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.

Gene Expression Noise in Spatial Patterning: hunchback Promoter Structure Affects Noise Amplitude and Distribution in Drosophila Segmentation

Positional information in developing embryos is specified by spatial gradients of transcriptional regulators. One of the classic systems for studying this is the activation of the hunchback (hb) gene in early fruit fly (Drosophila) segmentation by the maternally-derived gradient of the Bicoid (Bcd) protein. Gene regulation is subject to intrinsic noise which can produce variable expression. This variability must be constrained in the highly reproducible and coordinated events of development. We identify means by which noise is controlled during gene expression by characterizing the dependence of hb mRNA and protein output noise on hb promoter structure and transcriptional dynamics. We use a stochastic model of the hb promoter in which the number and strength of Bcd and Hb (self-regulatory) binding sites can be varied. Model parameters are fit to data from WT embryos, the self-regulation mutant hb(14F), and lacZ reporter constructs using different portions of the hb promoter. We have corroborated model noise predictions experimentally. The results indicate that WT (self-regulatory) Hb output noise is predominantly dependent on the transcription and translation dynamics of its own expression, rather than on Bcd fluctuations. The constructs and mutant, which lack self-regulation, indicate that the multiple Bcd binding sites in the hb promoter (and their strengths) also play a role in buffering noise. The model is robust to the variation in Bcd binding site number across a number of fly species. This study identifies particular ways in which promoter structure and regulatory dynamics reduce hb output noise. Insofar as many of these are common features of genes (e. g. multiple regulatory sites, cooperativity, self-feedback), the current results contribute to the general understanding of the reproducibility and determinacy of spatial patterning in early development.

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

Identification of COL6A1 as a differentially expressed gene in human astrocytomas

Diffuse infiltrating gliomas are the most common tumors of the central nervous system. Gliomas are classified by the WHO according to their histopathological and clinical characteristics into four classes: grade I (pilocytic astrocytoma), grade II (diffuse astrocytoma), grade III (anaplastic astrocytoma), and grade IV (glioblastoma multiforme). Several genes have already been correlated with astrocytomas, but many others are yet to be uncovered. By analyzing the public SAGE data from 21 patients, comprising low malignant grade astrocytomas and glioblastomas, we found COL6A1 to be differentially expressed, confirming this finding by real time RT-PCR in 66 surgical samples. To the best of our knowledge, COL6A1 has never been described in gliomas. The expression of this gene has significantly different means when normal glia is compared with low-grade astrocytomas (grades I and II) and high-grade astrocytomas (grades III and IV), with a tendency to be greater in higher grade samples, thus rendering it a powerful tumor marker.

Inference of gene regulatory networks from time series by Tsallis entropy

Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

Characterization of global transcription profile of normal and HPV-immortalized keratinocytes and their response to TNF treatment

Background: Persistent infection by high risk HPV types (e.g. HPV-16, -18, -31, and -45) is the main risk factor for development of cervical intraepithelial neoplasia and cervical cancer. Tumor necrosis factor (TNF) is a key mediator of epithelial cell inflammatory response and exerts a potent cytostatic effect on normal or HPV16, but not on HPV18 immortalized keratinocytes. Moreover, several cervical carcinoma-derived cell lines are resistant to TNF anti-proliferative effect suggesting that the acquisition of TNF-resistance may constitute an important step in HPV-mediated carcinogenesis. In the present study, we compared the gene expression profiles of normal and HPV16 or 18 immortalized human keratinocytes before and after treatment with TNF for 3 or 60 hours. Methods: In this study, we determined the transcriptional changes 3 and 60 hours after TNF treatment of normal, HPV16 and HPV18 immortalized keratinocytes by microarray analysis. The expression pattern of two genes observed by microarray was confirmed by Northern Blot. NF-kappa B activation was also determined by electrophoretic mobility shift assay (EMSA) using specific oligonucleotides and nuclear protein extracts. Results: We observed the differential expression of a common set of genes in two TNF-sensitive cell lines that differs from those modulated in TNF-resistant ones. This information was used to define genes whose differential expression could be associated with the differential response to TNF, such as: KLK7 (kallikrein 7), SOD2 (superoxide dismutase 2), 100P (S100 calcium binding protein P), PI3 (protease inhibitor 3, skin-derived), CSTA (cystatin A), RARRES1 (retinoic acid receptor responder 1), and LXN (latexin). The differential expression of the KLK7 and SOD2 transcripts was confirmed by Northern blot. Moreover, we observed that SOD2 expression correlates with the differential NF-kappa B activation exhibited by TNF-sensitive and TNF-resistant cells. Conclusion: This is the first in depth analysis of the differential effect of TNF on normal and HPV16 or HPV18 immortalized keratinocytes. Our findings may be useful for the identification of genes involved in TNF resistance acquisition and candidate genes which deregulated expression may be associated with cervical disease establishment and/or progression.

