alpha plus alpha scattering reexamined in the context of the Sao Paulo potential

We have analyzed a large set of alpha + alpha elastic scattering data for bombarding energies ranging from 0.6 to 29.5 MeV. Because of the complete lack of open reaction channels, the optical interaction at these energies must have a vanishing imaginary part. Thus, this system is particularly important because the corresponding elastic scattering cross sections are very sensitive to the real part of the interaction. The data were analyzed in the context of the velocity-dependent Sao Paulo potential, which is a successful theoretical model for the description of heavy-ion reactions from sub-barrier to intermediate energies. We have verified that, even in this low-energy region, the velocity dependence of the model is quite important for describing the data of the alpha + alpha system.

Comparison of (120)Sn((6)He, (6)He)(120)Sn and (120)Sn(alpha,alpha)(120)Sn elastic scattering and signatures of the (6)He neutron halo in the optical potential

Cross sections of (120)Sn(alpha,alpha)(120)Sn elastic scattering have been extracted from the alpha-particle-beam contamination of a recent (120)Sn((6)He,(6)He)(120)Sn experiment. Both reactions are analyzed using systematic double-folding potentials in the real part and smoothly varying Woods-Saxon potentials in the imaginary part. The potential extracted from the (120)Sn((6)He,(6)He)(120)Sn data may be used as the basis for the construction of a simple global (6)He optical potential. The comparison of the (6)He and alpha data shows that the halo nature of the (6)He nucleus leads to a clear signature in the reflexion coefficients eta(L) : The relevant angular momenta L with eta(L) >> 0 and eta(L) << 1 are shifted to larger L with a broader distribution. This signature is not present in the alpha-scattering data and can thus be used as a new criterion for the definition of a halo nucleus.

alpha-particle production in (6)He+(120)Sn collisions

The collision (6)He+ (120)Sn has been investigated at four energies near the Coulomb barrier. A large yield of a particles has been detected, with energies around the energy of the scattered (6)He beam. The energy and angular distributions of the a particles have been analyzed and compared with breakup and neutron transfer calculations.

Identification of the Schistosoma mansoni TNF-Alpha Receptor Gene and the Effect of Human TNF-Alpha on the Parasite Gene Expression Profile

Background: Schistosoma mansoni is the major causative agent of schistosomiasis. The parasite takes advantage of host signals to complete its development in the human body. Tumor necrosis factor-alpha (TNF-alpha) is a human cytokine involved in skin inflammatory responses, and although its effect on the adult parasite's metabolism and egg-laying process has been previously described, a comprehensive assessment of the TNF-alpha pathway and its downstream molecular effects is lacking. Methodology/Principal Findings: In the present work we describe a possible TNF-alpha receptor (TNFR) homolog gene in S. mansoni (SmTNFR). SmTNFR encodes a complete receptor sequence composed of 599 amino acids, and contains four cysteine-rich domains as described for TNFR members. Real-time RT-PCR experiments revealed that SmTNFR highest expression level is in cercariae, 3.5 (+/- 0.7) times higher than in adult worms. Downstream members of the known human TNF-alpha pathway were identified by an in silico analysis, revealing a possible TNF-alpha signaling pathway in the parasite. In order to simulate parasite's exposure to human cytokine during penetration of the skin, schistosomula were exposed to human TNF-alpha just 3 h after cercariae-to-schistosomula in vitro transformation, and large-scale gene expression measurements were performed with microarrays. A total of 548 genes with significantly altered expression were detected, when compared to control parasites. In addition, treatment of adult worms with TNF-alpha caused a significantly altered expression of 1857 genes. Interestingly, the set of genes altered in adults is different from that of schistosomula, with 58 genes in common, representing 3% of altered genes in adults and 11% in 3 h-old early schistosomula. Conclusions/Significance: We describe the possible molecular elements and targets involved in human TNF-alpha effect on S. mansoni, highlighting the mechanism by which recently transformed schistosomula may sense and respond to this host mediator at the site of cercarial penetration into the skin.

Hitting and returning to rare events for all alpha-mixing processes

We prove that for any a-mixing stationary process the hitting time of any n-string A(n) converges, when suitably normalized, to an exponential law. We identify the normalization constant lambda(A(n)). A similar statement holds also for the return time. To establish this result we prove two other results of independent interest. First, we show a relation between the rescaled hitting time and the rescaled return time, generalizing a theorem of Haydn, Lacroix and Vaienti. Second, we show that for positive entropy systems, the probability of observing any n-string in n consecutive observations goes to zero as n goes to infinity. (c) 2010 Elsevier B.V. All rights reserved.

