Salmonella enterica serovars Typhimurium and Typhi as model organisms Revealing paradigm of host-pathogen interactions

The lifestyle of intracellular pathogens has always questioned the skill of a microbiologist in the context of finding the permanent cure to the diseases caused by them. The best tool utilized by these pathogens is their ability to reside inside the host cell, which enables them to easily bypass the humoral immunity of the host, such as the complement system. They further escape from the intracellular immunity, such as lysosome and inflammasome, mostly by forming a protective vacuole-bound niche derived from the host itself. Some of the most dreadful diseases are caused by these vacuolar pathogens, for example, tuberculosis by Mycobacterium or typhoid fever by Salmonella. To deal with such successful pathogens therapeutically, the knowledge of a host-pathogen interaction system becomes primarily essential, which further depends on the use of a model system. A well characterized pathogen, namely Salmonella, suits the role of a model for this purpose, which can infect a wide array of hosts causing a variety of diseases. This review focuses on various such aspects of research on Salmonella which are useful for studying the pathogenesis of other intracellular pathogens.

Phospholipid Mediated Activation of Calcium Dependent Protein Kinase 1 (CaCDPK1) from Chickpea: A New Paradigm of Regulation

Phospholipids, the major structural components of membranes, can also have functions in regulating signaling pathways in plants under biotic and abiotic stress. The effects of adding phospholipids on the activity of stress-induced calcium dependent protein kinase (CaCDPK1) from chickpea are reported here. Both autophosphorylation as well as phosphorylation of the added substrate were enhanced specifically by phosphatidylcholine and to a lesser extent by phosphatidic acid, but not by phosphatidylethanolamine. Diacylgylerol, the neutral lipid known to activate mammalian PKC, stimulated CaCDPK1 but at higher concentrations. Increase in V-max of the enzyme activity by these phospholipids significantly decreased the K-m indicating that phospholipids enhance the affinity towards its substrate. In the absence of calcium, addition of phospholipids had no effect on the negligible activity of the enzyme. Intrinsic fluorescence intensity of the CaCDPK1 protein was quenched on adding PA and PC. Higher binding affinity was found with PC (K-1/2 = 114 nM) compared to PA (K-1/2 = 335 nM). We also found that the concentration of PA increased in chickpea plants under salt stress. The stimulation by PA and PC suggests regulation of CaCDPK1 by these phospholipids during stress response.

Robustness of early warning signals of regime shifts in time-delayed ecological models

Various ecological and other complex dynamical systems may exhibit abrupt regime shifts or critical transitions, wherein they reorganize from one stable state to another over relatively short time scales. Because of potential losses to ecosystem services, forecasting such unexpected shifts would be valuable. Using mathematical models of regime shifts, ecologists have proposed various early warning signals of imminent shifts. However, their generality and applicability to real ecosystems remain unclear because these mathematical models are considered too simplistic. Here, we investigate the robustness of recently proposed early warning signals of regime shifts in two well-studied ecological models, but with the inclusion of time-delayed processes. We find that the average variance may either increase or decrease prior to a regime shift and, thus, may not be a robust leading indicator in time-delayed ecological systems. In contrast, changing average skewness, increasing autocorrelation at short time lags, and reddening power spectra of time series of the ecological state variable all show trends consistent with those of models with no time delays. Our results provide insights into the robustness of early warning signals of regime shifts in a broader class of ecological systems.

Moore meets maxwell

Moore's Law has driven the semiconductor revolution enabling over four decades of scaling in frequency, size, complexity, and power. However, the limits of physics are preventing further scaling of speed, forcing a paradigm shift towards multicore computing and parallelization. In effect, the system is taking over the role that the single CPU was playing: high-speed signals running through chips but also packages and boards connect ever more complex systems. High-speed signals making their way through the entire system cause new challenges in the design of computing hardware. Inductance, phase shifts and velocity of light effects, material resonances, and wave behavior become not only prevalent but need to be calculated accurately and rapidly to enable short design cycle times. In essence, to continue scaling with Moore's Law requires the incorporation of Maxwell's equations in the design process. Incorporating Maxwell's equations into the design flow is only possible through the combined power that new algorithms, parallelization and high-speed computing provide. At the same time, incorporation of Maxwell-based models into circuit and system-level simulation presents a massive accuracy, passivity, and scalability challenge. In this tutorial, we navigate through the often confusing terminology and concepts behind field solvers, show how advances in field solvers enable integration into EDA flows, present novel methods for model generation and passivity assurance in large systems, and demonstrate the power of cloud computing in enabling the next generation of scalable Maxwell solvers and the next generation of Moore's Law scaling of systems. We intend to show the truly symbiotic growing relationship between Maxwell and Moore!

