Phylogenetic analysis and protective effects of thymol and its chromatographic fractions from a novel wild mushroom in combating oxidative stress

Mushrooms are good sources of phytochemicals that have antioxidant and anti-proliferative effects.This study identifi ed a unique isoform of 18S rRNA gene(864 bp)from a novel wild mushroom(SMK-1)(GenBank accession number:SUB3267363).Thin layer chromatographic(TLC)profiling of the methanolic extract of the dried mushroom fruiting bodies of SMK-1 revealed the presence of phenolic and fl avonoid fractions with retention factor(Rf)values of 0.955 and 0.927 respectively.The GC/MS chromatograms of the SMK-1 methanolic extract identifi ed the main bioactive compound was phenol,5-methyl-2-(1-methylethyl)(74.00%)(thymol).The radical scavenging activity for the fl avonoid fraction was greater than the phenolic fractions(Rf–phenolics fractions>Rf–fl avonoid fractions)with the antioxidant activity more than that of standard ascorbic acid.Also,the phenolic and flavonoid fractions of SMK-1 expressed cytotoxic effects in HeLa cells with IC50 values ranging from 5μg/mL to 80μg/mL in a dose-dependent manner.This present research highlights the presence of high thymol concentration in a novel wild mushroom that has antioxidant and anti-poliferative potential with therapeutic benefi ts.The application of thymol natural products from novel mushroom SMK-1 as nutrition supplements could inhibit oxidative stress triggered by numerous pathologies that may pave the way to develop a new therapeutic natural drug.

Junction Point Elimination based Tamil Handwritten Character Recognition:An Experimental Analysis

Optical Character Recognition is the mechanical or electronic conversion of images of typed,handwritten or printed text into machine-encoded text for online reading and study.In this OCR technique,Tamil handwritten character recognition is one of the most needed and challengeable subjects of research.An encounter between selection and extraction of proper features eliminates the issues faced by the Tamil handwritten recognition.The character and the writers complexities are the major difficulties and challenges faced by this recognition system.Eventually,the character complexity can be overcome by any pre-extraction or selection process,wherein,structured or statistical pre-extraction algorithm can be designed,discovering the essential features,in the case of writer difficulties.The challenges of Tamil handwritten characters are structure over looping;unnecessary character portion;structure discontinuations and so on.The character portions in this research are chosen by implementing a new algorithm called the Junction Point Elimination(JPE)after conscientious analysis done on the existing algorithms like Zoning,Zoning and Junction Point(ZJP)and the Junction Point (JP) based feature pre-extraction process.The novelty behind this work is introducing an algorithm in order to truncate the problem in the existing feature selection and preextraction algorithms.Suitable feature extraction and classification algorithm are chosen and applied on the features extracted by JPE to test whether the same can be reached in successful manner.The final analysis and experiments shows that the JPE is better than the others.