Synthetic Triterpenoid Cyano Enone of Methyl Boswellate Activates Intrinsic, Extrinsic, and Endoplasmic Reticulum Stress Cell Death Pathways in Tumor Cell Lines

We explored the effect of a novel synthetic triterpenoid compound cyano enone of methyl boswellates (CEMB) on various prostate cancer and glioma cancer cell lines. CEMB displayed concentration-dependent cytotoxic activity with submicromolar lethal dose 50% (LD(50)) values in 10 of 10 tumor cell lines tested. CEMB-induced cytotoxicity is accompanied by activation of downstream effector caspases (caspases 3 and 7) and by upstream initiator caspases involved in both the extrinsic (caspase 8) and intrinsic (caspase 9) apoptotic pathways. By using short interfering RNAs (siRNA), we show evidence that knockdown of caspase 8, DR4, Apaf-1, and Bid impairs CEMB-induced cell death. Similar to other proapoptotic synthetic triterpenoid compounds, CEMB-induced apoptosis involved endoplasmic reticulum stress, as shown by partial rescue of tumor cells by siRNA-mediated knockdown of expression of genes involved in the unfolded protein response such as IRE1 alpha, PERK, and ATF6. Altogether, our results suggest that CEMB stimulates several apoptotic pathways in cancer cells, suggesting that this compound should be evaluated further as a potential agent for cancer therapy. Mol Cancer Ther; 10(9); 1635-43. (C)2011 AACR.

Comparative Assessment of Techniques for Bioresource Monitoring Using GIS and Remote Sensing

Growing concern over the status of global and regional bioenergy resources has necessitated the analysis and monitoring of land cover and land use parameters on spatial and temporal scales. The knowledge of land cover and land use is very important in understanding natural resources utilization, conversion and management. Land cover, land use intensity and land use diversity are land quality indicators for sustainable land management. Optimal management of resources aids in maintaining the ecosystem balance and thereby ensures the sustainable development of a region. Thus sustainable development of a region requires a synoptic ecosystem approach in the management of natural resources that relates to the dynamics of natural variability and the effects of human intervention on key indicators of biodiversity and productivity. Spatial and temporal tools such as remote sensing (RS), geographic information system (GIS) and global positioning system (GPS) provide spatial and attribute data at regular intervals with functionalities of a decision support system aid in visualisation, querying, analysis, etc., which would aid in sustainable management of natural resources. Remote sensing data and GIS technologies play an important role in spatially evaluating bioresource availability and demand. This paper explores various land cover and land use techniques that could be used for bioresources monitoring considering the spatial data of Kolar district, Karnataka state, India. Slope and distance based vegetation indices are computed for qualitative and quantitative assessment of land cover using remote spectral measurements. Differentscale mapping of land use pattern in Kolar district is done using supervised classification approaches. Slope based vegetation indices show area under vegetation range from 47.65 % to 49.05% while distance based vegetation indices shoes its range from 40.40% to 47.41%. Land use analyses using maximum likelihood classifier indicate that 46.69% is agricultural land, 42.33% is wasteland (barren land), 4.62% is built up, 3.07% of plantation, 2.77% natural forest and 0.53% water bodies. The comparative analysis of various classifiers, indicate that the Gaussian maximum likelihood classifier has least errors. The computation of talukwise bioresource status shows that Chikballapur Taluk has better availability of resources compared to other taluks in the district.

Vegetation Analysis in Uttara Kannada District Using GIS and Remote Sensing Techniques

Uttara Kannada is the only district in Karnataka, which has a forested area of about 80% and falls in the region of the Western Ghats. It is considered to be a very resourceful in terms of abundant natural resources and constitutes an important district in Karnataka. The forest resources of the district are under pressure as a large portion of the forested area has been converted to non-forestry activities since independence owing to the increased demands from human and animal population resulting in degradation of the forest ecosystem. This has led to poor productivity and regenerative capacity which is evident in the form of barren hill tops, etc in Coastal taluks of Uttara Kannada, entailing regular monitoring of the forest resources very essential. The classification of forest is a prerequisite for managing forest resources. Geographical Information System (GIS), allows the spatial and temporal analysis of the features of interest, and helps in solving the problem of deforestation and associated environmental and ecological problems. Spatial and temporal tools such as GIS and remotely sensed data helps the planners and decision makers in evolving the sustainable strategies for management and conservation of natural resources. Uttara Kannada district was classified on the basis of the land-use using supervised hard classifiers. The land use categories identified were urban area, water bodies, agricultural land, forest cover, and waste land. Further classification was carried out on the basis of forest type. The types of forest categorised were semi-evergreen, evergreen, moist deciduous, dry deciduous, plantations and scrub, thorny and non-forested area. The identified classes were correlated with the ground data collected during field visits. The observed results were compared with the historic data and the changes in the forest cover were analysed. From the assessment made it was clear that there has been a considerable degree of forest loss in certain areas of the district. It was also observed that plantations and social forests have increased drastically over the last fifteen years,and natural forests have declined.