Ric-8A, a G alpha protein guanine nucleotide exchange factor potentiates taste receptor signaling

Taste receptors for sweet, bitter and umami tastants are G-protein-coupled receptors (GPCRs). While much effort has been devoted to understanding G-protein-receptor interactions and identifying the components of the signalling cascade downstream of these receptors, at the level of the G-protein the modulation of receptor signal transduction remains relatively unexplored. In this regard a taste-specific regulator of G-protein signaling (RGS), RGS21, has recently been identified. To study whether guanine nucleotide exchange factors (GEFs) are involved in the transduction of the signal downstream of the taste GPCRs we investigated the expression of Ric-8A and Ric-8B in mouse taste cells and their interaction with G-protein subunits found in taste buds. Mammalian Ric-8 proteins were initially identified as potent GEFs for a range of G alpha subunits and Ric-8B has recently been shown to amplify olfactory signal transduction. We find that both Ric-8A and Ric-8B are expressed in a large portion of taste bud cells and that most of these cells contain IP3R-3 a marker for sweet, umami and bitter taste receptor cells. Ric-8A interacts with G alpha-gustducin and G alpha i2 through which it amplifies the signal transduction of hTas2R16, a receptor for bitter compounds. Overall, these findings are consistent with a role for Ric-8 in mammalian taste signal transduction.

Bayesian updating rules in continuous opinion dynamics models

Here, I investigate the use of Bayesian updating rules applied to modeling how social agents change their minds in the case of continuous opinion models. Given another agent statement about the continuous value of a variable, we will see that interesting dynamics emerge when an agent assigns a likelihood to that value that is a mixture of a Gaussian and a uniform distribution. This represents the idea that the other agent might have no idea about what is being talked about. The effect of updating only the first moments of the distribution will be studied, and we will see that this generates results similar to those of the bounded confidence models. On also updating the second moment, several different opinions always survive in the long run, as agents become more stubborn with time. However, depending on the probability of error and initial uncertainty, those opinions might be clustered around a central value.

Double disruption of alpha(2A)- and alpha(2C)-adrenoceptors results in sympathetic hyperactivity and high-bone-mass phenotype

Evidence demonstrates that sympathetic nervous system (SNS) activation causes osteopenia via beta(2)-adrenoceptor (beta(2)-AR) signaling. Here we show that female mice with chronic sympathetic hyperactivity owing to double knockout of adrenoceptors that negatively regulate norepinephrine release, alpha(2A)-AR and alpha(2C)-AR(alpha(2A)/alpha(2C)-ARKO), present an unexpected and generalized phenotype of high bone mass with decreased bone resorption and increased formation. In alpha(2A)/alpha(2C)-ARKO versus wild-type (WT) mice, micro-computed tomographic (mu CT) analysis showed increased, better connected, and more plate-shaped trabeculae in the femur and vertebra and increased cortical thickness in the vertebra, whereas biomechanical analysis showed increased tibial and femoral strength. Tibial mRNA expression of tartrate-resistant acid phosphatase (TRACP) and receptor activator of NF-kappa B (RANK), which are osteoclast-related factors, was lower in knockout (KO) mice. Plasma leptin and brain mRNA levels of cocaine amphetamine-regulated transcript (CART), which are factors that centrally affect bone turnover, and serum levels of estradiol were similar between mice strains. Tibial beta(2)-AR mRNA expression also was similar in KO and WT littermates, whereas alpha(2A)-, alpha(2B)- and alpha(2C)-AR mRNAs were detected in the tibia of WT mice and in osteoblast-like MC3T3-E1 cells. By immunohistochemistry, we detected alpha(2A)-, alpha(2B)-, alpha(2C)- and beta(2)-ARs in osteoblasts, osteoclasts, and chondrocytes of 18.5-day-old mouse fetuses and 35-day-old mice. Finally, we showed that isolated osteoclasts in culture are responsive to the selective alpha(2)-AR agonist clonidine and to the nonspecific alpha-AR antagonist phentolamine. These findings suggest that beta(2)-AR is not the single adrenoceptor involved in bone turnover regulation and show that alpha(2)-AR signaling also may mediate the SNS actions in the skeleton. (c) 2011 American Society for Bone and Mineral Research.

