18 resultados para Tissue kinetics

em Cochin University of Science


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Plants were regenerated from callus induced from leaf disc explants of a tomato F, hybrid heterozygous for three marker loci (a), without anthocyanin (aw), and hairless (hl). Regenerants were studied for somaclonal variation at the phenotypic level by scoring for variation in the marker loci, and at the DNA level by probing geomic DNA blots with a chlorophyll a/b binding protein (Cab-3C) cDNA sequence. While no variation was observed at the phenotypic level in over 950 somaclones studied, DNA polymorphism for the Cab locus could be detected in two out of 17 somaclones tested. Tissue culture induced variation at the phenotypic level for specific loci is very low (less than 0.001 for a, awor hl) but DNA sequence changes are induced at much greater frequency (- 0.1 for a multicopy gene family such as Cab).

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The study deals with the generation of variability for salt tolerance in rice using tissue culture techniques. Rice is the staple food of more than half of the world’s population. The management of drought, salinity and acidity in soils are all energy intensive agricultural practices. The Genetic variability is the basis of crop improvement. Somaclonal and androclonal variation can be effectively used for this purpose. In the present study, eight isozymes were studied and esterase and isocitric dehydrogenase was found to have varietal specific, developmental stage specific and stress specific banding pattern in rice. Under salt stress thickness of bands and enzyme activity showed changes. Pokkali, a moderately salt tolerant variety, had a specific band 7, which was present only in this variety and showed slight changes under stress. This band was faint in tillering and flowering stage .Based on the results obtained in the present study it is suggested that esterase could possibly be used as an isozyme marker for salt tolerance in rice. Varietal differences and stage specific variations could be detected using esterase and isocitric dehydrogenase . Moreover somaclonal and androclonal variation could be effectively detected using isozyme markers.

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The metal complex, [Ni(en)2(H2O)2](NO3)2 (en = ethylenediamine), was decomposed in a static furnace at 200 C by autogenous decomposition to obtain phase pure metallic nickel nanocrystallites. The nickel metal thus obtained was studied by XRD, IR spectra, SEM and CHN analysis. The nickel crystallites are in the nanometer range as indicated by XRD studies. The IR spectral studies and CHN analyses show that the surface is covered with a nitrogen containing species. Thermogravimetric mass gain shows that the product purity is high (93%). The formed nickel is stable and resistant to oxidation up to 350 C probably due to the coverage of nitrogen containing species. Activation energy for the oxidation of the prepared nickel nanocrystallites was determined by non-isothermal methods and was found to depend on the conversion ratio. The oxidation kinetics of the nickel crystallites obeyed a Johnson–Mehl–Avrami mechanism probably due to the special morphology and crystallite strain present on the metal.

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The growth kinetics of an aerial bacterial colony on solid agar media was studied using laser induced fluorescence technique. Fluorescence quenching of Rhodamin B by the bacterial colony was utilized for the study. The lag phase, log phase, and stationary phase of growth curve of bacterial colony was identified by measuring peak fluorescence intensity of dye doped bacterial colony.

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Activation energy for crystallization (Ec) is a pertinent parameter that decides the application potential of many metallic glasses and is proportional to the crystallization temperature. Higher crystallization temperatures are desirable for soft magnetic applications, while lower values for data storage purposes. In this investigation, from the heating rate dependence of peak crystallization temperature Tp, the Ec values have been evaluated by three different methods for metglas 2826 MB (Fe40Ni38B18Mo4) accurately. The Ec values are correlated with the morphological changes, and the structural evolution associated with annealing temperatures is discussed.

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National Centre for Aquatic Animal Health, Cochin University of Science and Technology

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P rosea syn. Indica belong to the family of plumbaginaceae, is an important medicinal plant, cultivated widely in India. The roots of these plant are generally used for medicinal purposes mainly as diuretic, germicidal, vessicant, and abortifacient. It is also used for anaemia, diarrhea, leprosy and common wart. The bark of the root contains orange yellow pigment named plumbagin, a crystalline substance, belongs to the class of naphthoquinone. Its chemical structure is 5-hydroxy 2-methyl 1,4naphthoquinone. Apart from P rosea, P zeylanica, P europea, Drosera and Drosophyllum also contains plumbagin. The most exploited source of plumbagin is, of course, P. rosea roots. The roots contain O.9mg/ g D.Wt. of plumbagin in the roots. These plants grow very slowly and the roots suitable for plumbagin extraction can be obtained only after several years of growth. The productivity of the plant is also rather poor. The focus of the present study was to develop alternative strategies to obtain plumbagin. The tissue culture of P rosea for micropropagation has been studied

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The present study on naoplankton is based on the isolation and development of unialgai culturas from the inshore waters at Cochin. characterization of their growth assimilation products. ecophysioiogy and evaluation of nutritional quality. The work was carried out during the period 1980-1983. The nanoplankters were isolated and grown in the labratory as batch cultures to study the increase in cell population, the photosynthetic pigment: ana physioiogical activity. The chemical composition of these organisms and their rate of excretion were also determined. The environmental factors physical and chemical that influence the growth of these Cultures were defined by conducting independentexperiments. These cultures of the isolated nanoplankters have raised indoor and fed to the larvae of edible oyster to test their suitability as live-food.

