Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

Exceptional times for the dynamical discrete web

The dynamical discrete web (DyDW), introduced in the recent work of Howitt and Warren, is a system of coalescing simple symmetric one-dimensional random walks which evolve in an extra continuous dynamical time parameter tau. The evolution is by independent updating of the underlying Bernoulli variables indexed by discrete space-time that define the discrete web at any fixed tau. In this paper, we study the existence of exceptional (random) values of tau where the paths of the web do not behave like usual random walks and the Hausdorff dimension of the set of such exceptional tau. Our results are motivated by those about exceptional times for dynamical percolation in high dimension by Haggstrom, Peres and Steif, and in dimension two by Schramm and Steif. The exceptional behavior of the walks in the DyDW is rather different from the situation for the dynamical random walks of Benjamini, Haggstrom, Peres and Steif. For example, we prove that the walk from the origin S(0)(tau) violates the law of the iterated logarithm (LIL) on a set of tau of Hausdorff dimension one. We also discuss how these and other results should extend to the dynamical Brownian web, the natural scaling limit of the DyDW. (C) 2009 Elsevier B.V. All rights reserved.

Hitting and returning to rare events for all alpha-mixing processes

We prove that for any a-mixing stationary process the hitting time of any n-string A(n) converges, when suitably normalized, to an exponential law. We identify the normalization constant lambda(A(n)). A similar statement holds also for the return time. To establish this result we prove two other results of independent interest. First, we show a relation between the rescaled hitting time and the rescaled return time, generalizing a theorem of Haydn, Lacroix and Vaienti. Second, we show that for positive entropy systems, the probability of observing any n-string in n consecutive observations goes to zero as n goes to infinity. (c) 2010 Elsevier B.V. All rights reserved.

Molecular dynamics simulation of liquid trimethylphosphine

Structural and dynamical properties of liquid trimethylphosphine (TMP), (CH(3))(3)P, as a function of temperature is investigated by molecular dynamics (MD) simulations. The force field used in the MD simulations, which has been proposed from molecular mechanics and quantum chemistry calculations, is able to reproduce the experimental density of liquid TMP at room temperature. Equilibrium structure is investigated by the usual radial distribution function, g(r), and also in the reciprocal space by the static structure factor, S(k). On the basis of center of mass distances, liquid TMP behaves like a simple liquid of almost spherical particles, but orientational correlation due to dipole-dipole interactions is revealed at short-range distances. Single particle and collective dynamics are investigated by several time correlation functions. At high temperatures, diffusion and reorientation occur at the same time range as relaxation of the liquid structure. Decoupling of these dynamic properties starts below ca. 220 K, when rattling dynamics of a given TMP molecules due to the cage effect of neighbouring molecules becomes important. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3624408]

Simulation of sugarcane residue decomposition and aboveground growth

Due to the worldwide increase in demand for biofuels, the area cultivated with sugarcane is expected to increase. For environmental and economic reasons, an increasing proportion of the areas are being harvested without burning, leaving the residues on the soil surface. This periodical input of residues affects soil physical, chemical and biological properties, as well as plant growth and nutrition. Modeling can be a useful tool in the study of the complex interactions between the climate, residue quality, and the biological factors controlling plant growth and residue decomposition. The approach taken in this work was to parameterize the CENTURY model for the sugarcane crop, to simulate the temporal dynamics of aboveground phytomass and litter decomposition, and to validate the model through field experiment data. When studying aboveground growth, burned and unburned harvest systems were compared, as well as the effect of mineral fertilizer and organic residue applications. The simulations were performed with data from experiments with different durations, from 12 months to 60 years, in Goiana, TimbaA(0)ba and Pradpolis, Brazil; Harwood, Mackay and Tully, Australia; and Mount Edgecombe, South Africa. The differentiation of two pools in the litter, with different decomposition rates, was found to be a relevant factor in the simulations made. Originally, the model had a basically unlimited layer of mulch directly available for decomposition, 5,000 g m(-2). Through a parameter optimization process, the thickness of the mulch layer closer to the soil, more vulnerable to decomposition, was set as 110 g m(-2). By changing the layer of mulch at any given time available for decomposition, the sugarcane residues decomposition simulations where close to measured values (R (2) = 0.93), contributing to making the CENTURY model a tool for the study of sugarcane litter decomposition patterns. The CENTURY model accurately simulated aboveground carbon stalk values (R (2) = 0.76), considering burned and unburned harvest systems, plots with and without nitrogen fertilizer and organic amendment applications, in different climates and soil conditions.

