Scalar field description for parametric models of dark energy

We investigate theoretical and observational aspects of a time-dependent parameterization for the dark energy equation of state w(z), which is a well behaved function of the redshift z over the entire cosmological evolution, i.e., z is an element of [-1, infinity). By using a theoretical algorithm of constructing the quintes-sence potential directly from the w(z) function, we derive and discuss the general features of the resulting potential for the cases in which dark energy is separately conserved and when it is coupled to dark matter. Since the parameterization here discussed allows us to divide the parametric plane in defined regions associated to distinct classes of dark energy models, we use some of the most recent observations from type Ia supernovae, baryon acoustic oscillation peak and Cosmic Microwave Background shift parameter to check which class is observationally preferred. We show that the largest portion of the confidence contours lies into the region corresponding to a possible crossing of the so-called phantom divide line at some point of the cosmic evolution.

Validation of the MAPGEO2010 and comparison with recent geopotential models

This paper presents the offorts to calculate the geoid model for Brazil. It is limited by 6 degrees N and 35 degrees S in latitude and 30 degrees W and 75 degrees W in longitude. The terrestrial gravity data for the continent have been updated by means of the most recent surveys in Brazil and in the neighbour countries. The complete Bouguer and Helmert gravity anomalies have been derived through the Canadian package SHGEO. The short wavelength component was estimated via FFT. The geopotential model EGM2008 was used as a reference field restricted to degree and order 150. The model was validated over 844 GPS observations on Bench Marks of the spirit leveling network. The height anomalies plus a topography dependent correction term derived from EGM2008 (degree 2190 and order 2159), GO_CONS_GCF_2_DIR_R2 (degree and order 240), GOCO02S (degree and order 250), EIGEN 51C (degree and order 359) and EIGEN 6C (degree and order 1420), geoidal height derived from MAPGEO2004 (old official geoid model in Brazil) have also been compared to the GPS points on Bench Marks.

Covariates of high-risk human papillomavirus (HPV) infections are distinct for incident CIN1, CIN2 and CIN3 as disclosed by competing-risks regression models

Background: In addition to the oncogenic human papillomavirus (HPV), several cofactors are needed in cervical carcinogenesis, but whether the HPV covariates associated with incident i) CIN1 are different from those of incident ii) CIN2 and iii) CIN3 needs further assessment. Objectives: To gain further insights into the true biological differences between CIN1, CIN2 and CIN3, we assessed HPV covariates associated with incident CIN1, CIN2, and CIN3. Study Design and Methods: HPV covariates associated with progression to CIN1, CIN2 and CIN3 were analysed in the combined cohort of the NIS (n = 3,187) and LAMS study (n = 12,114), using competing-risks regression models (in panel data) for baseline HR-HPV-positive women (n = 1,105), who represent a sub-cohort of all 1,865 women prospectively followed-up in these two studies. Results: Altogether, 90 (4.8%), 39 (2.1%) and 14 (1.4%) cases progressed to CIN1, CIN2, and CIN3, respectively. Among these baseline HR-HPV-positive women, the risk profiles of incident GIN I, CIN2 and CIN3 were unique in that completely different HPV covariates were associated with progression to CIN1, CIN2 and CIN3, irrespective which categories (non-progression, CIN1, CIN2, CIN3 or all) were used as competing-risks events in univariate and multivariate models. Conclusions: These data confirm our previous analysis based on multinomial regression models implicating that distinct covariates of HR-HPV are associated with progression to CIN1, CIN2 and CIN3. This emphasises true biological differences between the three grades of GIN, which revisits the concept of combining CIN2 with CIN3 or with CIN1 in histological classification or used as a common end-point, e.g., in HPV vaccine trials.

Lipopolysaccharide-Induced Sickness Behaviour Evaluated in Different Models of Anxiety and Innate Fear in Rats

