Twinlike models for kinks and compactons in flat and warped spacetime

This work deals with the presence of twinlike models in scalar field theories. We show how to build distinct scalar field theories having the same extended solution, with the same energy density and linear stability. Here, however, we start from a given but generalized scalar field theory, and we construct the corresponding twin model, which also engenders generalized dynamics. We investigate how the twinlike models arise in both flat and curved spacetimes. In the curved spacetime, we consider a braneworld model with the warp factor controlling the spacetime geometry with a single extra dimension of infinite extent. In particular, we study linear stability in both flat and curved spacetimes, and in the case of curved spacetime-in both the gravity and the scalar field sectors-for the two braneworld models. DOI: 10.1103/PhysRevD.86.125021

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.

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.

Bayesian Analysis for Errors in Variables with Changepoint Models

Changepoint regression models have originally been developed in connection with applications in quality control, where a change from the in-control to the out-of-control state has to be detected based on the avaliable random observations. Up to now various changepoint models have been suggested for differents applications like reliability, econometrics or medicine. In many practical situations the covariate cannot be measured precisely and an alternative model are the errors in variable regression models. In this paper we study the regression model with errors in variables with changepoint from a Bayesian approach. From the simulation study we found that the proposed procedure produces estimates suitable for the changepoint and all other model parameters.

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.

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.

On the impact of disproportional samples in credit scoring models: An application to a Brazilian bank data

Statistical methods have been widely employed to assess the capabilities of credit scoring classification models in order to reduce the risk of wrong decisions when granting credit facilities to clients. The predictive quality of a classification model can be evaluated based on measures such as sensitivity, specificity, predictive values, accuracy, correlation coefficients and information theoretical measures, such as relative entropy and mutual information. In this paper we analyze the performance of a naive logistic regression model (Hosmer & Lemeshow, 1989) and a logistic regression with state-dependent sample selection model (Cramer, 2004) applied to simulated data. Also, as a case study, the methodology is illustrated on a data set extracted from a Brazilian bank portfolio. Our simulation results so far revealed that there is no statistically significant difference in terms of predictive capacity between the naive logistic regression models and the logistic regression with state-dependent sample selection models. However, there is strong difference between the distributions of the estimated default probabilities from these two statistical modeling techniques, with the naive logistic regression models always underestimating such probabilities, particularly in the presence of balanced samples. (C) 2012 Elsevier Ltd. All rights reserved.

Quantum Integrability in Non-Linear Sigma Models related to Gauge/String Correspondences

The Thermodynamic Bethe Ansatz analysis is carried out for the extended-CP^N class of integrable 2-dimensional Non-Linear Sigma Models related to the low energy limit of the AdS_4xCP^3 type IIA superstring theory. The principal aim of this program is to obtain further non-perturbative consistency check to the S-matrix proposed to describe the scattering processes between the fundamental excitations of the theory by analyzing the structure of the Renormalization Group flow. As a noteworthy byproduct we eventually obtain a novel class of TBA models which fits in the known classification but with several important differences. The TBA framework allows the evaluation of some exact quantities related to the conformal UV limit of the model: effective central charge, conformal dimension of the perturbing operator and field content of the underlying CFT. The knowledge of this physical quantities has led to the possibility of conjecturing a perturbed CFT realization of the integrable models in terms of coset Kac-Moody CFT. The set of numerical tools and programs developed ad hoc to solve the problem at hand is also discussed in some detail with references to the code.

Steady-state function of the ubiquitous mammalian Na/H exchanger (NHE1) in relation to dimer coupling models with 2Na/2H stoichiometry

