Synthetic Hydrogel as an Artificial Vitreous Body. A One-Year Animal Study of Its Effects on the Retina

A hydrogel with a high water content was assessed in vitro and in vivo as a possible vitreous substitute. From a large series of polymers produced by the aqueous polymerization of methyl acrylamidoglycolate methyl ether (MAGME), a gel synthesized in 80% water was selected for an animal study. The gel was injected intravitreally into rabbit eyes and followed clinically by ophthalmoscopy, tonometry, and fundus photography. The gel was clinically well tolerated, but after 6 months ophthalmoscopy revealed progressive pallor of the optic nerve head. The eyes were enucleated one year after injection of polymer. Histopathological examination by light microscopy of retinal and vitreal sections revealed significant retinal disorganization, degeneration of the optic nerve and retinal neural elements, retinal detachment, and inflammatory changes. Analysis of immunohistochemically labeled retinal sections revealed loss of ganglion cells and extensive pathological reaction of the Muller cells and astrocytes. All these findings were consistent with a toxic effect of the polymer itself or some residual contaminants. The cytotoxicity of the hydrogel was assessed in vitro using cultured mouse (Balb/c-3T3) fibroblasts. The bioassay showed both cytostatic and cytocidal effects of the polymer. Our results indicate that hydrogels produced from MAGME monomer cannot function as vitreous substitutes because of severe toxic reaction elicited to the posterior segment of the eye

Mapping invasive plant <i>Prosopis juliflora</i> in arid land using high resolution remote sensing data and biophysical parameters

1135-1144In this study, high resolution remote sensing data is used to extract Prosopis juliflora (P.juliflora), which is a major invader in the study area. Support Vector Machine (SVM) classification is applied to map this invader with Normalized Difference Vegetation Index (NDVI) as an additional parameter. Optimal kernel selection has been done for SVM classification, and a polynomial kernel has been selected for the analysis. SVM polynomial kernel generated the overall accuracy of 70% and Kappa of 0.63. Classification results were compared with the results of conventional maximum likelihood classification (MLC). It was observed that the classification accuracy is improved from 68% to 74% when NDVI was used in MLC. But, when the SVM approach was used with NDVI, the accuracy dramatically increased to 93%. This is because the NDVI is a ratio based index, which introduces information about biophysical properties, thereby helping in better separation of P.juliflora

Bronchoalveolar lavage in pediatrics

Bronchoalveolar lavage is a relatively new technique that is used to study the local cellular, biochemical and immunological changes occuring in the lower respiratory tract. The procedure involves instilling a fixed volume of saline into a lung segment after the flexible fibreoptic bronchoscope is wedged into a distal bronchus. The saline is aspirated back and can be used for microbiological and other studies. Recently, attempts have been made to standardise the procedure in children and obtain data on BAL cellular profile in healthy children. The main indications for BAL are diagnostic, particularly to diagnose unusual infections in immunocompromised children. It is also helpful in the diagnosis of a number on non infectious conditions, based on the cellular profile and other constituents. With the availability of new techniques like flow cytometry, analysis of lymphoctye and other cell subsets has become possible leading to a better understanding of the immunopathgenesis of various respiratory diseases

Hypothyroidism with scholastic excellence

A 9-year-old boy had presented with not gaining adequate height with complaints of constipation from 5 years, lethargy and loss of appetite from past 6 months. He was diagnosed to have hypothyroidism with high thyroid antibody levels. Though he was stunted his neurocognition and scholastic performance was excellent as evidenced by his school rank cards. His physical symptoms had improved after thyroxin supplemen

Allometric model for estimating above ground biomass and carbon storage in Karankadu mangrove swamp, Palk bay, Southeast coast of India

1682-1692Above ground biomass (AGB) is a tool for estimating carbon storage capacity of plants and hence the estimation methods are crucial. Karankadu mangrove swamp in the Palk Bay, Southeast coast of India is characterized by the presence of young mangrove species Avicennia marina (A. marina). AGB of A. marina in Karankadu mangrove swamp with 10 hectares (ha) plots was estimated using the non-destructive allometric method. Analyses of allometric regression comprised of leaves, branches and stems of A. Marina depend upon the independent variables of diameter at breast height (DBH), height (H) and basal area (BA). Average AGB of A. marina in the Karankadu mangrove swamp was found to be 10.71 t h-1. A. Marina species amidst in hyper saline conditions effectively captures the atmospheric CO2 and storing them as biomass in the above ground parts than that of terrestrial ecosystem. Above ground carbon (AGC) content of A. marina trees calculated using AGB values was ranged between 1.15 and 7.92 t ha-1

Effect of wavelet based image fusion techniques with principal component analysis (PCA) and singular value decomposition (SVD) in supervised classification

338-348With more promotion in satellite image processing techniques and the accessibility of various resolution images, fusion is necessary to combine panchromatic and multispectral images for further applications. Recent researches show that wavelet based image fusion algorithms provide high spectral quality in the fused images, but less spatial information in fused images due to critical down sampling .To increase spatial and spectral resolution, we have implemented wavelet based image fusion algorithms along with singular value decomposition(SVD) and principal component analysis (PCA) and its influences on supervised classification. The quality of the fused images is evaluated by quantitative and qualitative measurements. Qualitative evaluation is confirmed by edge detection methods. Quantitative results proved in terms of with reference and no reference image quality metrics. Supervised classification is used to check whether the spectral distortion caused by wavelet based fusion methods and the classification accuracy is measured by Kappa index (K). Results shows wavelet based image fusion combined with Eigen value methods such as SVD and PCA improves the classification accuracy as compared to actual multispectral images. Best classification results are achieved by framelet transform with SVD based fusion

Denoising and Dimensionality Reduction of Hyperspectral Images Using Framelet Transform with Different Shrinkage Functions

978-986Present study is focussed on providing alternatives beyond discrete wavelet transform that not only reduce the dimensionality of the data and also simultaneously denoised the data cube by combining framelet transform (FRT) with different shrinkage functions and dimensionality reduction methods. Universal shrink (US), Visu shrink (VS), Minimax shrink (MS), Sure shrink (SS), Bayes shrink (BS) and Normal shrink (NS) will be applied to threshold the detail coefficients of framelet transform. Discrete wavelet transform (DWT), wavelet packet transform (WPT) and curvelet transform (CUT) also used for evaluating the performance of the proposed method. Peak signal to noise ratio (PSNR) is calculated for each method and the results are compared. A higher value of the PSNR indicates the good quality of the denoised data cube. Then dimensionality reduction methods such as principal component analysis (PCA), Singular value decomposition (SVD) and Linear discriminant analysis (LDA) are applied on the denoised data cube. The efficiency of the simultaneous denoising and dimensionality reduction of hyperspectral data cube is calculated in terms of entropy with and without denoising. Edge detection also performed, directional properties of framelet transform can able to capture edges and contours which are the main features in images. The framelet transform, Bayes shrink with soft thresholding produce sound results in terms of denoising and edge detection over DWT, WPT and curvelet transform based methods