Structural Brain Connectivity in School-Age Preterm Infants Provides Evidence for Impaired Networks Relevant for Higher Order Cognitive Skills and Social Cognition.

Extreme prematurity and pregnancy conditions leading to intrauterine growth restriction (IUGR) affect thousands of newborns every year and increase their risk for poor higher order cognitive and social skills at school age. However, little is known about the brain structural basis of these disabilities. To compare the structural integrity of neural circuits between prematurely born controls and children born extreme preterm (EP) or with IUGR at school age, long-ranging and short-ranging connections were noninvasively mapped across cortical hemispheres by connection matrices derived from diffusion tensor tractography. Brain connectivity was modeled along fiber bundles connecting 83 brain regions by a weighted characterization of structural connectivity (SC). EP and IUGR subjects, when compared with controls, had decreased fractional anisotropy-weighted SC (FAw-SC) of cortico-basal ganglia-thalamo-cortical loop connections while cortico-cortical association connections showed both decreased and increased FAw-SC. FAw-SC strength of these connections was associated with poorer socio-cognitive performance in both EP and IUGR children.

Beyond contact-based transmission networks: the role of spatial coincidence.

Animal societies rely on interactions between group members to effectively communicate and coordinate their actions. To date, the transmission properties of interaction networks formed by direct physical contacts have been extensively studied for many animal societies and in all cases found to inhibit spreading. Such direct interactions do not, however, represent the only viable pathways. When spreading agents can persist in the environment, indirect transmission via 'same-place, different-time' spatial coincidences becomes possible. Previous studies have neglected these indirect pathways and their role in transmission. Here, we use rock ant colonies, a model social species whose flat nest geometry, coupled with individually tagged workers, allowed us to build temporally and spatially explicit interaction networks in which edges represent either direct physical contacts or indirect spatial coincidences. We show how the addition of indirect pathways allows the network to enhance or inhibit the spreading of different types of agent. This dual-functionality arises from an interplay between the interaction-strength distribution generated by the ants' movement and environmental decay characteristics of the spreading agent. These findings offer a general mechanism for understanding how interaction patterns might be tuned in animal societies to control the simultaneous transmission of harmful and beneficial agents.

Networks of noisy oscillators with correlated degree and frequency dispersion

We investigate how correlations between the diversity of the connectivity of networks and the dynamics at their nodes affect the macroscopic behavior. In particular, we study the synchronization transition of coupled stochastic phase oscillators that represent the node dynamics. Crucially in our work, the variability in the number of connections of the nodes is correlated with the width of the frequency distribution of the oscillators. By numerical simulations on Erdös-Rényi networks, where the frequencies of the oscillators are Gaussian distributed, we make the counterintuitive observation that an increase in the strength of the correlation is accompanied by an increase in the critical coupling strength for the onset of synchronization. We further observe that the critical coupling can solely depend on the average number of connections or even completely lose its dependence on the network connectivity. Only beyond this state, a weighted mean-field approximation breaks down. If noise is present, the correlations have to be stronger to yield similar observations.

Bayesian Networks for the Age Classification of Living Individuals: a Study on Transition Analysis

Over the past few decades, age estimation of living persons has represented a challenging task for many forensic services worldwide. In general, the process for age estimation includes the observation of the degree of maturity reached by some physical attributes, such as dentition or several ossification centers. The estimated chronological age or the probability that an individual belongs to a meaningful class of ages is then obtained from the observed degree of maturity by means of various statistical methods. Among these methods, those developed in a Bayesian framework offer to users the possibility of coherently dealing with the uncertainty associated with age estimation and of assessing in a transparent and logical way the probability that an examined individual is younger or older than a given age threshold. Recently, a Bayesian network for age estimation has been presented in scientific literature; this kind of probabilistic graphical tool may facilitate the use of the probabilistic approach. Probabilities of interest in the network are assigned by means of transition analysis, a statistical parametric model, which links the chronological age and the degree of maturity by means of specific regression models, such as logit or probit models. Since different regression models can be employed in transition analysis, the aim of this paper is to study the influence of the model in the classification of individuals. The analysis was performed using a dataset related to the ossifications status of the medial clavicular epiphysis and results support that the classification of individuals is not dependent on the choice of the regression model.

