beta-Hydroxy-beta-methylbutyrate (HM beta) supplementation stimulates skeletal muscle hypertrophy in rats via the mTOR pathway

beta-Hydroxy-beta-methylbutyrate (HM beta) supplementation is used to treat cancer, sepsis and exercise-induced muscle damage. However, its effects on animal and human health and the consequences of this treatment in other tissues (e. g., fat and liver) have not been examined. The purpose of this study was to evaluate the effects of HM beta supplementation on skeletal muscle hypertrophy and the expression of proteins involved in insulin signalling. Rats were treated with HM beta (320 mg/kg body weight) or saline for one month. The skeletal muscle hypertrophy and insulin signalling were evaluated by western blotting, and hormonal concentrations were evaluated using ELISAs. HM beta supplementation induced muscle hypertrophy in the extensor digitorum longus (EDL) and soleus muscles and increased serum insulin levels, the expression of the mammalian target of rapamycin (mTOR) and phosphorylation of p70S6K in the EDL muscle. Expression of the insulin receptor was increased only in liver. Thus, our results suggest that HM beta supplementation can be used to increase muscle mass without adverse health effects.

PAKs supplement improves immune status and body composition but not muscle strength in resistance trained individuals

Mixed formula supplements are very popular among recreational and professional weightlifters. They are usually known as PAKs and they are supposed to have a synergistic effect of their different nutrients. The purpose of this study was to determine the effects of chronic (4 weeks) PAKS supplementation in combination with strength training on body composition, immune status and performance measures in recreationally trained individuals with or without PAKs supplementation. Methods: Twelve male subjects (Placebo n = 6 and PAKs supplement n = 6) were recruited for this study. The body composition, one maximum strength repetition tests and immune status were assessed before and after 4 week supplementation. Our data showed that, 4 week PAK supplementation associated with strength exercise not was effective in change strength than compared with placebo group. However, we observed that, PAK supplement was able to improve immune status and reduced body composition when compared with placebo group. These results indicate that, a mixed formula supplement is able to improve immune status and body composition but not maximum strength in recreational strength trained subjects in a 4 weeks period.

Effect of oat bran on time to exhaustion, glycogen content and serum cytokine profile following exhaustive exercise

The aim of this study was to evaluate the effect of oat bran supplementation on time to exhaustion, glycogen stores and cytokines in rats submitted to training. The animals were divided into 3 groups: sedentary control group (C), an exercise group that received a control chow (EX) and an exercise group that received a chow supplemented with oat bran (EX-O). Exercised groups were submitted to an eight weeks swimming training protocol. In the last training session, the animals performed exercise to exhaustion, (e.g. incapable to continue the exercise). After the euthanasia of the animals, blood, muscle and hepatic tissue were collected. Plasma cytokines and corticosterone were evaluated. Glycogen concentrations was measured in the soleus and gastrocnemius muscles, and liver. Glycogen synthetase-alpha gene expression was evaluated in the soleus muscle. Statistical analysis was performed using a factorial ANOVA. Time to exhaustion of the EX-O group was 20% higher (515 +/- 3 minutes) when compared with EX group (425 +/- 3 minutes) (p = 0.034). For hepatic glycogen, the EX-O group had a 67% higher concentrations when compared with EX (p = 0.022). In the soleus muscle, EX-O group presented a 59.4% higher glycogen concentrations when compared with EX group (p = 0.021). TNF-alpha was decreased, IL-6, IL-10 and corticosterone increased after exercise, and EX-O presented lower levels of IL-6, IL-10 and corticosterone levels in comparison with EX group. It was concluded that the chow rich in oat bran increase muscle and hepatic glycogen concentrations. The higher glycogen storage may improve endurance performance during training and competitions, and a lower post-exercise inflammatory response can accelerate recovery.

Antimicrobial activities of Garcinia kola on oral Fusobacterium nucleatum and biofilm

The extracts from the root, bark and seed of Garcinia kola are currently used in traditional medicine in Nigeria. The aim of this study was to evaluate the inhibitory activity of crude extracts of G. kola on Fusobacterium nucleatum isolated from the oral cavity. Methanol and aqueous extracts were prepared from the seed and the minimal inhibitory concentration was evaluated by the agar dilution method, using a Wilkins-Chalgren agar supplemented with horse blood (5%), hemin (5 mu g/ml) and menadione (1 mu g/ml). Antimicrobial activity of plant extracts on microbial biofilms was determined in microtiter plates. The seed of G. kola demonstrated significant inhibitory action on F. nucleatum isolates at a concentration of 1.25 and 12.5 mg/ml for amoxicillin resistant strain. It was able to inhibit the microbial biofilm formed by the association of F. nucleatum with Porphyromonas gingivalis ATCC 33277, Aggregatibacter actinomycetemcomitans ATCC 33384 and Prevotella intermedia ATCC 2564 at a concentration of 25 mg/ml. The in-vitro inhibitory effect of G. kola on F. nucleatum population suggests a potential role for its use in oral hygiene.

