11 research outputs found
Converting genetic network oscillations into somite spatial pattern
In most vertebrate species, the body axis is generated by the formation of
repeated transient structures called somites. This spatial periodicity in
somitogenesis has been related to the temporally sustained oscillations in
certain mRNAs and their associated gene products in the cells forming the
presomatic mesoderm. The mechanism underlying these oscillations have been
identified as due to the delays involved in the synthesis of mRNA and
translation into protein molecules [J. Lewis, Current Biol. {\bf 13}, 1398
(2003)]. In addition, in the zebrafish embryo intercellular Notch signalling
couples these oscillators and a longitudinal positional information signal in
the form of an Fgf8 gradient exists that could be used to transform these
coupled temporal oscillations into the observed spatial periodicity of somites.
Here we consider a simple model based on this known biology and study its
consequences for somitogenesis. Comparison is made with the known properties of
somite formation in the zebrafish embryo . We also study the effects of
localized Fgf8 perturbations on somite patterning.Comment: 7 pages, 7 figure
The Naming Game in Social Networks: Community Formation and Consensus Engineering
We study the dynamics of the Naming Game [Baronchelli et al., (2006) J. Stat.
Mech.: Theory Exp. P06014] in empirical social networks. This stylized
agent-based model captures essential features of agreement dynamics in a
network of autonomous agents, corresponding to the development of shared
classification schemes in a network of artificial agents or opinion spreading
and social dynamics in social networks. Our study focuses on the impact that
communities in the underlying social graphs have on the outcome of the
agreement process. We find that networks with strong community structure hinder
the system from reaching global agreement; the evolution of the Naming Game in
these networks maintains clusters of coexisting opinions indefinitely. Further,
we investigate agent-based network strategies to facilitate convergence to
global consensus.Comment: The original publication is available at
http://www.springerlink.com/content/70370l311m1u0ng3
Opinion dynamics: models, extensions and external effects
Recently, social phenomena have received a lot of attention not only from
social scientists, but also from physicists, mathematicians and computer
scientists, in the emerging interdisciplinary field of complex system science.
Opinion dynamics is one of the processes studied, since opinions are the
drivers of human behaviour, and play a crucial role in many global challenges
that our complex world and societies are facing: global financial crises,
global pandemics, growth of cities, urbanisation and migration patterns, and
last but not least important, climate change and environmental sustainability
and protection. Opinion formation is a complex process affected by the
interplay of different elements, including the individual predisposition, the
influence of positive and negative peer interaction (social networks playing a
crucial role in this respect), the information each individual is exposed to,
and many others. Several models inspired from those in use in physics have been
developed to encompass many of these elements, and to allow for the
identification of the mechanisms involved in the opinion formation process and
the understanding of their role, with the practical aim of simulating opinion
formation and spreading under various conditions. These modelling schemes range
from binary simple models such as the voter model, to multi-dimensional
continuous approaches. Here, we provide a review of recent methods, focusing on
models employing both peer interaction and external information, and
emphasising the role that less studied mechanisms, such as disagreement, has in
driving the opinion dynamics. [...]Comment: 42 pages, 6 figure
Quality of life, clinical outcome, personality and coping in chronic hemodialysis patients
Rational: Our aim was to investigate the quality of life (QoL) in 103 patients undergoing chronic hemodialysis (HD) in an integrated assessment of clinical, personological, and adaptation parameters, also in a non-urban context. Objectives: We collected data from all chronic HD patients attending four HD units. Clinical status was assessed by Kidney Disease Outcomes Quality Initiative (KDOQI) guidelines and by Age-adjusted Charlson Comorbidity Index (ACCI). Patients completed the following questionnaires: Kidney Disease Quality of Life Short Form (KDQOL-SF), Pittsburgh Sleep Quality Index (PSQI). Personality profile and coping style were assessed by Temperament and Character Inventory (TCI) revised and Coping Inventory for Stressful Situation (CISS). Data were analyzed by conventional descriptive statistics. Multiple forward stepwise linear regression analyses were performed. Main findings: Variables significantly associated with physical and mental components of KDQOL-SF were: intact parathyroid hormone (iPTH) (p=.004; p=.0015), typology of cohabitant (family member or not) (p=.022; p=.007), years of dialysis (p=.022; p=.048). Variables associated with mental component of KDQOL-SF were: PSQI (p=.000), task-coping (p=.000), avoidance-coping (p=.003), work status (p=.021). Principle conclusions: Our results suggest the importance of an integrated and multidirectional management of patients chronically undergoing HD and living in a non-urban context
Workshop on the Italian Pharmacovigilance System in the International Context: Critical Issues and Perspectives
Risk for chronic kidney disease in the general population: Italian reports for World Kidney Days 2007-2009
The prevalence of chronic kidney disease (CKD) has rapidlyincreased in recent decades in many countries, leading toconsistent economic implications. Considering the fact thatpatients surviving to CKD often develop end-stage renal disease,the number of patients requiring replacement therapyreached 169/million population (pmp) in Italy in 2004 and342 pmp in the Unites States. Furthermore, CKD weighs onpatients survival with a considerably increased cardiovascular(CV) morbidity and mortality
Drugs-Induced Pathological Gambling: An Analysis of Italian Spontaneous Reporting System
Evolutionary Developmental Biology and the Limits of Philosophical Accounts of Mechanistic Explanation
Abstract Evolutionary developmental biology (evo-devo) is considered a ‘mechanistic science, ’ in that it causally explains morphological evolution in terms of changes in developmental mechanisms. Evo-devo is also an interdisciplinary and integrative approach, as its explanations use contributions from many fields and pertain to different levels of organismal organization. Philosophical accounts of mechanistic explanation are currently highly prominent, and have been particularly able to capture the integrative nature of multifield and multilevel explanations. However, I argue that evo-devo demonstrates the need for a broadened philosophical conception of mechanisms and mechanistic explanation. Mechanistic explanation (in terms of the qualitative interactions of the structural parts of a whole) has been developed as an alternative to the traditional idea of explanation as derivation from laws or quantitative principles. Against the picture promoted by Carl Craver, that mathematical models describe but do not explain, my discussion of cases from the strand of evo-devo which is concerned with developmental processes points to qualitative phenomena where quantitative mathematical models are an indispensable part of the explanation. While philosophical accounts have focused on the actual organization and operation of mechanisms, properties of developmental mechanisms that are about how a mechanism reacts to modifications are of major evolutionary significance, including robustness, phenotypic plasticity, and modularity. A philosophical conception of mechanisms is needed that takes into account quantitative changes, transient entities and the generation of novel types of entities, feedback loops and complex interaction networks, emergent properties, and, in particular, functional-dynamical aspects of mechanisms, including functional (as opposed to structural) organization and distributed, system-wide phenomena. I conclude with general remarks on philosophical accounts of explanation