Coronary artery disease (CAD) is one of the major cardiovascular diseases affecting the global human population. This disease has been proved to be the major cause of death in both the developed and developing countries. Lifestyle, environmental factors, and genetic factors pose as risk factors for the development of cardiovascular disease. The prevalence of risk factors among healthy individuals elucidates the probable occurrence of CAD in near future. Genome‐wide association studies have suggested the association of chromosome 9p21.3 in the premature onset of CAD. The risk factors of CAD include diabetes mellitus, hypertension, smoking, hyperlipidemia, obesity, homocystinuria, and psychosocial stress. The eradication and management of CAD has been established through extensive studies and trials. Antiplatelet agents, nitrates, β‐blockers, calcium antagonists, and ranolazine are some of the few therapeutic agents used for the relief of symptomatic angina associated with CAD.

Ovarian cancer (OC) is the sixth most common cancer in women globally. However, even with the advances in detection and therapeutics it still represents the most dangerous gynecologic malignancy in women of the industrialized countries. The discovery of micro-RNAs (miRNA), a small noncoding RNA molecule targeting multiple mRNAs and regulation of gene expression by triggering translation repression and/or RNA degradation, has revealed the existence of a new array for regulation of genes involved in cancer. This review summarizes the current knowledge regarding the role of miRNAs expression in OC. It also provides information about potential clinical relevance of circulating miRNAs for OC diagnosis, prognosis, and therapeutics. The identification of functional targets for miRNAs represents a major obstacle in our understanding of microRNA function in OC, but significant progress is being made. The better understanding of the role of microRNA expression in ovarian cancer may provide new array for the detection, diagnosis, and therapy of the OC.

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Lung cancer (LC) is the leading cause of cancer-related deaths all over the world, among both men and women, with an incidence of over 200,000 new cases per year coupled with a very high mortality rate. LC comprises of two major clinicopathological categories: small-cell (SCLC) and nonsmall-cell lung carcinoma (NSCLC). The microRNAs (miRNAs) are small noncoding RNAs, usually 18-25 nucleotides long, which repress protein translation through binding to complementary target mRNAs. The miRNAs regulate many biological processes including cell cycle regulation, cellular growth, proliferation, differentiation, apoptosis, metabolism, neuronal patterning, and aging. This review summarizes the role of miRNAs expression in LC. It also provides information about the miRNAs as biomarker and therapeutic target for lung cancer. Understanding the role of miRNAs in LC may provide insights into the diagnosis and treatment strategy for LC.

Codon usage bias (CUB) is the non-uniform usage of synonymous codons in which some codons are more preferred to others in the transcript. Analysis of codon usage bias has applications in understanding the basics of molecular biology, genetics, gene expression, and molecular evolution. To understand the patterns of codon usage in genes involved in the central nervous system (CNS), we used bioinformatic approaches to analyze the protein-coding sequences of genes involved in the CNS. The improved effective number of codons (ENC) suggested that the overall codon usage bias was low. The relative synonymous codon usage (RSCU) revealed that the most frequently occurring codons had a G or C at the third codon position. The codons namely TCC, AGC, CTG, CAG, CGC, ATC, ACC, GTG, GCC, GGC, and CGG (average RSCU > 1.6) were over-represented. Both mutation pressure and natural selection might affect the codon usage pattern as evident from correspondence and parity plot analyses. The overall GC content (59.93) was higher than AT content, i.e., genes were GC-rich. The correlation of GC12 with GC3 suggested that mutation pressure might affect the codon usage pattern.