On the stability of the extracellular hemoglobin of Glossoscolex paulistus, in two iron oxidation states, in the presence of urea

The stability of the Glossoscolex paulistus hemoglobin (HbGp), in two iron oxidation states (and three forms), as monitored by optical absorption, fluorescence emission and circular dichroism (CD) spectroscopies, in the presence of the chaotropic agent urea, is studied. HbGp oligomeric dissociation, denaturation and iron oxidation are observed. CD data show that the cyanomet-HbGp is more stable than the oxy-form. Oxy- and cyanomet-HbGp show good fits on the basis of a two state model with critical urea concentrations at 220-222 nm of 5.1 +/- 0.2 and 6.1 +/- 0.1 mol/L, respectively. The three-state model was able to reveal a subtle second transition at lower urea concentration (1.0-2.0 mol/L) associated to partial oligomeric dissociation. The intermediate state for oxy- and cyanomet-HbGp is very similar to the native state. For met-HbGp, a different equilibrium, in the presence of urea, is observed. A sharp transition at 1.95 +/- 0.05 mol/L of denaturant is observed, associated to oligomeric dissociation and hemichrome formation. In this case, analysis by a three-state model reveals the great similarity between the intermediate and the unfolded states. Analysis of spectroscopic data, by two-state and three-state models, reveals consistency of obtained thermodynamic parameters for HbGp urea denaturation. (C) 2012 Elsevier Inc. All rights reserved.

Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing

Background: In the analysis of effects by cell treatment such as drug dosing, identifying changes on gene network structures between normal and treated cells is a key task. A possible way for identifying the changes is to compare structures of networks estimated from data on normal and treated cells separately. However, this approach usually fails to estimate accurate gene networks due to the limited length of time series data and measurement noise. Thus, approaches that identify changes on regulations by using time series data on both conditions in an efficient manner are demanded. Methods: We propose a new statistical approach that is based on the state space representation of the vector autoregressive model and estimates gene networks on two different conditions in order to identify changes on regulations between the conditions. In the mathematical model of our approach, hidden binary variables are newly introduced to indicate the presence of regulations on each condition. The use of the hidden binary variables enables an efficient data usage; data on both conditions are used for commonly existing regulations, while for condition specific regulations corresponding data are only applied. Also, the similarity of networks on two conditions is automatically considered from the design of the potential function for the hidden binary variables. For the estimation of the hidden binary variables, we derive a new variational annealing method that searches the configuration of the binary variables maximizing the marginal likelihood. Results: For the performance evaluation, we use time series data from two topologically similar synthetic networks, and confirm that our proposed approach estimates commonly existing regulations as well as changes on regulations with higher coverage and precision than other existing approaches in almost all the experimental settings. For a real data application, our proposed approach is applied to time series data from normal Human lung cells and Human lung cells treated by stimulating EGF-receptors and dosing an anticancer drug termed Gefitinib. In the treated lung cells, a cancer cell condition is simulated by the stimulation of EGF-receptors, but the effect would be counteracted due to the selective inhibition of EGF-receptors by Gefitinib. However, gene expression profiles are actually different between the conditions, and the genes related to the identified changes are considered as possible off-targets of Gefitinib. Conclusions: From the synthetically generated time series data, our proposed approach can identify changes on regulations more accurately than existing methods. By applying the proposed approach to the time series data on normal and treated Human lung cells, candidates of off-target genes of Gefitinib are found. According to the published clinical information, one of the genes can be related to a factor of interstitial pneumonia, which is known as a side effect of Gefitinib.

Low-Resolution Molecular Models Reveal the Oligomeric State of the PPAR and the Conformational Organization of Its Domains in Solution

The peroxisome proliferator-activated receptors (PPARs) regulate genes involved in lipid and carbohydrate metabolism, and are targets of drugs approved for human use. Whereas the crystallographic structure of the complex of full length PPAR gamma and RXR alpha is known, structural alterations induced by heterodimer formation and DNA contacts are not well understood. Herein, we report a small-angle X-ray scattering analysis of the oligomeric state of hPPAR gamma alone and in the presence of retinoid X receptor (RXR). The results reveal that, in contrast with other studied nuclear receptors, which predominantly form dimers in solution, hPPAR gamma remains in the monomeric form by itself but forms heterodimers with hRXR alpha. The low-resolution models of hPPAR gamma/RXR alpha complexes predict significant changes in opening angle between heterodimerization partners (LBD) and extended and asymmetric shape of the dimer (LBD-DBD) as compared with X-ray structure of the full-length receptor bound to DNA. These differences between our SAXS models and the high-resolution crystallographic structure might suggest that there are different conformations of functional heterodimer complex in solution. Accordingly, hydrogen/deuterium exchange experiments reveal that the heterodimer binding to DNA promotes more compact and less solvent-accessible conformation of the receptor complex.

