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The Italian Neuroimaging Network Initiative (INNI) is an expanding repository of brain MRI data from multiple sclerosis (MS) patients recruited at four Italian MRI research sites. We describe the raw data quality of resting-state functional MRI (RS-fMRI) time-series in INNI and the inter-site variability in functional connectivity (FC) features after unified automated data preprocessing. MRI datasets from 489 MS patients and 246 healthy control (HC) subjects were retrieved from the INNI database. Raw data quality metrics included temporal signal-to-noise ratio (tSNR), spatial smoothness (FWHM), framewise displacement (FD), and differential variation in signals (DVARS). Automated preprocessing integrated white-matter lesion segmentation (SAMSEG) into a standard fMRI pipeline (fMRIPrep). FC features were calculated on pre-processed data and harmonized between sites (Combat) prior to assessing general MS-related alterations. Across centers (both groups), median tSNR and FWHM ranged from 47 to 84 and from 2.0 to 2.5, and median FD and DVARS ranged from 0.08 to 0.24 and from 1.06 to 1.22. After preprocessing, only global FC-related features were significantly correlated with FD or DVARS. Across large-scale networks, age/sex/FD-adjusted and harmonized FC features exhibited both inter-site and site-specific inter-group effects. Significant general reductions were obtained for somatomotor and limbic networks in MS patients (vs. HC). The implemented procedures provide technical information on raw data quality and outcome of fully automated preprocessing that might serve as reference in future RS-fMRI studies within INNI. The unified pipeline introduced little bias across sites and appears suitable for multisite FC analyses on harmonized network estimates.

Social comparison is the process through which people compare their opinions, abilities, behaviours and emotions with those of others for selfevaluation and to obtain an external guide for themselves. There is wide evidence that social comparison is a pervasive behaviour, particularly among adults, both in their social life and in online relationships established through Social Network Sites. A growing number of studies show unmistakably that online social comparison through social media can influence people's everyday life. Features such as Facebook's News Feed or Instagram's Daily Stories provide a stream of information about friends' lives, achievements, abilities and personality, creating a perfect environment for social comparison to take place. Researchers have therefore begun to examine more closely how social comparison operates on Social Network Sites, given that social media allows users to constantly monitor what friends are doing and talking about, and how others are responding. In this chapter, online social comparison is analysed from a social psychological perspective by examining the classical theories and the most recent theoretical contributions of the construct, and above all by highlighting the main differences in interpretations about its occurrence in face-to-face and social media contexts. Recent perspectives on clinical outcomes and mental health are also discussed.

Esclerosi múltiple; Diagnòstic diferencial; Imatges Esclerosis múltiple; Diagnóstico diferencial; Imagen Multiple sclerosis; Differential diagnosis; Imaging Background: Differentiating multiple sclerosis (MS) from vascular risk factor (VRF)-small vessel disease (SVD) can be challenging. Objective and Methods: In order to determine whether or not pontine lesion location is a useful discriminator of MS and VRF-SVD, we classified pontine lesions on brain magnetic resonance imaging (MRI) as central or peripheral in 93 MS cases without VRF, 108 MS patients with VRF and 43 non-MS cases with VRF. Results: MS without VRF were more likely to have peripheral pons lesions (31.2%, 29/93) than non-MS with VRF (0%, 0/43) (Exp(B) = 29.8; 95% confidence interval (CI) = (1.98, 448.3); p = 0.014) but there were no significant differences regarding central pons lesions between MS without VRF (5.4%, 5/93) and non-MS with VRF patients (16.3%, 7/43) (Exp(B) = 0.89; 95% CI = (0.2, 3.94); p = 0.87). The presence of peripheral pons lesions discriminated between MS and VRF-SVD with 100% (95% CI = (91.8, 100)) specificity. The proportion of peripheral pons lesions in MS with VRF (30.5%, 33/108) was similar to that seen in MS without VRF (31.2%, 29/93, p = 0.99). Central lesions occurred in similar frequency in MS with VRF (8.3%, 9/108) and non-MS with VRF (16.3%, 7/43, p = 0.15). Conclusion: Peripheral pons lesion location is a good discriminator of MS from vascular lesions. The author(s) received no financial support for the research, authorship and/or publication of this article.

The study of the seismic vulnerability of historical centres, especially in the Mediterranean zone, is one of the main issues in ongoing scientific research. This is due, on the one hand, to the continuous evolution of the seismic demand and, on the other hand, to the high vulnerability of the masonry existing building stock. The seismic events of the last few years highlighted the necessity to perform a large-scale survey of the huge amount of masonry buildings in historical centres, in order to provide prioritization scales for planning mitigation strategies. With this regard, the scientific literature provides several methodologies that allow a rapid assessment based on pre- defined survey forms. The data obtained from the surveys are usually used as the input for algorithms aimed at estimating the vulnerability level of the building investigated. The aim of the present work is to propose a general framework for analysing seismic vulnerability of masonry historical centres and deriving fragility curves basing on multiple data sources. In particular, using data collected through existing territorial databases, supplemented by a set of vulnerability forms available for the city centre of the Municipality of Foggia, Southern Italy, some vulnerability classes are defined. Based on the mechanical and geometrical features identified for each class, several ideal and representative buildings are generated, and their seismic behaviour is investigated through the variation of significant parameters. At the end, the capacity of the buildings is evaluated by performing simplified nonlinear analyses and, subsequently, by estimating the damage level of the sample through the definition of regional fragility curves.

We assessed 168 patients with multiple sclerosis (MS) by force platform to obtain the dual-task cost (DTC) of balance, that is, the change in postural sway from quiet standing to dual-task condition (Stroop test). After a median follow-up time of 3.5 years from this assessment, disability progression occurred in 45 (27%) patients. Disability progression was predicted by the adoption of a ‘posture second’ strategy, that is, values of DTC of balance exceeding those obtained from 62 healthy controls, even after controlling by demographic and clinical characteristics. The DTC of balance may potentially represent a novel and easy tool to predict MS progression.

The Italian Neuroimaging Network Initiative (INNI) supports the creation of a repository, where MRI, clinical, and neuropsychological data from multiple sclerosis (MS) patients and healthy controls are collected from Italian Research Centers with internationally recognized expertise in MRI applied to MS. However, multicenter MRI data integration needs standardization and quality control (QC). This study aimed to implement quantitative measures for characterizing the standardization and quality of MRI collected within INNI. MRI scans of 423 MS patients, including 3D T1- and T2-weighted, were obtained from INNI repository (from Centers A, B, C, and D). QC measures were implemented to characterize: (1) head positioning relative to the magnet isocenter; (2) intensity inhomogeneity; (3) relative image contrast between brain tissues; and (4) image artefacts. Centers A and D showed the most accurate subject positioning within the MR scanner (median z-offsets = − 2.6 ± 1.7cm and − 1.1 ± 2cm). A low, but significantly different, intensity inhomogeneity on 3D T1-weighted MRI was found between all centers (p < 0.05), except for Centers A and C that showed comparable image bias fields. Center D showed the highest relative contrast between gray and normal appearing white matter (NAWM) on 3D T1-weighed MRI (0.63 ± 0.04), while Center B showed the highest relative contrast between NAWM and MS lesions on FLAIR (0.21 ± 0.06). Image artefacts were mainly due to brain movement (60%) and ghosting (35%). The implemented QC procedure ensured systematic data quality assessment within INNI, thus making available a huge amount of high-quality MRI to better investigate pathophysiological substrates and validate novel MRI biomarkers in MS.