Simulation of Soil Carbon Dynamics under Sugarcane with the CENTURY Model

Currently there is a trend for the expansion of the area cropped with sugarcane (Saccharum officinarum L.), driven by an increase in the world demand for biofuels, due to economical, environmental, and geopolitical issues. Although sugarcane is traditionally harvested by burning dried leaves and tops, the unburned, mechanized harvest has been progressively adopted. The use of process based models is useful in understanding the effects of plant litter in soil C dynamics. The objective of this work was to use the CENTURY model in evaluating the effect of sugarcane residue management in the temporal dynamics of soil C. The approach taken in this work was to parameterize the CENTURY model for the sugarcane crop, to simulate the temporal dynamics of soil C, validating the model through field experiment data, and finally to make predictions in the long term regarding soil C. The main focus of this work was the comparison of soil C stocks between the burned and unburned litter management systems, but the effect of mineral fertilizer and organic residue applications were also evaluated. The simulations were performed with data from experiments with different durations, from 1 to 60 yr, in Goiana and Timbauba, Pernambuco, and Pradopolis, Sao Paulo, all in Brazil; and Mount Edgecombe, Kwazulu-Natal, South Africa. It was possible to simulate the temporal dynamics of soil C (R(2) = 0.89). The predictions made with the model revealed that there is, in the long term, a trend for higher soil C stocks with the unburned management. This increase is conditioned by factors such as climate, soil texture, time of adoption of the unburned system, and N fertilizer management.

Continuous opinions and discrete actions in opinion dynamics problems

A model where agents show discrete behavior regarding their actions, but have continuous opinions that are updated by interacting with other agents is presented. This new updating rule is applied to both the voter and Sznajd models for interaction between neighbors, and its consequences are discussed. The appearance of extremists is naturally observed and it seems to be a characteristic of this model.

Brazilian registered nurses` perceptions and attitudes towards adverse events in nursing care: a phenomenological study

Aim To describe the perceptions and attitudes of registered nurses (RNs) towards adverse events (AEs) in nursing care. Background The professionals` subjective perspectives should be taken into account for the prevention of AEs in care settings. Method Schutz`s social phenomenology was developed. Interviews were conducted with nine Intensive Care Unit RNs. Results The following five descriptive categories emerged: (1) the occurrence of AEs is inherent to the human condition but provokes a feeling of insecurity, (2) the occurrence of AEs indicates the existence of failures in health care systematization, (3) the professionals` attitudes towards AEs should be permeated by ethical principles; (4) the priority regarding AEs should be the mitigation of harm to patients, and (5) decisions regarding the communication of AEs were determined by the severity of the error. Conclusions The various subjective perspectives related to the occurrence of AEs requires a health care systematization with a focus on prevention. Ethical behaviour is essential for the patients` safety. Implications for nursing management Activities aimed at the prevention of AEs should be integrated jointly with both the professionals and the health care institution. A culture of safety, not punishment, and improvement in the quality of care provided to patients should be priorities.

Energy systems contributions in 2,000 m race simulation: a comparison among rowing ergometers and water

This study investigated the energy system contributions of rowers in three different conditions: rowing on an ergometer without and with the slide and rowing in the water. For this purpose, eight rowers were submitted to 2,000 m race simulations in each of the situations defined above. The fractions of the aerobic (W(AER)), anaerobic alactic (W(PCR)) and anaerobic lactic (W([La-])) systems were calculated based on the oxygen uptake, the fast component of excess post-exercise oxygen uptake and changes in net blood lactate, respectively. In the water, the metabolic work was significantly higher [(851 (82) kJ] than during both ergometer [674 (60) kJ] and ergometer with slide [663 (65) kJ] (P <= 0.05). The time in the water [515 (11) s] was higher (P < 0.001) than in the ergometers with [398 (10) s] and without the slide [402 (15) s], resulting in no difference when relative energy expenditure was considered: in the water [99 (9) kJ min(-1)], ergometer without the slide [99.6 (9) kJ min(-1)] and ergometer with the slide [100.2 (9.6) kJ min(-1)]. The respective contributions of the WAER, WPCR and W[La-] systems were water = 87 (2), 7 (2) and 6 (2)%, ergometer = 84 (2), 7 (2) and 9 (2)%, and ergometer with the slide = 84 (2), 7 (2) and 9 (1)%. (V) over dotO(2), HR and lactate were not different among conditions. These results seem to indicate that the ergometer braking system simulates conditions of a bigger and faster boat and not a single scull. Probably, a 2,500 m test should be used to properly simulate in the water single-scull race.