Characterization of subgraph relationships and distribution in complex networks

A network can be analyzed at different topological scales, ranging from single nodes to motifs, communities, up to the complete structure. We propose a novel approach which extends from single nodes to the whole network level by considering non-overlapping subgraphs (i.e. connected components) and their interrelationships and distribution through the network. Though such subgraphs can be completely general, our methodology focuses on the cases in which the nodes of these subgraphs share some special feature, such as being critical for the proper operation of the network. The methodology of subgraph characterization involves two main aspects: (i) the generation of histograms of subgraph sizes and distances between subgraphs and (ii) a merging algorithm, developed to assess the relevance of nodes outside subgraphs by progressively merging subgraphs until the whole network is covered. The latter procedure complements the histograms by taking into account the nodes lying between subgraphs, as well as the relevance of these nodes to the overall subgraph interconnectivity. Experiments were carried out using four types of network models and five instances of real-world networks, in order to illustrate how subgraph characterization can help complementing complex network-based studies.

The gross theory model for neutrino-nucleus cross-section

The nuclear gross theory, originally formulated by Takahashi and Yamada (1969 Prog. Theor. Phys. 41 1470) for the beta-decay, is applied to the electronic-neutrino nucleus reactions, employing a more realistic description of the energetics of the Gamow-Teller resonances. The model parameters are gauged from the most recent experimental data, both for beta(-)-decay and electron capture, separately for even-even, even-odd, odd-odd and odd-even nuclei. The numerical estimates for neutrino-nucleus cross-sections agree fairly well with previous evaluations done within the framework of microscopic models. The formalism presented here can be extended to the heavy nuclei mass region, where weak processes are quite relevant, which is of astrophysical interest because of its applications in supernova explosive nucleosynthesis.

Manipulation of quantum state transfer in cold Rydberg atom collisions

We investigate the role of the dc Stark effect in multilevel pairwise interactions between cold Rydberg atoms. We have observed the decay of nD + nD quasi-molecules by detecting the products in the (n + 2) P state after pulsed excitation for 29 <= n <= 41. The decay rate can be manipulated with a dc electric field and requires a consideration of the multilevel nature of the process to explain the observations. The time dependence of the (n + 2) P signal is found to support a time-dependent picture of the dynamics.

Musical genres: beating to the rhythms of different drums

Online music databases have increased significantly as a consequence of the rapid growth of the Internet and digital audio, requiring the development of faster and more efficient tools for music content analysis. Musical genres are widely used to organize music collections. In this paper, the problem of automatic single and multi-label music genre classification is addressed by exploring rhythm-based features obtained from a respective complex network representation. A Markov model is built in order to analyse the temporal sequence of rhythmic notation events. Feature analysis is performed by using two multi-variate statistical approaches: principal components analysis (unsupervised) and linear discriminant analysis (supervised). Similarly, two classifiers are applied in order to identify the category of rhythms: parametric Bayesian classifier under the Gaussian hypothesis (supervised) and agglomerative hierarchical clustering (unsupervised). Qualitative results obtained by using the kappa coefficient and the obtained clusters corroborated the effectiveness of the proposed method.

Connectivity and dynamics of neuronal networks as defined by the shape of individual neurons

Biological neuronal networks constitute a special class of dynamical systems, as they are formed by individual geometrical components, namely the neurons. In the existing literature, relatively little attention has been given to the influence of neuron shape on the overall connectivity and dynamics of the emerging networks. The current work addresses this issue by considering simplified neuronal shapes consisting of circular regions (soma/axons) with spokes (dendrites). Networks are grown by placing these patterns randomly in the two-dimensional (2D) plane and establishing connections whenever a piece of dendrite falls inside an axon. Several topological and dynamical properties of the resulting graph are measured, including the degree distribution, clustering coefficients, symmetry of connections, size of the largest connected component, as well as three hierarchical measurements of the local topology. By varying the number of processes of the individual basic patterns, we can quantify relationships between the individual neuronal shape and the topological and dynamical features of the networks. Integrate-and-fire dynamics on these networks is also investigated with respect to transient activation from a source node, indicating that long-range connections play an important role in the propagation of avalanches.

Border detection in complex networks

One important issue implied by the finite nature of real-world networks regards the identification of their more external (border) and internal nodes. The present work proposes a formal and objective definition of these properties, founded on the recently introduced concept of node diversity. It is shown that this feature does not exhibit any relevant correlation with several well-established complex networks measurements. A methodology for the identification of the borders of complex networks is described and illustrated with respect to theoretical (geographical and knitted networks) as well as real-world networks (urban and word association networks), yielding interesting results and insights in both cases.