Multiclass Core Vector Machine

Even though several techniques have been proposed in the literature for achieving multiclass classification using Support Vector Machine(SVM), the scalability aspect of these approaches to handle large data sets still needs much of exploration. Core Vector Machine(CVM) is a technique for scaling up a two class SVM to handle large data sets. In this paper we propose a Multiclass Core Vector Machine(MCVM). Here we formulate the multiclass SVM problem as a Quadratic Programming(QP) problem defining an SVM with vector valued output. This QP problem is then solved using the CVM technique to achieve scalability to handle large data sets. Experiments done with several large synthetic and real world data sets show that the proposed MCVM technique gives good generalization performance as that of SVM at a much lesser computational expense. Further, it is observed that MCVM scales well with the size of the data set.

Strength of lime-fly ash compacts using different curing techniques and gypsum additive

Lime-fly ash mixtures are exploited for the manufacture of fly ash bricks finding applications in load bearing masonry. Lime-pozzolana reactions take place at a slow pace under ambient temperature conditions and hence very long curing durations are required to achieve meaningful strength values. The present investigation examines the improvements in strength development in lime-fly ash compacts through low temperature steam curing and use of additives like gypsum. Results of density-strength-moulding water content relationships, influence of lime-fly ash ratio, steam curing and role of gypsum on strength development, and characteristics of compacted lime-fly ash-gypsum bricks have been discussed. The test results reveal that (a) strength increases with increase in density irrespective of lime content, type of curing and moulding water content, (b) optimum lime-fly ash ratio yielding maximum strength is about 0.75 in the normal curing conditions, (c) 24 h of steam curing (at 80A degrees C) is sufficient to achieve nearly possible maximum strength, (d) optimum gypsum content yielding maximum compressive strength is at 2%, (e) with gypsum additive it is possible to obtain lime-fly ash bricks or blocks having sufficient strength (> 10 MPa) at 28 days of normal wet burlap curing.

Tracing the source of bottled water using stable isotope techniques

The Indian Summer Monsoon (ISM) precipitation recharges ground water aquifers in a large portion of the Indian subcontinent. Monsoonal precipitation over the Indian region brings moisture from the Arabian Sea and the Bay of Bengal (BoB). A large difference in the salinity of these two reservoirs, owing to the large amount of freshwater discharge from the continental rivers in the case of the BoB and dominating evaporation processes over the Arabian Sea region, allows us to distinguish the isotopic signatures in water originating in these two water bodies. Most bottled water manufacturers exploit the natural resources of groundwater, replenished by the monsoonal precipitation, for bottling purposes. The work presented here relates the isotopic ratios of bottled water to latitude, moisture source and seasonality in precipitation isotope ratios. We investigated the impact of the above factors on the isotopic composition of bottled water. The result shows a strong relationship between isotope ratios in precipitation (obtained from the GNIP data base)/bottled water with latitude. The approach can be used to predict the latitude at which the bottled water was manufactured. The paper provides two alternative approaches to address the site prediction. The limitations of this approach in identifying source locations and the uncertainty in latitude estimations are discussed. Furthermore, the method provided here can also be used as an important forensic tool for exploring the source location of bottled water from other regions. Copyright (C) 2011 John Wiley & Sons, Ltd.

Pickup and delivery problem using metaheuristics techniques

Dial-a-ride problem (DARP) is an optimization problem which deals with the minimization of the cost of the provided service where the customers are provided a door-to-door service based on their requests. This optimization model presented in earlier studies, is considered in this study. Due to the non-linear nature of the objective function the traditional optimization methods are plagued with the problem of converging to a local minima. To overcome this pitfall we use metaheuristics namely Simulated Annealing (SA), Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Artificial Immune System (AIS). From the results obtained, we conclude that Artificial Immune System method effectively tackles this optimization problem by providing us with optimal solutions. Crown Copyright (C) 2011 Published by Elsevier Ltd. All rights reserved.