Strategy and model building in the fourth dimension: a null model for genotype × age interaction as a Gaussian stationary stochastic process

Abstract Background Using univariate and multivariate variance components linkage analysis methods, we studied possible genotype × age interaction in cardiovascular phenotypes related to the aging process from the Framingham Heart Study. Results We found evidence for genotype × age interaction for fasting glucose and systolic blood pressure. Conclusions There is polygenic genotype × age interaction for fasting glucose and systolic blood pressure and quantitative trait locus × age interaction for a linkage signal for systolic blood pressure phenotypes located on chromosome 17 at 67 cM.

Nonlocal growth processes and conformal invariance

Up to now the raise-and-peel model was the single known example of a one-dimensional stochastic process where one can observe conformal invariance. The model has one parameter. Depending on its value one has a gapped phase, a critical point where one has conformal invariance, and a gapless phase with changing values of the dynamical critical exponent z. In this model, adsorption is local but desorption is not. The raise-and-strip model presented here, in which desorption is also nonlocal, has the same phase diagram. The critical exponents are different as are some physical properties of the model. Our study suggests the possible existence of a whole class of stochastic models in which one can observe conformal invariance.

IL-5 and IL-17A are critical for the chronic IgE response and differentiation of long-lived antibody-secreting cells in inflamed tissues

Prolonged survival of long-lived antibody-secreting cells in the BM has been implicated as a key component of long-term humoral immunity. The current study was designed to uncover the extrinsic signals required for the generation and maintenance of ASC in several niches (peritoneum, spleen and bone-marrow). Our results show that protein mixture of the Thalassophryne nattereri venom induced a chronic Th2 humoral response that is characterized by splenic hyperplasia with GC formation and venom retention by follicular DCs. Retention of B1a in the BM were observed. In the late phase (120 d) of chronic venom-response the largest pool of ASC into the peritoneal cavity consisted of B220(neg)CD43(high) phenotype; the largest pool of ASC into spleen was constituted by B220 positive cells (B220(high) and B220(low)), whereas the largest pool of ASC into in the BM was constituted by the B220(high)CD43(low) phenotype; and finally, terminally differentiated cells (B220(neg)CD43(high)) were only maintained in the inflamed peritoneal cavity in late phase. After 120 d a sustained production of cytokines (KC, IL-5, TNF-alpha, IL-6, IL-17A and IL-23) and leukocytes recruitment (eosinophils, mast cells, and neutrophils) were induced. IL-5- and IL-17A-producing CD4+ CD44+ CD40L+ Ly6C+ effector memory T cells were also observed in peritoneal cavity. Finally, treatment of venom-mice with anti-IL-5- and anti-IL17A-neutralizing mAbs abolished the synthesis of specific IgE, without modifying the splenic hyperplasia or GC formation. In addition, IL-5 and IL-17A negatively regulated the expansion of B1a in peritoneal cavity and BM, and promoted the differentiation of these cells in spleen. And more, IL-5 and IL-17A are sufficient for the generation of ASC B220(neg) in the peritoneal cavity and negatively regulate the number of ASC B220(Pos), confirming that the hierarchical process of ASC differentiation triggered by venom needs the signal derived from IL-5 and IL-17A. (C) 2012 Elsevier Ltd. All rights reserved.

Exact field-driven interface dynamics in the two-dimensional stochastic Ising model with helicoidal boundary conditions

We investigate the interface dynamics of the two-dimensional stochastic Ising model in an external field under helicoidal boundary conditions. At sufficiently low temperatures and fields, the dynamics of the interface is described by an exactly solvable high-spin asymmetric quantum Hamiltonian that is the infinitesimal generator of the zero range process. Generally, the critical dynamics of the interface fluctuations is in the Kardar-Parisi-Zhang universality class of critical behavior. We remark that a whole family of RSOS interface models similar to the Ising interface model investigated here can be described by exactly solvable restricted high-spin quantum XXZ-type Hamiltonians. (C) 2012 Elsevier B.V. All rights reserved.

