Proteomic profiling of forskolin-induced differentiated BeWo cells: an in-vitro model of cytotrophoblast differentiation

Placental trophoblastic differentiation is characterized by the fusion of monolayer cytotrophoblasts into syncytiotrophoblasts. During this process of differentiation, several morphological and biochemical changes are known to occur, and this model has been employed to investigate the changes that occur at the gene and protein level during differentiation. Using the sensitive technique of proteomics [two-dimensional gel electrophoresis (2DGE)], changes in protein profile were evaluated in the control and forskolin-induced differentiated cells of trophoblastic choriocarcinoma BeWo cell line. Several proteins were differentially expressed in control and differentiated cells. Four major proteins were up-regulated as assessed by silver staining, and were further characterized as c-h-ras p 21 (phosphorylated), retinoblastoma susceptibility protein I and integrase interactor protein 1. These proteins are known to play an important role in growth arrest of cells, and thus may play a role in initiating the process of differentiation.

Taking Multiple Infections of Cells and Recombination into Account Leads to Small Within-Host Effective-Population-Size Estimates of HIV-1

Whether HIV-1 evolution in infected individuals is dominated by deterministic or stochastic effects remains unclear because current estimates of the effective population size of HIV-1 in vivo, N-e, are widely varying. Models assuming HIV-1 evolution to be neutral estimate N-e similar to 10(2)-10(4), smaller than the inverse mutation rate of HIV-1 (similar to 10(5)), implying the predominance of stochastic forces. In contrast, a model that includes selection estimates N-e>10(5), suggesting that deterministic forces would hold sway. The consequent uncertainty in the nature of HIV-1 evolution compromises our ability to describe disease progression and outcomes of therapy. We perform detailed bit-string simulations of viral evolution that consider large genome lengths and incorporate the key evolutionary processes underlying the genomic diversification of HIV-1 in infected individuals, namely, mutation, multiple infections of cells, recombination, selection, and epistatic interactions between multiple loci. Our simulations describe quantitatively the evolution of HIV-1 diversity and divergence in patients. From comparisons of our simulations with patient data, we estimate N-e similar to 10(3)-10(4), implying predominantly stochastic evolution. Interestingly, we find that N-e and the viral generation time are correlated with the disease progression time, presenting a route to a priori prediction of disease progression in patients. Further, we show that the previous estimate of N-e>10(5) reduces as the frequencies of multiple infections of cells and recombination assumed increase. Our simulations with N-e similar to 10(3)-10(4) may be employed to estimate markers of disease progression and outcomes of therapy that depend on the evolution of viral diversity and divergence.

Implications of climate change on mitigation potential estimates for forest sector in India

Climate change is projected to impact forest ecosystems, including biodiversity and Net Primary Productivity (NPP). National level carbon forest sector mitigation potential estimates are available for India; however impacts of projected climate change are not included in the mitigation potential estimates. Change in NPP (in gC/m(2)/yr) is taken to represent the impacts of climate change. Long term impacts of climate change (2085) on the NPP of Indian forests are available; however no such regional estimates are available for short and medium terms. The present study based on GCM climatology scenarios projects the short, medium and long term impacts of climate change on forest ecosystems especially on NPP using BIOME4 vegetation model. We estimate that under A2 scenario by the year 2030 the NPP changes by (-5) to 40% across different agro-ecological zones (AEZ). By 2050 it increases by 15% to 59% and by 2070 it increases by 34 to 84%. However, under B2 scenario it increases only by 3 to 25%, 3.5 to 34% and (-2.5) to 38% respectively, in the same time periods. The cumulative mitigation potential is estimated to increase by up to 21% (by nearly 1 GtC) under A2 scenario between the years 2008 and 2108, whereas, under B2 the mitigation potential increases only by 14% (646 MtC). However, cumulative mitigation potential estimates obtained from IBIS-a dynamic global vegetation model suggest much smaller gains, where mitigation potential increases by only 6% and 5% during the period 2008 to 2108.

