Nitric oxide (NO) was initially described as a physiological mediator of endothelial cell relaxation, an important role in hypotension. NO is an intercellular messenger that has been recognized as one of the most versatile players in the immune system. Cells of the innate immune system--macrophages, neutrophils and natural killer cells--use pattern recognition receptors to recognize the molecular patterns associated with pathogens. Activated macrophages then inhibit pathogen replication by releasing a variety of effector molecules, including NO. In addition to macrophages, a large number of other immune-system cells produce and respond to NO. Thus, NO is important as a toxic defense molecule against infectious organisms. It also regulates the functional activity, growth and death of many immune and inflammatory cell types including macrophages, T lymphocytes, antigen-presenting cells, mast cells, neutrophils and natural killer cells. However, the role of NO in nonspecific and specific immunity in vivo and in immunologically mediated diseases and inflammation is poorly understood. This Minireview will discuss the role of NO in immune response and inflammation, and its mechanisms of action in these processes.

The leishmaniases are a group of diseases caused by protozoan parasites of the genus Leishmania. Various Leishmania species can cause human infection, producing a spectrum of clinical manifestations. It is estimated that 350 million people are at risk, with a global yearly incidence of 1-1.5 million for cutaneous and 500,000 for visceral leishmaniasis (VL). VL is a major cause of morbidity and mortality in East Africa and the Indian subcontinent. Coinfection with HIV enhances the risk of the disease. The only control measure currently available in India is case detection and treatment with antimonial drugs, which are expensive, not always available and cannot be self-administered. Newer drugs like oral miltefosine have not become widely available. Vector and reservoir control is difficult due to the elusive nature of the vector and the diversity of the animal reservoir. A detailed knowledge of immune response to the parasite would help in designing prophylactic and therapeutic strategies against this infection.

Effective diagnosis and surveillance of Bladder Cancer (BCa) is currently challenged by detection methods that are of poor sensitivity, particularly for low-grade tumors, resulting in unnecessary invasive procedures and economic burden. We performed HR-MAS NMR-based global metabolomic profiling and applied unsupervised principal component analysis (PCA) and hierarchical clustering performed on NMR dataset of bladder derived tissues and identified metabolic signatures that differentiate BCa from benign disease. A partial least-square discriminant analysis (PLS-DA) model (leave-one-out cross-validation) was used as diagnostic model to distinguish benign and BCa tissues. Receiver operating characteristic curve generated either from PC1 loadings of PCA or from predicted Y-values resulted in an area under curve of 0.97. Relative quantification of more than fifteen tissue metabolites derived from HR-MAS NMR showed significant differences (P < 0.001) between benign and BCa samples. Noticeably, striking metabolic signatures were observed even for early stage BCa tissues (Ta-T1) demonstrating the sensitivity in detecting BCa. With the goal of cross-validating metabolic signatures derived from HR-MAS NMR, we utilized the same tissue samples to analyze eight metabolites through gas chromatography-mass spectrometry (GC-MS)-targeted analysis, which undoubtedly complements HR-MAS NMR derived metabolomic information. Cross-validation through GC-MS clearly demonstrates the utility of straightforward, non-destructive and rapid HR-MAS NMR technique for clinical diagnosis of BCa with even greater sensitivity. In addition to its utility as a diagnostic tool, these studies will lead to a better understanding of aberrant metabolic pathways in cancer as well as the design and implementation of personalized cancer therapy through metabolic modulation.