Bivariate gamma-geometric law and its induced Levy process

In this article we introduce a three-parameter extension of the bivariate exponential-geometric (BEG) law (Kozubowski and Panorska, 2005) [4]. We refer to this new distribution as the bivariate gamma-geometric (BGG) law. A bivariate random vector (X, N) follows the BGG law if N has geometric distribution and X may be represented (in law) as a sum of N independent and identically distributed gamma variables, where these variables are independent of N. Statistical properties such as moment generation and characteristic functions, moments and a variance-covariance matrix are provided. The marginal and conditional laws are also studied. We show that BBG distribution is infinitely divisible, just as the BEG model is. Further, we provide alternative representations for the BGG distribution and show that it enjoys a geometric stability property. Maximum likelihood estimation and inference are discussed and a reparametrization is proposed in order to obtain orthogonality of the parameters. We present an application to a real data set where our model provides a better fit than the BEG model. Our bivariate distribution induces a bivariate Levy process with correlated gamma and negative binomial processes, which extends the bivariate Levy motion proposed by Kozubowski et al. (2008) [6]. The marginals of our Levy motion are a mixture of gamma and negative binomial processes and we named it BMixGNB motion. Basic properties such as stochastic self-similarity and the covariance matrix of the process are presented. The bivariate distribution at fixed time of our BMixGNB process is also studied and some results are derived, including a discussion about maximum likelihood estimation and inference. (C) 2012 Elsevier Inc. All rights reserved.

On Disruption of Fear Memory by Reconsolidation Blockade: Evidence from Cannabidiol Treatment

The search for reconsolidation blockers may uncover clinically relevant drugs for disrupting memories of significant stressful life experiences, such as those underlying the posttraumatic stress disorder. Considering the safety of systemically administered cannabidiol (CBD), the major non-psychotomimetic component of Cannabis sativa, to animals and humans, the present study sought to investigate whether and how this phytocannabinoid (3-30 mg/kg intraperitoneally; i.p.) could mitigate an established memory, by blockade of its reconsolidation, evaluated in a contextual fear-conditioning paradigm in rats. We report that CBD is able to disrupt 1- and 7-days-old memories when administered immediately, but not 6 h, after their retrieval for 3 min, with the dose of 10 mg/kg being the most effective. This effect persists in either case for at least 1 week, but is prevented when memory reactivation was omitted, or when the cannabinoid type-1 receptors were antagonized selectively with AM251 (1.0 mg/kg). Pretreatment with the serotonin type-1A receptor antagonist WAY100635, however, failed to block CBD effects. These results highlight that recent and older fear memories are equally vulnerable to disruption induced by CBD through reconsolidation blockade, with a consequent long-lasting relief in contextual fear-induced freezing. Importantly, this CBD effect is dependent on memory reactivation, restricted to time window of <6h, and is possibly dependent on cannabinoid type-1 receptor-mediated signaling mechanisms. We also observed that the fear memories disrupted by CBD treatment do not show reinstatement or spontaneous recovery over 22 days. These findings support the view that reconsolidation blockade, rather than facilitated extinction, accounts for the aforementioned CBD results in our experimental conditions. Neuropsychopharmacology (2012) 37, 2132-2142; doi:10.1038/npp.2012.63; published online 2 May 2012

A spatial stochastic model for rumor transmission

We consider an interacting particle system representing the spread of a rumor by agents on the d-dimensional integer lattice. Each agent may be in any of the three states belonging to the set {0,1,2}. Here 0 stands for ignorants, 1 for spreaders and 2 for stiflers. A spreader tells the rumor to any of its (nearest) ignorant neighbors at rate lambda. At rate alpha a spreader becomes a stifler due to the action of other (nearest neighbor) spreaders. Finally, spreaders and stiflers forget the rumor at rate one. We study sufficient conditions under which the rumor either becomes extinct or survives with positive probability.

