The nuclear pore complex and its transporters : from virus-host interactors to subverting the innate antiviral immunity

Les virus ont besoin d’interagir avec des facteurs cellulaires pour se répliquer et se propager dans les cellules d’hôtes. Une étude de l'interactome des protéines du virus d'hépatite C (VHC) par Germain et al. (2014) a permis d'élucider de nouvelles interactions virus-hôte. L'étude a également démontré que la majorité des facteurs de l'hôte n'avaient pas d'effet sur la réplication du virus. Ces travaux suggèrent que la majorité des protéines ont un rôle dans d'autres processus cellulaires tel que la réponse innée antivirale et ciblées pas le virus dans des mécanismes d'évasion immune. Pour tester cette hypothèse, 132 interactant virus-hôtes ont été sélectionnés et évalués par silençage génique dans un criblage d'ARNi sur la production interferon-beta (IFNB1). Nous avons ainsi observé que les réductions de l'expression de 53 interactants virus-hôte modulent la réponse antivirale innée. Une étude dans les termes de gène d'ontologie (GO) démontre un enrichissement de ces protéines au transport nucléocytoplasmique et au complexe du pore nucléaire. De plus, les gènes associés avec ces termes (CSE1L, KPNB1, RAN, TNPO1 et XPO1) ont été caractérisé comme des interactant de la protéine NS3/4A par Germain et al. (2014), et comme des régulateurs positives de la réponse innée antivirale. Comme le VHC se réplique dans le cytoplasme, nous proposons que ces interactions à des protéines associées avec le noyau confèrent un avantage de réplication et bénéficient au virus en interférant avec des processus cellulaire tel que la réponse innée. Cette réponse innée antivirale requiert la translocation nucléaire des facteurs transcriptionnelles IRF3 et NF-κB p65 pour la production des IFNs de type I. Un essai de microscopie a été développé afin d'évaluer l’effet du silençage de 60 gènes exprimant des protéines associés au complexe du pore nucléaire et au transport nucléocytoplasmique sur la translocation d’IRF3 et NF-κB p65 par un criblage ARNi lors d’une cinétique d'infection virale. En conclusion, l’étude démontre qu’il y a plusieurs protéines qui sont impliqués dans le transport de ces facteurs transcriptionnelles pendant une infection virale et peut affecter la production IFNB1 à différents niveaux de la réponse d'immunité antivirale. L'étude aussi suggère que l'effet de ces facteurs de transport sur la réponse innée est peut être un mécanisme d'évasion par des virus comme VHC.

Permutation Entropy Based Analysis of Complex Signals for Characterising Change in System Dynamics

Timely detection of sudden change in dynamics that adversely affect the performance of systems and quality of products has great scientific relevance. This work focuses on effective detection of dynamical changes of real time signals from mechanical as well as biological systems using a fast and robust technique of permutation entropy (PE). The results are used in detecting chatter onset in machine turning and identifying vocal disorders from speech signal.Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. Here we propose the use of permutation entropy (PE), to detect the dynamical changes in two non linear processes, turning under mechanical system and speech under biological system.Effectiveness of PE in detecting the change in dynamics in turning process from the time series generated with samples of audio and current signals is studied. Experiments are carried out on a lathe machine for sudden increase in depth of cut and continuous increase in depth of cut on mild steel work pieces keeping the speed and feed rate constant. The results are applied to detect chatter onset in machining. These results are verified using frequency spectra of the signals and the non linear measure, normalized coarse-grained information rate (NCIR).PE analysis is carried out to investigate the variation in surface texture caused by chatter on the machined work piece. Statistical parameter from the optical grey level intensity histogram of laser speckle pattern recorded using a charge coupled device (CCD) camera is used to generate the time series required for PE analysis. Standard optical roughness parameter is used to confirm the results.Application of PE in identifying the vocal disorders is studied from speech signal recorded using microphone. Here analysis is carried out using speech signals of subjects with different pathological conditions and normal subjects, and the results are used for identifying vocal disorders. Standard linear technique of FFT is used to substantiate thc results.The results of PE analysis in all three cases clearly indicate that this complexity measure is sensitive to change in regularity of a signal and hence can suitably be used for detection of dynamical changes in real world systems. This work establishes the application of the simple, inexpensive and fast algorithm of PE for the benefit of advanced manufacturing process as well as clinical diagnosis in vocal disorders.

