Recession-induced societal changes- Challanges and Opportunities

The greatest damage inflicted by the recent recession has not necessarily been financial but emotional and psychological. There are a lot of direct and indirect societal challenges ,changes and oppurtunuties that were brought by recession everywhere including in India. In this paper an attempt is made to analyse such societal changes challenges and oppurtunities.

Study of chemical properties and evaluation of collagen in mantle, epidermal connective tissue and tentacle of Indian Squid, Loligo duvauceli Orbigny

The chemical composition and evaluation of Indian squid (Loligo duvauceli) mantle, epidermal connective tissue and tentacle is investigated in this current study. It is observed that squid mantle contains 22.2% total protein; 63.5% of the total protein is myofibrillar protein. The unique property of squid myofibrillar protein is its water solubility. Squid mantle contains 12.0% total collagen. Epidermal connective tissue has highest amounts of total collagen (17.8%). SDS-PAGE of total collagen identified high molecular weight α-, β- and γ- sub-chains. Amino acid profile analysis indicates that mantle and tentacle contain essential amino acids. Arginine forms a major portion of mantle collagen (272.5 g/100 g N). Isoleucine, glutamic acid and lysine are other amino acids that are found in significantly high amounts in the mantle. Sulphur containing cystine is deficit in mantle collagen. Papain digest of mantle and epidermal connective tissue is rich in uronic acid, while papain digest, collagenase digest and urea digest of epidermal connective tissue has significant amounts of sialic acid (25.2, 33.2 and 99.8 μmol /100 g, respectively). PAS staining of papain digest, collagenase digest and urea digest also identify the association of hexoses with low molecular weight collagen fragments. Histochemical sectioning also emphasized the localized distribution of collagen in epidermal and dermal region and very sparse fibres traverse the myotome bundles

Improving food and nutritional security of small and marginal coconut growers through diversification of crops and enterprises

This paper presents the impact of integrating interventions like nutrition gardening, livestock rearing, product diversification and allied income generation activities in small and marginal coconut homesteads along with nutrition education in improving the food and nutritional security as well as the income of the family members. The activities were carried out through registered Community Based Organizations (CBOs) in three locations in Kerala, India during 2005-2008. Data was collected before and after the project periods through interviews using a pre-tested questionnaire containing statements indicating the adequacy, quality and diversity of food materials. Fifty respondents each were randomly selected from the three communities, thereby resulting in a total sample size of 150. The data was analysed using SPSS by adopting statistical tools like frequency, average, percentage analysis, t – test and regression. Participatory planning and implementation of diverse interventions notably intercropping and off-farm activities along with nutrition education brought out significant improvements in the food and nutritional security, in terms of frequency and quantity of consumption as well as diet diversity. At the end of the project, 96%of the members became completely food secure and 72% nutritionally secure. The overall consumption of fruits, vegetables and milk by both children and adults and egg by children recorded increase over the project period. Consumption of fish was more than the Recommended Dietary Intake (RDI) level during pre and post project periods. Project interventions like nutrition gardening could bring in surplus consumption of vegetables (35%) and fruits (10%) than RDI. In spite of the increased consumption of green leafy vegetables and milk and milk products over the project period, the levels of consumption were still below the RDI levels. CBO-wise analysis of the consumption patterns revealed the need for location-specific interventions matching to the needs and preferences of the communities.

Effects of dietary lipid source on growth, digestibility and tissue fatty acid composition of Heterobranchus longifilis fingerlings

