Understanding Mutations in Human SARS-CoV-2 Spike Glycoprotein: A Systematic Review & Meta-Analysis.

Genetic variant(s) of concern (VoC) of SARS-CoV-2 have been emerging worldwide due to mutations in the gene encoding spike glycoprotein. We performed comprehensive analyses of spike protein mutations in the significant variant clade of SARS-CoV-2, using the data available on the Nextstrain server. We selected various mutations, namely, A222V, N439K, N501Y, L452R, Y453F, E484K, K417N, T478K, L981F, L212I, N856K, T547K, G496S, and Y369C for this study. These mutations were chosen based on their global entropic score, emergence, spread, transmission, and their location in the spike receptor binding domain (RBD). The relative abundance of these mutations was mapped with global mutation D614G as a reference. Our analyses suggest the rapid emergence of newer global mutations alongside D614G, as reported during the recent waves of COVID-19 in various parts of the world. These mutations could be instrumentally imperative for the transmission, infectivity, virulence, and host immune system's evasion of SARS-CoV-2. The probable impact of these mutations on vaccine effectiveness, antigenic diversity, antibody interactions, protein stability, RBD flexibility, and accessibility to human cell receptor ACE2 was studied in silico. Overall, the present study can help researchers to design the next generation of vaccines and biotherapeutics to combat COVID-19 infection.

Molecular Insights of MAP4K4 Signaling in Inflammatory and Malignant Diseases.

Mitogen-activated protein kinase (MAPK) cascades are crucial in extracellular signal transduction to cellular responses. The classical three-tiered MAPK cascades include signaling through MAP kinase kinase kinase (MAP3K) that activates a MAP kinase kinase (MAP2K), which in turn induces MAPK activation and downstream cellular responses. The upstream activators of MAP3K are often small guanosine-5'-triphosphate (GTP)-binding proteins, but in some pathways, MAP3K can be activated by another kinase, which is known as a MAP kinase kinase kinase kinase (MAP4K). MAP4K4 is one of the widely studied MAP4K members, known to play a significant role in inflammatory, cardiovascular, and malignant diseases. The MAP4K4 signal transduction plays an essential role in cell proliferation, transformation, invasiveness, adhesiveness, inflammation, stress responses, and cell migration. Overexpression of MAP4K4 is frequently reported in many cancers, including glioblastoma, colon, prostate, and pancreatic cancers. Besides its mainstay pro-survival role in various malignancies, MAP4K4 has been implicated in cancer-associated cachexia. In the present review, we discuss the functional role of MAP4K4 in malignant/non-malignant diseases and cancer-associated cachexia and its possible use in targeted therapy.

COVID-19: Social distancing monitoring using faster-RCNN and YOLOv3 algorithms.

As of March 31, 2021, the Coronavirus COVID-19 was affecting 219 countries and territories worldwide, with approximately 129,574,017 confirmed cases and 2,830,220 death cases. Social isolation is the most reliable way to deal with this pandemic situation. Motivated by this notion, this paper proposes a deep learning-based technique for automating the task of monitoring social distancing using surveillance cameras. To separate humans from the background, the proposed system employs object detection models based on F-RCNN (Faster Region-based Convolutional Neural Networks) and YOLO (You Only Look Once) algorithms. In the COVID-19 environment, these models track the percentage of people who violate social distancing norms on a daily basis. The authors compared the performance of both models in experimental work using the MS COCO dataset. Many tests were carried out, and we discovered that YOLOv3 demonstrated efficient performance with balanced FPS (frames per second).

Cucumis melo var. momordica as a Potent Antidiabetic, Antioxidant and Possible Anticovid Alternative: Investigation through Experimental and Computational Methods.

