Modularity and robustness of bone networks

Cortical bones, essential for mechanical support and structure in many animals, involve a large number of canals organized in intricate fashion. By using state-of-the art image analysis and computer graphics, the 3D reconstruction of a whole bone (phalange) of a young chicken was obtained and represented in terms of a complex network where each canal was associated to an edge and every confluence of three or more canals yielded a respective node. The representation of the bone canal structure as a complex network has allowed several methods to be applied in order to characterize and analyze the canal system organization and the robustness. First, the distribution of the node degrees (i.e. the number of canals connected to each node) confirmed previous indications that bone canal networks follow a power law, and therefore present some highly connected nodes (hubs). The bone network was also found to be partitioned into communities or modules, i.e. groups of nodes which are more intensely connected to one another than with the rest of the network. We verified that each community exhibited distinct topological properties that are possibly linked with their specific function. In order to better understand the organization of the bone network, its resilience to two types of failures (random attack and cascaded failures) was also quantified comparatively to randomized and regular counterparts. The results indicate that the modular structure improves the robustness of the bone network when compared to a regular network with the same average degree and number of nodes. The effects of disease processes (e. g., osteoporosis) and mutations in genes (e.g., BMP4) that occur at the molecular level can now be investigated at the mesoscopic level by using network based approaches.

Kinematic analysis and membership status of TWA22 AB

Context. TWA22 was initially regarded as a member of the TW Hydrae association (TWA). In addition to being one of the youngest (approximate to 8 Myr) and nearest (approximate to 20 pc) stars to Earth, TWA22 has proven to be very interesting after being resolved as a tight, very low-mass binary. This binary can serve as a very useful dynamical calibrator for pre-main sequence evolutionary models. However, its membership in the TWA has been recently questioned despite due to the lack of accurate kinematic measurements. Aims. Based on proper motion, radial velocity, and trigonometric parallax measurements, we aim here to re-analyze the membership of TWA22 to young, nearby associations. Methods. Using the ESO NTT/SUSI2 telescope, we observed TWA22 AB during 5 different observing runs over 1.2 years to measure its trigonometric parallax and proper motion. This is a part of a larger project measuring trigonometric parallaxes and proper motions of most known TWA members at a sub-milliarcsec level. HARPS at the ESO 3.6 m telescope was also used to measure the system's radial velocity over 2 years. Results. We report an absolute trigonometric parallax of TWA22 AB, pi = 57.0 +/- 0.7 mas, corresponding to a distance 17.5 +/- 0.2 pc from Earth. Measured proper motions of TWA 22AB are mu(alpha) cos(delta) = -175.8 +/- 0.8 mas/yr and mu delta = -21.3 +/- 0.8 mas/yr. Finally, from HARPS measurements, we obtain a radial velocity V(rad) = 14.8 +/- 2.1 km s(-1). Conclusions. A kinematic analysis of TWA22 AB space motion and position implies that a membership of TWA22 AB to known young, nearby associations can be excluded except for the beta Pictoris and TW Hydrae associations. Membership probabilities based on the system's Galactic space motion and/or the trace-back technique support a higher chance of being a member to the beta Pictoris association. Membership of TWA22 in the TWA cannot be fully excluded because of large uncertainties in parallax measurements and radial velocities and to the uncertain internal velocity dispersion of its members.

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.

Transmission lines distance protection using artificial neural networks

This work presents the development and implementation of an artificial neural network based algorithm for transmission lines distance protection. This algorithm was developed to be used in any transmission line regardless of its configuration or voltage level. The described ANN-based algorithm does not need any topology adaptation or ANN parameters adjustment when applied to different electrical systems. This feature makes this solution unique since all ANN-based solutions presented until now were developed for particular transmission lines, which means that those solutions cannot be implemented in commercial relays. (c) 2011 Elsevier Ltd. All rights reserved.

Simultaneous Analysis of Tramadol, O-Desmethyltramadol, and N-Desmethyltramadol Enantiomers in Rat Plasma by High-Performance Liquid Chromatography-Tandem Mass Spectrometry: Application to Pharmacokinetics

Tramadol (T) is available as a racemic mixture of (+)-trans-T and (-)-trans-T. The main metabolic pathways are O-demethylation and N-demethylation, producing trans-O-desmethyltramadol (M1) and trans-N-desmethyltramadol (M2) enantiomers, respectively. The analgesic effect of T is related to the opioid activity of (+)-trans-T and (+)-M1 and to the monoaminergic action of (+/-)-trans-T. This is the first study using tandem mass spectrometry as a detection system for the simultaneous analysis of trans-T, M1, and M2 enantiomers. The analytes were resolved on a Chiralpak (R) AD column using hexane: ethanol (95.5:4.5, v/v) plus 0.1% diethylamine as the mobile phase. The quantitation limits were 0.5 ng/ml for trans-T and M1 and 0.1 ng/ml for M2. The method developed and validated here was applied to a pharmacokinetic study in rats. Male Wistar rats (n = 6 at each time point) received a single oral dose of 20 mg/kg racemic trans-T. Blood samples were collected up to 12 h after drug administration. The kinetic disposition of trans-T and M2 was enantioselective (AUC((+)/(-)) ratio = 4.16 and 6.36, respectively). The direction and extent of enantioselectivity in the pharmacokinetics of trans-T and M2 in rats were comparable to data previously reported for healthy volunteers, suggesting that rats are a suitable model for enantioselective studies of trans-T pharmacokinetics. Chirality 23: 287-293, 2011. (C) 2010 Wiley-Liss, Inc.