Construct and Compare Gene Coexpression Networks with DAPfinder and DAPview

Background: DAPfinder and DAPview are novel BRB-ArrayTools plug-ins to construct gene coexpression networks and identify significant differences in pairwise gene-gene coexpression between two phenotypes. Results: Each significant difference in gene-gene association represents a Differentially Associated Pair (DAP). Our tools include several choices of filtering methods, gene-gene association metrics, statistical testing methods and multiple comparison adjustments. Network results are easily displayed in Cytoscape. Analyses of glioma experiments and microarray simulations demonstrate the utility of these tools. Conclusions: DAPfinder is a new friendly-user tool for reconstruction and comparison of biological networks.

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.

Beta-2 adrenergic receptor gene polymorphisms Gln27Glu, Arg16Gly in patients with heart failure

Background -: Beta-2 adrenergic receptor gene polymorphisms Gln27Glu, Arg16Gly and Thr164Ile were suggested to have an effect in heart failure. We evaluated these polymorphisms relative to clinical characteristics and prognosis of alarge cohort of patients with heart failure of different etiologies. Methods -: We studied 501 patients with heart failure of different etiologies. Mean age was 58 years (standard deviation 14.4 years), 298 (60%) were men. Polymorphisms were identified by polymerase chain reaction-restriction fragment length polymorphism. Results -: During the mean follow-up of 12.6 months (standard deviation 10.3 months), 188 (38%) patients died. Distribution of genotypes of polymorphism Arg16Gly was different relative to body mass index (chi(2) = 9.797; p = 0.04). Overall the probability of survival was not significantly predicted by genotypes of Gln27Glu, Arg16Gly, or Thr164Ile. Allele and haplotype analysis also did not disclose any significant difference regarding mortality. Exploratory analysis through classification trees pointed towards a potential association between the Gln27Glu polymorphism and mortality in older individuals. Conclusion -: In this study sample, we were not able to demonstrate an overall influence of polymorphisms Gln27Glu and Arg16Gly of beta-2 receptor gene on prognosis. Nevertheless, Gln27Glu polymorphism may have a potential predictive value in older individuals.

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.

Haplotype distribution of five nuclear genes based on network genealogies and Bayesian inference indicates that Trypanosoma cruzi hybrid strains are polyphyletic

Chagas disease is still a major public health problem in Latin America. Its causative agent, Trypanosoma cruzi, can be typed into three major groups, T. cruzi I, T. cruzi II and hybrids. These groups each have specific genetic characteristics and epidemiological distributions. Several highly virulent strains are found in the hybrid group; their origin is still a matter of debate. The null hypothesis is that the hybrids are of polyphyletic origin, evolving independently from various hybridization events. The alternative hypothesis is that all extant hybrid strains originated from a single hybridization event. We sequenced both alleles of genes encoding EF-1 alpha, actin and SSU rDNA of 26 T. cruzi strains and DHFR-TS and TR of 12 strains. This information was used for network genealogy analysis and Bayesian phylogenies. We found T. cruzi I and T. cruzi II to be monophyletic and that all hybrids had different combinations of T. cruzi I and T. cruzi II haplotypes plus hybrid-specific haplotypes. Bootstrap values (networks) and posterior probabilities (Bayesian phylogenies) of clades supporting the monophyly of hybrids were far below the 95% confidence interval, indicating that the hybrid group is polyphyletic. We hypothesize that T. cruzi I and T. cruzi II are two different species and that the hybrids are extant representatives of independent events of genome hybridization, which sporadically have sufficient fitness to impact on the epidemiology of Chagas disease.