The fact that there is a complex and bidirectional communication between the immune and nervous systems has been well demonstrated. Lipopolysaccharide (LPS), a component of gram-negative bacteria, is widely used to systematically stimulate the immune system and generate profound physiological and behavioural changes, also known as sickness behaviour (e.g. anhedonia, lethargy, loss of appetite, anxiety, sleepiness). Different ethological tools have been used to analyse the behavioural modifications induced by LPS; however, many researchers analysed only individual tests, a single LPS dose or a unique ethological parameter, thus leading to disagreements regarding the data. In the present study, we investigated the effects of different doses of LPS (10, 50, 200 and 500 mu g/kg, i.p.) in young male Wistar rats (weighing 180200 g; 89 weeks old) on the ethological and spatiotemporal parameters of the elevated plus maze, light-dark box, elevated T maze, open-field tests and emission of ultrasound vocalizations. There was a dose-dependent increase in anxiety-like behaviours caused by LPS, forming an inverted U curve peaked at LPS 200 mu g/kg dose. However, these anxiety-like behaviours were detected only by complementary ethological analysis (stretching, grooming, immobility responses and alarm calls), and these reactions seem to be a very sensitive tool in assessing the first signs of sickness behaviour. In summary, the present work clearly showed that there are resting and alertness reactions induced by opposite neuroimmune mechanisms (neuroimmune bias) that could lead to anxiety behaviours, suggesting that misunderstanding data could occur when only few ethological variables or single doses of LPS are analysed. Finally, it is hypothesized that this bias is an evolutionary tool that increases animals security while the body recovers from a systemic infection.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

Holographic field theory models of dark energy in interaction with dark matter

We discuss two Lagrangian interacting dark energy models in the context of the holographic principle. The potentials of the interacting fields are constructed. The models are compared with CMB distance information, baryonic acoustic oscillations, lookback time and the Constitution supernovae sample. For both models, the results are consistent with a nonvanishing interaction in the dark sector of the Universe and the sign of coupling is consistent with dark energy decaying into dark matter, alleviating the coincidence problem-with more than 3 standard deviations of confidence for one of them. However, this is because the noninteracting holographic dark energy model is a bad fit to the combination of data sets used in this work as compared to the cosmological constant with cold dark matter model, so that one needs to introduce the interaction in order to improve this model.

Methane airborne measurements and comparison to global models during BARCA

Tropical regions, especially the Amazon region, account for large emissions of methane (CH4). Here, we present CH4 observations from two airborne campaigns conducted within the BARCA (Balanco Atmosferico Regional de Carbono na Amazonia) project in the Amazon basin in November 2008 (end of the dry season) and May 2009 (end of the wet season). We performed continuous measurements of CH4 onboard an aircraft for the first time in the Amazon region, covering the whole Amazon basin with over 150 vertical profiles between altitudes of 500 m and 4000 m. The observations support the finding of previous ground-based, airborne, and satellite measurements that the Amazon basin is a large source of atmospheric CH4. Isotope analysis verified that the majority of emissions can be attributed to CH4 emissions from wetlands, while urban CH4 emissions could be also traced back to biogenic origin. A comparison of five TM5 based global CH4 inversions with the observations clearly indicates that the inversions using SCIAMACHY observations represent the BARCA observations best. The calculated CH4 flux estimate obtained from the mismatch between observations and TM5-modeled CH4 fields ranges from 36 to 43 mg m(-2) d(-1) for the Amazon lowland region.

Protein quality control disruption by PKC beta II in heart failure: rescue by the selective PKC beta II inhibitor, beta IIV5-3

Myocardial remodeling and heart failure (HF) are common sequelae of many forms of cardiovascular disease and a leading cause of mortality worldwide. Accumulation of damaged cardiac proteins in heart failure has been described. However, how protein quality control (PQC) is regulated and its contribution to HF development are not known. Here, we describe a novel role for activated protein kinase C isoform beta II (PKC beta II) in disrupting PQC. We show that active PKC beta II directly phosphorylated the proteasome and inhibited proteasomal activity in vitro and in cultured neonatal cardiomyocytes. Importantly, inhibition of PKC beta II, using a selective PKC beta II peptide inhibitor (beta IIV5-3), improved proteasomal activity and conferred protection in cultured neonatal cardiomyocytes. We also show that sustained inhibition of PKC beta II increased proteasomal activity, decreased accumulation of damaged and misfolded proteins and increased animal survival in two rat models of HF. Interestingly, beta IIV5-3-mediated protection was blunted by sustained proteasomal inhibition in HF. Finally, increased cardiac PKC beta II activity and accumulation of misfolded proteins associated with decreased proteasomal function were found also in remodeled and failing human hearts, indicating a potential clinical relevance of our findings. Together, our data highlights PKC beta II as a novel inhibitor of proteasomal function. PQC disruption by increased PKC beta II activity in vivo appears to contribute to the pathophysiology of heart failure, suggesting that PKC beta II inhibition may benefit patients with heart failure. (218 words)

Validation and comparison of two soil-vegetation-atmosphere transfer models for tropical Africa