Optimal control of grinding mill circuit using model predictive static programming: A new nonlinear MPC paradigm

The recently developed reference-command tracking version of model predictive static programming (MPSP) is successfully applied to a single-stage closed grinding mill circuit. MPSP is an innovative optimal control technique that combines the philosophies of model predictive control (MPC) and approximate dynamic programming. The performance of the proposed MPSP control technique, which can be viewed as a `new paradigm' under the nonlinear MPC philosophy, is compared to the performance of a standard nonlinear MPC technique applied to the same plant for the same conditions. Results show that the MPSP control technique is more than capable of tracking the desired set-point in the presence of model-plant mismatch, disturbances and measurement noise. The performance of MPSP and nonlinear MPC compare very well, with definite advantages offered by MPSP. The computational speed of MPSP is increased through a sequence of innovations such as the conversion of the dynamic optimization problem to a low-dimensional static optimization problem, the recursive computation of sensitivity matrices and using a closed form expression to update the control. To alleviate the burden on the optimization procedure in standard MPC, the control horizon is normally restricted. However, in the MPSP technique the control horizon is extended to the prediction horizon with a minor increase in the computational time. Furthermore, the MPSP technique generally takes only a couple of iterations to converge, even when input constraints are applied. Therefore, MPSP can be regarded as a potential candidate for online applications of the nonlinear MPC philosophy to real-world industrial process plants. (C) 2014 Elsevier Ltd. All rights reserved.

Combination of Cyanine Behaviour and Giant Hyperpolarisability in Novel Merocyanine Dyes: Beyond the Bond Length Alternation (BLA) Paradigm

Merocyanine dyes that exhibit antithetic cyaninelike behaviour and giant first-order hyperpolarisability (beta) values have been designed. These cyanine-type dyes open up an intriguing route towards molecular-based electrooptic materials as well as new second-harmonic generation dyes for imaging.

Ab Initio MD Simulations of the Bronsted Acidity of Glutathione in Aqueous Solutions: Predicting pK(a) Shifts of the Cysteine Residue

The tripeptide glutathione (GSH) is one of the most abundant peptides and the major repository for nonprotein sulfur in both animal and plant cells. It plays a critical role in intracellular oxidative stress management by the reversible formation of glutathione disulfide with the thiol-disulfide pair acting as a redox buffer. The state of charge of the ionizable groups of GSH can influence the redox couple, and hence the pK(a) value of the cysteine residue of GSH is critical to its functioning. Here we report ab initio Car-Parrinello molecular dynamics simulations of glutathione solvated by 200 water molecules, all of which are considered in the simulation. We show that the free-energy landscape for the protonation-deprotonation reaction of the cysteine residue of GSH computed using metadynamics sampling provides shift in the dissociation constant values as compared with the isolated accurate estimates of the pK(a) and correctly predicts the cysteine amino acid.

Chemical Shifts to Metabolic Pathways: Identifying Metabolic Pathways Directly from a Single 2D NMR Spectrum