Models for capacitated lot-sizing problem with backlogging, setup carryover and crossover

Setup operations are significant in some production environments. It is mandatory that their production plans consider some features, as setup state conservation across periods through setup carryover and crossover. The modelling of setup crossover allows more flexible decisions and is essential for problems with long setup times. This paper proposes two models for the capacitated lot-sizing problem with backlogging and setup carryover and crossover. The first is in line with other models from the literature, whereas the second considers a disaggregated setup variable, which tracks the starting and completion times of the setup operation. This innovative approach permits a more compact formulation. Computational results show that the proposed models have outperformed other state-of-the-art formulation.

The Ground State Energy per Site of the Quantum and Classical Edwards-Anderson Spin Glass in the Thermodynamic Limit

We derive general rigorous lower bounds for the average ground state energy per site e ((d)) of the quantum and classical Edwards-Anderson spin-glass model in dimensions d=2 and d=3 in the thermodynamic limit. For the classical model they imply that e ((2))a parts per thousand yena'3/2 and e ((3))a parts per thousand yena'2.204a <-.

Constraining H-0 in general dark energy models from Sunyaev-Zeldovich/X-ray technique and complementary probes

In accelerating dark energy models, the estimates of the Hubble constant, Ho, from Sunyaev-Zerdovich effect (SZE) and X-ray surface brightness of galaxy clusters may depend on the matter content (Omega(M)), the curvature (Omega(K)) and the equation of state parameter GO. In this article, by using a sample of 25 angular diameter distances of galaxy clusters described by the elliptical beta model obtained through the SZE/X-ray technique, we constrain Ho in the framework of a general ACDM model (arbitrary curvature) and a flat XCDM model with a constant equation of state parameter omega = p(x)/rho(x). In order to avoid the use of priors in the cosmological parameters, we apply a joint analysis involving the baryon acoustic oscillations (BA()) and the (MB Shift Parameter signature. By taking into account the statistical and systematic errors of the SZE/X-ray technique we obtain for nonflat ACDM model H-0 = 74(-4.0)(+5.0) km s(-1) Mpc(-1) (1 sigma) whereas for a fiat universe with constant equation of state parameter we find H-0 = 72(-4.0)(+5.5) km s(-1) Mpc(-1)(1 sigma). By assuming that galaxy clusters are described by a spherical beta model these results change to H-0 = 6(-7.0)(+8.0) and H-0 = 59(-6.0)(+9.0) km s(-1) Mpc(-1)(1 sigma), respectively. The results from elliptical description are in good agreement with independent studies from the Hubble Space Telescope key project and recent estimates based on the Wilkinson Microwave Anisotropy Probe, thereby suggesting that the combination of these three independent phenomena provides an interesting method to constrain the Bubble constant. As an extra bonus, the adoption of the elliptical description is revealed to be a quite realistic assumption. Finally, by comparing these results with a recent determination for a, flat ACDM model using only the SZE/X-ray technique and BAO, we see that the geometry has a very weak influence on H-0 estimates for this combination of data.

Predictive models for mutations in mismatch repair genes: implication for genetic counseling in developing countries

Background: Lynch syndrome (LS) is the most common form of inherited predisposition to colorectal cancer (CRC), accounting for 2-5% of all CRC. LS is an autosomal dominant disease characterized by mutations in the mismatch repair genes mutL homolog 1 (MLH1), mutS homolog 2 (MSH2), postmeiotic segregation increased 1 (PMS1), post-meiotic segregation increased 2 (PMS2) and mutS homolog 6 (MSH6). Mutation risk prediction models can be incorporated into clinical practice, facilitating the decision-making process and identifying individuals for molecular investigation. This is extremely important in countries with limited economic resources. This study aims to evaluate sensitivity and specificity of five predictive models for germline mutations in repair genes in a sample of individuals with suspected Lynch syndrome. Methods: Blood samples from 88 patients were analyzed through sequencing MLH1, MSH2 and MSH6 genes. The probability of detecting a mutation was calculated using the PREMM, Barnetson, MMRpro, Wijnen and Myriad models. To evaluate the sensitivity and specificity of the models, receiver operating characteristic curves were constructed. Results: Of the 88 patients included in this analysis, 31 mutations were identified: 16 were found in the MSH2 gene, 15 in the MLH1 gene and no pathogenic mutations were identified in the MSH6 gene. It was observed that the AUC for the PREMM (0.846), Barnetson (0.850), MMRpro (0.821) and Wijnen (0.807) models did not present significant statistical difference. The Myriad model presented lower AUC (0.704) than the four other models evaluated. Considering thresholds of >= 5%, the models sensitivity varied between 1 (Myriad) and 0.87 (Wijnen) and specificity ranged from 0 (Myriad) to 0.38 (Barnetson). Conclusions: The Barnetson, PREMM, MMRpro and Wijnen models present similar AUC. The AUC of the Myriad model is statistically inferior to the four other models.