A macroeconomic analysis of adaptation to climate change impacts on forests in India

We examine the potential for adaptation to climate change in Indian forests, and derive the macroeconomic implications of forest impacts and adaptation in India. The study is conducted by integrating results from the dynamic global vegetation model IBIS and the computable general equilibrium model GRACE-IN, which estimates macroeconomic implications for six zones of India. By comparing a reference scenario without climate change with a climate impact scenario based on the IPCC A2-scenario, we find major variations in the pattern of change across zones. Biomass stock increases in all zones but the Central zone. The increase in biomass growth is smaller, and declines in one more zone, South zone, despite higher stock. In the four zones with increases in biomass growth, harvest increases by only approximately 1/3 of the change in biomass growth. This is due to two market effects of increased biomass growth. One is that an increase in biomass growth encourages more harvest given other things being equal. The other is that more harvest leads to higher supply of timber, which lowers market prices. As a result, also the rent on forested land decreases. The lower prices and rent discourage more harvest even though they may induce higher demand, which increases the pressure on harvest. In a less perfect world than the model describes these two effects may contribute to an increase in the risk of deforestation because of higher biomass growth. Furthermore, higher harvest demands more labor and capital input in the forestry sector. Given total supply of labor and capital, this increases the cost of production in all the other sectors, although very little indeed. Forestry dependent communities with declining biomass growth may, however, experience local unemployment as a result.

Modelling electricity demand with representative load curves

Models for electricity planning require inclusion of demand. Depending on the type of planning, the demand is usually represented as an annual demand for electricity (GWh), a peak demand (MW) or in the form of annual load-duration curves. The demand for electricity varies with the seasons, economic activities, etc. Existing schemes do not capture the dynamics of demand variations that are important for planning. For this purpose, we introduce the concept of representative load curves (RLCs). Advantages of RLCs are demonstrated in a case study for the state of Karnataka in India. Multiple discriminant analysis is used to cluster the 365 daily load curves for 1993-94 into nine RLCs. Further analyses of these RLCs help to identify important factors, namely, seasonal, industrial, agricultural, and residential (water heating and air-cooling) demand variations besides rationing by the utility. (C) 1999 Elsevier Science Ltd. All rights reserved.

Greenhouse gas inventory estimates for India

This article reports the greenhouse gas emissions of anthropogenic origin by sources and removals by sinks of India for 2007 prepared under the aegis of the Indian Network for Climate Change Assessment (INCCA) (note 1). The emission profile includes carbon dioxide (CO(2)), methane and nitrous oxide. It also includes the estimates of hydrofluorocarbons, perfluorocarbons and sulphur hexafluoride at the national level from various sectors, viz, energy, industrial process and product use, agriculture, land-use, land-use change and forestry (LULUCF), and waste. In 2007, emissions were of the order of 2008.67 Tg (note 2) of CO(2) equivalents without emissions from the LULUCF sector. Whereas with LULUCF the emissions were about 1831.65 Tg CO(2) equivalents. The energy sector accounted for 69% of the total emissions, the agriculture sector contributed 19% of the emissions, 9% of the emissions was from the industrial processes and product use, and only 3% of the emissions was attributable to the waste sector. The LULUCF sector on the whole was net sink category for CO(2). The study tracks the improvements made in inventory estimates at the national level through the years, in terms of the expanding coverage of sources, reducing uncertainties and inclusion of new methodologies, including some elements of future areas of work.

Fault-tolerant Video on Demand in RSerPool Architecture

With the advent of Internet, video over IP is gaining popularity. In such an environment, scalability and fault tolerance will be the key issues. Existing video on demand (VoD) service systems are usually neither scalable nor tolerant to server faults and hence fail to comply to multi-user, failure-prone networks such as the Internet. Current research areas concerning VoD often focus on increasing the throughput and reliability of single server, but rarely addresses the smooth provision of service during server as well as network failures. Reliable Server Pooling (RSerPool), being capable of providing high availability by using multiple redundant servers as single source point, can be a solution to overcome the above failures. During a possible server failure, the continuity of service is retained by another server. In order to achieve transparent failover, efficient state sharing is an important requirement. In this paper, we present an elegant, simple, efficient and scalable approach which has been developed to facilitate the transfer of state by the client itself, using extended cookie mechanism, which ensures that there is no noticeable change in disruption or the video quality.