Exercise training changes IL-10/TNF-alpha ratio in the skeletal muscle of post-MI rats

Heart failure (HF) is associated with changes in the skeletal muscle (SM) which might be a consequence of the unbalanced local expression of pro- (TNF-alpha) and anti- (IL-10) inflammatory cytokines, leading to inflammation-induced myopathy, and SM wasting. This local effect of HF on SM may, on the other hand, contribute to systemic inflammation, as this tissue actively secretes cytokines. Since increasing evidence points out to an anti-inflammatory effect of exercise training, the goal of the present study was to investigate its effect in rats with HF after post-myocardial infarction (MI), with special regard to the expression of TNF-alpha and IL-10 in the soleus and extensor digitorum longus (EDL), muscles with different fiber composition. Wistar rats underwent left thoracotomy with ligation of the left coronary artery, and were randomly assigned to either a sedentary (Sham-operated and MI sedentary) or trained (Sham-operated and MI trained) group. Animals in the trained groups ran on a treadmill (0% grade at 13-20 m/min) for 60 min/day, 5 days/week, for 8-10 weeks. The training protocol was able to reverse the changes induced by MI, decreasing TNF-alpha protein (26%, P < 0.05) and mRNA (58%, P < 0.05) levels in the soleus, when compared with the sedentary MI group. Training also increased soleus IL-10 expression (2.6-fold, P < 0.001) in post-MI HF rats. As a consequence, the IL-10/TNF-alpha ratio was increased. This ""anti-inflammatory effect"" was more pronounced in the soleus than in the EDL, suggesting a fiber composition dependent response. (C) 2009 Elsevier Ltd. All rights reserved.

Tick saliva inhibits the chemotactic function of MIP-1 alpha and selectively impairs chemotaxis of immature dendritic cells by down-regulating cell-surface CCR5

Ticks are blood-feeding arthropods that secrete immunomodulatory molecules through their saliva to antagonize host inflammatory and immune responses. As dendritic cells (DCs) play a major role in host immune responses, we studied the effects of Rhipicephalus sanguineus tick saliva on DC migration and function. Bone marrow-derived immature DCs pre-exposed to tick saliva showed reduced migration towards macrophage inflammatory protein (MIP)-1 alpha, MIP-1 beta and regulated upon activation, normal T cell expressed and secreted (RANTES) chemokines in a Boyden microchamber assay. This inhibition was mediated by saliva which significantly reduced the percentage and the average cell-surface expression of CC chemokine receptor CCR5. In contrast, saliva did not alter migration of DCs towards MIP-3 beta, not even if the cells were induced for maturation. Next, we evaluated the effect of tick saliva on the activity of chemokines related to DC migration and showed that tick saliva per se inhibits the chemotactic function of MIP-1 alpha, while it did not affect RANTES, MIP-1 beta and MIP-3 beta. These data suggest that saliva possibly reduces immature DC migration, while mature DC chemotaxis remains unaffected. In support of this, we have analyzed the percentage of DCs on mice 48 h after intradermal inoculation with saliva and found that the DC turnover in the skin was reduced compared with controls. Finally, to test the biological activity of the saliva-exposed DCs, we transferred DCs pre-cultured with saliva and loaded with the keyhole limpet haemocyanin (KLH) antigen to mice and measured their capacity to induce specific T cell cytokines. Data showed that saliva reduced the synthesis of both T helper (Th)1 and Th2 cytokines, suggesting the induction of a non-polarised T cell response. These findings propose that the inhibition of DCs migratory ability and function may be a relevant mechanism used by ticks to subvert the immune response of the host. (c) 2007 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