One of the major problems facing aquaculture is the inadequate supply of fish oil mostly used for fish feed manufacturing. The continued growth in aquaculture production cannot depend on this finite feed resources, therefore, it is imperative that cheap and readily available substitutes that do not compromise fish growth and fillet quality be found. To achieve this, a 12-week feeding trial with Heterobranchus longifilis fed diets differing in lipid source was conducted. Diets were supplemented with 6% lipid as fish oil, soybean oil, palm oil, coconut oil, groundnut oil and melon seed oil. Triplicate groups of 20 H. longifilis were fed the experimental diets two times a day to apparent satiation, over 84 days. Growth, digestibility, and muscle fatty acid profile were measured to assess diet effects. At the end of the study, survival, feed intake and hepatosomatic index were similar for fish fed experimental diets. However, weight gain, SGR and FCR of fish fed soybean oil-based diet was significantly reduced. Apparent nutrient digestibility coefficients were significantly lower in fish fed soybean, coconut and groundnut oil-based diets. Fillet and hepatic fatty acid compositions differed and reflected the fatty acid compositions of the diets. Docosahexaenoic acid (22:6n-3), 20:5n-3 and 20:4n-6 were conserved in vegetable oils-based diets fed fish possibly due to synthesis of HUFA from 18:3n-3 and 18:4n-6. Palm oil diet was the least expensive, and had the best economic conversion ratio. The use of vegetable oils in the diets had positive effect on growth and fillet composition of H. longifilis.

Programa amigo : un intento de resolver los problemas de convivencia en un IES marginal.

Se incluyen todas las actividades y las metodologías desarrolladas

Segmentation of Brain Tissue from Magnetic Resonance Images

Segmentation of medical imagery is a challenging problem due to the complexity of the images, as well as to the absence of models of the anatomy that fully capture the possible deformations in each structure. Brain tissue is a particularly complex structure, and its segmentation is an important step for studies in temporal change detection of morphology, as well as for 3D visualization in surgical planning. In this paper, we present a method for segmentation of brain tissue from magnetic resonance images that is a combination of three existing techniques from the Computer Vision literature: EM segmentation, binary morphology, and active contour models. Each of these techniques has been customized for the problem of brain tissue segmentation in a way that the resultant method is more robust than its components. Finally, we present the results of a parallel implementation of this method on IBM's supercomputer Power Visualization System for a database of 20 brain scans each with 256x256x124 voxels and validate those against segmentations generated by neuroanatomy experts.

Apatite-Polymer Composites for the Controlled Dual Delivery of BMP-2 and BMP-6 for Bone Tissue Engineering

The release of growth factors from tissue engineering scaffolds provides signals that influence the migration, differentiation, and proliferation of cells. The incorporation of a drug delivery platform that is capable of tunable release will give tissue engineers greater versatility in the direction of tissue regeneration. We have prepared a novel composite of two biomaterials with proven track records - apatite and poly(lactic-co-glycolic acid) (PLGA) – as a drug delivery platform with promising controlled release properties. These composites have been tested in the delivery of a model protein, bovine serum albumin (BSA), as well as therapeutic proteins, recombinant human bone morphogenetic protein-2 (rhBMP-2) and rhBMP-6. The controlled release strategy is based on the use of a polymer with acidic degradation products to control the dissolution of the basic apatitic component, resulting in protein release. Therefore, any parameter that affects either polymer degradation or apatite dissolution can be used to control protein release. We have modified the protein release profile systematically by varying the polymer molecular weight, polymer hydrophobicity, apatite loading, apatite particle size, and other material and processing parameters. Biologically active rhBMP-2 was released from these composite microparticles over 100 days, in contrast to conventional collagen sponge carriers, which were depleted in approximately 2 weeks. The released rhBMP-2 was able to induce elevated alkaline phosphatase and osteocalcin expression in pluripotent murine embryonic fibroblasts. To augment tissue engineering scaffolds with tunable and sustained protein release capabilities, these composite microparticles can be dispersed in the scaffolds in different combinations to obtain a superposition of the release profiles. We have loaded rhBMP-2 into composite microparticles with a fast release profile, and rhBMP-6 into slow-releasing composite microparticles. An equi-mixture of these two sets of composite particles was then injected into a collagen sponge, allowing for dual release of the proteins from the collagenous scaffold. The ability of these BMP-loaded scaffolds to induce osteoblastic differentiation in vitro and ectopic bone formation in a rat model is being investigated. We anticipate that these apatite-polymer composite microparticles can be extended to the delivery of other signalling molecules, and can be incorporated into other types of tissue engineering scaffolds.

