INTEGRATING CLIMATE CHANGE ADAPTATION INTO SEA AN ASSESSMENT FOR SARDINIA, ITALY

Climate Change (CC) is recognized as an urgent concern, which implies negative effects on the environment, such as sea level rise, coastal erosion, fl ooding, droughts, and desertifi cation. It involves not only the environmental, but also the economic, and social sphere. The impacts of CC are addressed through two complementary strategies: mitigation and adaptation. The fi rst one operates on the reasons of CC aiming at preventing or reducing greenhouse gases emissions, while the second one focuses on the damage they can cause, aiming at minimizing it or to take advantage of opportunities that may occur. Strategic Environmental Assessment (SEA) represents a systematic and participatory decisionmaking support process, aiming at integrating environmental considerations in the elaboration of plans and programs. While SEA regards explicitly mitigation strategies, so far it still refers marginally to CC adaptation measures to be carried on when implementing spatial planning tools at the regional and local scale. The integration of SEA processes with concepts inspired to adaptation to CCs represents a powerful tool for mainstreaming the corresponding policies and strategies. In this study, we scrutinize SEA and spatial planning tools issued in Sardinia (Italy), with reference to their attitude to incorporate possible climate adaptation concerns. We are interested in proposing and applying a framework based on internationally acknowledged criteria that need to be met to properly implement climate change adaptation measures and actions in current spatial planning and SEA practices

Reactivity of the drug methimazole and its iodine adduct with elemental zinc

The reactivity of zinc complexes with N,S-donor molecules may be of relevance to the study of Zn-metalloproteins and -metalloenzymes. In this context, the zinc complex [Zn(MeImSH)2I2] was synthesised by the reaction of zinc powder with the 1 : 1 iodine adduct of the drug methimazole [(MeImSH)·I2]. The molecular structure of the complex, elucidated by X-ray diffraction analysis, showed a tetrahedral zinc(II) centre coordinated by two neutral methimazole units (through the sulfur atoms) and two iodides. From the reaction of MeImSH and Zn powder, the complex [Zn(MeImSH)(MeImS)2] (MeImS = deprotonated form of methimazole) was separated and characterised. An analysis of the crystal packing of the neutral complexes [Zn(MeImSH)2X2] (X = I, Br and Cl) and the ionic complex [Zn(MeImSH)3I]I showed that in all of the complexes the sulfur atom, in addition to binding to the metal centre, contributes to the formation of 1-D chains built via C(4)–HS and N–HX interactions in the neutral complexes, and via C(4)–HS and N–CH3S interactions in the ionic complex [Zn(MeImSH)3I]I. The deprotonation/protonation of the coordinated methimazole units can modulate the coordination environment at the Zn core. From the reaction of complex [Zn(MeImSH)3I]I with a strong non-coordinating organic base, we have shown that, as a consequence of the NH deprotonation of methimazole S-coordinated to zinc(II), the ligand coordination mode changes from S-monodentate to N,S-bridging. Correspondingly, in the complex [Zn(MeImSH)(MeImS)2], the MeImS that displays the N,S-bridging mode at zinc can be N-protonated and thereby changes to the S-monodentate coordination

Gravity model in the Korean highway

We investigate the traffic flows of the Korean highway system, which contains both public and private transportation information. We find that the traffic flow T(ij) between city i and j forms a gravity model, the metaphor of physical gravity as described in Newton's law of gravity, P(i)P(j)/r(ij)^2, where P(i) represents the population of city i and r(ij) the distance between cities i and j. It is also shown that the highway network has a heavy tail even though the road network is a rather uniform and homogeneous one. Compared to the highway network, air and public ground transportation establish inhomogeneous systems and have power-law behaviors.Comment: 13 page

Exploring the role of gut microbiota in major depressive disorder and in treatment resistance to antidepressants

