Side Chain Structure Determines Unique Physiologic and Therapeutic Properties of norUrsodeoxycholic Acid in Mdr2(-/-) Mice

24-norursodeoxycholic acid (norUDCA), a side chain-modified ursodeoxycholic acid derivative, has dramatic therapeutic effects in experimental cholestasis and may be a promising agent for the treatment of cholestatic liver diseases. We aimed to better understand the physiologic and therapeutic properties of norUDCA and to test if they are related to its side chain length and/or relative resistance to amidation. For this purpose, Mdr2-/- mice, a model for sclerosing cholangitis, received either a standard diet or a norUDCA-, tauro norursodeoxycholic acid (tauro- norUDCA)-, or di norursodeoxycholic acid (di norUDCA)-enriched diet. Bile composition, serum biochemistry, liver histology, fibrosis, and expression of key detoxification and transport systems were investigated. Direct choleretic effects were addressed in isolated bile duct units. The role of Cftr for norUDCA-induced choleresis was explored in Cftr-/- mice. norUDCA had pharmacologic features that were not shared by its derivatives, including the increase in hepatic and serum bile acid levels and a strong stimulation of biliary HCO3- -output. norUDCA directly stimulated fluid secretion in isolated bile duct units in a HCO3- -dependent fashion to a higher extent than the other bile acids. Notably, the norUDCA significantly stimulated HCO 3- -output also in Cftr-/- mice. In Mdr2-/- mice, cholangitis and fibrosis strongly improved with norUDCA, remained unchanged with tauro- norUDCA, and worsened with di norUDCA. Expression of Mrp4, Cyp2b10, and Sult2a1 was increased by norUDCA and di norUDCA, but was unaffected by tauro- norUDCA. Conclusion:The relative resistance of norUDCA to amidation may explain its unique physiologic and pharmacologic properties. These include the ability to undergo cholehepatic shunting and to directly stimulate cholangiocyte secretion, both resulting in a HCO3- -rich hypercholeresis that protects the liver from cholestatic injury.

An innovative clustering technique for unsupervized learning in the context of remotely sensed earth resources data analysis

A new clustering technique, based on the concept of immediato neighbourhood, with a novel capability to self-learn the number of clusters expected in the unsupervized environment, has been developed. The method compares favourably with other clustering schemes based on distance measures, both in terms of conceptual innovations and computational economy. Test implementation of the scheme using C-l flight line training sample data in a simulated unsupervized mode has brought out the efficacy of the technique. The technique can easily be implemented as a front end to established pattern classification systems with supervized learning capabilities to derive unified learning systems capable of operating in both supervized and unsupervized environments. This makes the technique an attractive proposition in the context of remotely sensed earth resources data analysis wherein it is essential to have such a unified learning system capability.

The potential of certification for conservation and management of wild MAP resources

Medicinal and aromatic plants (MAPs) are an integral part of our biodiversity. In majority of MAP rich countries, wild collection practices are the livelihood options for a large number of rural peoples and MAPs play a significant role in socio-economic development of their communities. Recent concern over the alarming situation of the status of wild MAP resources, raw material quality, as well as social exploitation of rural communities, leads to the idea of certification for MAP resource conservation and management. On one hand, while MAP certification addresses environmental, social and economic perspectives of MAP resources, on the other hand, it ensures multi-stakeholder participation in improvement of the MAP sector. This paper presents an overview of MAP certification encompassing its different parameters, current scenario (Indian background), implementation strategies as well as stakeholders’ role in MAP conservation. It also highlights Indian initiatives in this direction.

Performance evaluation of elitist-mutated multi-objective particle swarm optimization for integrated water resources management

Optimal allocation of water resources for various stakeholders often involves considerable complexity with several conflicting goals, which often leads to multi-objective optimization. In aid of effective decision-making to the water managers, apart from developing effective multi-objective mathematical models, there is a greater necessity of providing efficient Pareto optimal solutions to the real world problems. This study proposes a swarm-intelligence-based multi-objective technique, namely the elitist-mutated multi-objective particle swarm optimization technique (EM-MOPSO), for arriving at efficient Pareto optimal solutions to the multi-objective water resource management problems. The EM-MOPSO technique is applied to a case study of the multi-objective reservoir operation problem. The model performance is evaluated by comparing with results of a non-dominated sorting genetic algorithm (NSGA-II) model, and it is found that the EM-MOPSO method results in better performance. The developed method can be used as an effective aid for multi-objective decision-making in integrated water resource management.

