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

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

Doping and Respiratory System

Historically many different drugs have been used to enhance sporting performances. The magic elixir is still elusive and the drugs are still used despite the heavy adverse effects. The respiratory system is regularly involved in this research probably because of its central location in the body with several connections to the cardiovascular system. Moreover people are aware that O2 consumption and its delivery to mitochondria firstly depend on ventilation and on the respiratory exchanges. The second step consists in the tendency to increase V'O2 max and to prolong its availability with the aim of improving the endurance time and to relieve the fatigue. Many methods and substances had been used in order to gain an artificial success. Additional oxygen, autologous and homologous transfusion and erithropoietin, mainly the synthetic type, have been administered with the aim of increasing the amount of oxygen being delivered to the tissues. Some compounds like stimulants and caffeine are endowed of excitatory activity on the CNS and stimulate pulmonary ventilation. They did not prove to have any real activity in supporting the athletic performances. Beta-adrenergic drugs, particularly clenbuterol, when administered orally or parentherally develop a clear illicit activity on the myosin fibres and on the muscles as a whole. Salbutamol, terbutaline, salmeterol and formoterol are legally admitted when administrated by MDI in the treatment of asthma. The prevalence of asthma and bronchial hyperactivity is higher in athletes than amongst the general population. This implies that clear rules must be provided to set a correct diagnosis of asthma in the athletes and a correct therapy to align with the actual guidelines according to the same rights of the "other" asthmatic patients

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

Association between anti-citrullinated alpha enolase antibodies and clinical features in a cohort of patients with rheumatoid arthritis: a pilot study.

In recent years several antibodies against citrullinated peptides (ACPAs) have been identified in patients with rheumatoid arthritis (RA) and their pathogenic, diagnostic and prognostic significance is under intense investigation. Among ACPAs, those targeting citrullinated alpha enolase (anti-CEP1) have been identified in RA but data about their ability to predict the development of erosive disease are conflicting. Furthermore, no data are currently available concerning their possible association with extra-articular manifestations (EAMs) in RA. The aim of this study was to investigate the prevalence and significance of anti-CEP1 from a prognostic point of view. In this pilot study we confirmed that anti-CEP1 Abs are associated with higher prevalence of bone erosions, but we also provided the first evidence of an association between anti-CEP1 Abs and RA interstitial lung disease (ILD). These results provide the basis to investigate the association between anti-CEP1 Abs and EAMs in larger cohorts of RA patients to possibly confirm its role as biomarker for RA-ILD

Transoral-transpharyngeal CO2 laser en bloc excision of voluminous left recurrent laryngeal nerve schwannoma: Case report and review of the literature

Recurrent nerve laryngeal schwannoma is a rare benign tumor that, in expert hands, can be treated by transoral CO2 laser surgery

Skin rash and response to cetuximab treatment: a retrospective single-center analysis

Background: The standard of care for patients with recurrent/metastatic head and neck squamous cell cancer (R/M HNSCC) not susceptible for surgery or reirradiation is chemotherapy with 5-FU and cisplatin plus cetuximab. Skin rash (SR) is a common adverse event of cetuximab. In patients treated with cetuximab for colorectal cancer there is strong evidence of a better outcome in those who undergo moderate or high grade of SR, and some retrospective data seem to confirm this finding in HNSCC. We report our experience. Materials and methods: We retrospectively reviewed 107 patients treated with cetuximab for R/M HNSCC from January 2014 to December 2016. Patients were divided in two groups by the grade of SR (G0-1 and G2-4), conforming to Common Terminology Criteria for Adverse Events (CTCAE) v 4.0. Progression-free survival (PFS) was computed as time of progression or death since the date of assessment of recurrent/metastatic disease. Overall response rate (ORR) was computed as the sum of partial and complete responses and evaluated according to RECIST 1.1. PFS and ORR were correlated to the grade of rash. Results: 67 patients were evaluable for PFS: among them PFS was significantly longer (p 0.0014) in those who underwent a G2-4 rash (9,3 months) vs G0-1 (4,9 months). Hazard Ratio was 2,445 (CI 1.412-4.232). 95 patients were evaluable for ORR: among them G0-1 group had 4,2%, while G2-4 group had 36,8% of ORR. Conclusions: Our results support data of literature on improved outcome according to the development of skin rash in HNSCC. SR might be considered a predictive marker of response in these patients; nonetheless further ad hoc studies would be interesting