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Protein kinase C (PKC) comprises a family of lipid-sensitive enzymes that have been involved in a broad range of cellular functions. PKC-α is a member of classical PKC with ubiquitous expression and different cellular localization. This unique PKC isoform is activated by various signals which evoke lipid hydrolysis, after activation it interacts with various adapter proteins and is localized to specific cellular compartments where it is devised to work. The universal expression and activation by various stimuli make it a perfect player in uncountable cellular functions including differentiation, proliferation, apoptosis, cellular transformation, motility, adhesion and so on. However, these functions are not intrinsic properties of PKC-α, but depend on cell types and conditions. The activities of PKC-α are managed by the various pharmacological activators/inhibitors and antisense oligonucleotides. The aim of this review is to elaborate the structural feature, and provide an insight into the mechanism of PKC-α activation and regulation of its key biological functions in different cellular compartments to develop an effective pharmacological approach to regulate the PKC-α signal array.

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ABSTRACT:A study was conducted to explore the spatial variability of major soil nutrients in a soybean grown region of Malwa plateau. From the study area, one hundred sixty two surface soil samples were collected by a random sampling strategy using GPS. Then soil physico-chemical properties i.e., pH, EC, organic carbon, soil available nutrients (N, P, K, S and Zn) were measured in laboratory. After data normalization, classical and geo-statistical analyses were used to describe soil properties and spatial correlation of soil characteristics. Spatial variability of soil physico-chemical properties was quantified through semi-variogram analysis and the respective surface maps were prepared through ordinary Kriging. Exponential model fits well with experimental semi-variogram of pH, EC, OC, available N, P, K, S and Zn. pH, EC, OC, N, P, and K has displayed moderate spatial dependence whereas S and Zn showed weak spatial dependence. Cross validation of kriged map shows that spatial prediction of soil nutrients using semi-variogram parameters is better than assuming mean of observed value for any un-sampled location. Therefore it is a suitable alternative method for accurate estimation of chemical properties of soil in un-sampled positions as compared to direct measurement which has time and costs concerned.

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