Major depressive disorder (MDD) is a common severe psychiatric illness, exhibiting suboptimal response to existing pharmacological treatments. Although its etiopathogenesis is still not completely understood, recent findings suggest that an altered composition of the gut microbiota might play a role. Here we aimed to explore potential differences in the composition of the gut microbiota between patients with MDD and healthy controls (HC) and to identify possible signatures of treatment response by analyzing two groups of MDD patients characterized as treatment-resistant (TR) or responders (R) to antidepressants. Stool samples were collected from 34 MDD patients (8 TR, 19 R and 7 untreated) and 20 HC. Microbiota was characterized using the 16S metagenomic approach. A penalized logistic regression analysis algorithm was applied to identify bacterial populations that best discriminate the diagnostic groups. Statistically significant differences were identified for the families of Paenibacillaceae and Flavobacteriaceaea, for the genus Fenollaria, and the species Flintibacter butyricus, Christensenella timonensis, and Eisenbergiella massiliensis among others. The phyla Proteobacteria, Tenericutes and the family Peptostreptococcaceae were more abundant in TR, whereas the phylum Actinobacteria was enriched in R patients. Moreover, a number of bacteria only characterized the microbiota of TR patients, and many others were only detected in R. Our results confirm that dysbiosis is a hallmark of MDD and suggest that microbiota of TR patients significantly differs from responders to antidepressants. This finding further supports the relevance of an altered composition of the gut microbiota in the etiopathogenesis of MDD, suggesting a role in response to antidepressants

Involvement of gut microbiota in schizophrenia and treatment resistance to antipsychotics

The gut microbiota is constituted by more than 40, 000 bacterial species involved in key processes including high order brain functions. Altered composition of gut microbiota has been implicated in psychiatric disorders and in modulating the efficacy and safety of psychotropic medications. In this work we characterized the composition of the gut microbiota in 38 patients with schizophrenia (SCZ) and 20 healthy controls (HC), and tested if SCZ patients with different response to antipsychotics (18 patients with treatment resistant schizophrenia (TRS), and 20 responders (R)) had specific patterns of gut microbiota composition associated with different response to antipsychotics. Moreover, we also tested if patients treated with typical antipsychotics (n=20) presented significant differences when compared to patients treated with atypical antipsychotics (n=31). Our findings showed the presence of distinct composition of gut microbiota in SCZ versus HC, with several bacteria at the different taxonomic levels only present in either one group or the other. Similar findings were observed also depending on treatment response and exposure to diverse classes of antipsychotics. Our results suggest that composition of gut microbiota could constitute a biosignatures of SCZ and TRS

Spatial correlations in attribute communities

Community detection is an important tool for exploring and classifying the properties of large complex networks and should be of great help for spatial networks. Indeed, in addition to their location, nodes in spatial networks can have attributes such as the language for individuals, or any other socio-economical feature that we would like to identify in communities. We discuss in this paper a crucial aspect which was not considered in previous studies which is the possible existence of correlations between space and attributes. Introducing a simple toy model in which both space and node attributes are considered, we discuss the effect of space-attribute correlations on the results of various community detection methods proposed for spatial networks in this paper and in previous studies. When space is irrelevant, our model is equivalent to the stochastic block model which has been shown to display a detectability-non detectability transition. In the regime where space dominates the link formation process, most methods can fail to recover the communities, an effect which is particularly marked when space-attributes correlations are strong. In this latter case, community detection methods which remove the spatial component of the network can miss a large part of the community structure and can lead to incorrect results.Comment: 10 pages and 7 figure

Antidepressant and pro-motivational effects of repeated lamotrigine treatment in a rat model of depressive symptoms

Background: The antiepileptic lamotrigine is approved for maintenance treatment of bipolar disorder and augmentation therapy in treatment-resistant depression. Previous preclinical investigations showed lamotrigine antidepressant-like effects without addressing its possible activity on motivational aspects of anhedonia, a symptom clinically associated with poor treatment response and with blunted mesolimbic dopaminergic responsiveness to salient stimuli in preclinical models. Thus, in rats expressing a depressive-like phenotype we studied whether repeated lamotrigine administration restored behavioral responses to aversive and positive stimuli and the dopaminergic response to sucrose in the nucleus accumbens shell (NAcS), all disrupted by stress exposure. Methods: Depressive-like phenotype was induced in non-food-deprived adult male Sprague-Dawley rats by exposure to a chronic protocol of alternating unavoidable tail-shocks or restraint periods. We examined whether lamotrigine administration (7.5 mg/kg twice a day, i.p.) for 14–21 days restored a) the competence to escape aversive stimuli; b) the motivation to operate in sucrose self-administration protocols; c) the dopaminergic response to sucrose consumption, evaluated measuring phosphorylation levels of cAMP-regulated phosphoprotein Mr 32,000 (DARPP-32) in the NAcS, by immunoblotting. Results: Lamotrigine administration restored the response to aversive stimuli and the motivation to operate for sucrose. Moreover, it reinstated NAcS DARPP-32 phosphorylation changes in response to sucrose consumption. Limitations: The pro-motivational effects of lamotrigine that we report may not completely transpose to clinical use, since anhedonia is a multidimensional construct and the motivational aspects, although relevant, are not the only components. Conclusions: This study shows antidepressant-like and pro-motivational effects of repeated lamotrigine administration in a rat model of depressive symptoms