Mathematical Model of Viral Kinetics In Vitro Estimates the Number of E2-CD81 Complexes Necessary for Hepatitis C Virus Entry

Interaction between the hepatitis C virus (HCV) envelope protein E2 and the host receptor CD81 is essential for HCV entry into target cells. The number of E2-CD81 complexes necessary for HCV entry has remained difficult to estimate experimentally. Using the recently developed cell culture systems that allow persistent HCV infection in vitro, the dependence of HCV entry and kinetics on CD81 expression has been measured. We reasoned that analysis of the latter experiments using a mathematical model of viral kinetics may yield estimates of the number of E2-CD81 complexes necessary for HCV entry. Here, we constructed a mathematical model of HCV viral kinetics in vitro, in which we accounted explicitly for the dependence of HCV entry on CD81 expression. Model predictions of viral kinetics are in quantitative agreement with experimental observations. Specifically, our model predicts triphasic viral kinetics in vitro, where the first phase is characterized by cell proliferation, the second by the infection of susceptible cells and the third by the growth of cells refractory to infection. By fitting model predictions to the above data, we were able to estimate the threshold number of E2-CD81 complexes necessary for HCV entry into human hepatoma-derived cells. We found that depending on the E2-CD81 binding affinity, between 1 and 13 E2-CD81 complexes are necessary for HCV entry. With this estimate, our model captured data from independent experiments that employed different HCV clones and cells with distinct CD81 expression levels, indicating that the estimate is robust. Our study thus quantifies the molecular requirements of HCV entry and suggests guidelines for intervention strategies that target the E2-CD81 interaction. Further, our model presents a framework for quantitative analyses of cell culture studies now extensively employed to investigate HCV infection.

Ganga-Brahmaputra river discharge from Jason-2 radar altimetry: An update to the long-term satellite-derived estimates of continental freshwater forcing flux into the Bay of Bengal

This paper discusses the use of Jason-2 radar altimeter measurements to estimate the Ganga-Brahmaputra surface freshwater flux into the Bay of Bengal for the period mid-2008 to December 2011. A previous estimate was generated for 1993-2008 using TOPEX-Poseidon, ERS-2 and ENVISAT, and is now extended using Jason-2. To take full advantages of the new availability of in situ rating curves, the processing scheme is adapted and the adjustments of the methodology are discussed here. First, using a large sample of in situ river height measurements, we estimate the standard error of Jason-2-derived water levels over the Ganga and the Brahmaputra to be respectively of 0.28 m and 0.19 m, or less than similar to 4% of the annual peak-to-peak variations of these two rivers. Using the in situ rating curves between water levels and river discharges, we show that Jason-2 accurately infers Ganga and Brahmaputra instantaneous discharges for 2008-2011 with mean errors ranging from similar to 2180 m(3)/s (6.5%) over the Brahmaputra to similar to 1458 m(3)/s (13%) over the Ganga. The combined Ganga-Brahmaputra monthly discharges meet the requirements of acceptable accuracy (15-20%) with a mean error of similar to 16% for 2009-2011 and similar to 17% for 1993-2011. The Ganga-Brahmaputra monthly discharge at the river mouths is then presented, showing a marked interannual variability with a standard deviation of similar to 12500 m(3)/s, much larger than the data set uncertainty. Finally, using in situ sea surface salinity observations, we illustrate the possible impact of extreme continental freshwater discharge event on the northern Bay of Bengal as observed in 2008.

Algal biofuel production and mitigation potential in India

Energy and energy services are the backbone of growth and development in India and is increasingly dependent upon the use of fossil based fuels that lead to greenhouse gases (GHG) emissions and related concerns. Algal biofuels are being evolved as carbon (C)-neutral alternative biofuels. Algae are photosynthetic microorganisms that convert sunlight, water and carbon dioxide (CO2) to various sugars and lipids Tri-Acyl-Glycols (TAG) and show promise as an alternative, renewable and green fuel source for India. Compared to land based oilseed crops algae have potentially higher yields (5-12 g/m(2)/d) and can use locations and water resources not suited for agriculture. Within India, there is little additional land area for algal cultivation and therefore needs to be carried out in places that are already used for agriculture, e.g. flooded paddy lands (20 Mha) with village level technologies and on saline wastelands (3 Mha). Cultivating algae under such conditions requires novel multi-tier, multi-cyclic approaches of sharing land area without causing threats to food and water security as well as demand for additional fertilizer resources by adopting multi-tier cropping (algae-paddy) in decentralized open pond systems. A large part of the algal biofuel production is possible in flooded paddy crop land before the crop reaches dense canopies, in wastewaters (40 billion litres per day), in salt affected lands and in nutrient/diversity impoverished shallow coastline fishery. Mitigation will be achieved through avoidance of GHG, C-capture options and substitution of fossil fuels. Estimates made in this paper suggest that nearly half of the current transportation petro-fuels could be produced at such locations without disruption of food security, water security or overall sustainability. This shift can also provide significant mitigation avenues. The major adaptation needs are related to socio-technical acceptance for reuse of various wastelands, wastewaters and waste-derived energy and by-products through policy and attitude change efforts.

