed to aggregate the results of the studies which reported imaging of the olfactory system of patients with COVID-19 versus controls. METHODS: PubMed and EMBASE were searched to identify relevant literature reporting the structural imaging characteristics of the olfactory bulb (OB), olfactory cleft, olfactory sulcus (OS), or olfactory tract in COVID-19 patients. Hedge's g and weighted mean difference were used as a measure of effect size. Quality assessment, subgroup analyses, meta-regression, and sensitivity analysis were also conducted. RESULTS: Ten studies were included in the qualitative synthesis, out of which seven studies with 183 cases with COVID-19 and 308 controls without COVID-19 were enrolled in the quantitative synthesis. No significant differences were detected in analyses of right OB volume and left OB volume. Likewise, right OS depth and left OS depth were also not significantly different in COVID-19 cases compared to non-COVID-19 controls. Also, we performed subgroup analysis, meta-regression, and sensitivity analysis to investigate the potential effect of confounding moderators. CONCLUSION: The findings of this review did not confirm alterations in structural imaging of the olfactory system, including OB volume and OS depth by Covid-19 which is consistent with the results of recent histopathological evaluations.

Respiratory Bacterial and Fungal Superinfections During the Third Surge of the COVID-19 Pandemic in Iran.

Objective: We characterized bacterial and fungal superinfection and evaluated the antimicrobial resistance profile against the most common superinfection-causing pathogens (Klebsiella pneumoniae, Acinetobacter baumannii, and Staphylococcus aureus). Methods: In a cross-sectional study, 192 respiratory samples were collected from patients with and without SARS-COV-2 admitted to a teaching hospital in Tehran. Superinfection proportions and the antibiotic resistance profile were assessed and compared with demographic, comorbidities, and other clinical factors. Results: Superinfection rate was 60% among COVID-19 patients (p = 0.629). Intensive care unit admission (p = 0.017), mortality rate (p ≤ 0.001), and antiviral and corticosteroid therapy (p ≤ 0.001) were significantly more common among patients with severe acute respiratory syndrome coronavirus 2 (SARS-COV-2). The most common superinfections were caused by K. pneumoniae (42.7%, 82/192), A. baumannii (14.6%, 28/192), and S. aureus (13%, 25/192). A. baumannii isolates exhibited greater antibiotic resistance. Forty-four percent (11/25) of S. aureus isolates were cefoxitin resistant and also confirmed as methicillin-resistant S. aureus by PCR. Conclusion: The rise of difficult-to-treat infections with a high burden of antibiotic resistance, coupled with an increase in mortality rate of SARS-COV-2 superinfected individuals, illustrates the impact of the COVID-19 pandemic on antimicrobial resistance. Post-pandemic antimicrobial resistance crisis management requires precise microbiological diagnosis, drug susceptibility testing, and prescription of antimicrobials appropriate for the patient's condition.

Evaluation of the Association between Antiphospholipid Antibodies and ICU Admission Outcome in Critically Ill COVID-19 Patients in Iranian Population.

Background: The role of anti-phospholipid antibodies (aPLs) in the prognosis of COVID-19 patients is controversial. In order to prove the role of this factor, the necessary measures such as early initiation of anticoagulants should be started even in the early stages of the disease and in outpatients or the use of other drugs in addition to anticoagulants. We decided to investigate the role of these antibodies in ICU admission outcomes in critically ill COVID-19 patients. Methods: The case-control study was carried out in Isfahan, Iran, from March to September 2021. One hundred nine patients in the case group were selected, including patients admitted to the ICU with a COVID-19 diagnosis. The 140 patients in the control group were selected from hospitalized and outpatients with COVID-19 with PCR + and pulmonary involvement, similar to the case group without the need for ICU hospitalization. The anti B2GP1 (IgM, IgG) and anti-cardiolipin (IgM, IgG)) were compared in two groups. Results: The frequency percentage of patients in the abnormal group of anti-phospholipid antibodies was about 10% in total. No statistically significant difference in these aPLs in continued measures was observed between the two groups of patients admitted to the ICU and those outside the ICU. Also, in the logistics regression analysis, no significant association was observed. Conclusions: Therefore, the cause of coagulation in patients admitted to the ICU is not related to these aPLs. This means that aPLs could not be a good predictor of patient admission to the ICU.

