A systems perspective of host-pathogen interactions: predicting disease outcome in tuberculosis

The complex web of interactions between the host immune system and the pathogen determines the outcome of any infection. A computational model of this interaction network, which encodes complex interplay among host and bacterial components, forms a useful basis for improving the understanding of pathogenesis, in filling knowledge gaps and consequently to identify strategies to counter the disease. We have built an extensive model of the Mycobacterium tuberculosis host-pathogen interactome, consisting of 75 nodes corresponding to host and pathogen molecules, cells, cellular states or processes. Vaccination effects, clearance efficiencies due to drugs and growth rates have also been encoded in the model. The system is modelled as a Boolean network. Virtual deletion experiments, multiple parameter scans and analysis of the system's response to perturbations, indicate that disabling processes such as phagocytosis and phagolysosome fusion or cytokines such as TNF-alpha and IFN-gamma, greatly impaired bacterial clearance, while removing cytokines such as IL-10 alongside bacterial defence proteins such as SapM greatly favour clearance. Simulations indicate a high propensity of the pathogen to persist under different conditions.

A systems perspective of host-pathogen interactions: predicting disease outcome in tuberculosis

The complex web of interactions between the host immune system and the pathogen determines the outcome of any infection. A computational model of this interaction network, which encodes complex interplay among host and bacterial components, forms a useful basis for improving the understanding of pathogenesis, in filling knowledge gaps and consequently to identify strategies to counter the disease. We have built an extensive model of the Mycobacterium tuberculosis host-pathogen interactome, consisting of 75 nodes corresponding to host and pathogen molecules, cells, cellular states or processes. Vaccination effects, clearance efficiencies due to drugs and growth rates have also been encoded in the model. The system is modelled as a Boolean network. Virtual deletion experiments, multiple parameter scans and analysis of the system's response to perturbations, indicate that disabling processes such as phagocytosis and phagolysosome fusion or cytokines such as TNF-alpha and IFN-gamma, greatly impaired bacterial clearance, while removing cytokines such as IL-10 alongside bacterial defence proteins such as SapM greatly favour clearance. Simulations indicate a high propensity of the pathogen to persist under different conditions.

Defining the pathway to insulin-like growth factor system targeting in cancer

The insulin-like growth factors (IGEs; IGF-1 and IGF-2) play central roles in cell growth, differentiation, survival, transformation and metastasis. The biologic effects of the IGFs are mediated by the IGF-1 receptor (IGF-1R), a receptor tyrosine kinase with homology to the insulin receptor (IR). Dysregulation of the ICE system is well recognized as a key contributor to the progression of multiple cancers, with IGF-1R activation increasing the tumorigenic potential of breast, prostate, lung, colon and head and neck squamous cell carcinoma (HNSCC). Despite this relationship, targeting the IGF-1R has only recently undergone development as a molecular cancer therapeutic. As it has taken hold, we are witnessing a robust increase and interest in targeting the inhibition of IGF-1R signaling. This is accentuated by the list of over 30 drugs, including monoclonal antibodies (mAbs) and tyrosine kinase inhibitors (TKIs) that are under evaluation as single agents or in combination therapies 1]. The ICE-binding proteins (IGFBPs) represent the third component of the ICE system consisting of a class of six soluble secretory proteins. They represent a unique class of naturally occurring ICE-antagonists that bind to and sequester IGF-1 and IGF-2, inhibiting their access to the IGF-1R. Due to their dual targeting of the IGFs without affecting insulin action, the IGFBPs are an untapped ``third'' class of IGF-1R inhibitors. in this commentary, we highlight some of the significant aspects of and prospects for targeting the IGF-1R and describe what the future may hold. (C) 2010 Elsevier Inc. All rights reserved.

The top 100 questions of importance to the future of global agriculture

Despite a significant growth in food production over the past half-century, one of the most important challenges facing society today is how to feed an expected population of some nine billion by the middle of the 20th century. To meet the expected demand for food without significant increases in prices, it has been estimated that we need to produce 70-100 per cent more food, in light of the growing impacts of climate change, concerns over energy security, regional dietary shifts and the Millennium Development target of halving world poverty and hunger by 2015. The goal for the agricultural sector is no longer simply to maximize productivity, but to optimize across a far more complex landscape of production, rural development, environmental, social justice and food consumption outcomes. However, there remain significant challenges to developing national and international policies that support the wide emergence of more sustainable forms of land use and efficient agricultural production. The lack of information flow between scientists, practitioners and policy makers is known to exacerbate the difficulties, despite increased emphasis upon evidence-based policy. In this paper, we seek to improve dialogue and understanding between agricultural research and policy by identifying the 100 most important questions for global agriculture. These have been compiled using a horizon-scanning approach with leading experts and representatives of major agricultural organizations worldwide. The aim is to use sound scientific evidence to inform decision making and guide policy makers in the future direction of agricultural research priorities and policy support. If addressed, we anticipate that these questions will have a significant impact on global agricultural practices worldwide, while improving the synergy between agricultural policy, practice and research. This research forms part of the UK Government's Foresight Global Food and Farming Futures project.

