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Rheumatoid arthritis (RA) is a chronic autoimmune disorder that affects and damages the joints of human beings. It causes swelling, discomfort, and inflammation in and around the joints and affects other body organs; that affects 1% of the world's population, with 6 to 60 people out of 100,000 developing the disease each year. However, a recent study describes that there are several factors involved in the regulation of RA disease, including genetic factors like MicroRNAs (miRNAs) variants, which are tiny molecules that bind to complementary target RNA molecules to regulate the protein-coding region of the genome, these non-coding short RNA molecules attach to target mRNA molecules at 3′-untranslated regions (UTR). The current study aimed to investigate the impact of variants rs11614913, rs6505162, and rs3746444 located in MIR196A2, MIR423, and MIR499, respectively, in RA patients. These SNPs were genotyped in RA patients and age- and gender-matched healthy controls using allele-specific T-ARMS-PCR. Allelic and genotypic frequencies of each variant were noted. Furthermore, from the selected variants, the association of rs11614913 and rs6505162 variants with the risk of RA was measured using a statistically odds ratio and confidence of interval (95%). In co-dominant models, the genotypic frequency of MIR423 variant rs6505162 was in cases A/A 75(35.21%), C/C 108 (50.7%) and A/C 30 (14.08%) while in controls A/A 34(16%), C/C 94(44.1%) and A/C 85(40%). These values indicate the best relationship between C/C and A/C, which were higher in cases and found significant association according to P-value and χ2. [χ2=14.03; P value=0.0009]. This concludes that SNPs (rs6505162) in MIR423 are the susceptibility factors for RA in the Pakistani Population. While SNPs rs11614913 in MIR196A2 have shown no association with RA.

BackgroundChronic Kidney Disease (CKD) is a complex condition leading to loss of kidney function. The objective of this study was to develop and validate a Knowledge, Attitude, and Practice questionnaire on CKD (CKD-KAP) among practicing physicians in Pakistan since no validated tool was available for the said purpose.MethodsThe study consisted of four phases with phase-I focusing on literature review, phase II was the actual questionnaire development phase, face and content validity was determined in phase III, and finally pilot testing was performed in phase IV to determine validity and reliability. The development phase encompassed a thorough review of literature, focus-group discussion, expert review, and evaluation. The validation phase consisted of content validity, face validity, construct validity, convergent validity, and reliability. The pilot testing was performed by studying the KAP of 100 practicing physicians in tertiary care hospitals in Pakistan. The knowledge section of the validation phase utilized Item Response Theory (IRT) analysis. The attitude and practices sections utilized Exploratory Factor Analysis (EFA) theory. The reliability analysis utilized Cronbach’s alpha and correlations.ResultsThe CKD-KAP questionnaire had three main sections: knowledge, attitude, and practice. During the validation, IRT analysis was performed on knowledge, which focused on the measure of the coefficient of discrimination and difficulty of the items; 40 out of 41 knowledge items have both discrimination and difficulty coefficients within an acceptable range. The EFA model was also fitted in the attitude and practices section, and scree plot and Eigenvalues suggested three and four dimensions within the attitude and practices section. The factor loading of all items was found to be acceptable except for one item in attitude which was deleted. The convergent validity demonstrated a significant association between all three sections except knowledge and practices. The reliability (internal consistency) analysis demonstrated Cronbach’s alpha values above 0.7 and significant inter-item correlation. The final model of CKD-KAP had 40 knowledge, 13 attitude, and 10 practice items with a combination of both positive as well as negative questions and statements.ConclusionsThe CKD-KAP was found to be psychometrically valid and reliable, hence can be used to determine the knowledge, attitude, and practices of physicians toward chronic kidney disease.