Automated deep learning-based segmentation of COVID-19 lesions from chest computed tomography images.

Purpose: The novel coronavirus COVID-19, which spread globally in late December 2019, is a global health crisis. Chest computed tomography (CT) has played a pivotal role in providing useful information for clinicians to detect COVID-19. However, segmenting COVID-19-infected regions from chest CT results is challenging. Therefore, it is desirable to develop an efficient tool for automated segmentation of COVID-19 lesions using chest CT. Hence, we aimed to propose 2D deep-learning algorithms to automatically segment COVID-19-infected regions from chest CT slices and evaluate their performance. Material and methods: Herein, 3 known deep learning networks: U-Net, U-Net++, and Res-Unet, were trained from scratch for automated segmenting of COVID-19 lesions using chest CT images. The dataset consists of 20 labelled COVID-19 chest CT volumes. A total of 2112 images were used. The dataset was split into 80% for training and validation and 20% for testing the proposed models. Segmentation performance was assessed using Dice similarity coefficient, average symmetric surface distance (ASSD), mean absolute error (MAE), sensitivity, specificity, and precision. Results: All proposed models achieved good performance for COVID-19 lesion segmentation. Compared with Res-Unet, the U-Net and U-Net++ models provided better results, with a mean Dice value of 85.0%. Compared with all models, U-Net gained the highest segmentation performance, with 86.0% sensitivity and 2.22 mm ASSD. The U-Net model obtained 1%, 2%, and 0.66 mm improvement over the Res-Unet model in the Dice, sensitivity, and ASSD, respectively. Compared with Res-Unet, U-Net++ achieved 1%, 2%, 0.1 mm, and 0.23 mm improvement in the Dice, sensitivity, ASSD, and MAE, respectively. Conclusions: Our data indicated that the proposed models achieve an average Dice value greater than 84.0%. Two-dimensional deep learning models were able to accurately segment COVID-19 lesions from chest CT images, assisting the radiologists in faster screening and quantification of the lesion regions for further treatment. Nevertheless, further studies will be required to evaluate the clinical performance and robustness of the proposed models for COVID-19 semantic segmentation.

Neutrophil to Lymphocyte Ratio (NLR) and Derived NLR Combination: A Cost-effective Predictor of Moderate to Severe COVID-19 Progression.

Inflammation is an essential contributor to Coronavirus disease 2019 (COVID-19).   In this regard, finding a prognostic indicator is valuable because the treatment will be more effective if critical patients with high inflammation are diagnosed earlier. We aimed to evaluate some hematologic markers for COVID-19 and assess their association with the severity of the disease. A total of 154 COVID-19 patients were laboratory-confirmed and admitted to Imam Khomeini Hospital Complex, Tehran, Iran, from February 12, 2020, to April 4, 2020, and 55 healthy individuals were enrolled in the study. The severity of the patients' illnesses was classified into three subgroups according to the types of oxygen therapies (moderate (61), severe (28), and critical (43)) and examined the different ratios of total white blood cell (WBC) count, neutrophil to lymphocyte ratio (NLR), platelet to monocyte ratio (PLR), macrophage to lymphocyte ratio (MLR), derived NLR ratio (dNLR), and some biochemical tests. COVID-19 patients had higher levels of NLR, MLR, PLR, and dNLR than healthy subjects. receiver operating characteristic (ROC) analysis of the curve revealed that NLR and dNLR had a high diagnostic value to differentiate COVID-19 patients from healthy subjects (area under the curve [AUC]=0.923 and 0.910, respectively) and predict mortality (AUC=0.726 and 0.735, respectively). NLR and dNLR may be reliable markers to evaluate the severity of COVID-19. NLR and dNLR had a high diagnostic value for differentiating COVID-19 patients from healthy subjects, and they could predict the severity and outcome of the disease.

Vaccines for COVID-19: A Systematic Review of Feasibility and Effectiveness.