Electrochemical phase formation involving multicomponents: hemispherical overlap models for varied nucleation and growth conditions

The phenomenological theory of hemispherical growth in the context of phase formation with more than one component is presented. The model discusses in a unified manner both instantaneous and progressive nucleation (at the substrate) as well as arbitrary growth rates (e.g. constant and diffusion controlled growth rates). A generalized version of Avrami ansatz (a mean field description) is used to tackle the ''overlap'' aspects arising from the growing multicentres of the many components involved, observing that the nucleation is confined to the substrate plane only. The time evolution of the total extent of macrogrowth as well as those of the individual components are discussed explicitly for the case of two phases. The asymptotic expressions for macrogrowth are derived. Such analysis depicts a saturation limit (i.e. the maximum extent of growth possible) for the slower growing component and its dependence on the kinetic parameters which, in the electrochemical context, can be controlled through potential. The significance of this model in the context of multicomponent alloy deposition and possible future directions for further development are pointed out.

Evaluation of relative growth limitation due to depletion of glucose and oxygen during fungal growth on a spherical solid particle

A mathematical model for glucose and oxygen consumption, and cell growth during fungal growth on a single solid particle is developed. A moving biofilm is assumed to be present on the surface of the solid particle. Initially only glucose is assumed to be growth limiting and later oxygen transferred from the gas phase on to the biofilm is also assumed to be growth limiting. Glucose is found to be severely growth limiting when assumed to be the only growth limiting factor and its limiting levels far less severe when oxygen limitation is also included. The objective of the model is to gain a better understanding of the mass transfer and relative growth limiting characteristics of glucose and oxygen in fungal growth systems. The results obtained from the model proposed here will be the subject of future work.

Experimental investigation of link between growth and decay of fiber Bragg gratings

We report here an experimental investigation for establishing and quantifying a link between the growth and decay characteristics of fiber Bragg gratings. One of the key aspects of our work is the determination of the defect energy distribution from the grating characteristics measured during their fabrication. We observe a strong correlation between the growth-based defect energy distribution and that obtained through accelerated aging experiments, paving the way for predicting the decay characteristics of fiber Bragg gratings from their growth data. Such a prediction is significant in simplifying the postfabrication steps required to enhance the thermal stability of fiber Bragg gratings. (c) 2011 Optical Society of America

The Future of Product Development in India

A product is reflects the constraints, beliefs and aspirations of a society. Product development both influences and is influenced by the growth of a society and its economy. India is a fast growing economy. We use a brief historical, socioeconomic account of India as a backdrop to detect the drivers and roadblocks to its economic and social growth. In this context, current and future trends of PD practice, education and research are sketched. Products are taken as artefacts of the act of designing, without limiting to only those created by industry in a market-economic context.

Pattern-growth based frequent serial episode discovery

Frequent episode discovery is a popular framework for pattern discovery from sequential data. It has found many applications in domains like alarm management in telecommunication networks, fault analysis in the manufacturing plants, predicting user behavior in web click streams and so on. In this paper, we address the discovery of serial episodes. In the episodes context, there have been multiple ways to quantify the frequency of an episode. Most of the current algorithms for episode discovery under various frequencies are apriori-based level-wise methods. These methods essentially perform a breadth-first search of the pattern space. However currently there are no depth-first based methods of pattern discovery in the frequent episode framework under many of the frequency definitions. In this paper, we try to bridge this gap. We provide new depth-first based algorithms for serial episode discovery under non-overlapped and total frequencies. Under non-overlapped frequency, we present algorithms that can take care of span constraint and gap constraint on episode occurrences. Under total frequency we present an algorithm that can handle span constraint. We provide proofs of correctness for the proposed algorithms. We demonstrate the effectiveness of the proposed algorithms by extensive simulations. We also give detailed run-time comparisons with the existing apriori-based methods and illustrate scenarios under which the proposed pattern-growth algorithms perform better than their apriori counterparts. (C) 2013 Elsevier B.V. All rights reserved.

