This work reports an ecofriendly approach for the synthesis of Ruthenium nanoparticles (Ru NPs) using aqueous leaf extract of Gloriosa superba. G. superba contains cholidonic, superbine, colchicine, gloriosol, phytosterils and stigmasterin, which are found to be responsible for the bio-reduction of Ru NPs. The synthesized Ru NPs were characterized using UV-Vis spectroscopy, Fluorescence spectra, FTIR, XRD, SEM and EDX analyses. UV-Vis spectra of the aqueous medium containing Ru NPs showed a gradual decrease of the absorbance peak observed at 494 nm. Fluorescence spectra of Ru NPs emission (k em ) exhibited at 464 nm are attributed to the Ru=N p bonds transition. The biomolecules responsible for the reduction of Ru NPs were analyzed by FTIR. XRD results confirmed the presence of Ru NPs with hexagonal crystal structure. The calculated crystallite sizes using Scherrer formula are in the range from 25 to 90 nm. Scanning electron microscopy ascertained spherical nature of the Ru NPs. The EDX analysis showed the complete elemental composition of the synthesized Ru NPs. The synthesized Ru NPs exhibited good antibacterial performance against gram-positive and gram-negative bacterial strains, which was studied using standard disc diffusion method. The synthesis of Ru NPs by this method is rapid, facile and can be used for various applications.

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A Decision based scheme using a improved mesh based snake like sorting is proposed for the restoration of gray scale images that are heavily corrupted by salt and pepper noise. The proposed algorithm uses modified mean or median for image restoration. The processed pixel is examined for 0 or 255; if checked pixel is equal to 0 or 255, then it is considered as noisy pixel else not noisy. The noisy pixel is replaced by median of unsymmetrical trimmed output, if the current window has at least three noisy pixels or mean of first and last values of the un-symmetrical trimmed output. The uncorrupted pixel is left unchanged. The proposed algorithm shows excellent noise suppression capability with good edge preservation in heavy noisy conditions both qualitative and quantitatively. The proposed algorithm was applied on various grayscale images and found to have excellent PSNR and high IEF , low MSE and consumes less time even at very high noise densities with edge preservation.

Background: Rheumatoid Arthritis (RA) is a chronic inflammatory and autoimmune disease leading to bones and joints destruction. It is one of the major causes of lifetime disability and mortality among humans in the developing and developed countries. It was evident that epigenetic dysregulation is related to the pathogenesis of RA. MicroRNAs (miRNAs) are small non-coding RNAs that are epigenetic regulators for diverse biological processes and also provided novel molecular insights in the formation of arthritis. Objective: The influences of miRNAs in the alteration of gene regulation during the pathogenesis of arthritis were exposed in recent years. Method: The computational approach to identify miRNA through EST-based homology is more powerful, economical and time-efficient. In this study, we applied EST-based homology search to identify miRNAs responsible for the development of arthritis in human beings. Results: Our study on 36519 ESTs in human RA condition revealed the expression of four miRNAs, HSA-miR-198, HSA-miR-4647, has-miR-7167-5p and has-miR-7167-3p. The present study is the first report about has-miR-7167 that was homologous to Macaca mulatta. Conclusion: The predicted targets of these identified miRNAs revealed many biological functions in the pathogenesis of RA. Further elaborated studies on these miRNAs will help to understand their function in the development of RA and the use of miRNAs as therapeutic targets in the future.

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