Vascular smooth muscle cell phenotypic modulation in culture is associated with reorganisation of contractile and cytoskeletal proteins

Smooth muscle cells (SMC) exhibit a functional plasticity, modulating from the mature phenotype in which the primary function is contraction, to a less differentiated state with increased capacities for motility, protein synthesis, and proliferation. The present study determined, using Western analysis, double-label immunofluorescence and confocal microscopy, whether changes in phenotypic expression of rabbit aortic SMC in culture could be correlated with alterations in expression and distribution of structural proteins. Contractile state SMC (days 1 and 3 of primary culture) showed distinct sorting of proteins into subcellular domains, consistent with the theory that the SMC structural machinery is compartmentalised within the cell. Proteins specialised for contraction (alpha -SM actin, SM-MHC, and calponin) were highly expressed in these cells and concentrated in the upper central region of the cell. Vimentin was confined to the body of the cell, providing support for the contractile apparatus but not co-localising with it. In line with its role in cell attachment and motility, beta -NM actin was localised to the cell periphery and basal cortex. The dense body protein alpha -actinin was concentrated at the cell periphery, possibly stabilising both contractile and motile apparatus. Vinculin-containing focal adhesions were well developed, indicating the cells' strong adhesion to substrate. In synthetic state SMC (passages 2-3 of culture), there was decreased expression of contractile and adhesion (vinculin) proteins with a concomitant increase in cytoskeletal proteins (beta -non-muscle [NM] actin and vimentin). These quantitative changes in structural proteins were associated with dramatic chan-es in their distribution. The distinct compartmentalisation of structural proteins observed in contractile state SMC was no longer obvious, with proteins more evenly distributed throughout die cytoplasm to accommodate altered cell function. Thus, SMC phenotypic modulation involves not only quantitative changes in contractile and cytoskeletal proteins, but also reorganisation of these proteins. Since the cytoskeleton acts as a spatial regulator of intracellular signalling, reorganisation of the cytoskeleton may lead to realignment of signalling molecules, which, in turn, may mediate the changes in function associated with SMC phenotypic modulation. (C) 2001 Wiley-Liss, Inc.

Quantum interference in optical fields and atomic radiation

We discuss the connection between quantum interference effects in optical beams and radiation fields emitted from atomic systems. We illustrate this connection by a study of the first- and second-order correlation functions of optical fields and atomic dipole moments. We explore the role of correlations between the emitting systems and present examples of practical methods to implement two systems with non-orthogonal dipole moments. We also derive general conditions for quantum interference in a two-atom system and for a control of spontaneous emission. The relation between population trapping and dark states is also discussed. Moreover, we present quantum dressed-atom models of cancellation of spontaneous emission, amplification on dark transitions, fluorescence quenching and coherent population trapping.

Field quantization, photons and non-Hermitean modes

Field quantization in unstable optical systems is treated by expanding the vector potential in terms of non-Hermitean (Fox-Li) modes. We define non-Hermitean modes and their adjoints in both the cavity and external regions and make use of the important bi-orthogonality relationships that exist within each mode set. We employ a standard canonical quantization procedure involving the introduction of generalized coordinates and momenta for the electromagnetic (EM) field. Three-dimensional systems are treated, making use of the paraxial and monochromaticity approximations for the cavity non-Hermitean modes. We show that the quantum EM field is equivalent to a set of quantum harmonic oscillators (QHOs), associated with either the cavity or the external region non-Hermitean modes, and thus confirming the validity of the photon model in unstable optical systems. Unlike in the conventional (Hermitean mode) case, the annihilation and creation operators we define for each QHO are not Hermitean adjoints. It is shown that the quantum Hamiltonian for the EM field is the sum of non-commuting cavity and external region contributions, each of which can be expressed as a sum of independent QHO Hamiltonians for each non-Hermitean mode, except that the external field Hamiltonian also includes a coupling term responsible for external non-Hermitean mode photon exchange processes. The non-commutativity of certain cavity and external region annihilation and creation operators is associated with cavity energy gain and loss processes, and may be described in terms of surface integrals involving cavity and external region non-Hermitean mode functions on the cavity-external region boundary. Using the essential states approach and the rotating wave approximation, our results are applied to the spontaneous decay of a two-level atom inside an unstable cavity. We find that atomic transitions leading to cavity non-Hermitean mode photon absorption are associated with a different coupling constant to that for transitions leading to photon emission, a feature consequent on the use of non-Hermitean mode functions. We show that under certain conditions the spontaneous decay rate is enhanced by the Petermann factor.