Residence Time Distribution Models Derived from Non-Ideal Laminar Velocity Profiles in Tubes

The theoretical E-curve for the laminar flow of non-Newtonian fluids in circular tubes may not be accurate for real tubular systems with diffusion, mechanical vibration, wall roughness, pipe fittings, curves, coils, or corrugated walls. Deviations from the idealized laminar flow reactor (LFR) cannot be well represented using the axial dispersion or the tanks-in-series models of residence time distribution (RTD). In this work, four RTD models derived from non-ideal velocity profiles in segregated tube flow are proposed. They were used to represent the RTD of three tubular systems working with Newtonian and pseudoplastic fluids. Other RTD models were considered for comparison. The proposed models provided good adjustments, and it was possible to determine the active volumes. It is expected that these models can be useful for the analysis of LFR or for the evaluation of continuous thermal processing of viscous foods.

Plasma corticosterone levels in mouse models of pain

Background: Pain markedly activates the hypothalamic-pituitary-adrenal (HPA) axis and increases plasma corticosterone release interfering significantly with nociceptive behaviour as well as the mechanism of action of analgesic drugs. Aims/Methods: In the present study, we monitored the time course of circulating corticosterone in two mouse strains (C57Bl/6 and Balb/C) under different pain models. In addition, the stress response was investigated following animal handling, intrathecal (i.t.) manipulation and habituation to environmental conditions commonly used in nociceptive experimental assays. We also examined the influence of within-cage order of testing on plasma corticosterone. Results: Subcutaneous injection of capsaicin precipitated a prompt stress response whereas carrageenan and complete Freund's adjuvant induced an increased corticosterone release around the third hour post-injection. However, carrageenan induced a longer increased corticosterone in C57Bl/6 mice. In partial sciatic nerve ligation, neuropathic pain model corticosterone increased only in the first days whereas mechanical hypersensitivity remained much longer. Animal handling also represents an important stressor whereas the i.t. injection per se does not exacerbate the handling-induced stress response. Moreover, the order of testing animals from the same cage does not interfere with plasma corticosterone levels in the intrathecal procedure. Animal habituation to the testing apparatus also does not reduce the immediate corticosterone increase as compared with non-habituated mice. Conclusion: Our data indicate that HPA axis activation in acute and chronic pain models is time dependent and may be dissociated from evoked hyperalgesia. Therefore, HPA-axis activation represents an important variable to be considered when designing experimental assays of persistent pain as well as for interpretation of data.

The Environmental Theme in Representations and Practices of Family Health Professionals in the Municipality of Manaus - State of Amazonas/Brazil

There are abundant scientific evidences showing that the increased risk of exposure to diseases is a consequence of anthropogenic environmental changes. In the Family Health Strategy, tasks with a clear environmental focus are prescribed, indicating to the professional teams that they should consider these aspects in their health practices. The objective of this research was to study representations and practices of Family Health Professionals of Manaus - State of Amazonas, Northern Brazil - about environmental issues and their interface with public health. Data were collected by means of participant observation and semi-structured interviews, and the qualitative analysis was carried out through Content Analysis and Methodological Triangulation. The results showed that most professionals do not understand the environment in a systemic way, even though they recognize the great impact that environmental factors have on human health; as interventions, the educational practices follow traditional methodologies and focus on blaming the individual and on the simple transmission of knowledge; the professionals' relationship with the community is limited to personal and/or collective care. It is concluded that in order to the Family Health Strategy to contribute to restructure the system, it is essential to redirect this new health policy model so that it becomes effective as a social and environmental practice.