Probabilistic age classification with Bayesian networks: a study on the ossification status of the medial clavicular epiphysis

In the past few decades, the rise of criminal, civil and asylum cases involving young people lacking valid identification documents has generated an increase in the demand of age estimation. The chronological age or the probability that an individual is older or younger than a given age threshold are generally estimated by means of some statistical methods based on observations performed on specific physical attributes. Among these statistical methods, those developed in the Bayesian framework allow users to provide coherent and transparent assignments which fulfill forensic and medico-legal purposes. The application of the Bayesian approach is facilitated by using probabilistic graphical tools, such as Bayesian networks. The aim of this work is to test the performances of the Bayesian network for age estimation recently presented in scientific literature in classifying individuals as older or younger than 18 years of age. For these exploratory analyses, a sample related to the ossification status of the medial clavicular epiphysis available in scientific literature was used. Results obtained in the classification are promising: in the criminal context, the Bayesian network achieved, on the average, a rate of correct classifications of approximatively 97%, whilst in the civil context, the rate is, on the average, close to the 88%. These results encourage the continuation of the development and the testing of the method in order to support its practical application in casework.

Increased voltage-dependent K+ channel Kv1.3 and Kv1.5 expression correlates with leiomyosarcoma aggressiveness

Voltage-dependent K+ channels (Kv) are involved in the proliferation and differentiation of mammalian cells, since Kv antagonists impair cell cycle progression. Although myofibers are terminally differentiated, some myoblasts may re-enter the cell cycle and proliferate. Since Kv1.3 and Kv1.5 expression is remodeled during tumorigenesis and is involved in smooth muscle proliferation, the purpose of this study was to analyze the expression of Kv1.3 and Kv1.5 in smooth muscle neoplasms. In the present study, we examined human samples of smooth muscle tumors together with healthy speci­mens. Thus, leiomyoma (LM) and leiomyosarcoma (LMS) tumors were analyzed. Results showed that Kv1.3 was poorly expressed in the healthy muscle and indolent LM specimens, whereas aggressive LMS showed high levels of Kv1.3 expression. Kv1.5 staining was correlated with malignancy. The findings show a remodeling of Kv1.3 and Kv1.5 in human smooth muscle sarcoma. A correlation of Kv1.3 and Kv1.5 expression with tumor aggressiveness was observed. Thus, our results indicate Kv1.5 and Kv1.3 as potential tumorigenic targets for aggressive human LMS.

Research networks and inventors’ mobility as drivers of innovation evidence from Europe

We investigate the importance of the labour mobility of inventors, as well as the scale, extent and density of their collaborative research networks, for regional innovation outcomes. To do so, we apply a knowledge production function framework at the regional level and include inventors’ networks and their labour mobility as regressors. Our empirical approach takes full account of spatial interactions by estimating a spatial lag model together, where necessary, with a spatial error model. In addition, standard errors are calculated using spatial heteroskedasticity and autocorrelation consistent estimators to ensure their robustness in the presence of spatial error autocorrelation and heteroskedasticity of unknown form. Our results point to the existence of a robust positive correlation between intraregional labour mobility and regional innovation, whilst the relationship with networks is less clear. However, networking across regions positively correlates with a region’s innovation intensity.

Cosmological networks

Networks often represent systems that do not have a long history of study in traditional fields of physics; albeit, there are some notable exceptions, such as energy landscapes and quantum gravity. Here, we consider networks that naturally arise in cosmology. Nodes in these networks are stationary observers uniformly distributed in an expanding open Friedmann-Lemaitre-Robertson-Walker universe with any scale factor and two observers are connected if one can causally influence the other. We show that these networks are growing Lorentz-invariant graphs with power-law distributions of node degrees. These networks encode maximum information about the observable universe available to a given observer.

