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.

Evaluation of the influence of the ADH3 ILE349VAL polymorphism in the frequency of genotoxicity biomarkers in workers exposed to formaldehyde and tobacco smoking

Formaldehyde (FA) is a colourless gas widely used in the industry and hospitals as an aqueous solution, formalin. It is extremely reactive and induces various genotoxic effects in proliferating cultured mammalian cells. Tobacco smoke has been epidemiologically associated to a higher risk of development of cancer, especially in the oral cavity, larynx and lungs, as these are places of direct contact with many carcinogenic tobacco’s compounds. Genetic polymorphisms in enzymes involved in the metabolism are very important and can make changes in the individual susceptibility to disease. Alcohol dehydrogenase class 3 (ADH3), also known as formaldehyde dehydrogenase dependent of glutathione, is the major enzyme involved in the formaldehyde oxidation, especially in the buccal mucosa. The polymorphism in study is a substitution of an isoleucine for a valine in codon 349. The cytokinesis-blocked micronucleus assay (CBMN) in human lymphocytes is one of the most commonly used methods for measuring DNA damage, namely the detection of micronucleus, nucleoplasmic bridges, and nuclear buds, classified as genotoxicity biomarkers.

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 dependent mainly on minority carriers the diffusion.

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.

Cytomegalovirus seroepidemiology in an urban community of São Paulo, Brazil

INTRODUCTION: After the era of rubella vaccine, cytomegalovirus (CMV) infection is one of the most frequently causes of mental retardation and congenital deafness. Seroepidemiological studies are necessary to understand the transmission dynamics of the disease. The purpose of the study was to quantify the transmission rate of CMV disease in a community in the state of São Paulo, Brazil. METHODS: Using ELISA test (IgG), a retrospective serological survey looking for CMV antibodies was performed in an non-immunized community. Frozen sera from 443 individuals, randomly selected by cluster sampling technique in the town of Caieiras, São Paulo, were collected from November 1990 to January 1991. Seroprevalence was stratified by age (0-40 years). Mathematical techniques were applied to determine the age-dependent decay function of maternal antibodies during the first year of life, the age-dependent seroprevalence function and the force of infection for CMV in this community. RESULTS: It was observed a descending phase of seropositivity in the first 9 months, but changes in antibody titration were observed between 8 months old and one year of age. The average age of the first infection was 5.02 months of age and 19.84 years, when the age-dependent seroprevalence and the force of infection were analyzed between 10 months of age and 10 years of age and from 10 to 40 years old, respectively. CONCLUSION: CMV infection is highly prevalent among the population studied and infection occurs in the first year of life. This study shows that most women at reproductive age are vulnerable to the first infection, increasing the risk for congenital infection.

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.

Two-way MANCOVA: an application to public health

The aim of this work is to use the MANCOVA model to study the influence of the phenotype of an enzyme - Acid phosphatase - and a genetic factor - Haptoglobin genotype - on two dependent variables - Activity of Acid Phosphatase (ACP1) and the Body Mass Index (BMI). Therefore it's used a general linear model, namely a multivariate analysis of covariance (Two-way MANCOVA). The covariate is the age of the subject. This covariate works as control variable for the independent factors, serving to reduce the error term in the model. The main results showed that only the ACP1 phenotype has a significant effect on the activity of ACP1 and the covariate has a significant effect in both dependent variables. The univariate analysis showed that ACP1 phenotype accounts for about 12.5% of the variability in the activity of ACP1. In respect to this covariate it can be seen that accounts for about 4.6% of the variability in the activity of ACP1 and 37.3% in the BMI.

Expression of YAP4 in Saccharomyces cerevisiae under osmotic stress

YAP4, a member of the yeast activator protein (YAP) gene family, is induced in response to osmotic shock in the yeast Saccharomyces cerevisiae. The null mutant displays mild and moderate growth sensitivity at 0.4 M and 0.8 M NaCl respectively, a fact that led us to analyse YAP4 mRNA levels in the hog1 (high osmolarity glycerol) mutant. The data obtained show a complete abolition of YAP4 gene expression in this mutant, placing YAP4 under the HOG response pathway. YAP4 overexpression not only suppresses the osmosensitivity phenotype of the yap4 mutant but also relieves that of the hog1 mutant. Induction, under the conditions tested so far, requires the presence of the transcription factor Msn2p, but not of Msn4p, as YAP4 mRNA levels are depleted by at least 75% in the msn2 mutant. This result was further substantiated by the fact that full YAP4 induction requires the two more proximal stress response elements. Furthermore we find that GCY1, encoding a putative glycerol dehydrogenase, GPP2, encoding a NAD-dependent glycerol-3-phosphate phosphatase, and DCS2, a homologue to a decapping enzyme, have decreased mRNA levels in the yap4 -deleted strain. Our data point to a possible, as yet not entirely understood, role of the YAP4 in osmotic stress response.

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.