Ataxia-telangiectasia-mutated (ATM) and NBS1-dependent phosphorylation of Chk1 on Ser-317 in response to ionizing radiation

In mammals, the ATM (ataxia-telangiectasia-mutated) and ATR (ATM and Rad3-related) protein kinases function as critical regulators of the cellular DNA damage response. The checkpoint functions of ATR and ATM are mediated, in part, by a pair of checkpoint effector kinases termed Chk1 and Chk2. In mammalian cells, evidence has been presented that Chk1 is devoted to the ATR signaling pathway and is modified by ATR in response to replication inhibition and UV-induced damage, whereas Chk2 functions primarily through ATM in response to ionizing radiation (IR), suggesting that Chk2 and Chk1 might have evolved to channel the DNA damage signal from ATM and ATR, respectively. We demonstrate here that the ATR-Chk1 and ATM-Chk2 pathways are not parallel branches of the DNA damage response pathway but instead show a high degree of cross-talk and connectivity. ATM does in fact signal to Chk1 in response to IR. Phosphorylation of Chk1 on Ser-317 in response to IR is ATM-dependent. We also show that functional NBS1 is required for phosphorylation of Chk1, indicating that NES1 might facilitate the access of Chk1 to ATM at the sites of DNA damage. Abrogation of Chk1 expression by RNA interference resulted in defects in IR-induced S and G2/M phase checkpoints; however, the overexpression of phosphorylation site mutant (S317A, S345A or S317A/S345A double mutant) Chk1 failed to interfere with these checkpoints. Surprisingly, the kinase-dead Chk1 (D130A) also failed to abrogate the S and G2 checkpoint through any obvious dominant negative effect toward endogenous Chk1. Therefore, further studies will be required to assess the contribution made by phosphorylation events to Chk1 regulation. Overall, the data presented in the study challenge the model in which Chk1 only functions downstream from ATR and indicate that ATM does signal to Chk1. In addition, this study also demonstrates that Chk1 is essential for IR-induced inhibition of DNA synthesis and the G2/M checkpoint.

Antibody-dependent enhancement of Murray Valley encephalitis virus virulence in mice

Enhancement of flavivirus infection in vitro in the presence of subneutralizing concentrations of homologous or heterologous antiserum has been well described. However, the importance of this phenomenon in the enhancement of flavivirus infection in vivo has not been established. In order to study antibody- mediated enhancement of flavivirus infection in vivo, we investigated the effect of passive immunization of mice with Japanese encephalitis virus (JE) antiserum on the outcome of infection with Murray Valley encephalitis virus (MVE). We show that prior treatment of mice with subneutralizing concentrations of heterologous JE antiserum resulted in an increase in viraemia titres and in mortality following challenge with wild-type MVE. Our findings support the hypothesis that subneutralizing concentrations of antibody may enhance flavivirus infection and virulence in vivo. These findings are of potential importance for the design of JE vaccination programs in geographic areas in which MVE co-circulates. Should subneutralizing concentrations of antibody remain in the population following JE vaccination, it is possible that enhanced disease may be observed during MVE epidemics.

Acute lead-induced vasoconstriction in the vascular beds of isolated perfused rat tails is endothelium-dependent

Chronic lead exposure induces hypertension in humans and animals, affecting endothelial function. However, studies concerning acute cardiovascular effects are lacking. We investigated the effects of acute administration of a high concentration of lead acetate (100 µΜ) on the pressor response to phenylephrine (PHE) in the tail vascular bed of male Wistar rats. Animals were anesthetized with sodium pentobarbital and heparinized. The tail artery was dissected and cannulated for drug infusion and mean perfusion pressure measurements. Endothelium and vascular smooth muscle relaxation were tested with acetylcholine (5 µg/100 µL) and sodium nitroprusside (0.1 µg/100 µL), respectively, in arteries precontracted with 0.1 µM PHE. Concentration-response curves to PHE (0.001-300 µg/100 µL) were constructed before and after perfusion for 1 h with 100 µΜ lead acetate. In the presence of endothelium (E+), lead acetate increased maximal response (Emax) (control: 364.4 ± 36, Pb2+: 480.0 ± 27 mmHg; P < 0.05) and the sensitivity (pD2; control: 1.98 ± 0.07, 2.38 ± 0.14 log mM) to PHE. In the absence of endothelium (E-) lead had no effect but increased baseline perfusion pressure (E+: 79.5 ± 2.4, E-: 118 ± 2.2 mmHg; P < 0.05). To investigate the underlying mechanisms, this protocol was repeated after treatment with 100 µM L-NAME, 10 µM indomethacin and 1 µM tempol in the presence of lead. Lead actions on Emax and pD2 were abolished in the presence of indomethacin, and partially abolished with L-NAME and tempol. Results suggest that acute lead administration affects the endothelium, releasing cyclooxygenase-derived vasoconstrictors and involving reactive oxygen species.