Stochastic processes and their applications time dependent solutions for some queueing and inventory models

The objective of this thesis is to study the time dependent behaviour of some complex queueing and inventory models. It contains a detailed analysis of the basic stochastic processes underlying these models. In the theory of queues, analysis of time dependent behaviour is an area.very little developed compared to steady state theory. Tine dependence seems certainly worth studying from an application point of view but unfortunately, the analytic difficulties are considerable. Glosod form solutions are complicated even for such simple models as M/M /1. Outside M/>M/1, time dependent solutions have been found only in special cases and involve most often double transforms which provide very little insight into the behaviour of the queueing systems themselves. In inventory theory also There is not much results available giving the time dependent solution of the system size probabilities. Our emphasis is on explicit results free from all types of transforms and the method used may be of special interest to a wide variety of problems having regenerative structure.

Probability Theory. Stochastic Processes And Their Applications Probabilistic Analysis Of Some Queueing And Inventory Models

In this thesis we attempt to make a probabilistic analysis of some physically realizable, though complex, storage and queueing models. It is essentially a mathematical study of the stochastic processes underlying these models. Our aim is to have an improved understanding of the behaviour of such models, that may widen their applicability. Different inventory systems with randon1 lead times, vacation to the server, bulk demands, varying ordering levels, etc. are considered. Also we study some finite and infinite capacity queueing systems with bulk service and vacation to the server and obtain the transient solution in certain cases. Each chapter in the thesis is provided with self introduction and some important references

Designing in the real world is complex anyway - so what?

Designing is a heterogeneous, fuzzily defined, floating field of various activities and chunks of ideas and knowledge. Available theories about the foundations of designing as presented in "the basic PARADOX" (Jonas and Meyer-Veden 2004) have evoked the impression of Babylonian confusion. We located the reasons for this "mess" in the "non-fit", which is the problematic relation of theories and subject field. There seems to be a comparable interface problem in theory-building as in designing itself. "Complexity" sounds promising, but turns out to be a problematic and not really helpful concept. I will argue for a more precise application of systemic and evolutionary concepts instead, which - in my view - are able to model the underlying generative structures and processes that produce the visible phenomenon of complexity. It does not make sense to introduce a new fashionable meta-concept and to hope for a panacea before having clarified the more basic and still equally problematic older meta-concepts. This paper will take one step away from "theories of what" towards practice and doing and try to have a closer look at existing process models or "theories of how" to design instead. Doing this from a systemic perspective leads to an evolutionary view of the process, which finally allows to specify more clearly the "knowledge gaps" inherent in the design process. This aspect has to be taken into account as constitutive of any attempt at theory-building in design, which can be characterized as a "practice of not-knowing". I conclude, that comprehensive "unified" theories, or methods, or process models run aground on the identified knowledge gaps, which allow neither reliable models of the present, nor reliable projections into the future. Consolation may be found in performing a shift from the effort of adaptation towards strategies of exaptation, which means the development of stocks of alternatives for coping with unpredictable situations in the future.

Mapping and controlling molecular processes: The application of control theory and system identification algorithms to ASOPS and other fast pulse spectroscopies

Asynchronous Optical Sampling (ASOPS) [1,2] and frequency comb spectrometry [3] based on dual Ti:saphire resonators operated in a master/slave mode have the potential to improve signal to noise ratio in THz transient and IR sperctrometry. The multimode Brownian oscillator time-domain response function described by state-space models is a mathematically robust framework that can be used to describe the dispersive phenomena governed by Lorentzian, Debye and Drude responses. In addition, the optical properties of an arbitrary medium can be expressed as a linear combination of simple multimode Brownian oscillator functions. The suitability of a range of signal processing schemes adopted from the Systems Identification and Control Theory community for further processing the recorded THz transients in the time or frequency domain will be outlined [4,5]. Since a femtosecond duration pulse is capable of persistent excitation of the medium within which it propagates, such approach is perfectly justifiable. Several de-noising routines based on system identification will be shown. Furthermore, specifically developed apodization structures will be discussed. These are necessary because due to dispersion issues, the time-domain background and sample interferograms are non-symmetrical [6-8]. These procedures can lead to a more precise estimation of the complex insertion loss function. The algorithms are applicable to femtosecond spectroscopies across the EM spectrum. Finally, a methodology for femtosecond pulse shaping using genetic algorithms aiming to map and control molecular relaxation processes will be mentioned.