Modeling associations between genetic markers using Bayesian networks

Motivation: Understanding the patterns of association between polymorphisms at different loci in a population ( linkage disequilibrium, LD) is of fundamental importance in various genetic studies. Many coefficients were proposed for measuring the degree of LD, but they provide only a static view of the current LD structure. Generative models (GMs) were proposed to go beyond these measures, giving not only a description of the actual LD structure but also a tool to help understanding the process that generated such structure. GMs based in coalescent theory have been the most appealing because they link LD to evolutionary factors. Nevertheless, the inference and parameter estimation of such models is still computationally challenging. Results: We present a more practical method to build GM that describe LD. The method is based on learning weighted Bayesian network structures from haplotype data, extracting equivalence structure classes and using them to model LD. The results obtained in public data from the HapMap database showed that the method is a promising tool for modeling LD. The associations represented by the learned models are correlated with the traditional measure of LD D`. The method was able to represent LD blocks found by standard tools. The granularity of the association blocks and the readability of the models can be controlled in the method. The results suggest that the causality information gained by our method can be useful to tell about the conservability of the genetic markers and to guide the selection of subset of representative markers.

Using Bayesian networks with rule extraction to infer the risk of weed infestation in a corn-crop

This paper describes the modeling of a weed infestation risk inference system that implements a collaborative inference scheme based on rules extracted from two Bayesian network classifiers. The first Bayesian classifier infers a categorical variable value for the weed-crop competitiveness using as input categorical variables for the total density of weeds and corresponding proportions of narrow and broad-leaved weeds. The inferred categorical variable values for the weed-crop competitiveness along with three other categorical variables extracted from estimated maps for the weed seed production and weed coverage are then used as input for a second Bayesian network classifier to infer categorical variables values for the risk of infestation. Weed biomass and yield loss data samples are used to learn the probability relationship among the nodes of the first and second Bayesian classifiers in a supervised fashion, respectively. For comparison purposes, two types of Bayesian network structures are considered, namely an expert-based Bayesian classifier and a naive Bayes classifier. The inference system focused on the knowledge interpretation by translating a Bayesian classifier into a set of classification rules. The results obtained for the risk inference in a corn-crop field are presented and discussed. (C) 2009 Elsevier Ltd. All rights reserved.

Effect of alpha prime due to 475 degrees C aging on fracture behavior and corrosion resistance of DIN 1.4575 and MA 956 high performance ferritic stainless steels

The 475 degrees C embrittlement in stainless steels is a well-known phenomenon associated to alpha prime (alpha`) formed by precipitation or spinodal decomposition. Many doubts still remain on the mechanism of alpha` formation and its consequence on deformation and fracture mechanisms and corrosion resistance. In this investigation, the fracture behavior and corrosion resistance of two high performance ferritic stainless steels were investigated: a superferritic DIN 1.4575 and MA 956 superalloy were evaluated. Samples of both stainless steels (SS) were aged at 475 degrees C for periods varying from 1 to 1,080 h. Their fracture surfaces were observed using scanning electron microscopy (SEM) and the cleavage planes were determined by electron backscattering diffraction (EBSD). Some samples were tested for corrosion resistance using electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization. Brittle and ductile fractures were observed in both ferritic stainless steels after aging at 475 degrees C. For aging periods longer than 500 h, the ductile fracture regions completely disappeared. The cleavage plane in the DIN 1.4575 samples aged at 475 degrees C for 1,080 h was mainly {110}, however the {102}, {314}, and {131} families of planes were also detected. The pitting corrosion resistance decreased with aging at 475 degrees C. The effect of alpha prime on the corrosion resistance was more significant in the DIN 1.4575 SS comparatively to the Incoloy MA 956.

Corrosion Versus Mechanical Tests for Indirect Detection of Alpha Prime Phase in UNS S32520 Super Duplex Stainless Steel

Alpha prime formation leads to material embrittlement and deterioration of corrosion resistance. In the present study, the mechanical and corrosion behavior of super duplex stainless steel UNS S32520 aged at 475 degrees C from 0.5 h to 1,032 h was evaluated using microhardness measurements, Charpy impact tests, electrochemical impedance spectroscopy, and cyclic polarization curves. The sensibility of these tests to the effects of alpha prime phase was investigated. The microhardness test showed a gradual increase in hardness with aging time, whereas the impact tests revealed losses of about 80% in the energy absorption capacity for the material aged for 12 h in comparison with the solution-annealed samples. The most responsive analysis was the impact test, which indirectly revealed the presence of this deleterious phase in samples aged for 0.5 h. The electrochemical impedance spectroscopy and polarization tests were not highly sensitive to the alpha prime phase unless these are present in large amounts in the stainless steel.

Double generalized linear model for tissue culture proportion data: a Bayesian perspective

Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.