Proteins of Leishmania (Viannia) shawi confer protection associated with Th1 immune response and memory generation

Background: Leishmania (Viannia) shawi parasite was first characterized in 1989. Recently the protective effects of soluble leishmanial antigen (SLA) from L. (V.) shawi promastigotes were demonstrated using BALB/c mice, the susceptibility model for this parasite. In order to identify protective fractions, SLA was fractionated by reverse phase HPLC and five antigenic fractions were obtained. Methods: F1 fraction was purified from L. (V.) shawi parasite extract by reverse phase HPLC. BALB/c mice were immunized once a week for two consecutive weeks by subcutaneous routes in the rump, using 25 mu g of F1. After 1 and 16 weeks of last immunization, groups were challenged in the footpad with L. (V.) shawi promastigotes. After 2 months, those same mice were sacrificed and parasite burden, cellular and humoral immune responses were evaluated. Results: The F1 fraction induced a high degree of protection associated with an increase in IFN-gamma, a decrease in IL-4, increased cell proliferation and activation of CD8(+)T lymphocytes. Long-term protection was acquired in F1-immunized mice, associated with increased CD4(+) central memory T lymphocytes and activation of both CD4+ and CD8(+) T cells. In addition, F1-immunized groups showed an increase in IgG2a levels. Conclusions: The inductor capability of antigens to generate memory lymphocytes that can proliferate and secrete beneficial cytokines upon infection could be an important factor in the development of vaccine candidates against American Tegumentary Leishmaniasis.

Stochastic competitive learning in complex networks

Competitive learning is an important machine learning approach which is widely employed in artificial neural networks. In this paper, we present a rigorous definition of a new type of competitive learning scheme realized on large-scale networks. The model consists of several particles walking within the network and competing with each other to occupy as many nodes as possible, while attempting to reject intruder particles. The particle's walking rule is composed of a stochastic combination of random and preferential movements. The model has been applied to solve community detection and data clustering problems. Computer simulations reveal that the proposed technique presents high precision of community and cluster detections, as well as low computational complexity. Moreover, we have developed an efficient method for estimating the most likely number of clusters by using an evaluator index that monitors the information generated by the competition process itself. We hope this paper will provide an alternative way to the study of competitive learning.

17 beta-Estradiol replacement in young, adult and middle-aged female ovariectomized rats promotes improvement of spatial reference memory and an antidepressant effect and alters monoamines and BDNF levels in memory- and depression-related brain areas

Clinical and experimental evidence suggest that estrogens have a major impact on cognition, presenting neurotrophic and neuroprotective actions in regions involved in such function. In opposite, some studies indicate that certain hormone therapy regimens may provoke detrimental effects over female cognitive and neurological function. Therefore, we decided to investigate how estrogen treatment would influence cognition and depression in different ages. For that matter, this study assessed the effects of chronic 17 beta-estradiol treatment over cognition and depressive-like behaviors of young (3 months old), adult (7 months old) and middle-aged (12 months old) reproductive female Wistar rats. These functions were also correlated with alterations in the serotonergic system, as well as hippocampal BDNF. 17 beta-Estradiol treatment did not influence animals' locomotor activity and exploratory behavior, but it was able to improve the performance of adult and middle-aged rats in the Morris water maze, the latter being more responsive to the treatment. Young and adult rats displayed decreased immobility time in the forced swimming test, suggesting an effect of 17 beta-estradiol also over such depressive-like behavior. This same test revealed increased swimming behavior, triggered by serotonergic pathway, in adult rats. Neurochemical evaluations indicated that 17 beta-estradiol treatment was able to increase serotonin turnover rate in the hippocampus of adult rats. Interestingly, estrogen treatment increased BDNF levels from animals of all ages. These findings support the notion that the beneficial effects of 17 beta-estradiol over spatial reference memory and depressive-like behavior are evident only when hormone therapy occurs at early ages and early stages of hormonal decline. (C) 2011 Elsevier B.V. All rights reserved.

Network-based stochastic semisupervised learning

Semisupervised learning is a machine learning approach that is able to employ both labeled and unlabeled samples in the training process. In this paper, we propose a semisupervised data classification model based on a combined random-preferential walk of particles in a network (graph) constructed from the input dataset. The particles of the same class cooperate among themselves, while the particles of different classes compete with each other to propagate class labels to the whole network. A rigorous model definition is provided via a nonlinear stochastic dynamical system and a mathematical analysis of its behavior is carried out. A numerical validation presented in this paper confirms the theoretical predictions. An interesting feature brought by the competitive-cooperative mechanism is that the proposed model can achieve good classification rates while exhibiting low computational complexity order in comparison to other network-based semisupervised algorithms. Computer simulations conducted on synthetic and real-world datasets reveal the effectiveness of the model.

