Virtually all plants are inhabited by diverse bacteria known as Endophytes. Endophytic bacteria are referred to as those which can be detected at a particular moment within the tissues of apparently healthy plant hosts. L-Asparaginase is a well-recognized as amino acid degrading enzyme. L-Asparaginase (EC 3.5.1.1.) has grown considerably since this enzyme was found to have antitumor activity. Most bacterial endophytes belong to mainly four phyla, but they encompass many genera and species. Their functions cannot be assigned clearly to taxonomy and seem to depend on the host and environmental parameters. Endophytic bacteria have been isolated from a large diversity of plant was reported as many as 46 different bacterial species from 27 plant species. Freshly collected leaves of Aegle marmelos were selected for the isolation of endophytic bacteria. The isolated bacterial strain tested by gram staining and identification done in a lab care pathology laboratory. The present study enlightens the medicinal plants like A. marmelos as potential sources of endophytic bacteria with the L-asparaginase activity. The optimization studies indicated the maximum enzyme was produced at 30°C for 72 hours in 120 rpm rotatory shaker incubator and pH: 8 presence of glucose as most suitable carbon source.
Enicostemma littorale Blume, Syn.Enicostemma axillare (Lam.)Raynal. is a well-known plant used as drug in Ayurved, Unani-Tibbi, Siddha, Allopathy, Homeopathy, Naturopathyand Home Remedies. The present communication deals with the pharmacognostic evaluation on the different parts of Enicostemma littorale Blume (Enicostemma littorale) Family-Gentianaceae. Macroscopic and microscopic examinations of the different organ, observations and differential microchemical test have been carried out for the authentication of the samples. Physiochemical values such as the moisture contents, percentage of total ash, acid insoluble ash, acid soluble ash, water soluble ash, extractive values as petroleum ether-soluble extractives, ethanol-soluble extractives, methanol-soluble extractives and water-soluble extractives were calculated as well as color reactions of powder and extract with different chemicals were performed to observe fluorescence analysis. The extracts were subjected to qualitative screening test for various constituents. This revealed the presence protein, glycosides, alkaloids, tannins and phenolic compound, steroid reducing sugars and saponin glycosides. These observations will help in the Pharmacognostical identification and standardization of the drug in the crude form and also to differentiate the drug from its adulteration.
Metallography is the study of the microstructure of metallic alloys. The integrity of metals in vital in the case of any manufacturing industry as the durability is dependent on quality of metal. Microscopic analysis is essential part of modern manufacturing process. Micro-structural Inclusions measurement is routinely required process for maintaining quality. The most important physical properties of particulate samples are particle size and grain size. The diameter of individual grains of sediments is called as grain size. Gran size determination is actually depends upon the manual process which leading to time-consuming and errors are occur at the time of determination. The main objective to propose this system is to automatically analyze the material according to their size/shape and grain sizes. Fuzzy logic model is a classifier used to detect edges and corners of grains available in the input image. The system categories the metal using its grain size. The obtained results are compared with ASTM standards and other reported results in survey. The proposed system is useful in metal industry which are depends upon size and shape of the grains.
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