Genetic analysis of complex demographic scenarios: Spatially expanding populations of the cane toad, Bufo marinus

Inferring the spatial expansion dynamics of invading species from molecular data is notoriously difficult due to the complexity of the processes involved. For these demographic scenarios, genetic data obtained from highly variable markers may be profitably combined with specific sampling schemes and information from other sources using a Bayesian approach. The geographic range of the introduced toad Bufo marinus is still expanding in eastern and northern Australia, in each case from isolates established around 1960. A large amount of demographic and historical information is available on both expansion areas. In each area, samples were collected along a transect representing populations of different ages and genotyped at 10 microsatellite loci. Five demographic models of expansion, differing in the dispersal pattern for migrants and founders and in the number of founders, were considered. Because the demographic history is complex, we used an approximate Bayesian method, based on a rejection-regression algorithm. to formally test the relative likelihoods of the five models of expansion and to infer demographic parameters. A stepwise migration-foundation model with founder events was statistically better supported than other four models in both expansion areas. Posterior distributions supported different dynamics of expansion in the studied areas. Populations in the eastern expansion area have a lower stable effective population size and have been founded by a smaller number of individuals than those in the northern expansion area. Once demographically stabilized, populations exchange a substantial number of effective migrants per generation in both expansion areas, and such exchanges are larger in northern than in eastern Australia. The effective number of migrants appears to be considerably lower than that of founders in both expansion areas. We found our inferences to be relatively robust to various assumptions on marker. demographic, and historical features. The method presented here is the only robust, model-based method available so far, which allows inferring complex population dynamics over a short time scale. It also provides the basis for investigating the interplay between population dynamics, drift, and selection in invasive species.

Synthesis of hyperbranched poly(aryl ether)s via carbene insertion processes

Homopolymerization of alkylarylcarbenes derived from diazirine monomers that featured benzyl alcohol or phenol residues was found to lead to the production of soluble hyperbranched poly(aryl ether)s. The polymerization process was influenced by the solvents employed, monomer concentration, and the reaction time. An increase in the monomer concentration and reaction time was found to lead to an increase in the molecular weight characteristics of the resulting polymers as determined by gel permeation chromatography (GPC). The composition and architecture of the polyethers were determined by nuclear magnetic resonance (NMR) spectroscopic analysis and were found to be highly complex and dependent on the structure of the monomers used. All of the polymers were found to contain ether linkages formed via carbene insertion into O-H bonds, although polymers derived from phenolic carbenes also contained linkages arising from C-alkylation.

Quartz crystal microbalance monitoring of density changes in mesoporous TiO2 phytate films during redox and ion exchange processes

Nanofilm deposits of TiO2 nanoparticle phytates are formed on gold electrode surfaces by 'directed assembly' methods. Alternate exposure of a 3-mercapto-propionic acid modified gold surface to (i) a TiO2 sol and (ii) an aqueous phytic acid solution (pH 3) results in layer-by-layer formation of a mesoporous film. Ru(NH3)(6)(3+) is shown to strongly adsorb/accumulate into the mesoporous structure whilst remaining electrochemically active. Scanning the electrode potential into a sufficiently negative potential range allows the Ru(NH3)(6)(3+) complex to be reduced to Ru(NH3)(6)(2+) which undergoes immediate desorption. When applied to a gold coated quartz crystal microbalance (QCM) sensor, electrochemically driven adsorption and desorption processes in the mesoporous structure become directly detectable as a frequency response, which corresponds directly to a mass or density change in the membrane. The frequency response (at least for thin films) is proportional to the thickness of the mass-responsive film, which suggests good mechanical coupling between electrode and film. Based on this observation, a method for the amplified QCM detection of small mass/density changes is proposed by conducting measurements in rigid mesoporous structures. (C) 2003 Elsevier Science B.V. All rights reserved.

Modelling complex systems for project planning - A semiotics motivated method

A large and complex IT project may involve multiple organizations and be constrained within a temporal period. An organization is a system comprising of people, activities, processes, information, resources and goals. Understanding and modelling such a project and its interrelationship with relevant organizations are essential for organizational project planning. This paper introduces the problem articulation method (PAM) as a semiotic method for organizational infrastructure modelling. PAM offers a suite of techniques, which enables the articulation of the business, technical and organizational requirements, delivering an infrastructural framework to support the organization. It works by eliciting and formalizing (e. g. processes, activities, relationships, responsibilities, communications, resources, agents, dependencies and constraints) and mapping these abstractions to represent the manifestation of the "actual" organization. Many analysts forgo organizational modelling methods and use localized ad hoc and point solutions, but this is not amenable for organizational infrastructures modelling. A case study of the infrared atmospheric sounding interferometer (IASI) will be used to demonstrate the applicability of PAM, and to examine its relevancy and significance in dealing with the innovation and changes in the organizations.

