A shared mechanism of muscle wasting in cancer and Huntington's disease.

Skeletal muscle loss and dysfunction in aging and chronic diseases is one of the major causes of mortality in patients, and is relevant for a wide variety of diseases such as neurodegeneration and cancer. Muscle loss is accompanied by changes in gene expression and metabolism that lead to contractile impairment and likely affect whole-body metabolism and function. The changes may be caused by inactivity, inflammation, age-related factors or unbalanced nutrition. Although links with skeletal muscle loss have been found in diseases with disparate aetiologies, for example both in Huntingtons disease (HD) and cancer cachexia, the outcome is a similar impairment and mortality. This short commentary aims to summarize recent achievements in the identification of common mechanisms leading to the skeletal muscle wasting syndrome seen in diseases as different as cancer and HD. The latter is the most common hereditary neurodegenerative disorder and muscle wasting is an important component of its pathology. In addition, possible therapeutic strategies for anti-cachectic treatment will be also discussed in the light of their translation into possible therapeutic approaches for HD

Searching for optimal variables in real multivariate stochastic data

By implementing a recent technique for the determination of stochastic eigendirections of two coupled stochastic variables, we investigate the evolution of fluctuations of NO2 concentrations at two monitoring stations in the city of Lisbon, Portugal. We analyze the stochastic part of the measurements recorded at the monitoring stations by means of a method where the two concentrations are considered as stochastic variables evolving according to a system of coupled stochastic differential equations. Analysis of their structure allows for transforming the set of measured variables to a set of derived variables, one of them with reduced stochasticity. For the specific case of NO2 concentration measures, the set of derived variables are well approximated by a global rotation of the original set of measured variables. We conclude that the stochastic sources at each station are independent from each other and typically have amplitudes of the order of the deterministic contributions. Such findings show significant limitations when predicting such quantities. Still, we briefly discuss how predictive power can be increased in general in the light of our methods

Dynamical and quasistatic structural relaxation paths in Pd_(40)Ni_(40)P_(20) glass

By sequential heat treatment of a Pd_(40)Ni_(40)P_(20) metallic glass at temperatures and durations for which α-relaxation is not possible, dynamic, and quasistatic relaxation paths below the glass transition are identified via ex situ ultrasonic measurements following each heat treatment. The dynamic relaxation paths are associated with hopping between nonequilibrium potential energy states of the glass, while the quasistatic relaxation path is associated with reversible β-relaxation events toward quasiequilibrium states. These quasiequilibrium states are identified with secondary potential energy minima that exist within the inherent energy minimum of the glass, thereby supporting the concept of the sub-basin/metabasin organization of the potential-energy landscape

Voice Flows To And Around Leaders: Understanding When Units Are Helped Or Hurt By Employee Voice

In two studies, we develop and test theory about the relationship between speaking up, one type of organizational citizenship behavior, and unit performance by accounting for where employee voice is flowing. Results from a qualitative study of managers and professionals across a variety of industries suggest that voice to targets at different formal power levels (peers or superiors) and locations in the organization (inside or outside a focal unit) differs systematically in terms of its usefulness in generating actions to a unit's benefit on the issues raised and in the likely information value of the ideas expressed. We then theorize how distinct voice flows should be differentially related to unit performance based on these core characteristics and test our hypotheses using time-lagged field data from 801 employees and their managers in 93 units across nine North American credit unions. Results demonstrate that voice flows are positively related to a unit's effectiveness when they are targeted at the focal leader of that unitwho should be able to take actionwhether from that leader's own subordinates or those in other units, and negatively related to a unit's effectiveness when they are targeted at coworkers who have little power to effect change. Together, these studies provide a structural framework for studying the nature and impact of multiple voice flows, some along formal reporting lines and others that reflect the informal communication structure within organizations. This research demonstrates that understanding the potential performance benefits and costs of voice for leaders and their units requires attention to the structure and complexity of multiple voice flows rather than to an undifferentiated amount of voice.Business Administratio

Spectral Simplicity of Apparent Complexity, Part II: Exact Complexities and Complexity Spectra

The meromorphic functional calculus developed in Part I overcomes the nondiagonalizability of linear operators that arises often in the temporal evolution of complex systems and is generic to the metadynamics of predicting their behavior. Using the resulting spectral decomposition, we derive closed-form expressions for correlation functions, finite-length Shannon entropy-rate approximates, asymptotic entropy rate, excess entropy, transient information, transient and asymptotic state uncertainty, and synchronization information of stochastic processes generated by finite-state hidden Markov models. This introduces analytical tractability to investigating information processing in discrete-event stochastic processes, symbolic dynamics, and chaotic dynamical systems. Comparisons reveal mathematical similarities between complexity measures originally thought to capture distinct informational and computational properties. We also introduce a new kind of spectral analysis via coronal spectrograms and the frequency-dependent spectra of past-future mutual information. We analyze a number of examples to illustrate the methods, emphasizing processes with multivariate dependencies beyond pairwise correlation. An appendix presents spectral decomposition calculations for one example in full detail.Comment: 27 pages, 12 figures, 2 tables; most recent version at http://csc.ucdavis.edu/~cmg/compmech/pubs/sdscpt2.ht

New approaches to model and study social networks

We describe and develop three recent novelties in network research which are particularly useful for studying social systems. The first one concerns the discovery of some basic dynamical laws that enable the emergence of the fundamental features observed in social networks, namely the nontrivial clustering properties, the existence of positive degree correlations and the subdivision into communities. To reproduce all these features we describe a simple model of mobile colliding agents, whose collisions define the connections between the agents which are the nodes in the underlying network, and develop some analytical considerations. The second point addresses the particular feature of clustering and its relationship with global network measures, namely with the distribution of the size of cycles in the network. Since in social bipartite networks it is not possible to measure the clustering from standard procedures, we propose an alternative clustering coefficient that can be used to extract an improved normalized cycle distribution in any network. Finally, the third point addresses dynamical processes occurring on networks, namely when studying the propagation of information in them. In particular, we focus on the particular features of gossip propagation which impose some restrictions in the propagation rules. To this end we introduce a quantity, the spread factor, which measures the average maximal fraction of nearest neighbors which get in contact with the gossip, and find the striking result that there is an optimal non-trivial number of friends for which the spread factor is minimized, decreasing the danger of being gossiped.Comment: 16 Pages, 9 figure

Gossip on Weighted Networks

We investigate how suitable a weighted network is for gossip spreading. The proposed model is based on the gossip spreading model introduced by Lind et.al. on unweighted networks. Weight represents "friendship." Potential spreader prefers not to spread if the victim of gossip is a "close friend". Gossip spreading is related to the triangles and cascades of triangles. It gives more insight about the structure of a network. We analyze gossip spreading on real weighted networks of human interactions. 6 co-occurrence and 7 social pattern networks are investigated. Gossip propagation is found to be a good parameter to distinguish co-occurrence and social pattern networks. As a comparison some miscellaneous networks and computer generated networks based on ER, BA, WS models are also investigated. They are found to be quite different than the human interaction networks.Comment: 8 pages, 4 figures, 1 tabl