Coronaviruses belong to the group of RNA family of viruses that trigger diseases in birds, humans, and mammals, which can cause respiratory tract infections. The COVID-19 pandemic has badly affected every part of the world. Our study aimed to explore the genome of SARS-CoV-2, followed by in silico analysis of its proteins. Different nucleotide and protein variants of SARS-CoV-2 were retrieved from NCBI. Contigs and consensus sequences were developed to identify these variants using SnapGene. Data of the variants that significantly differed from each other was run through Predict Protein software to understand the changes produced in the protein structure. The SOPMA web server was used to predict the secondary structure of the proteins. Tertiary structure details of the selected proteins were analyzed using the web server SWISS-MODEL. Sequencing results showed numerous single nucleotide polymorphisms in the surface glycoprotein, nucleocapsid, ORF1a, and ORF1ab polyprotein while the envelope, membrane, ORF3a, ORF6, ORF7a, ORF8, and ORF10 genes had no or few SNPs. Contigs were used to identify variations in the Alpha and Delta variants of SARS-CoV-2 with the reference strain (Wuhan). Some of the secondary structures of the SARS-CoV-2 proteins were predicted by using Sopma software and were further compared with reference strains of SARS-CoV-2 (Wuhan) proteins. The tertiary structure details of only spike proteins were analyzed through the SWISS-MODEL and Ramachandran plots. Through the Swiss-model, a comparison of the tertiary structure model of the SARS-CoV-2 spike protein of the Alpha and Delta variants was made with the reference strain (Wuhan). Alpha and Delta variants of the SARS-CoV-2 isolates submitted in GISAID from Pakistan with changes in structural and nonstructural proteins were compared with the reference strain, and 3D structure mapping of the spike glycoprotein and mutations in the amino acids were seen. The surprisingly increased rate of SARS-CoV-2 transmission has forced numerous countries to impose a total lockdown due to an unusual occurrence. In this research, we employed in silico computational tools to analyze the SARS-CoV-2 genomes worldwide to detect vital variations in structural proteins and dynamic changes in all SARS-CoV-2 proteins, mainly spike proteins, produced due to many mutations. Our analysis revealed substantial differences in the functionality, immunological, physicochemical, and structural variations in the SARS-CoV-2 isolates. However, the real impact of these SNPs can only be determined further by experiments. Our results can aid in vivo and in vitro experiments in the future.

BACKGROUND Coronavirus disease 2019 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) leads to respiratory failure and obstructive alveolar damage, which may be fatal in immunocompromised individuals. COVID-19 pandemic has severe global implications badly, and the situation in the world is depreciating with the emergence of novel variants. OBJECTIVE The aim of our study is to explore the genome of SARS-CoV2 followed by in silico reverse vaccinology analysis. This will help to identify the most putative vaccine candidate against the virus in a robust manner and enables cost-effective development of vaccines compared with traditional strategies METHODS The genomic sequencing data is retrieved from NCBI (Reference Sequence Number NC_045512.2). The sequences are explored through comparative genomics approaches by GENOMICS to find out the core genome. The comprehensive set of proteins obtained was employed in computational vaccinology approaches for the prediction of the best possible B and T cell epitopes through ABCpred and IEDB Analysis Resource, respectively. The multi-epitopes were further tested against human toll-like receptors and cloned in an E. coli plasmid vector. RESULTS The designed Multiepitope Subunit Vaccine was non-allergenic, antigenic (0.6543), & non-toxic, with significant connections with the human leukocyte antigen (HLA) binding alleles, and collective global population coverage of 84.38%. It has 276 amino acids, consisting of an adjuvant with the aid of an EAAAK linker, AAY linkers used to join the 4 CTL epitopes, GPGPG linkers used to join the 3 HTL epitopes and KK linkers used to join the 7 B-cell epitopes. MESV docking with human pathogenic toll-like receptors-3 (TLR3) exhibited a stable & high binding affinity. An in-silico codon optimization approach was used in the codon system of E. coli (strain K12) to obtain the GC-Content of Escherichia coli (strain K12): 50.7340272413779 and CAI-Value of the improved sequence: 0.9542834278823386. The multi-epitope vaccine's optimized gene sequence was cloned in-silico in E. coli plasmid vector pET-30a (+), and BamHI, and HindIII restriction sites were added to the N and C-terminals of the sequence, respectively. CONCLUSIONS There is a pressing need to combat COVID-19 and we need quick and reliable approaches against Covid-19. By using In-silico approaches, we acquire an effective vaccine that could trigger adequate immune responses at the cellular and humoral levels. The suggested sequences can be further validated through in vivo and in vitro experimentation.