This study aims to compare and validate two soil-vegetation-atmosphere-transfer (SVAT) schemes: TERRA-ML and the Community Land Model (CLM). Both SVAT schemes are run in standalone mode (decoupled from an atmospheric model) and forced with meteorological in-situ measurements obtained at several tropical African sites. Model performance is quantified by comparing simulated sensible and latent heat fluxes with eddy-covariance measurements. Our analysis indicates that the Community Land Model corresponds more closely to the micrometeorological observations, reflecting the advantages of the higher model complexity and physical realism. Deficiencies in TERRA-ML are addressed and its performance is improved: (1) adjusting input data (root depth) to region-specific values (tropical evergreen forest) resolves dry-season underestimation of evapotranspiration; (2) adjusting the leaf area index and albedo (depending on hard-coded model constants) resolves overestimations of both latent and sensible heat fluxes; and (3) an unrealistic flux partitioning caused by overestimated superficial water contents is reduced by adjusting the hydraulic conductivity parameterization. CLM is by default more versatile in its global application on different vegetation types and climates. On the other hand, with its lower degree of complexity, TERRA-ML is much less computationally demanding, which leads to faster calculation times in a coupled climate simulation.

Influence diagnostics in Gaussian spatial linear models

Spatial linear models have been applied in numerous fields such as agriculture, geoscience and environmental sciences, among many others. Spatial dependence structure modelling, using a geostatistical approach, is an indispensable tool to estimate the parameters that define this structure. However, this estimation may be greatly affected by the presence of atypical observations in the sampled data. The purpose of this paper is to use diagnostic techniques to assess the sensitivity of the maximum-likelihood estimators, covariance functions and linear predictor to small perturbations in the data and/or the spatial linear model assumptions. The methodology is illustrated with two real data sets. The results allowed us to conclude that the presence of atypical values in the sample data have a strong influence on thematic maps, changing the spatial dependence structure.

Percutaneous sciatic nerve block with tramadol induces analgesia and motor blockade in two animal pain models

Local anesthetic efficacy of tramadol has been reported following intradermal application. Our aim was to investigate the effect of perineural tramadol as the sole analgesic in two pain models. Male Wistar rats (280-380 g; N = 5/group) were used in these experiments. A neurostimulation-guided sciatic nerve block was performed and 2% lidocaine or tramadol (1.25 and 5 mg) was perineurally injected in two different animal pain models. In the flinching behavior test, the number of flinches was evaluated and in the plantar incision model, mechanical and heat thresholds were measured. Motor effects of lidocaine and tramadol were quantified and a motor block score elaborated. Tramadol, 1.25 mg, completely blocked the first and reduced the second phase of the flinching behavior test. In the plantar incision model, tramadol (1.25 mg) increased both paw withdrawal latency in response to radiant heat (8.3 +/- 1.1, 12.7 +/- 1.8, 8.4 +/- 0.8, and 11.1 +/- 3.3 s) and mechanical threshold in response to von Frey filaments (459 +/- 82.8, 447.5 +/- 91.7, 320.1 +/- 120, 126.43 +/- 92.8 mN) at 5, 15, 30, and 60 min, respectively. Sham block or contralateral sciatic nerve block did not differ from perineural saline injection throughout the study in either model. The effect of tramadol was not antagonized by intraperitoneal naloxone. High dose tramadol (5 mg) blocked motor function as well as 2% lidocaine. In conclusion, tramadol blocks nociception and motor function in vivo similar to local anesthetics.

Co-metabolic models of Streptococcus thermophilus in co-culture with Lactobacillus bulgaricus or Lactobacillus acidophilus

To shed light on the interactions occurring in fermented milks when using co-cultures of Streptococcus thermophilus with Lactobacillus bulgaricus (StLb) or Lactobacillus acidophilus (StLa), a new co-metabolic model was proposed and checked either in the presence of Inulin as a prebiotic or not. For this purpose, the experimental data of concentrations of substrates and fermented products were utilized in balances of carbon, reduction degree and ATP. S. thermophilus exhibited always quicker growth compared to the other two microorganisms, while the percentage of lactose fermented to lactic acid, that of galactose metabolized, and the levels of diacetyl and acetoin formed strongly depended on the type of co-culture and the presence of inulin. The StLb co-culture led to higher acetoin and lower diacetyl levels compared to StLa, probably because of more reducing conditions or limited acetoin dehydrogenation. Inulin addition to StLa suppressed acetoin accumulation and hindered that of diacetyl, suggesting catabolite repression of alpha-acetolactate synthase expression in S. thermophilus. Both co-cultures showed the highest ATP requirements for biomass growth and maintenance at the beginning of fermentation, consistently with the high energy demand of enzyme induction during lag phase. Inulin reduced these requirements making biomass synthesis and maintenance less energy-consuming. Only a fraction of galactose was released from lactose, consistently with the galactose-positive phenotype of most dairy strains. The galactose fraction metabolized without inulin was about twice that in its presence, which suggests inhibition of the galactose transport system of S. thermophilus by fructose released from partial inulin hydrolysis. (C) 2012 Elsevier B.V. All rights reserved.

