The Impact of LEP rs7799039 Polymorphism and Obesity on the Severity of Coronavirus Disease-19.

Background and Aims: SARS-CoV-2 infection has been recorded in 230 countries to date. Obesity has a negative impact on one's quality of life and is one of the main causes of mortality globally. Obesity affects the immune system, making the host more susceptible to infectious infections. Also, obesity commonly provokes the severity of respiratory diseases so the correlation of LEP rs7799039 Polymorphism in corpulent patients with COVID-19 infection was clearly investigated in the current study. Methods: A total of 232 patients were recruited, 116 patients were obese with COVID-19 infection, and 116 patients were non obese COVID-19. Fasting blood glucose test (FBG), hemoglobin A1C (HbA1C), complete blood count (CBC), international normalized ratio (INR), urea, alanine transaminase (ALT), aspartate aminotransferase (AST), D dimer and C-reactive protein (CRP) were estimated. C.T. scan was performed for each patient, and C.T. severity score was calculated. Genotyping for the leptin rs7799039 SNPs was performed by TaqMan® (Applied Biosystems Step One TM Real-time PCR). Results: Regarding LEP polymorphism, all individuals of non-obese groups significantly had the homozygous allele GG (100%), whereas only 56% of obese groups had GG alleles (P = 0.001). The severity scores significantly (P = 0.001) varied regarding LEP polymorphism regarding Rs7799039, where the largest proportion of those with Grade IV had the homozygous allele AA (57.1%). Conclusion: There was a correlation between the leptin gene allelic discrimination and COVID-19 CT brutality in obese patients. The A allele was considered a risk factor for severity in COVID-19 patients while the G allele contributes to decreasing that risk.

HBD-2 variants and SARS-CoV-2: New insights into inter-individual susceptibility.

Background: A deep understanding of the causes of liability to SARS-CoV-2 is essential to develop new diagnostic tests and therapeutics against this serious virus in order to overcome this pandemic completely. In the light of the discovered role of antimicrobial peptides [such as human b-defensin-2 (hBD-2) and cathelicidin LL-37] in the defense against SARS-CoV-2, it became important to identify the damaging missense mutations in the genes of these molecules and study their role in the pathogenesis of COVID-19. Methods: We conducted a comprehensive analysis with multiple in silico approaches to identify the damaging missense SNPs for hBD-2 and LL-37; moreover, we applied docking methods and molecular dynamics analysis to study the impact of the filtered mutations. Results: The comprehensive analysis reveals the presence of three damaging SNPs in hBD-2; these SNPs were predicted to decrease the stability of hBD-2 with a damaging impact on hBD-2 structure as well. G51D and C53G mutations were located in highly conserved positions and were associated with differences in the secondary structures of hBD-2. Docking-coupled molecular dynamics simulation analysis revealed compromised binding affinity for hBD-2 SNPs towards the SARS-CoV-2 spike domain. Different protein-protein binding profiles for hBD-2 SNPs, in relation to their native form, were guided through residue-wise levels and differential adopted conformation/orientation. Conclusions: The presented model paves the way for identifying patients prone to COVID-19 in a way that would guide the personalization of both the diagnostic and management protocols for this serious disease.

Modelling the COVID-19 Mortality Rate with a New Versatile Modification of the Log-Logistic Distribution.

The goal of this paper is to develop an optimal statistical model to analyze COVID-19 data in order to model and analyze the COVID-19 mortality rates in Somalia. Combining the log-logistic distribution and the tangent function yields the flexible extension log-logistic tangent (LLT) distribution, a new two-parameter distribution. This new distribution has a number of excellent statistical and mathematical properties, including a simple failure rate function, reliability function, and cumulative distribution function. Maximum likelihood estimation (MLE) is used to estimate the unknown parameters of the proposed distribution. A numerical and visual result of the Monte Carlo simulation is obtained to evaluate the use of the MLE method. In addition, the LLT model is compared to the well-known two-parameter, three-parameter, and four-parameter competitors. Gompertz, log-logistic, kappa, exponentiated log-logistic, Marshall-Olkin log-logistic, Kumaraswamy log-logistic, and beta log-logistic are among the competing models. Different goodness-of-fit measures are used to determine whether the LLT distribution is more useful than the competing models in COVID-19 data of mortality rate analysis.

In Silico Designing of a Multitope Vaccine against Rhizopus microsporus with Potential Activity against Other Mucormycosis Causing Fungi.

During the current era of the COVID-19 pandemic, the dissemination of Mucorales has been reported globally, with elevated rates of infection in India, and because of the high rate of mortality and morbidity, designing an effective vaccine against mucormycosis is a major health priority, especially for immunocompromised patients. In the current study, we studied shared Mucorales proteins, which have been reported as virulence factors, and after analysis of several virulent proteins for their antigenicity and subcellular localization, we selected spore coat (CotH) and serine protease (SP) proteins as the targets of epitope mapping. The current study proposes a vaccine constructed based on top-ranking cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and B cell lymphocyte (BCL) epitopes from filtered proteins. In addition to the selected epitopes, ß-defensins adjuvant and PADRE peptide were included in the constructed vaccine to improve the stimulated immune response. Computational tools were used to estimate the physicochemical and immunological features of the proposed vaccine and validate its binding with TLR-2, where the output data of these assessments potentiate the probability of the constructed vaccine to stimulate a specific immune response against mucormycosis. Here, we demonstrate the approach of potential vaccine construction and assessment through computational tools, and to the best of our knowledge, this is the first study of a proposed vaccine against mucormycosis based on the immunoinformatics approach.

Statistical optimization of bile salt deployed nanovesicles as a potential platform for oral delivery of piperine: accentuated antiviral and anti-inflammatory activity in MERS-CoV challenged mice.

The objective of this paper is to confine piperine, a poor oral bioavailable herbal drug into bile salt based nano vesicles for improving its aqueous solubility, hence, its therapeutic activity. Piperine-loaded bilosomes were fabricated adopting thin film hydration technique according to 32.21 full factorial design to investigate the impact of different formulation variables on the characters of bilosomes: entrapment efficiency (EE%), particle size, and % of drug released post 8 h (Q8hr). The selected optimum formula was F2 (enclosing 1% bile salt, brij72 as a surfactant, and ratio of surfactant:cholesterol was 9:1) with desirability value 0.801, exhibiting high EE% (97.2 ± 0.8%) nanosized spherical vesicles (220.2 ± 20.5 nm) and Q8hr (88.2%±5.6). The superiority of the optimized formula (F2) over the drug suspension was revealed via ex vivo permeation study, also pharmacokinetic study denoted to the boosted oral bioavailability of piperine-loaded bilosome compared to piperine suspension. Moreover, antiviral activity and safety margin of F2 was significantly higher than that of the drug suspension. The ability of piperine to interact with the key amino acids in the receptor binding domain 4L3N as indicated by its docking configuration, rationalized its observed activity. Furthermore, F2 significantly reduce oxidant markers, inflammatory cytokines in MERS-CoV-infected mice. Hence, bilosomes can be considered as a carrier of choice for piperine with potential antiviral and anti-inflammatory activities.