Diabetes mellitus is a typical life threatening of disease, which generate due to the dysfunction of ß cells of pancreas. In 2014, WHO stated that 422 million people were infected with DM. The current pattern of management of diabetes included synthetic or plant based oral hypoglycemic drugs and insulin but drug resentence is become a very big issues in antidiabetic therapy. Thus, it's very earnest to discover now medication for this disease. Now the days, it is well acknowledged that diabetic patients are more prone towards covid and related complications. Thus, medical practitioners reformed the methodology of prescribing medication for covid infected antidiabetic therapy and encouraging the medication contains dual pharmacological properties. It is also well know that polyphenols specifically hold a significant role in oxidative stress and reduced the severity of many inflammatory diseases. Cucumis melo has rich history as ethano-pharmacological use in Indian subcontinent. The fruit and seed are well-known for the treatment of various diseases due to the presence of phenolics. Therefore, in this study, the combined mixture of flower and seeds were used for the extraction of polyphenolic rich extract and tested for antidiabetic activity through the antioxidant and in vivo experiments. The antioxidant potential measurement exhibited that the selected plant extract has the significant competence to down-regulate oxidative stress (DPPH scavenging IC50 at 60.7±1.05 µg/mL, ABTS IC50 at 62.15±0.50 µg/mL). Furthermore, the major polyphenolic phyto-compounds derived from the Cucumis melo were used for in silico anticovid activity, docking, and complementarity studies. The anticovid activity prognosis reflected that selected phyto-compounds amentoflavone and vanillic acid have optimal possibility to interact with 3C-like protease and through this moderate anticovid activity can be exhibit. The docking experiments established that the selected compounds have propensity to interact with protein tyrosine phosphatase 1B, 11ß-Hydroxysteroid dehydrogenase, superoxide dismutase, glutathione peroxidase, and catalase ß-glucuronidase receptor. In vivo experiments showed that 500 mg/kg, Cucumis melo extract ominously amplified body weight, plasma insulin, high-density lipoprotein levels, and biochemical markers. Furthermore, extract significantly downregulate the blood glucose, total cholesterol, triglycerides, low-density lipoprotein, and very low-density lipoprotein.

Mapping of epidemiological determinants of confirmed COVID-19 cases among health-care workers of municipal corporation of Delhi: A roadmap to risk reduction.

BACKGROUND: Coronavirus disease (COVID-19) is a respiratory illness caused by a novel coronavirus which can spread from person to person. Health-care workers of any medical college and hospital are at more risk to the coronavirus disease (COVID-19) than the general population. The aim of this study was to assess the epidemiological profile of confirmed COVID-19 cases among health-care workers of Municipal Corporation of Delhi. METHODOLOGY: A cross-sectional study was planned among 422 health-care workers of Municipal Corporation of Delhi. The questionnaire consisted of questions about sociodemographic data, personal history, and clinical profile such as signs and symptoms and their duration. Data were analyzed by SPSS software version 21.0, and, Chi-square test and logistic regression were used. RESULTS: Mean age of study subjects was 41.1 ± 9.8 years, and males (57.6%) were more as compared to (42.4%) females. Out of total participants, about one-third (36.4%) of study participants were asymptomatic. Study participants with higher education status adjusted odds ratio (AOR) 2.43 (1.25-4.70), living in overcrowding AOR 3.74 (1.86-7.54), and having some comorbidity AOR 2.78 (1.57-4.92) were at higher risk of being symptomatic. CONCLUSION: This study concludes that about one-third of study participants were asymptomatic. Factors such as higher education status, living in overcrowding, presence of some comorbidity, and smokeless tobacco consumption were significantly associated with symptomatic COVID-19 cases. Hence, there is a need to identify these risk factors at an early stage in order to design prevention strategies for better control of such pandemics in future.

An Epidemiological Investigation to evaluate the link between hypovitaminosis D and COVID-19.

Background: The COVID-19 pandemic has become a global threat, with an inexplicable course of action and suboptimal response to the multitudes of therapies being tried. Vitamin D's pleiotropic effects (immunomodulatory, anti-inflammatory, and antiviral) have lately received considerable attention in the scientific community, and it has been shown to be helpful in the defense against viral respiratory infections. Aim: To find out the association between vitamin D and COVID-19. Methods: Overall, 360 (156 COVID-19 +ve and 204 COVID-19 -ve) subjects were investigated in this hospital-based case-control study. The study participants were taken from the COVID-19 wards and Flu clinic of a dedicated COVID hospital between August 1 and September 15, 2020. The demographics and clinical data including alcohol and smoking history along with serum vitamin D levels were recorded. Binary logistic regression analysis was performed to assess the association between age, gender, alcohol intake, smoking history, vitamin D status, and COVID-19. Results: There was no significant difference in the mean vitamin D levels between cases and controls. Bivariate analysis of predictors and COVID-19 revealed that predictors such as advanced age, BMI, alcohol intake, smoking habit, diabetes, hypertension, and vitamin D deficiency were significantly associated with COVID-19. Conclusions: This study showed that serum vitamin D status might be able to reduce the impact of COVID-19, although more studies are required to establish clear causality.

Computational Approach to Combat COVID-19 Infection: Emerging Tools for Accelerating Drug Research.