Cloning of a differentially expressed tropomyosin isoform from cultured rabbit aortic smooth muscle cells

The four known tropomyosin genes have highly conserved DNA and amino acid sequences, and at least 18 isoforms are generated by alternative RNA splicing in muscle and non-muscle cells. No rabbit tropomyosin nucleotide sequences are known, although protein sequences for alpha- and beta-tropomyosin expressed by rabbit skeletal muscle have been described. Subtractive hybridisation was used to select for genes differentially expressed in rabbit aortic smooth muscle cells (SMC), during the change in cell phenotype in primary culture that is characterised by a loss of cytoskeletal filaments and contractile proteins. This led to the cloning of a tropomyosin gene predominantly expressed in rabbit SMC during this change. The full-length cDNA clone, designated rabbit TM-beta, contains an open reading frame of 284 amino acids, 5' untranslated region (UTR) of I 17 base pairs and 3' UTR of 79 base pairs. It is closely related to the beta-gene isoforms in other species, with the highest homology in DNA and protein sequences to the human fibroblast isoform TM-1 (91.7% identity in 1035 bp and 93.3% identity in the entire 284 amino acid sequence of the protein), It differs from rabbit skeletal muscle P-tropomyosin (81.7% homology at the protein level) mainly in two regions at amino acids 189-213 and 258-283 suggesting alternative splicing of exons 6a for 6b and 9d for 9a. Since this TM-P gene was the only gene strongly enough expressed in SMC changing phenotype to be observed by the subtractive hybridisation screen, it likely plays a significant role in this process. (C) 2002 Published by Elsevier Science Ltd.

Mean anisotropy of homogeneous Gaussian random fields and anisotropic norms of linear translation-invariant operators on multidimensional integer lattices

Sensitivity of output of a linear operator to its input can be quantified in various ways. In Control Theory, the input is usually interpreted as disturbance and the output is to be minimized in some sense. In stochastic worst-case design settings, the disturbance is considered random with imprecisely known probability distribution. The prior set of probability measures can be chosen so as to quantify how far the disturbance deviates from the white-noise hypothesis of Linear Quadratic Gaussian control. Such deviation can be measured by the minimal Kullback-Leibler informational divergence from the Gaussian distributions with zero mean and scalar covariance matrices. The resulting anisotropy functional is defined for finite power random vectors. Originally, anisotropy was introduced for directionally generic random vectors as the relative entropy of the normalized vector with respect to the uniform distribution on the unit sphere. The associated a-anisotropic norm of a matrix is then its maximum root mean square or average energy gain with respect to finite power or directionally generic inputs whose anisotropy is bounded above by a≥0. We give a systematic comparison of the anisotropy functionals and the associated norms. These are considered for unboundedly growing fragments of homogeneous Gaussian random fields on multidimensional integer lattice to yield mean anisotropy. Correspondingly, the anisotropic norms of finite matrices are extended to bounded linear translation invariant operators over such fields.

Non-compact generalized variational inequalities for quasi-monotone and hemi-continuous operators with applications

Some results are obtained for non-compact cases in topological vector spaces for the existence problem of solutions for some set-valued variational inequalities with quasi-monotone and lower hemi-continuous operators, and with quasi-semi-monotone and upper hemi-continuous operators. Some applications are given in non-reflexive Banach spaces for these existence problems of solutions and for perturbation problems for these set-valued variational inequalities with quasi-monotone and quasi-semi-monotone operators.

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.

Solar Intensity Forecasting using Artificial Neural Networks and Support Vector Machines

This paper presents several forecasting methodologies based on the application of Artificial Neural Networks (ANN) and Support Vector Machines (SVM), directed to the prediction of the solar radiance intensity. The methodologies differ from each other by using different information in the training of the methods, i.e, different environmental complementary fields such as the wind speed, temperature, and humidity. Additionally, different ways of considering the data series information have been considered. Sensitivity testing has been performed on all methodologies in order to achieve the best parameterizations for the proposed approaches. Results show that the SVM approach using the exponential Radial Basis Function (eRBF) is capable of achieving the best forecasting results, and in half execution time of the ANN based approaches.