Revision of the scolopendrid centipede digitipes Attems, 1930, from India (Chilopoda: Scolopendromorpha): reconciling molecular and morphological estimates of species diversity

Recent work on molecular phylogenetics of Scolopendridae from the Western Ghats, Peninsular India, has suggested the presence of six cryptic species of the otostigmine Digitipes Attems, 1930, together with three species described in previous taxonomic work by Jangi and Dass (1984). Digitipes is the correct generic attribution for a monophyletic group of Indian species, these being united with three species from tropical Africa (including the type) that share a distomedial process on the ultimate leg femur of males that is otherwise unknown in Otostigminae. Second maxillary characters previously used in the diagnosis of Digitipes are dismissed because Indian species do not possess the putatively diagnostic character states. Two new species from the Western Ghats that correspond to groupings identified based on monophyly, sequence divergence and coalescent analysis using molecular data are diagnosed based on distinct morphological characters. They are D. jangii and D. periyarensis n. spp. Three species named by Jangi and Dass (Digitipes barnabasi, D. coonoorensis and D. indicus) are revised based on new collections; D. indicus is a junior subjective synonym of Arthrorhabdus jonesii Verhoeff, 1938, the combination becoming Digitipes jonesii (Verhoeff, 1938) n. comb. The presence of Arthrorhabdus in India is accordingly refuted. Three putative species delimited by molecular and ecological data remain cryptic from the perspective of diagnostic morphological characters and are presently retained in D. barnabasi, D. jangii and D. jonesii. A molecularly-delimited species that resolved as sister group to a well-supported clade of Indian Digitipes is identified as Otostigmus ruficeps Pocock, 1890, originally described from a single specimen and revised herein. One Indian species originally assigned to Digitipes, D. gravelyi, deviates from confidently-assigned Digitipes with respect to several characters and is reassigned to Otostigmus, as O. gravelyi (Jangi and Dass, 1984) n. comb.

A h-Adaptive Algorithm Using Residual Error Estimates for Fluid Flows

Algorithms for adaptive mesh refinement using a residual error estimator are proposed for fluid flow problems in a finite volume framework. The residual error estimator, referred to as the R-parameter is used to derive refinement and coarsening criteria for the adaptive algorithms. An adaptive strategy based on the R-parameter is proposed for continuous flows, while a hybrid adaptive algorithm employing a combination of error indicators and the R-parameter is developed for discontinuous flows. Numerical experiments for inviscid and viscous flows on different grid topologies demonstrate the effectiveness of the proposed algorithms on arbitrary polygonal grids.

Accurate performance analysis of single and opportunistic AF relay cooperation with imperfect cascaded channel estimates

Given the significant gains that relay-based cooperation promises, the practical problems of acquisition of channel state information (CSI) and the characterization and optimization of performance with imperfect CSI are receiving increasing attention. We develop novel and accurate expressions for the symbol error probability (SEP) for fixed-gain amplify-and-forward relaying when the destination acquires CSI using the time-efficient cascaded channel estimation (CCE) protocol. The CCE protocol saves time by making the destination directly estimate the product of the source-relay and relay-destination channel gains. For a single relay system, we first develop a novel SEP expression and a tight SEP upper bound. We then similarly analyze an opportunistic multi-relay system, in which both selection and coherent demodulation use imperfect estimates. A distinctive aspect of our approach is the use of as few simplifying approximations as possible, which results in new results that are accurate at signal-to-noise-ratios as low as 1 dB for single and multi-relay systems. Using insights gleaned from an asymptotic analysis, we also present a simple, closed-form, nearly-optimal solution for allocation of energy between pilot and data symbols at the source and relay(s).

A relational contract for water demand management

For necessary goods like water, under supply constraints, fairness considerations lead to negative externalities. The objective of this paper is to design an infinite horizon contract or relational contract (a type of long-term contract) that ensures self-enforcing (instead of court-enforced) behaviour by the agents to mitigate the externality due to fairness issues. In this contract, the consumer is induced to consume at firm-supply level using the threat of higher fair price for future time periods. The pricing mechanism, computed in this paper, internalizes the externality and is shown to be economically efficient and provides revenue sufficiency.