BACKGROUND: The process of drug discovery and development is expensive, complex, timeconsuming, and risky. There are different techniques involved in the process of drug development, including random screening, computational approaches, molecular manipulation, and serendipitous research. Among these methods, the computational approach is considered an efficient strategy to accelerate and economize the drug discovery process. OBJECTIVE: This approach is mainly applied in various phases of the drug discovery process, including target identification, target validation, lead identification, and lead optimization. Due to the increase in the availability of information regarding various biological targets of different disease states, computational approaches such as molecular docking, de novo design, molecular similarity calculation, virtual screening, pharmacophore-based modeling, and pharmacophore mapping have been applied extensively. METHODS: Various drug molecules can be designed by applying computational tools to explore the drug candidates for the treatment of Coronavirus infection. The World Health Organization announced the coronavirus disease as COVID-19 and declared it a global pandemic on 11 February 2020. Therefore, it is thought of interest to the scientific community to apply computational methods to design and optimize the pharmacological properties of various clinically available and FDA-approved drugs such as remdesivir, ribavirin, favipiravir, oseltamivir, ritonavir, arbidol, chloroquine, hydroxychloroquine, carfilzomib, baraticinib, prulifloxacin, etc., for effective treatment of COVID-19 infection. RESULTS: Further, various survey reports suggest that extensive studies are carried out by various research communities to find out the safety and efficacy profile of these drug candidates. CONCLUSION: This review is focused on the study of various aspects of these drugs related to their target sites on the virus, binding interactions, physicochemical properties, etc.

Nanometer-Thick Superhydrophobic Coating Renders Cloth Mask Potentially Effective against Aerosol-Driven Infections.

The advent of COVID-19 pandemic has made it necessary to wear masks across populations. While the N95 mask offers great performance against airborne infections, its multilayered sealed design makes it difficult to breathe for a longer duration of use. The option of using highly breathable cloth or silk masks especially for a large populace is fraught with the danger of infection. As a normal cloth or silk mask absorbs airborne liquid, it can be a source of plausible infection. We demonstrate the chemical modification of one such mask, Eri silk, to make it hydrophobic (contact angle of water is 143.7°), which reduces the liquid absorption capacity without reducing the breathability of the mask significantly. The breathability reduces only 22% for hydrophobic Eri silk compared to the pristine Eri silk, whereas N95 shows a 59% reduction of breathability. The modified hydrophobic silk can repel the incoming aqueous liquid droplets without wetting the surface. The results indicate that a multilayered modified silk mask to make it hydrophobic can be an affordable and breathable alternative to the N95 mask.

Deep Transfer Learning-Based COVID-19 Prediction Using Chest X-Rays

The novel coronavirus disease (COVID-19) is spreading very rapidly across the globe because of its highly contagious nature and is declared as a pandemic by the World Health Organization (WHO). Scientists are endeavouring to ascertain the drugs for its efficacious treatment. Because, until now, no full-proof drug is available to cure this deadly disease. Therefore, identifying COVID-19 positive people and quarantining them can be an effective solution to control its spread. Many machine learning and deep learning techniques are being used quite effectively to classify positive and negative cases. In this work, a deep transfer learning-based model is proposed to classify the COVID-19 cases using chest X-rays or CT scan images of infected persons. The proposed model is based on the ensembling of DenseNet121 and SqueezeNet1.0, which is named as DeQueezeNet. The model can extract the importance of various influential features from the X-ray images, which are effectively used to classify the COVID-19 cases. The performance study of the proposed model depicts its effectiveness in terms of accuracy and precision. A comparative study has also been done with the recently published works, and it is observed that the performance of the proposed model is significantly better.

Current trends in diagnosis and treatment strategies of COVID-19 infection.

Coronaviruses are terrifically precise and adapted towards specialized respiratory epithelial cells, observed in organ culture and human volunteers both. This virus is found to possess an unpredictable anti-viral T-cell response which in turn results in T-cell activation and finally apoptosis, leading to cytokine storm and collapse of the whole immune system. The present review provides comprehensive information regarding SARS-CoV-2 infection, mutant strains, and the impact of SARS-COV-2 on vital organs, the pathophysiology of the disease, diagnostic tests available, and possible treatments. It also includes all the vaccines developed so far throughout the world to control this pandemic. Until now, 18 vaccines have been approved by the WHO and further 22 vaccines are in the third trial. This study also provides up-to-date information regarding the drugs repurposed in clinical trials and the recent status of allopathic drugs along with its result. Although vaccines are available, specific treatment is not available for the disease. Furthermore, the effect of vaccines on new variants is a new area of research at this time. Therefore, a preventive attitude is the best approach to fight against this virus.

Vitamin D deficiency and COVID-19: A case-control study at a tertiary care hospital in India.