Exact cosmological solutions of models with an interacting dark sector

In this work we extend the first order formalism for cosmological models that present an interaction between a fermionic and a scalar field. Cosmological exact solutions describing universes filled with interacting dark energy and dark matter have been obtained. Viable cosmological solutions with an early period of decelerated expansion followed by late acceleration have been found, notably one which presents a dark matter component dominating in the past and a dark energy component dominating in the future. In another one, the dark energy alone is the responsible for both periods, similar to a Chaplygin gas case. Exclusively accelerating solutions have also been obtained.

Assessment of variance components in nonlinear mixed-effects elliptical models

The issue of assessing variance components is essential in deciding on the inclusion of random effects in the context of mixed models. In this work we discuss this problem by supposing nonlinear elliptical models for correlated data by using the score-type test proposed in Silvapulle and Silvapulle (1995). Being asymptotically equivalent to the likelihood ratio test and only requiring the estimation under the null hypothesis, this test provides a fairly easy computable alternative for assessing one-sided hypotheses in the context of the marginal model. Taking into account the possible non-normal distribution, we assume that the joint distribution of the response variable and the random effects lies in the elliptical class, which includes light-tailed and heavy-tailed distributions such as Student-t, power exponential, logistic, generalized Student-t, generalized logistic, contaminated normal, and the normal itself, among others. We compare the sensitivity of the score-type test under normal, Student-t and power exponential models for the kinetics data set discussed in Vonesh and Carter (1992) and fitted using the model presented in Russo et al. (2009). Also, a simulation study is performed to analyze the consequences of the kurtosis misspecification.

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.

Response plateau models fitting via isotonic regression

Within the nutritional context, the supplementation of microminerals in bird food is often made in quantities exceeding those required in the attempt to ensure the proper performance of the animals. The experiments of type dosage x response are very common in the determination of levels of nutrients in optimal food balance and include the use of regression models to achieve this objective. Nevertheless, the regression analysis routine, generally, uses a priori information about a possible relationship between the response variable. The isotonic regression is a method of estimation by least squares that generates estimates which preserves data ordering. In the theory of isotonic regression this information is essential and it is expected to increase fitting efficiency. The objective of this work was to use an isotonic regression methodology, as an alternative way of analyzing data of Zn deposition in tibia of male birds of Hubbard lineage. We considered the models of plateau response of polynomial quadratic and linear exponential forms. In addition to these models, we also proposed the fitting of a logarithmic model to the data and the efficiency of the methodology was evaluated by Monte Carlo simulations, considering different scenarios for the parametric values. The isotonization of the data yielded an improvement in all the fitting quality parameters evaluated. Among the models used, the logarithmic presented estimates of the parameters more consistent with the values reported in literature.

Comparative analysis of the pathological events involved in immune and non-immune TRALI models

Background and Objectives Transfusion-related acute lung injury (TRALI) is characterized by leukocyte transmigration and alveolar capillary leakage shortly after transfusion. TRALI pathogenesis has not been fully elucidated. In some cases, the infusion of alloantibodies (immune model), whereas in others the combination of neutrophil priming by proinflammatory molecules with the subsequent infusion of biological response modifiers (BRMs) in the hemocomponent (non-immune model) have been implicated. Our aim was to compare the pathological events involved in TRALI induced by antibodies or BRMs using murine models. Materials and Methods In the immune model, human HNA-2+ neutrophils were incubated in vitro with a monoclonal antibody (anti-CD177, clone 7D8) directed against the HNA-2 antigen and injected i.v. in NOD/SCID mice. In the non-immune model, BALB/c mice were treated with low doses of lipopolysaccharide (LPS) followed by platelet-activating factor (PAF) infusion 2 h later. Forty minutes after PAF administration, or 6 h after neutrophil injection, lungs were isolated and histological analysis, determination of a variety of cytokines and chemokines including keratinocyte-derived chemokine (KC), MIP-2, the interleukins IL-1 beta, IL-6, IL-8 as well as TNFa, cell influx and alveolar capillary leakage were performed. Results In both models, characteristic histological findings of TRALI and an increase in KC and MIP-2 levels were detected. In contrast to the immune model, in the non-immune model, there was a dramatic increase in IL-1 beta and TNFa. However, capillary leakage was only detected if PAF was administrated. Conclusions Regardless of the triggering event(s), KC, MIP-2 and integrins participate in TRALI pathogenesis, whereas PAF is essential for capillary leakage when two events are involved.