MATHEMATICAL MODELS AND POLYHEDRAL STUDIES FOR INTEGRAL SHEET METAL DESIGN

We deal with the optimization of the production of branched sheet metal products. New forming techniques for sheet metal give rise to a wide variety of possible profiles and possible ways of production. In particular, we show how the problem of producing a given profile geometry can be modeled as a discrete optimization problem. We provide a theoretical analysis of the model in order to improve its solution time. In this context we give the complete convex hull description of some substructures of the underlying polyhedron. Moreover, we introduce a new class of facet-defining inequalities that represent connectivity constraints for the profile and show how these inequalities can be separated in polynomial time. Finally, we present numerical results for various test instances, both real-world and academic examples.

Evaluation of Viral Load Thresholds for Predicting New World Health Organization Stage 3 and 4 Events in HIV-Infected Children Receiving Highly Active Antiretroviral Therapy

Background: This study evaluated a wide range of viral load (VL) thresholds to identify a cut-point that best predicts new clinical events in children on stable highly active antiretroviral therapy (HAART). Methods: Cox proportional hazards modeling was used to assess the adjusted risk for World Health Organization stage 3 or 4 clinical events (WHO events) as a function of time-varying CD4, VL, and hemoglobin values in a cohort study of Latin American children on HAART >= 6 months. Models were fit using different VL cut-points between 400 and 50,000 copies per milliliter, with model fit evaluated on the basis of the minimum Akaike information criterion value, a standard model fit statistic. Results: Models were based on 67 subjects with WHO events out of 550 subjects on study. The VL cut-points of >2600 and >32,000 copies per milliliter corresponded to the lowest Akaike information criterion values and were associated with the highest hazard ratios (2.0, P = 0.015; and 2.1, P = 0.0058, respectively) for WHO events. Conclusions: In HIV-infected Latin American children on stable HAART, 2 distinct VL thresholds (>2600 and >32,000 copies/mL) were identified for predicting children at significantly increased risk for HIV-related clinical illness, after accounting for CD4 level, hemoglobin level, and other significant factors.

Growth hormone pharmacogenetics: the interactive effect of a microsatellite in the IGF1 promoter region with the GHR-exon 3 and-202 A/C IGFBP3 variants on treatment outcomes of children with severe GH deficiency

Insulin-like growth factor type 1 (IGF1) is a mediator of growth hormone (GH) action, and therefore, IGF1 is a candidate gene for recombinant human GH (rhGH) pharmacogenetics. Lower serum IGF1 levels were found in adults homozygous for 19 cytosine-adenosine (CA) repeats in the IGF1 promoter. The aim of this study was to evaluate the influence of (CA)n IGF1 polymorphism, alone or in combination with GH receptor (GHR)-exon 3 and -202 A/C insulin-like growth factor binding protein-3 (IGFBP3) polymorphisms, on the growth response to rhGH therapy in GH-deficient (GHD) patients. Eighty-four severe GHD patients were genotyped for (CA) n IGF1, -202 A/C IGFBP3 and GHR-exon 3 polymorphisms. Multiple linear regressions were performed to estimate the effect of each genotype, after adjustment for other influential factors. We assessed the influence of genotypes on the first year growth velocity (1st y GV) (n = 84) and adult height standard deviation score (SDS) adjusted for target-height SDS (AH-TH SDS) after rhGH therapy (n = 37). Homozygosity for the IGF1 19CA repeat allele was negatively correlated with 1st y GV (P = 0.03) and AH-TH SDS (P = 0.002) in multiple linear regression analysis. In conjunction with clinical factors, IGF1 and IGFBP3 genotypes explain 29% of the 1st y GV variability, whereas IGF1 and GHR polymorphisms explain 59% of final height-target-height SDS variability. We conclude that homozygosity for IGF1 (CA) 19 allele is associated with less favorable short-and long-term growth outcomes after rhGH treatment in patients with severe GHD. Furthermore, this polymorphism exhibits a non-additive interaction with -202 A/C IGFBP3 genotype on the 1st y GV and with GHR-exon 3 genotype on adult height. The Pharmacogenomics Journal (2012) 12, 439-445; doi:10.1038/tpj.2011.13; published online 5 April 2011