Predictivity Strength of the Spatial Variability of Phenanthrene Sorption Across Two Sandy Loam Fields

Sorption is commonly agreed to be the major process underlying the transport and fate of polycyclic aromatic hydrocarbons (PAHs) in soils. However, there is still a scarcity of studies focusing on spatial variability at the field scale in particular. In order to investigate the variation in the field of phenanthrene sorption, bulk topsoil samples were taken in a 15 × 15-m grid from the plough layer in two sandy loam fields with different texture and organic carbon (OC) contents (140 samples in total). Batch experiments were performed using the adsorption method. Values for the partition coefficient K d (L kg−1) and the organic carbon partition coefficient K OC (L kg−1) agreed with the most frequently used models for PAH partitioning, as OC revealed a higher affinity for sorption. More complex models using different OC compartments, such as non-complexed organic carbon (NCOC) and complexed organic carbon (COC) separately, performed better than single K OC models, particularly for a subset including samples with Dexter n < 10 and OC <0.04 kg kg−1. The selected threshold revealed that K OC-based models proved to be applicable for more organic fields, while two-component models proved to be more accurate for the prediction of K d and retardation factor (R) for less organic soils. Moreover, OC did not fully reflect the changes in phenanthrene retardation in the field with lower OC content (Faardrup). Bulk density and available water content influenced the phenanthrene transport mechanism phenomenon.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Endobronchial leiomyoma: an unusual non-defining neoplasm in a patient with AIDS

Smooth muscle neoplasms are more frequent in human immunodeficiency infected children than in HIV seropositive adults. Endobronchial leiomyoma is a rare benign tumor in HIV infected adult patients. Epstein-Barr virus (EBV) has been implicated in the pathogenesis of these tumors. Here we describe an adult patient with HIV infection with atelectasis of the left upper pulmonary lobe as the first clinical expression of an intrabronchial leiomyoma. In this case, we can not show the association with EBV. Our report suggests that smooth muscle tumors as leiomyoma should be included in the differential diagnosis of endobronchial masses in AIDS patients.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

FIRST REPORT OF ACUTE CHAGAS DISEASE BY VECTOR TRANSMISSION IN RIO DE JANEIRO STATE, BRAZIL

SUMMARY Chagas disease (CD) is an endemic anthropozoonosis from Latin America of which the main means of transmission is the contact of skin lesions or mucosa with the feces of triatomine bugs infected by Trypanosoma cruzi. In this article, we describe the first acute CD case acquired by vector transmission in the Rio de Janeiro State and confirmed by parasitological, serological and PCR tests. The patient presented acute cardiomyopathy and pericardial effusion without cardiac tamponade. Together with fever and malaise, a 3 cm wide erythematous, non-pruritic, papule compatible with a "chagoma" was found on his left wrist. This case report draws attention to the possible transmission of CD by non-domiciled native vectors in non-endemic areas. Therefore, acute CD should be included in the diagnostic workout of febrile diseases and acute myopericarditis in Rio de Janeiro.

Influence of abiotic stress factors on VOCs emission from Portuguese rice paddy fields: relation with increased climate change

Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente Perfil de Gestão de Sistemas Ambientais

Observation and measurements of the production of prompt and non-prompt J/ψ mesons in association with a Z boson in pp collisions at s√ = 8 TeV with the ATLAS detector

The production of a Z boson in association with a J/ψ meson in proton--proton collisions probes the production mechanisms of quarkonium and heavy flavour in association with vector bosons, and allows studies of multiple parton scattering. Using 20.3fb−1 of data collected with the ATLAS experiment at the LHC, in pp collisions at s√=8 TeV, the first measurement of associated Z+J/ψ production is presented for both prompt and non-prompt J/ψ production, with both signatures having a significance in excess of 5σ. The inclusive production cross-sections for Z boson production (in μ+μ− or e+e− decay modes) in association with prompt and non-prompt J/ψ(→μ+μ−) are measured relative to the inclusive production rate of Z bosons in the same fiducial volume to be (88±16±6)×10−8 and (157±22±10)×10−8 respectively. Normalised differential production cross-sections are also determined as a function of the J/ψ transverse momentum. The fraction of signal events arising from single and double parton scattering is estimated, and a lower limit of 5.3 (3.7)mb at 68 (95) confidence level is placed on the effective cross-section regulating double parton interactions.