“Unmixing” Tissue Gene Expression Signatures from Tumor Biopsies

Emergent molecular measurement methods, such as DNA microarray, qRTPCR, and many others, offer tremendous promise for the personalized treatment of cancer. These technologies measure the amount of specific proteins, RNA, DNA or other molecular targets from tumor specimens with the goal of “fingerprinting” individual cancers. Tumor specimens are heterogeneous; an individual specimen typically contains unknown amounts of multiple tissues types. Thus, the measured molecular concentrations result from an unknown mixture of tissue types, and must be normalized to account for the composition of the mixture. For example, a breast tumor biopsy may contain normal, dysplastic and cancerous epithelial cells, as well as stromal components (fatty and connective tissue) and blood and lymphatic vessels. Our diagnostic interest focuses solely on the dysplastic and cancerous epithelial cells. The remaining tissue components serve to “contaminate” the signal of interest. The proportion of each of the tissue components changes as a function of patient characteristics (e.g., age), and varies spatially across the tumor region. Because each of the tissue components produces a different molecular signature, and the amount of each tissue type is specimen dependent, we must estimate the tissue composition of the specimen, and adjust the molecular signal for this composition. Using the idea of a chemical mass balance, we consider the total measured concentrations to be a weighted sum of the individual tissue signatures, where weights are determined by the relative amounts of the different tissue types. We develop a compositional source apportionment model to estimate the relative amounts of tissue components in a tumor specimen. We then use these estimates to infer the tissuespecific concentrations of key molecular targets for sub-typing individual tumors. We anticipate these specific measurements will greatly improve our ability to discriminate between different classes of tumors, and allow more precise matching of each patient to the appropriate treatment

Escuela y clase social desfavorecida : estudio de las relaciones a través del análisis del discurso en un Centro Educativo de una barriada marginal de Córdoba.

Descubrir los discursos, los objetivos, las creencias, los valores, etc., de una institución escolar en un contexto marginal y de los sujetos que la nutren es el objetivo prioritario. Saber si unos y otros son capaces de hablar un mismo lenguaje, si hay entendimiento, si se cree que lo hay sin haberlo, si lo que los sujetos demandan a la escuela es lo mismo que lo que la escuela está dispuesta a darles, si lo que la escuela pide a los alumnos es sólo un desiderátum, etc. Se trata de una investigación cualitativa que emplea como método básico la etnografía. Está realizada en una escuela marginal de Córdoba y se centra, fundamentalmente, en la reconstrucción del modo de vida de la unidad de estudio con objeto de descubrir los aspectos ocultos -creencias, sentimientos, intenciones, valores, deseos, etc.- tanto de la institución escolar como de los sujetos que la nutren. La particularidad del trabajo es que está realizado por una investigadora participante, una maestra inserta en el escenario de estudio durante veintiún años. Al tratarse de una investigación etnográfica, los hallazgos son, necesariamente, contingentes y singulares, por lo que no es posible realizar a partir de ellos inferencias -tomar las conclusiones como premisas de investigaciones futuras- ni generalizaciones -extender los resultados a otros casos-. Sin embargo, posibilitan el descubrimiento de las claves tanto de la realidad como de la utopía (posible). Es decir, el examen a fondo del objeto de estudio -una realidad social que soporta la violación de los derechos humanos más elementales- despliega su interrogación y el desarrollo de alternativas transformadoras. Es preciso entender la escuela como un espacio natural donde los niños viven y protagonizan su propio aprendizaje. No es, como suele entenderse, el lugar en el que los maestros enseñan, sino en el que los niños aprenden -que no es lo mismo-, y éstos han de aprender con la enseñanza de sus profesores o a pesar de ella.

Josep-Maria Terricabras: "Una universitat petita no té perquè ser esquifida, ni ha de ser marginal per ser perifèrica"

Josep-Maria Terricabras és el director de la Càtedra Ferrater Mora de Pensament Contemporani. Ara fa vint anysque va tenir la idea de crear una càtedra de pensament en una Girona que tenia estudis universitaris però que encara no tenia universitat pròpia. Han passat els anys i es pot afirmar que ha estat una jugada reeixida perquè, gràcies a la Càtedra, han passat per la ciutat personatges destacats de la cultura, com Chomsky, Quine, Cavalli-Sforza, Nyman o Stieglitz, fins a completar una llista que molt aviat arribarà a la trentena. La Càtedra Ferrater Mora de Pensament Contemporani és més antiga que la mateixa Universitat de Girona. El 2 de novembre vinent farà vint anys que es va crear