INTRODUCTION: Many potential vaccines for COVID-19 are being studied and developed. Several studies have reported on the safety and efficacy of these vaccines. This systematic review aimed to report on the current evidence concerning the feasibility and effectiveness of vaccines for COVID-19. METHODS: A systematic search was carried out utilizing the keywords in the online databases, including Scopus, Web of Science, PubMed, Embase, and Cochrane. We included both human and non-human studies because of the vaccine novelty, limiting our ability to include sufficient human studies. RESULTS: This review showed several SARS-CoV-2 vaccines to be currently under development using different platforms, including eight vaccines that are adenovirus-based vectors, six vaccines that are RNA-based formulations, one vaccine being DNA-based formulation, and other vaccines using other platforms, including lipid nanoparticles. Although the safety and efficacy profiles of these vaccines are still under debate, some countries have allowed for emergency use of some vaccines in at-risk populations, such as healthcare workers and the elderly. CONCLUSION: It is crucial to gather as much clinically relevant evidence as possible regarding the immunogenicity, efficacy, and safety profiles of available vaccines and adhere wisely to CDC protocols and guidelines for vaccine production.

The Hospitalization Rate of Cerebral Venous Sinus Thrombosis before and during COVID-19 Pandemic Era: A Single-Center Retrospective Cohort Study.

OBJECTIVES: There are several reports of the association between SARS-CoV-2 infection (COVID-19) and cerebral venous sinus thrombosis (CVST). In this study, we aimed to compare the hospitalization rate of CVST before and during the COVID-19 pandemic (before vaccination program). MATERIALS AND METHODS: In this retrospective cohort study, the hospitalization rate of adult CVST patients in Namazi hospital, a tertiary referral center in the south of Iran, was compared in two periods of time. We defined March 2018 to March 2019 as the pre-COVID-19 period and March 2020 to March 2021 as the COVID-19 period. RESULTS: 50 and 77 adult CVST patients were hospitalized in the pre-COVID-19 and COVID-19 periods, respectively. The crude CVST hospitalization rate increased from 14.33 in the pre-COVID-19 period to 21.7 per million in the COVID-19 era (P = 0.021). However, after age and sex adjustment, the incremental trend in hospitalization rate was not significant (95% CrI: -2.2, 5.14). Patients > 50-year-old were more often hospitalized in the COVID-19 period (P = 0.042). SARS-CoV-2 PCR test was done in 49.3% out of all COVID-19 period patients, which were positive in 6.5%. Modified Rankin Scale (mRS) score ≥3 at three-month follow-up was associated with age (P = 0.015) and malignancy (P = 0.014) in pre-COVID period; and was associated with age (P = 0.025), altered mental status on admission time (P<0.001), malignancy (P = 0.041) and COVID-19 infection (P = 0.008) in COVID-19 period. CONCLUSION: Since there was a more dismal outcome in COVID-19 associated CVST, a high index of suspicion for CVST among COVID-19 positive is recommended.

Mortality Predictive Value of APACHE II and SOFA Scores in COVID-19 Patients in the Intensive Care Unit.

Background: COVID-19 pandemic has become a global dilemma since December 2019. Are the standard scores, such as acute physiology and chronic health evaluation (APACHE II) and sequential organ failure assessment (SOFA) score, accurate for predicting the mortality rate of COVID-19 or the need for new scores? We aimed to evaluate the mortality predictive value of APACHE II and SOFA scores in critically ill COVID-19 patients. Methods: In a cohort study, we enrolled 204 confirmed COVID-19 patients admitted to the intensive care units at the Imam Khomeini hospital complex. APACHE II on the first day and daily SOFA scoring were performed. The primary outcome was the mortality rate in the nonsurvived and survived groups, and the secondary outcome was organ dysfunction. Two groups of survived and nonsurvived patients were compared by the chi-square test for categorical variables and an independent sample t-test for continuous variables. We used logistic regression models to estimate the mortality risk of high APACHE II and SOFA scores. Result: Among 204 severe COVID-19 patients, 114 patients (55.9%) expired and 169 patients (82.8%) had at least one comorbidity that 103 (60.9%) of them did not survive (P=0.002). Invasive mechanical ventilation and its duration were significantly different between survived and nonsurvived groups (P ≤ 0.001 and P=0.002, respectively). Mean APACHE II and mean SOFA scores were significantly higher in the nonsurvived than in the survived group (14.4 ± 5.7 vs. 9.5 ± 5.1, P ≤ 0.001, 7.3 ± 3.1 vs. 3.1 ± 1.1, P ≤ 0.001, respectively). The area under the curve was 89.5% for SOFA and 73% for the APACHE II score. Respiratory diseases and malignancy were risk factors for the mortality rate (P=0.004 and P=0.007, respectively) against diabetes and hypertension. Conclusion: The daily SOFA was a better mortality predictor than the APACHE II in critically ill COVID-19 patients. But they could not predict death with high accuracy. We need new scoring with consideration of the prognostic factors and daily evaluation of changes in clinical conditions.