Maternal LAMP/p55gagHIV-1 DNA Immunization Induces In Utero Priming and a Long-Lasting Immune Response in Vaccinated Neonates

Infants born to HIV-infected mothers are at high risk of becoming infected during gestation or the breastfeeding period. A search is thus warranted for vaccine formulations that will prevent mother-to-child HIV transmission. The LAMP/gag DNA chimeric vaccine encodes the HIV-1 p55gag fused to the lysosome-associated membrane protein-1 (LAMP-1) and has been shown to enhance anti-Gag antibody (Ab) and cellular immune responses in adult and neonatal mice; such a vaccine represents a new concept in antigen presentation. In this study, we evaluated the effect of LAMP/gag DNA immunization on neonates either before conception or during pregnancy. LAMP/gag immunization of BALB/c mice before conception by the intradermal route led to the transfer of anti-Gag IgG1 Ab through the placenta and via breastfeeding. Furthermore, there were an increased percentage of CD4+ CD25+ Foxp3+ T cells in the spleens of neonates. When offspring were immunized with LAMP/gag DNA, the anti-Gag Ab response and the Gag-specific IFN-gamma-secreting cells were decreased. Inhibition of anti-Gag Ab production and cellular responses were not observed six months after immunization, indicating that maternal immunization did not interfere with the long-lasting memory response in offspring. Injection of purified IgG in conjunction with LAMP/gag DNA immunization decreased humoral and cytotoxic T-cell responses. LAMP/gag DNA immunization by intradermal injection prior to conception promoted the transfer of Ab, leading to a diminished response to Gag without interfering with the development of anti-Gag T- and B-cell memory. Finally, we assessed responses after one intravenous injection of LAMP/gag DNA during the last five days of pregnancy. The intravenous injection led to in utero immunization. In conclusion, DNA vaccine enconding LAMP-1 with Gag and other HIV-1 antigens should be considered in the development of a protective vaccine for the maternal/fetal and newborn periods.

Chains of Infinite Order, Chains with Memory of Variable Length, and Maps of the Interval

We show how to construct a topological Markov map of the interval whose invariant probability measure is the stationary law of a given stochastic chain of infinite order. In particular we characterize the maps corresponding to stochastic chains with memory of variable length. The problem treated here is the converse of the classical construction of the Gibbs formalism for Markov expanding maps of the interval.

Robustness of the non-Markovian Alzheimer walk under stochastic perturbation

The elephant walk model originally proposed by Schutz and Trimper to investigate non-Markovian processes led to the investigation of a series of other random-walk models. Of these, the best known is the Alzheimer walk model, because it was the first model shown to have amnestically induced persistence-i.e. superdiffusion caused by loss of memory. Here we study the robustness of the Alzheimer walk by adding a memoryless stochastic perturbation. Surprisingly, the solution of the perturbed model can be formally reduced to the solutions of the unperturbed model. Specifically, we give an exact solution of the perturbed model by finding a surjective mapping to the unperturbed model. Copyright (C) EPLA, 2012

PERFORMANCE EVALUATION OF RESOURCE-AWARE BUSINESS PROCESSES USING STOCHASTIC AUTOMATA NETWORKS

In this work, we study the performance evaluation of resource-aware business process models. We define a new framework that allows the generation of analytical models for performance evaluation from business process models annotated with resource management information. This framework is composed of a new notation that allows the specification of resource management constraints and a method to convert a business process specification and its resource constraints into Stochastic Automata Networks (SANs). We show that the analysis of the generated SAN model provides several performance indices, such as average throughput of the system, average waiting time, average queues size, and utilization rate of resources. Using the BP2SAN tool - our implementation of the proposed framework - and a SAN solver (such as the PEPS tool) we show through a simple use-case how a business specialist with no skills in stochastic modeling can easily obtain performance indices that, in turn, can help to identify bottlenecks on the model, to perform workload characterization, to define the provisioning of resources, and to study other performance related aspects of the business process.