Forest observational studies in India: Past developments and considerations for the future

Long term forest research sites in India, going by different names including Linear Tree Increment Plots, Linear Increment Plots, Linear Sample Plots and Permanent Preservation Plots, cover diverse plant communities and environmental conditions. Presently, some of these long-term observational studies are functional, some are disturbed and others have almost been lost. The accumulated data will become increasingly important in the context of environmental modelling and climate change, especially if the plots and data can be maintained and/or revived. This contribution presents the history and current state of forest research plots in India, including details of locations and re-measurements. We provide a brief introduction of the National Forest Inventory (NFI), Preservation Plots in natural forests, the 50-ha Mudumalai Forest Dynamics Plot as part of the Centre for Tropical Forest Science and Smithsonian Institution Global Earth Observatories network (CTFS-SIGEO), and research plots established in plantations for tree growth studies and modelling. We also present some methodological details including assessment and analysis for two types of observational studies, the Tree Count Plots (TCP) and Tree Re-measurement Plots (TRP). Arguments are presented in favour of enumeration and analysis methods which are consistent with current approaches in forest ecological research. (c) 2013 Elsevier B.V. All rights reserved.

SPATIO-TEMPORAL DYNAMICS ALONG THE TERRAIN GRADIENT OF DIVERSE LANDSCAPE

Land use (LU) land cover (LC) information at a temporal scale illustrates the physical coverage of the Earth's terrestrial surface according to its use and provides the intricate information for effective planning and management activities. LULC changes are stated as local and location specific, collectively they act as drivers of global environmental changes. Understanding and predicting the impact of LULC change processes requires long term historical restorations and projecting into the future of land cover changes at regional to global scales. The present study aims at quantifying spatio temporal landscape dynamics along the gradient of varying terrains presented in the landscape by multi-data approach (MDA). MDA incorporates multi temporal satellite imagery with demographic data and other additional relevant data sets. The gradient covers three different types of topographic features, planes; hilly terrain and coastal region to account the significant role of elevation in land cover change. The seasonality is another aspect to be considered in the vegetation dominated landscapes; variations are accounted using multi seasonal data. Spatial patterns of the various patches are identified and analysed using landscape metrics to understand the forest fragmentation. The prediction of likely changes in 2020 through scenario analysis has been done to account for the changes, considering the present growth rates and due to the proposed developmental projects. This work summarizes recent estimates on changes in cropland, agricultural intensification, deforestation, pasture expansion, and urbanization as the causal factors for LULC change.

Two-step Synthesis of MoS2 Nanotubes using Shock Waves with Lead as Growth Promoter

A new two-step procedure for the synthesis of MoS2 nanotubes using lead as a growth promoter is reported. In the first step, molybdenum suboxide nanowhiskers containing a small amount of lead atoms were created by exposing a pressed MoS2+Pb mixture to highly compressed shock-heated argon gas, with estimated temperatures exceeding 9900 K. In the second step, these molybdenum suboxide nanowhiskers served as templates for the sulfidization of the oxide into MoS2 nanotubes (by using H2S gas in a reducing atmosphere at 820 degrees C). Unlike the case of WS2 nanotubes, the synthesis of a pure phase of MoS2 nanotubes from molybdenum oxide has proven challenging, due mostly to the volatile nature of the latter at the high requisite reaction temperatures (>800 degrees C). In contrast, the nature and apparent reaction mechanism of the method reported herein are amenable to future scale-up. The high-temperature shockwave system should also facilitate the synthesis of new nanostructures from other layered materials.

DTM AT 25: ESSAYS ON THEMES AND FUTURE DIRECTIONS

This paper describes the development and evolution of research themes in the Design Theory and Methodology (DTM) conference. Essays containing reflections on the history of DTM, supported by an analysis of session titles and papers winning the ``best paper award'', describe the development of the research themes. A second set of essays describes the evolution of several key research themes. Two broad trends in research themes are evident, with a third one emerging. The topics of the papers in the first decade or so reflect an underlying aim to apply artificial intelligence toward developing systems that could `design'. To do so required understanding how human designers behave, formalizing design processes so that they could be computed, and formalizing representations of design knowledge. The themes in the first DTM conference and the recollections of the DTM founders reflect this underlying aim. The second decade of DTM saw the emergence of product development as an underlying concern and included a growth in a systems view of design. More recently, there appears to be a trend toward design-led innovation, which entails both executing the design process more efficiently and understanding the characteristics of market-leading designs so as to produce engineered products and systems of exceptional levels of quality and customer satisfaction.