We describe the steady-state function of the ubiquitous mammalian Na/H exchanger (NHE)1 isoform in voltage-clamped Chinese hamster ovary cells, as well as other cells, using oscillating pH-sensitive microelectrodes to quantify proton fluxes via extracellular pH gradients. Giant excised patches could not be used as gigaseal formation disrupts NHE activity within the patch. We first analyzed forward transport at an extracellular pH of 8.2 with no cytoplasmic Na (i.e., nearly zero-trans). The extracellular Na concentration dependence is sigmoidal at a cytoplasmic pH of 6.8 with a Hill coefficient of 1.8. In contrast, at a cytoplasmic pH of 6.0, the Hill coefficient is <1, and Na dependence often appears biphasic. Results are similar for mouse skin fibroblasts and for an opossum kidney cell line that expresses the NHE3 isoform, whereas NHE1(-/-) skin fibroblasts generate no proton fluxes in equivalent experiments. As proton flux is decreased by increasing cytoplasmic pH, the half-maximal concentration (K(1/2)) of extracellular Na decreases less than expected for simple consecutive ion exchange models. The K(1/2) for cytoplasmic protons decreases with increasing extracellular Na, opposite to predictions of consecutive exchange models. For reverse transport, which is robust at a cytoplasmic pH of 7.6, the K(1/2) for extracellular protons decreases only a factor of 0.4 when maximal activity is decreased fivefold by reducing cytoplasmic Na. With 140 mM of extracellular Na and no cytoplasmic Na, the K(1/2) for cytoplasmic protons is 50 nM (pH 7.3; Hill coefficient, 1.5), and activity decreases only 25% with extracellular acidification from 8.5 to 7.2. Most data can be reconstructed with two very different coupled dimer models. In one model, monomers operate independently at low cytoplasmic pH but couple to translocate two ions in "parallel" at alkaline pH. In the second "serial" model, each monomer transports two ions, and translocation by one monomer allosterically promotes translocation by the paired monomer in opposite direction. We conclude that a large fraction of mammalian Na/H activity may occur with a 2Na/2H stoichiometry.

Models with Plants, Microorganisms and Viruses for Basic Research in Homeopathy

Most criticism about homeopathy concerns the lack of a scientific basis and theoretical models. In order to be accepted as a valid part of medical practice, a wellstructured research strategy for homeopathy is needed. This is often hampered by methodological problems as well as by gross underinvestment in the required academic resources. Fundamental research could make important contributions to our understanding of the homeopathic and high dilutions mechanisms of action. Since the pioneering works of Kolisko on wheat germination (Kolisko, 1923) and Junker on growth of microorganisms (paramecium, yeast, fungi) (Junker, 1928), a number of experiments have been performed either with healthy organisms (various physiological aspects of growth) or with artificially diseased organisms, which may react more markedly to homeopathic treatments than healthy ones. In the latter case, the preliminary stress may be either abiotic, e.g. heavy metals, or biotic, e.g. fungal and viral pathogens or nematode infection. Research has also been carried out into the applicability of homeopathic principles to crop growth and disease control (agrohomeopathy): because of the extreme dilutions used, the environmental impact is low and such treatments are well suited to the holistic approach of sustainable agriculture (Betti et al., 2006). Unfortunately, as Scofield reported in an extensive critical review (Scofield, 1984), there is little firm evidence to support the reliability of the reported results, due to poor experimental methodology and inadequate statistical analysis. Moreover, since there is no agricultural homeopathic pharmacopoeia, much work is required to find suitable remedies, potencies and dose levels.

Use of homeopathic preparations in phytopathological models and in field trails: a critical review

Background: The literature on the applications of homeopathy for controlling plant diseases in both plant pathological models and field trials was first reviewed by Scofield in 1984. No other review on homeopathy in plant pathology has been published since, though much new research has subsequently been carried out using more advanced methods. Objectives: To conduct an up-to-date review of the existing literature on basic research in homeopathy using phytopathological models and experiments in the field. Methods: A literature search was carried out on publications from 1969 to 2009, for papers that reported experiments on homeopathy using phytopathological models (in vitro and in planta) and field trials. The selected papers were summarized and analysed on the basis of a Manuscript Information Score (MIS) to identify those that provided sufficient information for proper interpretation (MIS ≥ 5). These were then evaluated using a Study Methods Evaluation Procedure (SMEP). Results: A total of 44 publications on phytopathological models were identified: 19 papers with statistics, 6 studies with MIS ≥ 5. Publications on field were 9, 6 with MIS ≥ 5. In general, significant and reproducible effects with decimal and centesimal potencies were found, including dilution levels beyond the Avogadro's number. Conclusions: The prospects for homeopathic treatments in agriculture are promising, but much more experimentation is needed, especially at a field level, and on potentisation techniques, effective potency levels and conditions for reproducibility. Phytopathological models may also develop into useful tools to answer pharmaceutical questions.

Extended kalman filter for estimation of parameters in nonlinear state-space models of biochemical networks.

It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks.