Ordovician Albitites Generated by Magmatic Fluids within a Volcano-Sedimentary Sequence from NW Sardinia

n/

Relations between Natural Phenomena and Solar Activity in the Oceanographic and Forest Fields

A great number of studies on the relationship between solar activity and various terrestrial phenomena, both in the climatic and geophysical fields, have been carried out over several decades. In the present work we analyse the shorter oscillations of the solar activity such as the ones recognized in the climatic and oceanographic oscillations, for which, as it is known, longer series of observations are unavailable. Specially we analyse both the sunspot series (Wolf relative number series) considered an index of solar activity and observed since 1700 and the series of the mean sea level variation of the longest ones available in the word and relative to three oceanographic stations in Poland (Swinoujscie), France (Brest) and Italy (Venezia), whose geographical distribution made the comparison interesting. Because of the sea level evolution fluctuate in intensity, an analysis of these fluctuations and their possible correlation with the solar activity was considered of great interest to give a contribution for the explanation of the various interactions between natural phenomena and other problems relating to the forecasting of the climatic evolution

A Comprehensive Analysis of Multilayer Community Detection Algorithms for Application to EEG-Based Brain Networks

Modular organization is an emergent property of brain networks, responsible for shaping communication processes and underpinning brain functioning. Moreover, brain networks are intrinsically multilayer since their attributes can vary across time, subjects, frequency, or other domains. Identifying the modular structure in multilayer brain networks represents a gateway toward a deeper understanding of neural processes underlying cognition. Electroencephalographic (EEG) signals, thanks to their high temporal resolution, can give rise to multilayer networks able to follow the dynamics of brain activity. Despite this potential, the community organization has not yet been thoroughly investigated in brain networks estimated from EEG. Furthermore, at the state of the art, there is still no agreement about which algorithm is the most suitable to detect communities in multilayer brain networks, and a way to test and compare them all under a variety of conditions is lacking. In this work, we perform a comprehensive analysis of three algorithms at the state of the art for multilayer community detection (namely, genLouvain, DynMoga, and FacetNet) as compared with an approach based on the application of a single-layer clustering algorithm to each slice of the multilayer network. We test their ability to identify both steady and dynamic modular structures. We statistically evaluate their performances by means of ad hoc benchmark graphs characterized by properties covering a broad range of conditions in terms of graph density, number of clusters, noise level, and number of layers. The results of this simulation study aim to provide guidelines about the choice of the more appropriate algorithm according to the different properties of the brain network under examination. Finally, as a proof of concept, we show an application of the algorithms to real functional brain networks derived from EEG signals collected at rest with closed and open eyes. The test on real data provided results in agreement with the conclusions of the simulation study and confirmed the feasibility of multilayer analysis of EEG-based brain networks in both steady and dynamic conditions

Androgen receptor mutations in prostate cancer

We analyzed the frequency and relevance of mutations in the coding region of the androgen receptor (AR) in genomic DNA extracted from 137 specimens of prostate cancer. The specimens were obtained from the primary tumors of patients affected by stage B disease [15 nonmicrodissected (group 1A) and 84 microdissected (group 1B)] and from the metastatic deposits of individuals with stage D1 disease [8 nonmicrodissected (group 2A) and 30 microdissected (group 2B)] who had not undergone androgen ablation therapy. The study was conducted by PCR-single strand conformational polymorphism (SSCP) analysis of exons 2-8 in the four groups and direct sequence analysis of exon 1 in group 1B. As positive and negative controls, we used genomic DNA extracted from genital skin fibroblasts of patients affected by various forms of androgen resistance with known mutations in the AR. To control for genetic instability, PCR-SSCP analysis of exon 2 of the human progesterone receptor was carried out on each specimen. The overall number of mutations detected was 11 (8%). No mutations were detected in any of the 99 patients with stage B disease. Eleven mutations were detected in exons 2-8 in 8 of the 38 patients with stage D1 disease (all in group 2B). Simultaneous analysis of exon 2 of the progesterone receptor was carried out, and no SSCP changes were identified. These data suggest that AR mutations are rare and presumably do not play a role in the initial phase of prostatic carcinogenesis. The presence of a significant number of AR mutations in metastatic disease indicates that mutations of this molecule may play a role in the most advanced phases of the natural history of this disease, either by facilitating growth or acquisition of the metastatic phenotype

The modular organization of brain cortical connectivity across the human lifespan

The network architecture of the human brain contributes in shaping neural activity, influencing cognitive and behavioral processes. The availability of neuroimaging data across the lifespan allows us to monitor how this architecture reorganizes, influenced by processes like learning, adaptation, maturation, and senescence. Changing patterns in brain connectivity can be analyzed with the tools of network science, which can be used to reveal organizational principles such as modular network topology. The identification of network modules is fundamental, as they parse the brain into coherent sub-systems and allow for both functional integration and segregation among different brain areas. In this work we examined the brain's modular organization by developing an ensemble-based multilayer network approach, allowing us to link changes of structural connectivity patterns to development and aging. We show that modular structure exhibits both linear and nonlinear age-related trends. In the early and late lifespan, communities are more modular, and we track the origins of this high modularity to two different substrates in brain connectivity, linked to the number and the weights of the intra-clusters edges. We also demonstrate that aging leads to a progressive and increasing reconfiguration of modules and a redistribution across hemispheres. Finally, we identify those brain regions that most contribute to network reconfiguration and those that remain more stable across the lifespan

Multi-modal and multi-subject modular organization of human brain networks

The human brain is a complex network of anatomically interconnected brain areas. Spontaneous neural activity is constrained by this architecture, giving rise to patterns of statistical dependencies between the activity of remote neural elements. The non-trivial relationship between structural and functional connectivity poses many unsolved challenges about cognition, disease, development, learning and aging. While numerous studies have focused on statistical relationships between edge weights in anatomical and functional networks, less is known about dependencies between their modules and communities. In this work, we investigate and characterize the relationship between anatomical and functional modular organization of the human brain, developing a novel multi-layer framework that expands the classical concept of multi-layer modularity. By simultaneously mapping anatomical and functional networks estimated from different subjects into communities, this approach allows us to carry out a multi-subject and multi-modal analysis of the brain's modular organization. Here, we investigate the relationship between anatomical and functional modules during resting state, finding unique and shared structures. The proposed framework constitutes a methodological advance in the context of multi-layer network analysis and paves the way to further investigate the relationship between structural and functional network organization in clinical cohorts, during cognitively demanding tasks, and in developmental or lifespan studies

Distinct profile of inflammatory and remodelling biomarkers in sputum of severe asthmatic patients with or without persistent airway obstruction

Background: Both inflammatory and remodelling processes are associated with irreversible airway obstruction observed in severe asthma. Our aim was to characterize a group of severe asthmatic patients with or without persistent airway obstruction in relation to specific sputum inflammatory and remodelling biomarkers. Methods: Forty-five patients under regular high-dose inhaled corticosteroid/ß-2agonist treatment were studied, after a follow-up period of at least 2 years, with a minimum of 4 visits. Periostin, TGF-ß, RANTES, IL-8, GM-CSF, FGF-2, and cell counts were measured in induced sputum. Serum periostin was also measured. Results: Sputum induction was successfully performed in all but 5 patients. There were no significant differences in demographic and clinical data between patients with non-persistent obstruction (NO: FEV1/VC>88%pred.) and those with persistent obstruction (O: a not completely reversible obstruction with FEV1/VC<88%pred. at each visit before the study visit). Patients with persistent obstruction had significantly higher sputum periostin and TGF-ß concentrations than NO patients and a trend of higher serum periostin levels. GM-CSF and FGF-2 were significantly increased in NO compared to O patients. No differences between groups were found for RANTES, IL-8 and differential cell counts. Sputum periostin inversely correlated with functional parameters (prebronch. FEV1: rho = −0.36, p < 0.05; postbronch. FEV1: rho = −0.33, p = 0.05). Patients with high sputum periostin concentration (>103.3 pg/ml: median value) showed an absolute number of sputum eosinophils significantly higher than patients with low sputum periostin; this behavior was unobserved when serum periostin was considered. Conclusions: Only periostin and TGF-ß identified a subgroup of severe asthmatic patients with persistent airway obstruction. Sputum periostin was also inversely associated with FEV1 and proved to be a more sensitive biomarker than serum periostin to identify severe asthmatics with higher sputum eosinophilia

Sialoendoscopy: state of the art, challenges and further perspectives. Round Table, 101st SIO National Congress, Catania 2014

This draft of the Official Round Table held during the 101st SIO National Congress is an updated review on sialoendoscopy, a technique used for diagnosis and treatment of obstructive pathologies of salivary glands in a minimally invasive fashion. This review treats many aspects of salivary gland endoscopy, starting from anatomy to deal with the more advanced surgical techniques and analyses the main decisional algorithms proposed in the literature. In addition, particular attention was directed to the current limitations of this technique and to the potential developments that sialoendoscopy could have in the near future