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Urea-formaldehyde resins find numerous applications in adhesive, textile finishing and moulded plastic industries. Kinetic investigations of the reactions of urea and its related compounds with formaldehyde in aqueous acid, alkaline and neutral media have been carried out. A thin—layer chromatographic method was developed for the separation and estimation of the products of these reactions. Using this technique the various initial steps in the reactions were analysed and the rate constants have been determined.

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A growth medium with Leibovitz-15 L-15.as the base, supplemented with foetal bovine serum 10% vrv., fish muscle extract 10% vrv., prawn muscle extract 10% vrv., lectin concanavalin A. 0.02 mg mly1., lipopolysaccharide 0.02 mg mly1., glucose D 0.2 mg mly1., ovary extract 0.5% vrv.and prawn haemolymph 0.5%. has been formulated with 354"10 mOsm for the development and maintenance of a cell culture system from the ovarian tissue of African catfish, Clarias gariepinus. For its subculturing, a cell dissociationrextracting solution, composed of equal portions of trypsin phosphate versene glucose TPVG. containing 0.0125% wrv.trypsin and 25% vrv.non-enzymatic cell dissociation solution 1 and 2, has also been developed with which the cell culture can be passaged 15 times after which they cease to multiply and consequently perish. The cell cultures can be maintained for 12–15 days without fluid change between the passages. This is the first report of a cell culture system from the ovarian tissues of African catfish

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A spectral angle based feature extraction method, Spectral Clustering Independent Component Analysis (SC-ICA), is proposed in this work to improve the brain tissue classification from Magnetic Resonance Images (MRI). SC-ICA provides equal priority to global and local features; thereby it tries to resolve the inefficiency of conventional approaches in abnormal tissue extraction. First, input multispectral MRI is divided into different clusters by a spectral distance based clustering. Then, Independent Component Analysis (ICA) is applied on the clustered data, in conjunction with Support Vector Machines (SVM) for brain tissue analysis. Normal and abnormal datasets, consisting of real and synthetic T1-weighted, T2-weighted and proton density/fluid-attenuated inversion recovery images, were used to evaluate the performance of the new method. Comparative analysis with ICA based SVM and other conventional classifiers established the stability and efficiency of SC-ICA based classification, especially in reproduction of small abnormalities. Clinical abnormal case analysis demonstrated it through the highest Tanimoto Index/accuracy values, 0.75/98.8%, observed against ICA based SVM results, 0.17/96.1%, for reproduced lesions. Experimental results recommend the proposed method as a promising approach in clinical and pathological studies of brain diseases

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In this paper, we propose a multispectral analysis system using wavelet based Principal Component Analysis (PCA), to improve the brain tissue classification from MRI images. Global transforms like PCA often neglects significant small abnormality details, while dealing with a massive amount of multispectral data. In order to resolve this issue, input dataset is expanded by detail coefficients from multisignal wavelet analysis. Then, PCA is applied on the new dataset to perform feature analysis. Finally, an unsupervised classification with Fuzzy C-Means clustering algorithm is used to measure the improvement in reproducibility and accuracy of the results. A detailed comparative analysis of classified tissues with those from conventional PCA is also carried out. Proposed method yielded good improvement in classification of small abnormalities with high sensitivity/accuracy values, 98.9/98.3, for clinical analysis. Experimental results from synthetic and clinical data recommend the new method as a promising approach in brain tissue analysis.

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Multispectral analysis is a promising approach in tissue classification and abnormality detection from Magnetic Resonance (MR) images. But instability in accuracy and reproducibility of the classification results from conventional techniques keeps it far from clinical applications. Recent studies proposed Independent Component Analysis (ICA) as an effective method for source signals separation from multispectral MR data. However, it often fails to extract the local features like small abnormalities, especially from dependent real data. A multisignal wavelet analysis prior to ICA is proposed in this work to resolve these issues. Best de-correlated detail coefficients are combined with input images to give better classification results. Performance improvement of the proposed method over conventional ICA is effectively demonstrated by segmentation and classification using k-means clustering. Experimental results from synthetic and real data strongly confirm the positive effect of the new method with an improved Tanimoto index/Sensitivity values, 0.884/93.605, for reproduced small white matter lesions