Schistosoma mansoni Tegument Protein Sm29 Is Able to Induce a Th1-Type of Immune Response and Protection against Parasite Infection

Background: Schistosomiasis continues to be a significant public health problem. This disease affects 200 million people worldwide and almost 800 million people are at risk of acquiring the infection. Although vaccine development against this disease has experienced more failures than successes, encouraging results have recently been obtained using membrane-spanning protein antigens from the tegument of Schistosoma mansoni. Our group recently identified Sm29, another antigen that is present at the adult worm tegument surface. In this study, we investigated murine cellular immune responses to recombinant (r) Sm29 and tested this protein as a vaccine candidate. Methods and Findings: We first show that Sm29 is located on the surface of adult worms and lung-stage schistosomula through confocal microscopy. Next, immunization of mice with rSm29 engendered 51%, 60% and 50% reduction in adult worm burdens, in intestinal eggs and in liver granuloma counts, respectively (p<0.05). Protective immunity in mice was associated with high titers of specific anti-Sm29 IgG1 and IgG2a and elevated production of IFN-gamma, TNF-alpha and IL-12, a typical Th1 response. Gene expression analysis of worms recovered from rSm29 vaccinated mice relative to worms from control mice revealed a significant (q<0.01) down-regulation of 495 genes and up-regulation of only 22 genes. Among down-regulated genes, many of them encode surface antigens and proteins associated with immune signals, suggesting that under immune attack schistosomes reduce the expression of critical surface proteins. Conclusion: This study demonstrates that Sm29 surface protein is a new vaccine candidate against schistosomiasis and suggests that Sm29 vaccination associated with other protective critical surface antigens is the next logical strategy for improving protection.

Mild Mitochondrial Uncoupling and Calorie Restriction Increase Fasting eNOS, Akt and Mitochondrial Biogenesis

Enhanced mitochondrial biogenesis promoted by eNOS activation is believed to play a central role in the beneficial effects of calorie restriction (CR). Since treatment of mice with dinitrophenol (DNP) promotes health and lifespan benefits similar to those observed in CR, we hypothesized that it could also impact biogenesis. We found that DNP and CR increase citrate synthase activity, PGC-1 alpha, cytochrome c oxidase and mitofusin-2 expression, as well as fasting plasma levels of NO(center dot) products. In addition, eNOS and Akt phosphorylation in skeletal muscle and visceral adipose tissue was activated in fasting CR and DNP animals. Overall, our results indicate that systemic mild uncoupling activates eNOS and Akt-dependent pathways leading to mitochondrial biogenesis.

Influence of the bacterioplankton community of a tropical eutrophic lagoon on the bacterial community of its neighbouring ocean

The Rodrigo de Freitas lagoon (RFL) is a tropical eutrophic coastal ecosystem located in the urban area of Rio de Janeiro, Brazil. This environment consists of freshwater but has communication with the ocean through a channel (Jardim de Alah`s Channel). The aim of this study was to evaluate the influence of lagoon water on the nearby ocean using molecular and traditional microbiological methods. We hypothesised that due to the eutrophic low-salinity environment, the bacterioplankton community from the RFL would have a native ""brackish"" composition influenced by both freshwater and marine phylotypes, and that bacterial phylotypes of this community would be detected in oceanic samples closer to the channel between the lagoon and the ocean. The cultivation and microscopy experiments clearly showed this influence. Bacterial cell counts revealed that the greater amounts of bacterial cells present in the lagoon increased the observed values seen at oceanic stations near the channel. The Denaturing gradient gel eletrophoresis community profiles also showed a clear influence of Rodrigo de Freitas lagoon waters on the adjacent beaches. The band patterns found for the stations near the channel showed that these communities were mixtures of the communities of the lagoon and sea, and as the distance from the channel increased, the samples became more similar to ocean bacterial communities. A 16S rRNA gene clone library was constructed using a sample acquired from the connection point between the lagoon and the ocean. Around 52% of the sequences in the library showed similarity to the genus Proteobacteria (1% Alpha, 21% Beta, 19% Gamma and 29% unclassified Proteobacteria), and the second most abundant genus was Bacteroidetes, with 15% of the total clones. The results showed that the structure of the bacterial community had both freshwater and marine characteristics.