Modeling and Classifying Breast Tissue Density in Mammograms

We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal

A Novel Breast Tissue Density Classification Methodology

It has been shown that the accuracy of mammographic abnormality detection methods is strongly dependent on the breast tissue characteristics, where a dense breast drastically reduces detection sensitivity. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. Here, we describe the development of an automatic breast tissue classification methodology, which can be summarized in a number of distinct steps: 1) the segmentation of the breast area into fatty versus dense mammographic tissue; 2) the extraction of morphological and texture features from the segmented breast areas; and 3) the use of a Bayesian combination of a number of classifiers. The evaluation, based on a large number of cases from two different mammographic data sets, shows a strong correlation ( and 0.67 for the two data sets) between automatic and expert-based Breast Imaging Reporting and Data System mammographic density assessment

A new approach to the classification of mammographic masses and normal breast tissue

A new approach to mammographic mass detection is presented in this paper. Although different algorithms have been proposed for such a task, most of them are application dependent. In contrast, our approach makes use of a kindred topic in computer vision adapted to our particular problem. In this sense, we translate the eigenfaces approach for face detection/classification problems to a mass detection. Two different databases were used to show the robustness of the approach. The first one consisted on a set of 160 regions of interest (RoIs) extracted from the MIAS database, being 40 of them with confirmed masses and the rest normal tissue. The second set of RoIs was extracted from the DDSM database, and contained 196 RoIs containing masses and 392 with normal, but suspicious regions. Initial results demonstrate the feasibility of using such approach with performances comparable to other algorithms, with the advantage of being a more general, simple and cost-effective approach

HLA-A Typing in formalin-fixed paraffin embedded tissue samples : towards potential retrospective analysis

El Antígeno Leucocitario Humano (HLA en inglés) ha sido descrito en muchos casos como factor de pronóstico para cáncer. La característica principal de los genes de HLA, localizados en el cromosoma 6 (6p21.3), son sus numerosos polimorfismos. Los análisis de secuencia de nucleótidos muestran que la variación está restringida predominantemente a los exones que codifican los dominios de unión a péptidos de la proteína. Por lo tanto, el polimorfismo del HLA define el repertorio de péptidos que se unen a los alotipos de HLA y este hecho define la habilidad de un individuo para responder a la exposición a muchos agentes infecciosos durante su vida. La tipificación de HLA se ha convertido en un análisis importante en clínica. Muestras de tejido embebidas en parafina y fijadas con formalina (FFPE en inglés) son recolectadas rutinariamente en oncología. Este procedimiento podría ser utilizado como una buena fuente de ADN, dado que en estudios en el pasado los ensayos de recolección de ADN no eran normalmente llevados a cabo de casi ningún tejido o muestra en procedimientos clínicos regulares. Teniendo en cuenta que el problema más importante con el ADN de muestras FFPE es la fragmentación, nosotros propusimos un nuevo método para la tipificación del alelo HLA-A desde muestras FFPE basado en las secuencias del exón 2, 3 y 4. Nosotros diseñamos un juego de 12 cebadores: cuatro para el exón 2 de HLA-A, tres para el exón 3 de HLA-A y cinco para el exón 4 de HLA-A, cada uno de acuerdo las secuencias flanqueantes de su respectivo exón y la variación en la secuencia entre diferentes alelos. 17 muestran FFPE colectadas en el Hospital Universitario de Karolinska en Estocolmo Suecia fueron sometidas a PCR y los productos fueron secuenciados. Finalmente todas las secuencias obtenidas fueron analizadas y comparadas con la base de datos del IMGT-HLA. Las muestras FFPE habían sido previamente tipificadas para HLA y los resultados fueron comparados con los de este método. De acuerdo con nuestros resultados, las muestras pudieron ser correctamente secuenciadas. Con este procedimiento, podemos concluir que nuestro estudio es el primer método de tipificación basado en secuencia que permite analizar muestras viejas de ADN de las cuales no se tiene otra fuente. Este estudio abre la posibilidad de desarrollar análisis para establecer nuevas relaciones entre HLA y diferentes enfermedades como el cáncer también.