Temporal networks of face-to-face human interactions

The ever increasing adoption of mobile technologies and ubiquitous services allows to sense human behavior at unprecedented levels of details and scale. Wearable sensors are opening up a new window on human mobility and proximity at the finest resolution of face-to-face proximity. As a consequence, empirical data describing social and behavioral networks are acquiring a longitudinal dimension that brings forth new challenges for analysis and modeling. Here we review recent work on the representation and analysis of temporal networks of face-to-face human proximity, based on large-scale datasets collected in the context of the SocioPatterns collaboration. We show that the raw behavioral data can be studied at various levels of coarse-graining, which turn out to be complementary to one another, with each level exposing different features of the underlying system. We briefly review a generative model of temporal contact networks that reproduces some statistical observables. Then, we shift our focus from surface statistical features to dynamical processes on empirical temporal networks. We discuss how simple dynamical processes can be used as probes to expose important features of the interaction patterns, such as burstiness and causal constraints. We show that simulating dynamical processes on empirical temporal networks can unveil differences between datasets that would otherwise look statistically similar. Moreover, we argue that, due to the temporal heterogeneity of human dynamics, in order to investigate the temporal properties of spreading processes it may be necessary to abandon the notion of wall-clock time in favour of an intrinsic notion of time for each individual node, defined in terms of its activity level. We conclude highlighting several open research questions raised by the nature of the data at hand.Comment: Chapter of the book "Temporal Networks", Springer, 2013. Series: Understanding Complex Systems. Holme, Petter; Saram\"aki, Jari (Eds.

Morgagni's diaphragmatic hernia mimicking a severe congenital heart disease in a newborn: a case report

<p>Abstract</p> <p>Introduction</p> <p>Morgagni's congenital diaphragmatic defect is a rare malformation, the diagnosis of which, as in our case report, may be problematic. To the best of our knowledge, this is the first report of this kind of hernia presenting with signs and symptoms of severe cardiac malformation.</p> <p>Case presentation</p> <p>We report the case of a three-month-old Caucasian baby boy, who presented with heart failure and severe pulmonary hypertension. Compression of the heart by a bowel loop in the chest led to an incorrect diagnosis of congenital heart disease.</p> <p>Conclusions</p> <p>Even in this era of highly sophisticated diagnostic tools, a simple radiograph can provide sufficient information for a precise, rapid diagnosis.</p

Dynamical Patterns of Cattle Trade Movements

Despite their importance for the spread of zoonotic diseases, our understanding of the dynamical aspects characterizing the movements of farmed animal populations remains limited as these systems are traditionally studied as static objects and through simplified approximations. By leveraging on the network science approach, here we are able for the first time to fully analyze the longitudinal dataset of Italian cattle movements that reports the mobility of individual animals among farms on a daily basis. The complexity and inter-relations between topology, function and dynamical nature of the system are characterized at different spatial and time resolutions, in order to uncover patterns and vulnerabilities fundamental for the definition of targeted prevention and control measures for zoonotic diseases. Results show how the stationarity of statistical distributions coexists with a strong and non-trivial evolutionary dynamics at the node and link levels, on all timescales. Traditional static views of the displacement network hide important patterns of structural changes affecting nodes' centrality and farms' spreading potential, thus limiting the efficiency of interventions based on partial longitudinal information. By fully taking into account the longitudinal dimension, we propose a novel definition of dynamical motifs that is able to uncover the presence of a temporal arrow describing the evolution of the system and the causality patterns of its displacements, shedding light on mechanisms that may play a crucial role in the definition of preventive actions