Identifying cellular processes in terms of metabolic pathways is one of the avowed goals of metabolomics studies. Currently, this is done after relevant metabolites are identified to allow their mapping onto specific pathways. This task is daunting due to the complex nature of cellular processes and the difficulty in establishing the identity of individual metabolites. We propose here a new method: ChemSMP (Chemical Shifts to Metabolic Pathways), which facilitates rapid analysis by identifying the active metabolic pathways directly from chemical shifts obtained from a single two-dimensional (2D) C-13-H-1] correlation NMR spectrum without the need for identification and assignment of individual metabolites. ChemSMP uses a novel indexing and scoring system comprised of a ``uniqueness score'' and a ``coverage score''. Our method is demonstrated on metabolic pathways data from the Small Molecule Pathway Database (SMPDB) and chemical shifts from the Human Metabolome Database (HMDB). Benchmarks show that ChemSMP has a positive prediction rate of >90% in the presence of deduttered data and can sustain the same at 60-70% even in the presence of noise, such as deletions of peaks and chemical shift deviations. The method tested on NMR data acquired for a mixture of 20 amino acids shows a success rate of 93% in correct recovery of pathways. When used on data obtained from the cell lysate of an unexplored oncogenic cell line, it revealed active metabolic pathways responsible for regulating energy homeostasis of cancer cells. Our unique tool is thus expected to significantly enhance analysis of NMIR-based metabolomics data by reducing existing impediments.

Enhancing parametric sensitivity using mode localization in electrically coupled mems resonators

We use vibration localization as a sensitive means of detecting small perturbations in stiffness in a pair of weakly coupled micromechanical resonators. For the first time, the variation in the eigenstates is studied by electrostatically coupling nearly identical resonators to allow for stronger localization of vibrational energy due to perturbations in stiffness. Eigenstate variations that are orders of magnitude greater than corresponding shifts in resonant frequency for an induced stiffness perturbation are experimentally demonstrated. Such high, voltagetunable parametric sensitivities together with the added advantage of intrinsic common mode rejection pave the way to a new paradigm of mechanical sensing. ©2009 IEEE.

Report of the Study Group on “ Fisheries and Ecosystem Response to Recent Regime Shifts”

EXECUTIVE SUMMARY 1. DECADAL-SCALE CLIMATE EVENTS 1.1 Introduction 1.2 Basin-scale Patterns 1.3 Long Time Series in the North Pacific 1.4 Decadal Climate Variability in Ecological Regions of the North Pacific 1.5 Mechanisms 1.6 References 2. COHERENT REGIONAL RESPONSES 2.1 Introduction 2.2 Central North Pacific (CNP) 2.3 California Current System (CCS) 2.4 Gulf of Alaska (GOA) 2.5 Bering Sea and Aleutian Islands 2.6 Western North Pacific (WNP) 2.7 Coherence in Regional Responses to the 1998 Regime Shift 2.8 Climate Indicators for Detecting Regime Shifts 2.9 References 3. IMPLICATIONS FOR THE MANAGEMENT OF MARINE RESOURCES 3.1 Introduction 3.2 Response Time of Biota to Regime Shifts 3.3 Response Time of Management to Regime Shifts 3.4 Provision of Stock Assessment Advice 3.5 Decision Rules 3.6 References 4. SUGGESTED LITERATURE 4.1 Climate Regimes 4.2 Impacts on Lower Trophic Levels 4.3 Impacts on Fish and Higher Trophic Levels 4.4 Impacts on Ecosystems and Possible Mechanisms 4.5 Regimes and Fisheries Management APPENDIX 1: RECENT ECOSYSTEM CHANGES IN THE CENTRAL NORTH PACIFIC A1.1 Introduction A1.2 Physical Oceanography A1.3 Lower Trophic Levels A1.4 Invertebrates A1.5 Fishes A1.6 References APPENDIX 2: RECENT ECOSYSTEM CHANGES IN THE CALIFORNIA CURRENT SYSTEM A2.1 Introduction A2.2 Physical Oceanography A2.3 Lower Trophic Levels A2.4 Invertebrates A2.5 Fishes A2.6 References APPENDIX 3: RECENT ECOSYSTEM CHANGES IN THE GULF OF ALASKA A3.1 Introduction A3.2 Physical Oceanography A3.3 Lower Trophic Levels A3.4 Invertebrates A3.5 Fishes A3.6 Higher Trophic Levels A3.7 Coherence in Gulf of Alaska Fish A3.8 Combined Standardized Indices of Recruitment and Survival Rate A3.9 References APPENDIX 4: RECENT ECOSYSTEM CHANGES IN THE BERING SEA AND ALEUTIAN ISLANDS A4.1 Introduction A4.2 Bering Sea Environmental Variables and Physical Oceanography A4.3 Bering Sea Lower Trophic Levels A4.4 Bering Sea Invertebrates A4.5 Bering Sea Fishes A4.6 Bering Sea Higher Trophic Levels A4.7 Coherence in Bering Sea Fish Responses A4.8 Combined Standardized Indices of Bering Fish Recruitment and Survival Rate A4.9 Aleutian Islands A4.10 References APPENDIX 5: RECENT ECOSYSTEM CHANGES IN THE WESTERN NORTH PACIFIC A5.1 Introduction A5.2 Sea of Okhotsk A5.3 Tsushima Current Region and Kuroshio/Oyashio Current Region A5.4 Bohai Sea, Yellow Sea, and East China Sea A5.5 References (168 page document)