Automated detection of pneumonia cases using deep transfer learning with paediatric chest X-ray images.

OBJECTIVE: Pneumonia is a lung infection and causes the inflammation of the small air sacs (Alveoli) in one or both lungs. Proper and faster diagnosis of pneumonia at an early stage is imperative for optimal patient care. Currently, chest X-ray is considered as the best imaging modality for diagnosing pneumonia. However, the interpretation of chest X-ray images is challenging. To this end, we aimed to use an automated convolutional neural network-based transfer-learning approach to detect pneumonia in paediatric chest radiographs. METHODS: Herein, an automated convolutional neural network-based transfer-learning approach using four different pre-trained models (i.e. VGG19, DenseNet121, Xception, and ResNet50) was applied to detect pneumonia in children (1-5 years) chest X-ray images. The performance of different proposed models for testing data set was evaluated using five performances metrics, including accuracy, sensitivity/recall, Precision, area under curve, and F1 score. RESULTS: All proposed models provide accuracy greater than 83.0% for binary classification. The pre-trained DenseNet121 model provides the highest classification performance of automated pneumonia classification with 86.8% accuracy, followed by Xception model with an accuracy of 86.0%. The sensitivity of the proposed models was greater than 91.0%. The Xception and DenseNet121 models achieve the highest classification performance with F1-score greater than 89.0%. The plotted area under curve of receiver operating characteristics of VGG19, Xception, ResNet50, and DenseNet121 models are 0.78, 0.81, 0.81, and 0.86, respectively. CONCLUSION: Our data showed that the proposed models achieve a high accuracy for binary classification. Transfer learning was used to accelerate training of the proposed models and resolve the problem associated with insufficient data. We hope that these proposed models can help radiologists for a quick diagnosis of pneumonia at radiology departments. Moreover, our proposed models may be useful to detect other chest-related diseases such as novel Coronavirus 2019. ADVANCES IN KNOWLEDGE: Herein, we used transfer learning as a machine learning approach to accelerate training of the proposed models and resolve the problem associated with insufficient data. Our proposed models achieved accuracy greater than 83.0% for binary classification.

Interpretation of Hematological, Biochemical, and Immunological Findings of COVID-19 Disease: Biomarkers Associated with Severity and Mortality.

The severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) spread rapidly all over the world in late 2019 and caused critical illness and death in some infected patients. This study aimed at examining several laboratory factors, especially inflammatory and immunological mediators, to identify severity and mortality associated biomarkers. Ninety-three hospitalized patients with confirmed coronavirus disease 2019 (COVID-19) were classified based on disease severity. The levels of biochemical, hematological, immunological, and inflammatory mediators were assessed, and their association with severity and mortality were evaluated. Hospitalized patients were mostly men (77.4%) with an average (standard deviation) age of 59.14 (14.81) years. The mortality rate was significantly higher in critical patients (85.7%). Increased serum levels of blood sugar, urea, creatinine, uric acid, phosphorus, total bilirubin, serum glutamic-oxaloacetic transaminase, serum glutamic-oxaloacetic transaminase, lactic dehydrogenase, C-reactive protein, ferritin, and procalcitonin were significantly prevalent (p=0.002, p<0.001, p<0.001, p=0.014, p=0.047, p=0.003, p<0.001, p<0.001, p<0.001, p<0.001, P<0.001, and p<0.001, respectively) in COVID-19 patients. Decreased red blood cell, hemoglobin, and hematocrit were significantly prevalent among COVID-19 patients than healthy control subjects (p<0.001 for all). Troponin-I, interleukin-6, neutrophil/lymphocyte ratio (NLR), procalcitonin, and D-dimer showed a significant association with the mortality of patients with specificity and sensitivity more than 60%. Age, sex, underlying diseases, blood oxygen pressure, complete blood count along with C-reactive protein, lactic dehydrogenase, procalcitonin, D-dimer, and interleukin-6 evaluation help to predict the severity and required management for COVID-19 patients. Further investigations are highly recommended in a larger cohort study for validation of the present findings.