NMR analog of Bell's inequalities violation test

In this paper, we present an analog of Bell's inequalities violation test for N qubits to be performed in a nuclear magnetic resonance (NMR) quantum computer. This can be used to simulate or predict the results for different Bell's inequality tests, with distinct configurations and a larger number of qubits. To demonstrate our scheme, we implemented a simulation of the violation of the Clauser, Horne, Shimony and Holt (CHSH) inequality using a two-qubit NMR system and compared the results to those of a photon experiment. The experimental results are well described by the quantum mechanics theory and a local realistic hidden variables model (LRHVM) that was specifically developed for NMR. That is why we refer to this experiment as a simulation of Bell's inequality violation. Our result shows explicitly how the two theories can be compatible with each other due to the detection loophole. In the last part of this work, we discuss the possibility of testing some fundamental features of quantum mechanics using NMR with highly polarized spins, where a strong discrepancy between quantum mechanics and hidden variables models can be expected.

Molecular determinants of improved cathepsin B inhibition by new cystatins obtained by DNA shuffling

Background: Cystatins are inhibitors of cysteine proteases. The majority are only weak inhibitors of human cathepsin B, which has been associated with cancer, Alzheimer's disease and arthritis. Results: Starting from the sequences of oryzacystatin-1 and canecystatin-1, a shuffling library was designed and a hybrid clone obtained, which presented higher inhibitory activity towards cathepsin B. This clone presented two unanticipated point mutations as well as an N-terminal deletion. Reversing each point mutation independently or both simultaneously abolishes the inhibitory activity towards cathepsin B. Homology modeling together with experimental studies of the reverse mutants revealed the likely molecular determinants of the improved inhibitory activity to be related to decreased protein stability. Conclusion: A combination of experimental approaches including gene shuffling, enzyme assays and reverse mutation allied to molecular modeling has shed light upon the unexpected inhibitory properties of certain cystatin mutants against Cathepsin B. We conclude that mutations disrupting the hydrophobic core of phytocystatins increase the flexibility of the N-terminus, leading to an increase in inhibitory activity. Such mutations need not affect the inhibitory site directly but may be observed distant from it and manifest their effects via an uncoupling of its three components as a result of increased protein flexibility.

Ultra-high-energy cosmic rays from centaurus A: jet interaction with gaseous shells

Ultra-high-energy cosmic rays (UHECRs), with energies above similar to 6 x 10(19) eV, seem to show a weak correlation with the distribution of matter relatively near to us in the universe. It has earlier been proposed that UHECRs could be accelerated in either the nucleus or the outer lobes of the nearby radio galaxy Cen A. We show that UHECR production at a spatially intermediate location about 15 kpc northeast from the nucleus, where the jet emerging from the nucleus is observed to strike a large star-forming shell of gas, is a plausible alternative. A relativistic jet is capable of accelerating lower energy heavy seed cosmic rays (CRs) to UHECRs on timescales comparable to the time it takes the jet to pierce the large gaseous cloud. In this model, many CRs arising from a starburst, with a composition enhanced in heavy elements near the knee region around PeV, are boosted to ultra-high energies by the relativistic shock of a newly oriented jet. This model matches the overall spectrum shown by the Auger data and also makes a prediction for the chemical composition as a function of particle energy. We thus predict an observable anisotropy in the composition at high energy in the sense that lighter nuclei should preferentially be seen toward the general direction of Cen A. Taking into consideration the magnetic field models for the Galactic disk and a Galactic magnetic wind, this scenario may resolve the discrepancy between HiRes and Auger results concerning the chemical composition of UHECRs.

A HARD AND VARIABLE X-RAY EMISSION FROM THE MASSIVE EMISSION-LINE STAR HD 157832

We report the discovery with XMM-Newton of a hard-thermal (T similar to 130 MK) and variable X-ray emission from the Be star HD 157832, a new member of the puzzling class of gamma-Cas-like Be/X-ray systems. Recent optical spectroscopy reveals the presence of a large/dense circumstellar disk seen at intermediate/high inclination. With a B1.5V spectral type, HD 157832 is the coolest gamma-Cas analog known. In addition, its non-detection in the ROSAT all-sky survey shows that its average soft X-ray luminosity varied by a factor larger than similar to 3 over a time interval of 14 yr. These two remarkable features, ""low"" effective temperature, and likely high X-ray variability turn HD 157832 into a promising object for understanding the origin of the unusually high-temperature X-ray emission in these systems.

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/.