Expert judgement in the processes of commercial property market forecasting

In this paper, we investigate the role of judgement in the formation of forecasts in commercial property markets. The investigation is based on interview surveys with the majority of UK forecast producers, who are using a range of inputs and data sets to form models to predict an array of variables for a range of locations. The findings suggest that forecasts need to be acceptable to their users (and purchasers) and consequently forecasters generally have incentives to avoid presenting contentious or conspicuous forecasts. Where extreme forecasts are generated by a model, forecasters often engage in ‘self‐censorship’ or are ‘censored’ following in‐house consultation. It is concluded that the forecasting process is significantly more complex than merely carrying out econometric modelling, forecasts are mediated and contested within organisations and that impacts can vary considerably across different organizational contexts.

Expert judgement in the processes of commercial property market forecasting

In this paper we investigate the role of judgement in the formation of forecasts in commercial real estate markets. Based on interview surveys with the majority of forecast producers, we find that real estate forecasters are using a range of inputs and data sets to form models to predict an array of variables for a range of locations. The findings suggest that forecasts need to be acceptable to their users (and purchasers) and consequently forecasters generally have incentives to avoid presenting contentious or conspicuous forecasts. Where extreme forecasts are generated by a model, forecasters often engage in ‘self-censorship’ or are ‘censored’ following in-house consultation. It is concluded that the forecasting process is more complex than merely carrying out econometric modelling and that the impact of the influences within this process vary considerably across different organizational contexts.

Using learning networks to understand complex systems: a case study of biological, geophysical and social research in the Amazon

Developing high-quality scientific research will be most effective if research communities with diverse skills and interests are able to share information and knowledge, are aware of the major challenges across disciplines, and can exploit economies of scale to provide robust answers and better inform policy. We evaluate opportunities and challenges facing the development of a more interactive research environment by developing an interdisciplinary synthesis of research on a single geographic region. We focus on the Amazon as it is of enormous regional and global environmental importance and faces a highly uncertain future. To take stock of existing knowledge and provide a framework for analysis we present a set of mini-reviews from fourteen different areas of research, encompassing taxonomy, biodiversity, biogeography, vegetation dynamics, landscape ecology, earth-atmosphere interactions, ecosystem processes, fire, deforestation dynamics, hydrology, hunting, conservation planning, livelihoods, and payments for ecosystem services. Each review highlights the current state of knowledge and identifies research priorities, including major challenges and opportunities. We show that while substantial progress is being made across many areas of scientific research, our understanding of specific issues is often dependent on knowledge from other disciplines. Accelerating the acquisition of reliable and contextualized knowledge about the fate of complex pristine and modified ecosystems is partly dependent on our ability to exploit economies of scale in shared resources and technical expertise, recognise and make explicit interconnections and feedbacks among sub-disciplines, increase the temporal and spatial scale of existing studies, and improve the dissemination of scientific findings to policy makers and society at large. Enhancing interaction among research efforts is vital if we are to make the most of limited funds and overcome the challenges posed by addressing large-scale interdisciplinary questions. Bringing together a diverse scientific community with a single geographic focus can help increase awareness of research questions both within and among disciplines, and reveal the opportunities that may exist for advancing acquisition of reliable knowledge. This approach could be useful for a variety of globally important scientific questions.

Multiscale evolving complex network model of functional connectivity in neuronal cultures

Cultures of cortical neurons grown on multielectrode arrays exhibit spontaneous, robust and recurrent patterns of highly synchronous activity called bursts. These bursts play a crucial role in the development and topological selforganization of neuronal networks. Thus, understanding the evolution of synchrony within these bursts could give insight into network growth and the functional processes involved in learning and memory. Functional connectivity networks can be constructed by observing patterns of synchrony that evolve during bursts. To capture this evolution, a modelling approach is adopted using a framework of emergent evolving complex networks and, through taking advantage of the multiple time scales of the system, aims to show the importance of sequential and ordered synchronization in network function.

The wind in the willows: flows in forest canopies in complex terrain

Forest canopies are important components of the terrestrial carbon budget, which has motivated a worldwide effort, FLUXNET, to measure CO2 exchange between forests and the atmosphere. These measurements are difficult to interpret and to scale up to estimate exchange across a landscape. Here we review the effects of complex terrain on the mean flow, turbulence, and scalar exchange in canopy flows, as exemplified by adjustment to forest edges and hills, including the effects of stable stratification. We focus on the fundamental fluid mechanics, in which developments in theory, measurements, and modeling, particularly through large-eddy simulation, are identifying important processes and providing scaling arguments. These developments set the stage for the development of predictive models that can be used in combination with measurements to estimate exchange at the landscape scale.