Cerebral venous sinus thrombosis associated with COVID-19: a case series and literature review.

BACKGROUND: Since the emergence of COVID-19 pandemic, several cases of cerebral venous sinus thrombosis (CVST) have been reported in SARS-CoV-2 infected individuals. METHODS: Consecutive patients with documented SARS-CoV-2 infection, as well as clinical and radiological characteristics of CVST, were reported from three teaching hospitals in the South West, North West, and the center of Iran between June and July 2020. We also searched the abstract archives until the end of August 2020 and gathered 28 reported cases. The diagnostic criteria for SARS-CoV-2 infection were determined according to SARS-CoV-2 detection in oropharyngeal or nasopharyngeal samples in clinically suspected patients. Demographics, prominent COVID-19 symptoms, confirmatory tests for SARS-CoV-2 infection diagnosis, the interval between the diagnosis of SARS-CoV-2 infection and CVST, clinical and radiological features of CVST, therapeutic strategies, CVST outcomes, rate of hemorrhagic transformation, and mortality rate were investigated. RESULTS: Six patients (31-62 years-old) with confirmed CVST and SARS-CoV-2 infection were admitted to our centers. Four patients had no respiratory symptoms of SARS-CoV-2 infection. Five patients developed the clinical manifestations of CVST and SARS-CoV-2 infection simultaneously. Three patients had known predisposing factors for CVST. Despite receiving CVST and SARS-CoV-2 infection treatments, four patients died. SARS-COV-2 associated CVST patients were older (49.26 vs. 37.77 years-old), had lower female/male ratio (1.42 vs. 2.19), and higher mortality rate (35.29% vs. 6.07%) than CVST not associated with COVID-19. CONCLUSIONS: The role of SARS-CoV-2 as a "cause" versus an "additive contributor" remains to be elucidated. Practitioners should be aware of the possibility of CVST in SARS-CoV-2 infection.

Experimental Models of SARS-CoV-2 Infection: Possible Platforms to Study COVID-19 Pathogenesis and Potential Treatments.

In December 2019, a novel coronavirus crossed species barriers to infect humans and was effectively transmitted from person to person, leading to a worldwide pandemic. Development of effective clinical interventions, including vaccines and antiviral drugs that could prevent or limit theburden or transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a global health priority. It is thus of utmost importance to assess possible therapeutic strategies against SARS-CoV-2 using experimental models that recapitulate aspects of the human disease. Here, we review available models currently being developed and used to study SARS-CoV-2 infection and highlight their application to screen potential therapeutic approaches, including repurposed antiviral drugs and vaccines. Each identified model provides a valuable insight into SARS-CoV-2 cellular tropism, replication kinetics, and cell damage that could ultimately enhance understanding of SARS-CoV-2 pathogenesis and protective immunity.

Preventing the frequency of infectious diseases in vulnerable groups - by anticipating the role of actors in implementing the decision-making model in conditions of uncertainty pandemic experience Covid-19.

BACKGROUND: The purpose of this study was to prevent the prevalence of infectious diseases in vulnerable groups by anticipating the role of actors in implementing decision-making models in conditions of uncertainty in medical universities. METHODS: This research is an applied research by combining qualitative and quantitative methods based on the foundation data theory (Grand Theory). To determine the dimensions of the model, the statistical population included crisis management managers and faculty members of Mazandaran University of Medical Sciences. The data collection was done through targeted sampling and interviews, semi-structured interviews, analysis and coding methods. The statistical population to present the model includes senior and middle managers of Mazandaran University of Medical Sciences. The simple random sampling method based on the sample size was determined by Cochran's method, and the collected data from the researcher's questionnaire were analyzed through nonparametric statistical experiments, Kolmogorov test Smirnov, SPSS SMARTPLS, Excel and the method of modeling structural equations with the least squares approach has been partial. RESULTS: The path coefficient of each dimension in explaining the decision model in uncertainty conditions based on T statistic and p value and SRMR value was 0.137, which was a good value and the main actors in implementing the model were policymakers, managers and staff. CONCLUSION: The implementation of this model will lead to a change in the decisions made by health system authorities in conditions of uncertainty, and will increase the ability of Head of medical universities and the resilience of the health system.