Scheduling of head-dependent cascaded reservoirs considering discharge ramping constraints and start/stop of units

This paper is on the problem of short-term hydro scheduling (STHS), particularly concerning head-dependent reservoirs under competitive environment. We propose a novel method, based on mixed-integer nonlinear programming (MINLP), for optimising power generation efficiency. This method considers hydroelectric power generation as a nonlinear function of water discharge and of the head. The main contribution of this paper is that discharge ramping constraints and start/stop of units are also considered, in order to obtain more realistic and feasible results. The proposed method has been applied successfully to solve two case studies based on Portuguese cascaded hydro systems, providing a higher profit at an acceptable computation time in comparison with classical optimisation methods based on mixed-integer linear programming (MILP).

Mixed-integer nonlinear approach for the optimal scheduling of a head-dependent hydro chain

This paper is on the problem of short-term hydro scheduling (STHS), particularly concerning a head-dependent hydro chain We propose a novel mixed-integer nonlinear programming (MINLP) approach, considering hydroelectric power generation as a nonlinear function of water discharge and of the head. As a new contribution to eat her studies, we model the on-off behavior of the hydro plants using integer variables, in order to avoid water discharges at forbidden areas Thus, an enhanced STHS is provided due to the more realistic modeling presented in this paper Our approach has been applied successfully to solve a test case based on one of the Portuguese cascaded hydro systems with a negligible computational time requirement.

Learning dependent sources using mixtures of Dirichlet: applications on hyperspectral unmixing

This paper is an elaboration of the DECA algorithm [1] to blindly unmix hyperspectral data. The underlying mixing model is linear, meaning that each pixel is a linear mixture of the endmembers signatures weighted by the correspondent abundance fractions. The proposed method, as DECA, is tailored to highly mixed mixtures in which the geometric based approaches fail to identify the simplex of minimum volume enclosing the observed spectral vectors. We resort then to a statitistical framework, where the abundance fractions are modeled as mixtures of Dirichlet densities, thus enforcing the constraints on abundance fractions imposed by the acquisition process, namely non-negativity and constant sum. With respect to DECA, we introduce two improvements: 1) the number of Dirichlet modes are inferred based on the minimum description length (MDL) principle; 2) The generalized expectation maximization (GEM) algorithm we adopt to infer the model parameters is improved by using alternating minimization and augmented Lagrangian methods to compute the mixing matrix. The effectiveness of the proposed algorithm is illustrated with simulated and read data.

Scheduling of head-dependent cascaded hydro systems: Mixed-integer quadratic programming approach

This paper is on the problem of short-term hydro, scheduling, particularly concerning head-dependent cascaded hydro systems. We propose a novel mixed-integer quadratic programming approach, considering not only head-dependency, but also discontinuous operating regions and discharge ramping constraints. Thus, an enhanced short-term hydro scheduling is provided due to the more realistic modeling presented in this paper. Numerical results from two case studies, based on Portuguese cascaded hydro systems, illustrate the proficiency of the proposed approach.

Bias dependent photocurrent collection in p-i-n a-Si : EVSiC : H heterojunction

A series of large area single layers and heterojunction cells in the assembly glass/ZnO:Al/p (SixC1-x:H)/i (Si:H)/n (SixC1-x:H)/Al (0

Bias-dependent photocurrent collection in p-i-n a-Si : H/SiC : H heterojunction

A series of large area single layers and glass/ZnO:AVp(SixC1-x:H)/i(Si:H)/n(SixC1-x:H)/AI (0 < x < 1) heterojunction cells were produced by plasma-enhanced chemical vapour deposition (PE-CVD) at low temperature. Junction properties, carrier transport and photogeneration are investigated from dark and illuminated current-voltage (J-V) and capacitance-voltage (C-V) characteristics. For the heterojunction cells atypical J-V characteristics under different illumination conditions are observed leading to poor fill factors. High series resistances around 106 Q are also measured. These experimental results were used as a basis for the numerical simulation of the energy band diagram, and the electrical field distribution of the structures. Further comparison with the sensor performance gave satisfactory agreement. Results show that the conduction band offset is the most limiting parameter for the optimal collection of the photogenerated carriers. As the optical gap increases and the conductivity of the doped layers decreases, the transport mechanism changes from a drift to a diffusion-limited process.