Customer driven business model – connecting customer value to firm resources in ICT value networks

The objective of this thesis is to provide a business model framework that connects customer value to firm resources and explains the change logic of the business model. Strategic supply management and especially dynamic value network management as its scope, the dissertation is based on basic economic theories, transaction cost economics and the resource-based view. The main research question is how the changing customer values should be taken into account when planning business in a networked environment. The main question is divided into questions that form the basic research problems for the separate case studies presented in the five Publications. This research adopts the case study strategy, and the constructive research approach within it. The material consists of data from several Delphi panels and expert workshops, software pilot documents, company financial statements and information on investor relations on the companies’ web sites. The cases used in this study are a mobile multi-player game value network, smart phone and “Skype mobile” services, the business models of AOL, eBay, Google, Amazon and a telecom operator, a virtual city portal business system and a multi-play offering. The main contribution of this dissertation is bridging the gap between firm resources and customer value. This has been done by theorizing the business model concept and connecting it to both the resource-based view and customer value. This thesis contributes to the resource-based view, which deals with customer value and firm resources needed to deliver the value but has a gap in explaining how the customer value changes should be connected to the changes in key resources. This dissertation also provides tools and processes for analyzing the customer value preferences of ICT services, constructing and analyzing business models and business concept innovation and conducting resource analysis.

Post-translational modifications of voltage-gated sodium channels in chronic pain syndromes.

In the peripheral sensory nervous system the neuronal expression of voltage-gated sodium channels (Navs) is very important for the transmission of nociceptive information since they give rise to the upstroke of the action potential (AP). Navs are composed of nine different isoforms with distinct biophysical properties. Studying the mutations associated with the increase or absence of pain sensitivity in humans, as well as other expression studies, have highlighted Nav1.7, Nav1.8, and Nav1.9 as being the most important contributors to the control of nociceptive neuronal electrogenesis. Modulating their expression and/or function can impact the shape of the AP and consequently modify nociceptive transmission, a process that is observed in persistent pain conditions. Post-translational modification (PTM) of Navs is a well-known process that modifies their expression and function. In chronic pain syndromes, the release of inflammatory molecules into the direct environment of dorsal root ganglia (DRG) sensory neurons leads to an abnormal activation of enzymes that induce Navs PTM. The addition of small molecules, i.e., peptides, phosphoryl groups, ubiquitin moieties and/or carbohydrates, can modify the function of Navs in two different ways: via direct physical interference with Nav gating, or via the control of Nav trafficking. Both mechanisms have a profound impact on neuronal excitability. In this review we will discuss the role of Protein Kinase A, B, and C, Mitogen Activated Protein Kinases and Ca++/Calmodulin-dependent Kinase II in peripheral chronic pain syndromes. We will also discuss more recent findings that the ubiquitination of Nav1.7 by Nedd4-2 and the effect of methylglyoxal on Nav1.8 are also implicated in the development of experimental neuropathic pain. We will address the potential roles of other PTMs in chronic pain and highlight the need for further investigation of PTMs of Navs in order to develop new pharmacological tools to alleviate pain.

A medição da grandeza practical peak voltage na prática radiológica

OBJETIVO: O objetivo deste trabalho foi estudar a grandeza practical peak voltage (PPV), determinada a partir da forma de onda de tensão aplicada a tubos radiológicos, e compará-la com algumas definições de kVp para diferentes tipos de geradores: monofásico (onda completa, clínico), trifásico (seis pulsos, clínico) e potencial constante (industrial). MATERIAIS E MÉTODOS: O trabalho envolveu a comparação do PPV medido invasivamente (utilizando um divisor de tensão) com a resposta de dois medidores comerciais não invasivos, além dos valores de outras grandezas usadas para medição da tensão de pico aplicada ao tubo de raios X, e a análise da variação do PPV com a ondulação percentual da tensão (ripple). RESULTADOS: Verificou-se que a diferença entre o PPV e as definições mais comuns de tensão de pico aumenta com o ripple. Os valores de PPV variaram em até 3% e 5%, respectivamente, na comparação entre medições invasivas e não invasivas feitas com os equipamentos trifásico e monofásico. CONCLUSÃO: Os resultados demonstraram que a principal grandeza de influência que afeta o PPV é o ripple da tensão. Adicionalmente, valores de PPV obtidos com medidores não invasivos devem ser avaliados considerando que eles dependem da taxa de aquisição e da forma de onda adquirida pelo instrumento.