Novel peptides of therapeutic promise from Indian Conidae

Highly structured small peptides are the major toxic constituents of the venom of cone snails, a family of widely distributed predatory marine molluscs. These animals use the venom for rapid prey immobilization. The peptide components in the venom target a wide variety of membrane-bound ion channels and receptors. Many have been found to be highly selective for a diverse range of mammalian ion channels and receptors associated with pain-signaling pathways. Their small size, structural stability, and target specificity make them attractive pharmacologic agents. A select number of laboratories mainly from the United States, Europe, Australia, Israel, and China have been engaged in intense drug discovery programs based on peptides from a few snail species. Coastal India has an estimated 20-30% of the known cone species; however, few serious studies have been reported so far. We have begun a comprehensive program for the identification and characterization of peptides from cone snails found in Indian Coastal waters. This presentation reviews our progress over the last 2 years. As expected from the evolutionary history of these venom components, our search has yielded novel peptides of therapeutic promise from the new species that we have studied.

Permanent Genetic Resources added to Molecular Ecology Resources Database 1 August 2010-30 September 2010

This article documents the addition of 229 microsatellite marker loci to the Molecular Ecology Resources Database. Loci were developed for the following species: Acacia auriculiformis x Acacia mangium hybrid, Alabama argillacea, Anoplopoma fimbria, Aplochiton zebra, Brevicoryne brassicae, Bruguiera gymnorhiza, Bucorvus leadbeateri, Delphacodes detecta, Tumidagena minuta, Dictyostelium giganteum, Echinogammarus berilloni, Epimedium sagittatum, Fraxinus excelsior, Labeo chrysophekadion, Oncorhynchus clarki lewisi, Paratrechina longicornis, Phaeocystis antarctica, Pinus roxburghii and Potamilus capax. These loci were cross-tested on the following species: Acacia peregrinalis, Acacia crassicarpa, Bruguiera cylindrica, Delphacodes detecta, Tumidagena minuta, Dictyostelium macrocephalum, Dictyostelium discoideum, Dictyostelium purpureum, Dictyostelium mucoroides, Dictyostelium rosarium, Polysphondylium pallidum, Epimedium brevicornum, Epimedium koreanum, Epimedium pubescens, Epimedium wushanese and Fraxinus angustifolia.

Cytochrome P4504f, a potential therapeutic target limiting neuroinflammation

Inflammatory processes are involved in the pathogenesis and/or progression of acute central nervous system (CNS) infection, traumatic brain injury and neurodegenerative disorders among others indicating the need for novel strategies to limit neuroinflammation. Eicosanoids including leukotrienes, particularly leukotriene B-4 (LTB4) are principle mediator(s) of inflammatory response, initiating and amplifying the generation of cytokines and chemokines. Cytochrome P450 (Cyp), a family of heme proteins mediate metabolism of xenobiotics and endogenous compounds, such as eicosanoids and leukotrienes. Cytochrome P4504F (Cyp4f) subfamily includes five functional enzymes in mouse. We cloned and expressed the mouse Cyp4f enzymes, assayed their relative expression in brain and examined their ability to hydroxylate the inflammatory cascade prompt LTB4 to its inactive 20-hydroxylated product. We then examined the role of Cyp4fs in regulating inflammatory response in vitro, in microglial cells and in vivo, in mouse brain using lipopolysacharide (LPS), as a model compound to generate inflammatory response. We demonstrate that mouse brain Cyp4fs are expressed ubiquitously in several cell types in the brain, including neurons and microglia, and modulate inflammatory response triggered by LPS, in vivo and in microglial cells, in vitro through metabolism of LTB4 to the inactive 20-hydroxy LTB4. Chemical inhibitor or shRNA to Cyp4fs enhance and inducer of Cyp4fs attenuates inflammatory response. Further, induction of Cyp4f expression lowers LTB4 levels and affords neuroprotection in microglial cells or mice exposed to LPS. Thus, catalytic activity of Cyp4fs is a novel target for modulating neuroinflammation through hydroxylation of LTB4. (C) 2011 Elsevier Inc. All rights reserved.