A reflection on the future of the quality management paradigm in the EU

In recent years, the Quality Management Paradigm has successfully taken root in the European Union’s business environment. Quality management besides being a multivariate issue including matters from management and economics till engineering may be called a global knowledge in permanent bubbling. This theoretical article is an eclectic effort to analyse the evolution of the Quality Management Paradigm. More specifically, the article deals with this management Paradigm evolution and change according to the present and future expected business environments.

From transistor to trapped-ion computers for quantum chemistry

Over the last few decades, quantum chemistry has progressed through the development of computational methods based on modern digital computers. However, these methods can hardly fulfill the exponentially-growing resource requirements when applied to large quantum systems. As pointed out by Feynman, this restriction is intrinsic to all computational models based on classical physics. Recently, the rapid advancement of trapped-ion technologies has opened new possibilities for quantum control and quantum simulations. Here, we present an efficient toolkit that exploits both the internal and motional degrees of freedom of trapped ions for solving problems in quantum chemistry, including molecular electronic structure, molecular dynamics, and vibronic coupling. We focus on applications that go beyond the capacity of classical computers, but may be realizable on state-of-the-art trapped-ion systems. These results allow us to envision a new paradigm of quantum chemistry that shifts from the current transistor to a near-future trapped-ion-based technology.

Using the system dynamics paradigm in teaching and learning technological university subjets

2nd International Conference on Education and New Learning Technologies

The biological sense of smell: olfactory search behavior and a metabolic view for olfactory perception

Part I of the thesis describes the olfactory searching and scanning behaviors of rats in a wind tunnel, and a detailed movement analysis of terrestrial arthropod olfactory scanning behavior. Olfactory scanning behaviors in rats may be a behavioral correlate to hippocampal place cell activity.

Part II focuses on the organization of olfactory perception, what it suggests about a natural order for chemicals in the environment, and what this in tum suggests about the organization of the olfactory system. A model of odor quality space (analogous to the "color wheel") is presented. This model defines relationships between odor qualities perceived by human subjects based on a quantitative similarity measure. Compounds containing Carbon, Nitrogen, or Sulfur elicit odors that are contiguous in this odor representation, which thus allows one to predict the broad class of odor qualities a compound is likely to elicit. Based on these findings, a natural organization for olfactory stimuli is hypothesized: the order provided by the metabolic process. This hypothesis is tested by comparing compounds that are structurally similar, perceptually similar, and metabolically similar in a psychophysical cross-adaptation paradigm. Metabolically similar compounds consistently evoked shifts in odor quality and intensity under cross-adaptation, while compounds that were structurally similar or perceptually similar did not. This suggests that the olfactory system may process metabolically similar compounds using the same neural pathways, and that metabolic similarity may be the fundamental metric about which olfactory processing is organized. In other words, the olfactory system may be organized around a biological basis.

The idea of a biological basis for olfactory perception represents a shift in how olfaction is understood. The biological view has predictive power while the current chemical view does not, and the biological view provides explanations for some of the most basic questions in olfaction, that are unanswered in the chemical view. Existing data do not disprove a biological view, and are consistent with basic hypotheses that arise from this viewpoint.