Malaria transmission model for different levels of acquired immunity and temperature-dependent parameters (vector)

OBJECTIVE: Describe the overall transmission of malaria through a compartmental model, considering the human host and mosquito vector. METHODS: A mathematical model was developed based on the following parameters: human host immunity, assuming the existence of acquired immunity and immunological memory, which boosts the protective response upon reinfection; mosquito vector, taking into account that the average period of development from egg to adult mosquito and the extrinsic incubation period of parasites (transformation of infected but non-infectious mosquitoes into infectious mosquitoes) are dependent on the ambient temperature. RESULTS: The steady state equilibrium values obtained with the model allowed the calculation of the basic reproduction ratio in terms of the model's parameters. CONCLUSIONS: The model allowed the calculation of the basic reproduction ratio, one of the most important epidemiological variables.

Re-entrant phase behaviour of network fluids: A patchy particle model with temperature-dependent valence

We study a model consisting of particles with dissimilar bonding sites ("patches"), which exhibits self-assembly into chains connected by Y-junctions, and investigate its phase behaviour by both simulations and theory. We show that, as the energy cost epsilon(j) of forming Y-junctions increases, the extent of the liquid-vapour coexistence region at lower temperatures and densities is reduced. The phase diagram thus acquires a characteristic "pinched" shape in which the liquid branch density decreases as the temperature is lowered. To our knowledge, this is the first model in which the predicted topological phase transition between a fluid composed of short chains and a fluid rich in Y-junctions is actually observed. Above a certain threshold for epsilon(j), condensation ceases to exist because the entropy gain of forming Y-junctions can no longer offset their energy cost. We also show that the properties of these phase diagrams can be understood in terms of a temperature-dependent effective valence of the patchy particles. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3605703]

Cost dependent strategy for electricity markets bidding based on adaptive reinforcement learning

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM provides several dynamic strategies for agents’ behavior. This paper presents a method that aims to provide market players with strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible bids. These bids are defined accordingly to the cost function that each producer presents.

Polycyclic aromatic hydrocarbon levels in three pelagic fish species from Atlantic Ocean: inter-specific and inter-season comparisons and assessment of potential public health risks

The concentrations of 18 polycyclic aromatic hydrocarbons (PAHs) were determined in three commercially valuable fish species (sardine, Sardina pilchardus; chub mackerel, Scomber japonicus; and horse mackerel, Trachurus trachurus) from the Atlantic Ocean. Specimens were collected seasonally during 2007–2009. Only low molecular weight PAHs were detected, namely, naphthalene, acenaphthene, fluorene and phenanthrene. Chub mackerel (1.80–19.90 microg/kg ww) revealed to be significantly more contaminated than horse mackerel (2.73–10.0 microg/kg ww) and sardine (2.29–14.18 microg/kg ww). Inter-specific and inter-season comparisons of PAHs bioaccumulation were statistically assessed. The more relevant statistical correlations were observed between PAH amounts and total fat content (significant positive relationships, p < 0.05), and season (sardine displayed higher amounts in autumn–winter while the mackerel species showed globally the inverse behavior). The health risks by consumption of these species were assessed and shown to present no threat to public health concerning PAH intakes.

Dependent component analysis: a hyperspectral unmixing algorithm

Linear unmixing decomposes a hyperspectral image into a collection of reflectance spectra of the materials present in the scene, called endmember signatures, and the corresponding abundance fractions at each pixel in a spatial area of interest. This paper introduces a new unmixing method, called Dependent Component Analysis (DECA), which overcomes the limitations of unmixing methods based on Independent Component Analysis (ICA) and on geometrical properties of hyperspectral data. DECA models the abundance fractions as mixtures of Dirichlet densities, thus enforcing the constraints on abundance fractions imposed by the acquisition process, namely non-negativity and constant sum. The mixing matrix is inferred by a generalized expectation-maximization (GEM) type algorithm. The performance of the method is illustrated using simulated and real data.

Optimising and adapting the QoS of a dynamic set of inter-dependent tasks

Due to the growing complexity and adaptability requirements of real-time systems, which often exhibit unrestricted Quality of Service (QoS) inter-dependencies among supported services and user-imposed quality constraints, it is increasingly difficult to optimise the level of service of a dynamic task set within an useful and bounded time. This is even more difficult when intending to benefit from the full potential of an open distributed cooperating environment, where service characteristics are not known beforehand and tasks may be inter-dependent. This paper focuses on optimising a dynamic local set of inter-dependent tasks that can be executed at varying levels of QoS to achieve an efficient resource usage that is constantly adapted to the specific constraints of devices and users, nature of executing tasks and dynamically changing system conditions. Extensive simulations demonstrate that the proposed anytime algorithms are able to quickly find a good initial solution and effectively optimise the rate at which the quality of the current solution improves as the algorithms are given more time to run, with a minimum overhead when compared against their traditional versions.