Acute kidney injury (AKI), characterised by fluid imbalance and overload, is prevalent in severe disease phenotypes of coronavirus disease 2019 . The elderly immunocompromised patients with pre-existing comorbidities being more risk-prone to severe COVID-19, the importance of early diagnosis and intervention in AKI is imperative. Histopathological examination of COVID-19 patients with AKI reveals viral invasion of the renal parenchyma and evidence of AKI. The definitive treatment for AKI includes renal replacement therapy and renal transplant. Immunosuppressant regimens and its interactions with COVID-19 have to be further explored to devise effective treatment strategies in COVID-19 transplant patients. Other supportive strategies for AKI patients include hemodynamic monitoring and maintenance of fluid balance. Antiviral drugs should be meticulously monitored in the management of these high-risk patients. We have focussed on the development of renal injury provoked by the SARS-CoV-2, the varying clinical characteristics, and employment of different management strategies, including renal replacement therapy, alongside the emerging cytokine lowering approaches.

Background Type 2 diabetes mellitus (T2DM) is a metabolic disorder with severe comorbidities. A multiomics approach can facilitate the identification of novel therapeutic targets and biomarkers with proper validation of potential microRNA (miRNA) interactions. Objective The aim of this study was to identify significant differentially expressed common target genes in various tissues and their regulating miRNAs from publicly available Gene Expression Omnibus (GEO) data sets of patients with T2DM using in silico analysis. Methods Using differentially expressed genes (DEGs) identified from 5 publicly available T2DM data sets, we performed functional enrichment, coexpression, and network analyses to identify pathways, protein-protein interactions, and miRNA-mRNA interactions involved in T2DM. Results We extracted 2852, 8631, 5501, 3662, and 3753 DEGs from the expression profiles of GEO data sets GSE38642, GSE25724, GSE20966, GSE26887, and GSE23343, respectively. DEG analysis showed that 16 common genes were enriched in insulin secretion, endocrine resistance, and other T2DM-related pathways. Four DEGs, MAML3, EEF1D, NRG1, and CDK5RAP2, were important in the cluster network regulated by commonly targeted miRNAs (hsa-let-7b-5p, hsa-mir-155-5p, hsa-mir-124-3p, hsa-mir-1-3p), which are involved in the advanced glycation end products (AGE)-receptor for advanced glycation end products (RAGE) signaling pathway, culminating in diabetic complications and endocrine resistance. Conclusions This study identified tissue-specific DEGs in T2DM, especially pertaining to the heart, liver, and pancreas. We identified a total of 16 common DEGs and the top four common targeting miRNAs (hsa-let-7b-5p, hsa-miR-124-3p, hsa-miR-1-3p, and has-miR-155-5p). The miRNAs identified are involved in regulating various pathways, including the phosphatidylinositol-3-kinase-protein kinase B, endocrine resistance, and AGE-RAGE signaling pathways.

The current pandemic of COVID-19, with its climbing number of cases and deaths, has us searching for tools for rapid, reliable, and affordable methods of detection on one hand, and novel, improved therapeutic strategies on the other. The currently employed RT-PCR method, despite its all-encompassing utility, has its shortcomings. Newer diagnostic tools, based on the Clustered Regularly Interspaced Short Palindromic Repeats/Cas(CRISPR-Cas) system, with its better diagnostic accuracy measures, have come up to fill that void. These assay platforms are expected to slowly take up the place of COVID-19 diagnostics. Further, the current therapeutic options focus mainly on counteracting the viral proteins and components and their entry into host cells. The CRISPR-based system, especially through the RNA-guided Cas13 approach, can identify the genomic characteristics of SARS-CoV-2 and provide a novel inhibition strategy for coronaviruses. In this mini-review, we have discussed the available and upcoming CRISPR-based diagnostic assays and the potential of the CRISPR/Cas system as a therapeutic or prevention strategy in COVID-19. CRISPR-Cas system shows promise in both diagnostics as well as therapeutics and may as well change the face of molecular diagnosis and precision medicine.

Introduction:Breast cancer (BC) is the leading cause of death among women across the globe. Abnormal gene expression plays a crucial role in tumour progression, carcinogenesis and metastasis of BC. The alteration of gene expression may be through aberrant gene methylation. In the present study, differentially expressed genes which may be regulated by DNA methylation and their pathways associated with BC have been identi ed. Methods:Expression microarray datasets GSE10780, GSE10797, GSE21422, GSE42568, GSE61304, GSE61724 and one DNA methylation pro le dataset GSE20713 were downloaded from Gene Expression Omnibus database (GEO). Differentially expressed-aberrantly methylated genes were identi ed using online Venn diagram tool. Based on fold change expression of differentially expressed-aberrantly methylated genes were chosen through heat map. Protein-protein interaction (PPI) network of the hub genes was constructed by Search Tool for the Retrieval of Interacting Genes (STRING). Gene expression and DNA methylation level of the hub genes were validated through UALCAN. Overall survival analysis of the hub genes was analysed through Kaplan Meier-plotter database for BC. Results:A total of 72 upregulated-hypomethylated genes and 92 downregulated-hypermethylated genes were