Cytokine release syndrome: inhibition of pro-inflammatory cytokines as a solution for reducing COVID-19 mortality.

Coronavirus disease (COVID-19) reached pandemic proportions at the beginning of 2020 and continues to be a worldwide concern. End organ damage and acute respiratory distress syndrome are the leading causes of death in severely or critically ill patients. The elevated cytokine levels in severe patients in comparison with mildly affected patients suggest that cytokine release syndrome (CRS) occurs in the severe form of the disease. In this paper, the significant role of pro-inflammatory cytokines, including IL-1, IL-6, and TNF-alpha, and their mechanism of action in the CRS cascade is explained. Potential therapeutic approaches involving anti-IL-6 and anti-TNF-alpha antibodies to fight COVID-19 and reduce mortality rate in severe cases are also discussed.

A Patient with COVID-19 Pneumonia Presenting with Plural Effusion: A Case Report.

BACKGROUND: In February 2020, coronavirus disease (COVID-19) emerged in Tehran, Iran. CASE PRESENTATION: Herein, we reported clinical features, laboratory tests, unusual radiological characteristics and therapeutic course of a patient with initial mild clinical symptoms at presentation with progression to pneumonia and pleural effusion in the emergency unit of a referral hospital.

Transmission Modes of COVID-19: A Systematic Review.

BACKGROUND: The Coronavirus disease 2019 (COVID-19) is a highly contagious viral infection that was initiated in Wuhan, China, and has spread around the world. The high prevalence and rapid transmission between individuals of COVID-19 have become an international challenge that requires careful consideration. We aimed to review the current evidence of COVID-19 transmission modes. METHODS: This study was a systematic review performed to identify current evidence of COVID-19 transmission modes. We searched selected keywords in six key databases to discover sources relevant to the main objective of the study. To identify studies meeting the inclusion criteria, the authors screened the titles and abstracts of the retrieved documents. The appropriate articles were then selected and their results were discussed to make the final inclusion. RESULTS: We identified five potential transmission modes of COVID-19, including airborne, droplet, contact with contaminated surfaces, oral and fecal secretions. Furthermore, some studies have pointed out other modes of virus transmission, such as person to person, and direct contact with animals. CONCLUSION: Droplet and contact with contaminated surfaces are the most frequent transmission modes of COVID-19. However, fecal excretion, environmental contamination, and fluid pollution may also contribute to viral transmission. The possibility of fecal transmission in COVID-19 has implications, especially in areas that are poorly hygienic. Environmental pollution can be caused by patients with SARS-CoV-2 through respiratory droplets and feces. Consequently, the human environment will become a potential medium of virus transmission.

Subcutaneous tocilizumab in adults with severe and critical COVID-19: A prospective open-label uncontrolled multicenter trial.

Potential therapeutic approaches in coronavirus disease 2019 (COVID-19) comprise antiviral and immunomodulatory agents; however, no immunomodulator drug has been approved. This multicenter, prospective, open-label, uncontrolled study aimed to assess the use of subcutaneous tocilizumab in adult patients with severe and critical COVID-19. Tocilizumab was added to the standard care of therapy at a dose of 324 mg (<100 kg bodyweight) or 486 mg (≥100 kg bodyweight). The study endpoints were all-cause mortality rate, changes in oxygen-support level, oxygen saturation, body temperature, respiratory rate, and laboratory variables during the study, and drug safety. Of 126 patients enrolled, 86 had severe and 40 had critical disease. Most patients were male (63.49%) and aged below 65 (78.57%). By day 14 of the study, 4.65% (4/86) of severe patients and 50.00% (20/40) of critical patients died. By the end, 6.98% (6/86) of severe patients and 60.00% (24/40) of critical patients died.Outcomes concerning three additional endpoints (oral temperature, oxygen saturation, and respiratory rate)were significantly improved as early as three days after tocilizumab administration in both groups of subjects, more considerably in severe patients. Significant improvement in the required level of oxygenation was reported in severe patients seven days after tocilizumab administration. No tocilizumab-related serious adverse event occurred in this study. Subcutaneous tocilizumab might improve some clinical parameters and reduce the risk of death in COVID-19 patients, particularly if used in the early stages of respiratory failure.