Optimal crop planning and conjunctive use of water resources in a coastal river basin

Due to increasing trend of intensive rice cultivation in a coastal river basin, crop planning and groundwater management are imperative for the sustainable agriculture. For effective management, two models have been developed viz. groundwater balance model and optimum cropping and groundwater management model to determine optimum cropping pattern and groundwater allocation from private and government tubewells according to different soil types (saline and non-saline), type of agriculture (rainfed and irrigated) and seasons (monsoon and winter). A groundwater balance model has been developed considering mass balance approach. The components of the groundwater balance considered are recharge from rainfall, irrigated rice and non-rice fields, base flow from rivers and seepage flow from surface drains. In the second phase, a linear programming optimization model is developed for optimal cropping and groundwater management for maximizing the economic returns. The models developed were applied to a portion of coastal river basin in Orissa State, India and optimal cropping pattern for various scenarios of river flow and groundwater availability was obtained.

Exploring use of climate information for optimal design of water resources infrastructure

We conducted surveys of fire and fuels managers at local, regional, and national levels to gain insights into decision processes and information flows in wildfire management. Survey results in the form of fire managers’ decision calendars show how climate information needs vary seasonally, over space, and through the organizational network, and help determine optimal points for introducing climate information and forecasts into decision processes. We identified opportunities to use climate information in fire management, including seasonal to interannual climate forecasts at all organizational levels, to improve the targeting of fuels treatments and prescribed burns, the positioning and movement of initial attack resources, and staffing and budgeting decisions. Longer-term (5–10 years) outlooks also could be useful at the national level in setting budget and research priorities. We discuss these opportunities and examine the kinds of organizational changes that could facilitate effective use of existing climate information and climate forecast capabilities.

Geographic Resources Decision Support System – an Open Source GIS

Fully structured and matured open source spatial and temporal analysis technology seems to be the official carrier of the future for planning of the natural resources especially in the developing nations. This technology has gained enormous momentum because of technical superiority, affordability and ability to join expertise from all sections of the society. Sustainable development of a region depends on the integrated planning approaches adopted in decision making which requires timely and accurate spatial data. With the increased developmental programmes, the need for appropriate decision support system has increased in order to analyse and visualise the decisions associated with spatial and temporal aspects of natural resources. In this regard Geographic Information System (GIS) along with remote sensing data support the applications that involve spatial and temporal analysis on digital thematic maps and the remotely sensed images. Open source GIS would help in wide scale applications involving decisions at various hierarchical levels (for example from village panchayat to planning commission) on economic viability, social acceptance apart from technical feasibility. GRASS (Geographic Resources Analysis Support System, http://wgbis.ces.iisc.ernet.in/grass) is an open source GIS that works on Linux platform (freeware), but most of the applications are in command line argument, necessitating a user friendly and cost effective graphical user interface (GUI). Keeping these aspects in mind, Geographic Resources Decision Support System (GRDSS) has been developed with functionality such as raster, topological vector, image processing, statistical analysis, geographical analysis, graphics production, etc. This operates through a GUI developed in Tcltk (Tool command language / Tool kit) under Linux as well as with a shell in X-Windows. GRDSS include options such as Import /Export of different data formats, Display, Digital Image processing, Map editing, Raster Analysis, Vector Analysis, Point Analysis, Spatial Query, which are required for regional planning such as watershed Analysis, Landscape Analysis etc. This is customised to Indian context with an option to extract individual band from the IRS (Indian Remote Sensing Satellites) data, which is in BIL (Band Interleaved by Lines) format. The integration of PostgreSQL (a freeware) in GRDSS aids as an efficient database management system.