Adverse drug events in an intensive care unit of a university hospital

Purpose Adverse drug events (ADEs) are harmful and occur with alarming frequency in critically ill patients. Complex pharmacotherapy with multiple medications increases the probability of a drug interaction (DI) and ADEs in patients in intensive care units (ICUs). The objective of the study is to determine the frequency of ADEs among patients in the ICU of a university hospital and the drugs implicated. Also, factors associated with ADEs are investigated. Methods This cross-sectional study investigated 299 medical records of patients hospitalized for 5 or more days in an ICU. ADEs were identified through intensive monitoring adopted in hospital pharmacovigilance and also ADE triggers. Adverse drug reactions (ADR) causality was classified using the Naranjo algorithm. Data were analyzed through descriptive analysis, and through univariate and multiple logistic regression. Results The most frequent ADEs were ADRs type A, of possible causality and moderate severity. The most frequent ADR was drug-induced acute kidney injury. Patients with ADEs related to DIs corresponded to 7% of the sample. The multiple logistic regression showed that length of hospitalization (OR = 1.06) and administration of cardiovascular drugs (OR = 2.2) were associated with the occurrence of ADEs. Conclusion Adverse drug reactions of clinical significance were the most frequent ADEs in the ICU studied, which reduces patient safety. The number of ADEs related to drug interactions was small, suggesting that clinical manifestations of drug interactions that harm patients are not frequent in ICUs.

H(infinity) filtering for rectangular discrete-time descriptor systems

This paper deals with the H(infinity) recursive estimation problem for general rectangular time-variant descriptor systems in discrete time. Riccati-equation based recursions for filtered and predicted estimates are developed based on a data fitting approach and game theory. In this approach, the nature determines a state sequence seeking to maximize the estimation cost, whereas the estimator tries to find an estimate that brings the estimation cost to a minimum. A solution exists for a specified gamma-level if the resulting cost is positive. In order to present some computational alternatives to the H(infinity) filters developed, they are rewritten in information form along with the respective array algorithms. (C) 2009 Elsevier Ltd. All rights reserved.

Cluster identification and characterization in the riser of a circulating fluidized bed from numerical simulation results

A methodology of identification and characterization of coherent structures mostly known as clusters is applied to hydrodynamic results of numerical simulation generated for the riser of a circulating fluidized bed. The numerical simulation is performed using the MICEFLOW code, which includes the two-fluids IIT`s hydrodynamic model B. The methodology for cluster characterization that is used is based in the determination of four characteristics, related to average life time, average volumetric fraction of solid, existing time fraction and frequency of occurrence. The identification of clusters is performed by applying a criterion related to the time average value of the volumetric solid fraction. A qualitative rather than quantitative analysis is performed mainly owing to the unavailability of operational data used in the considered experiments. Concerning qualitative analysis, the simulation results are in good agreement with literature. Some quantitative comparisons between predictions and experiment were also presented to emphasize the capability of the modeling procedure regarding the analysis of macroscopic scale coherent structures. (c) 2007 Elsevier Inc. All rights reserved.

Coloured Petri nets and graphical simulation for the validation of a robotic cell in aircraft industry

This paper proposes a mixed validation approach based on coloured Petri nets and 3D graphic simulation for the design of supervisory systems in manufacturing cells with multiple robots. The coloured Petri net is used to model the cell behaviour at a high level of abstraction. It models the activities of each cell component and its coordination by a supervisory system. The graphical simulation is used to analyse and validate the cell behaviour in a 3D environment, allowing the detection of collisions and the calculation of process times. The motivation for this work comes from the aeronautic industry. The automation of a fuselage assembly process requires the integration of robots with other cell components such as metrological or vision systems. In this cell, the robot trajectories are defined by the supervisory system and results from the coordination of the cell components. The paper presents the application of the approach for an aircraft assembly cell under integration in Brazil. This case study shows the feasibility of the approach and supports the discussion of its main advantages and limits. (C) 2011 Elsevier Ltd. All rights reserved.

Recursive linear estimation for general discrete-time descriptor systems

This paper considers the optimal linear estimates recursion problem for discrete-time linear systems in its more general formulation. The system is allowed to be in descriptor form, rectangular, time-variant, and with the dynamical and measurement noises correlated. We propose a new expression for the filter recursive equations which presents an interesting simple and symmetric structure. Convergence of the associated Riccati recursion and stability properties of the steady-state filter are provided. (C) 2010 Elsevier Ltd. All rights reserved.

Information Filtering and Array Algorithms for Discrete-Time Markovian Jump Linear Systems

This technical note develops information filter and array algorithms for a linear minimum mean square error estimator of discrete-time Markovian jump linear systems. A numerical example for a two-mode Markovian jump linear system, to show the advantage of using array algorithms to filter this class of systems, is provided.