BACKGROUND: As the pandemic COVID-19 affected developing and developed countries, there is no proven treatment options available yet. The anti-inflammatory, antiviral and immune modulator effect of Vitamin D could be beneficial to COVID-19. AIM: To find out the possible association between Vitamin D and COVID-19. METHODS: The present case-control study was conducted at tertiary care hospital, AIIMS, Patna, Bihar, India. Total 156 cases and 204 controls were enrolled in the study after obtaining informed consent. Categorization of the patients were done based on clinical severity and level of Vitamin D. The association between these categories with different variables were analyzed using regression analysis and other statistical tests. RESULTS: The status of Vitamin D (optimal, mild to moderate deficiency and severe deficiency) differed significantly among cases and controls. Diabetes and hypertension were most prevalent comorbidities among cases. On regression analysis, the difference in Vitamin D level was significant (aOR, 3.295; 95%CI, 1.25-8.685). The association between Vitamin D status and clinical severity group was statistically significant among cases. Among all variables, age, diabetes, hypertension and clinical severity were associated with worst outcome. CONCLUSION: Vitamin D status appears to be strongly associated with COVID-19 clinical severity. After COVID-19 confirmation, Vitamin D level should be measured in all patients and curative plus preventive therapy should be initiated.

Phytochemicals as Potential Therapeutics for SARS-CoV-2-Induced Cardiovascular Complications: Thrombosis and Platelet Perspective.

After gaining entry through ACE2 aided by TMPRSS2, the SARS-CoV-2 causes serious complications of the cardiovascular system leading to myocarditis and other myocardial injuries apart from causing lung, kidney and brain dysfunctions. Here in this review, we are going to divulge the cellular and immunological mechanisms behind the cardiovascular, thrombotic and platelet impairments that are caused in COVID-19. In addition, we also propose the significance of various anti-platelet and anti-thrombotic phytochemicals in the treatment of COVID-19. The virus induces many immune-modulatory cytokines and chemokines which help in the intravascular coagulation and create a pro-thrombotic environment along with pulmonary embolism and thrombocytopenia. Different types of innate and adaptive immune cells and their granular contents regulate the pathophysiology of SARS-CoV-2 induced endothelial and platelet dysfunctions which correlate the involvement of platelets with myocardial injury and intravascular thrombi directly or indirectly. Hence, by exploiting the natural bioactive compounds from medicinal plants and inhibiting the platelet mediated thrombus formation can be beneficial for the treatment of SARS-CoV-2 infection.

Face mask detection using YOLOv3 and faster R-CNN models: COVID-19 environment.

There are many solutions to prevent the spread of the COVID-19 virus and one of the most effective solutions is wearing a face mask. Almost everyone is wearing face masks at all times in public places during the coronavirus pandemic. This encourages us to explore face mask detection technology to monitor people wearing masks in public places. Most recent and advanced face mask detection approaches are designed using deep learning. In this article, two state-of-the-art object detection models, namely, YOLOv3 and faster R-CNN are used to achieve this task. The authors have trained both the models on a dataset that consists of images of people of two categories that are with and without face masks. This work proposes a technique that will draw bounding boxes (red or green) around the faces of people, based on whether a person is wearing a mask or not, and keeps the record of the ratio of people wearing face masks on the daily basis. The authors have also compared the performance of both the models i.e., their precision rate and inference time.

Potential SARS-CoV-2 interactions with proteins involved in trophoblast functions - An in-silico study.

BACKGROUND: Though a large number of pregnant females have been affected by COVID-19, there is a dearth of information on the effects of SARS-CoV-2 infection on trophoblast function. We explored in silico, the potential interactions between SARS-CoV-2 proteins and proteins involved in the key functions of placenta. METHODS: Human proteins interacting with SARS-CoV-2 proteins were identified by Gordon et al. (2020). Genes that are upregulated in trophoblast sub-types and stages were obtained by gene-expression data from NCBI-GEO and by text-mining. Genes altered in pathological states like pre-eclampsia and gestational diabetes mellitus were also identified. Genes crucial in placental functions thus identified were compared to the SARS-CoV-2 interactome for overlaps. Proteins recurring across multiple study scenarios were analyzed using text mining and network analysis for their biological functions. RESULTS: The entry receptors for SARS-CoV-2 - ACE2 and TMPRSS2 are expressed in placenta. Other proteins that interact with SARS-CoV-2 like LOX, Fibulins-2 and 5, NUP98, GDF15, RBX1, CUL3, HMOX1, PLAT, MFGE8, and MRPs are vital in placental functions like trophoblast invasion and migration, syncytium formation, differentiation, and implantation. TLE3, expressed across first trimester placental tissues and cell lines, is involved in formation of placental vasculature, and is important in SARS-CoV (2003) budding and exit from the cells by COPI vesicles. CONCLUSION: SARS-CoV-2 can potentially interact with proteins having crucial roles in the placental function. Whether these potential interactions identified in silico have effects on trophoblast functions in biological settings needs to be addressed by further in vitro and clinical studies.