Corrigendum: Computational Methods for Resting-State EEG of Patients With Disorders of Consciousness

An author name was incorrectly spelled as \u201cUrszulaMarkowska-Kacznar.\u201d The correct spelling is \u201cUrszulaMarkowska-Kaczmar.\u201d The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated

B Lymphocytes in Multiple Sclerosis : Bregs and BTLA/CD272 Expressing-CD19+ Lymphocytes Modulate Disease Severity

B lymphocytes contribute to the pathogenesis of Multiple Sclerosis (MS) by secreting antibodies and producing cytokines. This latter function was analyzed in myelin olygodendrocyte protein (MOG)-stimulated CD19+B lymphocytes of 71 MS patients with different disease phenotypes and 40 age- and sex-matched healthy controls (HC). Results showed that: 1) CD19+/TNF alpha+, CD19+/IL-12+ and CD19+/IFN gamma+ lymphocytes are significantly increased in primary progressive (PP) compared to secondary progressive (SP), relapsing-remitting (RR), benign (BE) MS and HC; 2) CD19+/IL-6+ lymphocytes are significantly increased in PP, SP and RR compared to BEMS and HC; and 3) CD19+/IL-13+, CD19+/IL-10+, and CD19+/IL-10+/TGF beta+ (Bregs) B lymphocytes are reduced overall in MS patients compared to HC. B cells expressing BTLA, a receptor whose binding to HVEM inhibits TcR-initiated cytokine production, as well as CD19+/ BTLA+/IL-10+ cells were also significantly overall reduced in MS patients compared to HC. Analyses performed in RRMS showed that fingolimod-induced disease remission is associated with a significant increase in Bregs, CD19+/BTLA+, and CD19+/BTLA+/IL-10+ B lymphocytes. B lymphocytes participate to the pathogenesis of MS via the secretion of functionally-diverse cytokines that might play a role in determining disease phenotypes. The impairment of Bregs and CD19+/BTLA+ cells, in particular, could play an important pathogenic role in MS

The NLRP3 and NLRP1 Inflammasomes are Activated in Alzheimer’s Disease

Background Interleukin-1 beta (IL-1\u3b2) and its key regulator, the inflammasome, are suspected to play a role in the neuroinflammation observed in Alzheimer\u2019s disease (AD); no conclusive data are nevertheless available in AD patients. Results mRNA for inflammasome components (NLRP1, NLRP3, PYCARD, caspase 1, 5 and 8) and downstream effectors (IL-1\u3b2, IL-18) was up-regulated in severe and MILD AD. Monocytes co-expressing NLRP3 with caspase 1 or caspase 8 were significantly increased in severe AD alone, whereas those co-expressing NLRP1 and NLRP3 with PYCARD were augmented in both severe and MILD AD. Activation of the NLRP1 and NLRP3 inflammasomes in AD was confirmed by confocal microscopy proteins co-localization and by the significantly higher amounts of the pro-inflammatory cytokines IL-1\u3b2 and IL-18 being produced by monocytes. In MCI, the expression of NLRP3, but not the one of PYCARD or caspase 1 was increased, indicating that functional inflammasomes are not assembled in these individuals: this was confirmed by lack of co-localization and of proinflammatory cytokines production. Conclusions The activation of at least two different inflammasome complexes explains AD-associated neuroinflammation. Strategies targeting inflammasome activation could be useful in the therapy of AD

Tectono-stratigraphic response of the Sandino Forearc Basin (N-Costa Rica and W-Nicaragua) to episodes of rough crust and oblique subduction

The southern Central American active margin is a world-class site where past and present subduction processes have been extensively studied. Tectonic erosion/accretion and oblique/orthogonal subduction are thought to alternate in space and time along the Middle American Trench. These processes may cause various responses in the upper plate, such as uplift/subsidence, deformation, and volcanic arc migration/ shut-off. We present an updated stratigraphic framework of the Late Cretaceous– Cenozoic Sandino Forearc Basin (SFB) which provides evidence of sedimentary response to tectonic events. Since its inception, the basin was predominantly filled with deep-water volcaniclastic deposits. In contrast, shallow-water deposits appeared episodically in the basin record and are considered as tectonic event markers. The SFB stretches for about 300 km and varies in thickness from 5 km (southern part) to about 16 km (northern part). The drastic, along-basin, thickness variation appears to be the result of (1) differential tectonic evolutions and (2) differential rates of sediment supply. (1) The northern SFB did not experience major tectonic events. In contrast, the reduced thickness of the southern SFB (5 km) is the result of at least four uplift phases related to the collision/accretion of bathymetric reliefs on the incoming plate: (i) the accretion of a buoyant oceanic plateau (Nicoya Complex) during the middle Campanian; (ii) the collision of an oceanic plateau (?) during the late Danian–Selandian; (iii) the collision/accretion of seamounts during the late Eocene–early Oligocene; (iv) the collision of seamounts and ridges during the Pliocene–Holocene. (2) The northwestward thickening of the SFB may have been enhanced by high sediment supply in the Fonseca Gulf area which reflects sourcing from wide, high relief drainage basins. In contrast, sedimentary input has possibly been lower along the southern SFB, due to the proximity of the narrow, lowland isthmus of southern Central America. Moreover, two phases of strongly oblique subduction affected the margin, producing strike-slip faulting in the forearc basin: (1) prior to the Farallon Plate breakup, an Oligocene transpressional phase caused deformation and uplift of the basin depocenter, triggering shallowing-upward of the Nicaraguan Isthmus in the central and northern SFB; (2) a Pleistocene–Holocene transtensional phase drives the NW-directed motion of a forearc sliver and reactivation of the graben-bounding faults of the late Neogene Nicaraguan Depression. We discuss arguments in favour of a Pliocene development of the Nicaraguan Depression and propose that the Nicaraguan Isthmus, which is the apparent rift shoulder of the depression, represents a structure inherited from the Oligocene transpressional phase

Subsymbolically Managing Pieces of Symbolical Functions for Sorting

We present a hybrid system for managing both symbolic and subsymbolic knowledge in a uniform way. Our aim is to solve problems where some gap in formal theories occurs which stops us from getting a fully symbolical solution. The idea is to use neural modules to functionally connect pieces of symbolical knowledge, such as mathematical formulas and deductive rules. The whole system is trained through a backpropagation learning algorithm where all (symbolic or subsymbolic) free parameters are updated piping back the error through each component of the system. The structure of this system is very general, possibly varying over time, possibly managing fuzzy variables and decision trees. We use as a test-bed the problem of sorting a file, where suitable suggestions on next sorting moves are supplied by the network also on the basis of hints provided by some conventional sorters. A comprehensive discussion of system performance is provided in order to understand behaviors and capabilities of ..

Controlling the loasing probability in a monotone game

We deal with a complex game between Alice and Bob where each contender\u2019s probability of victory grows monotonically by unknown amounts with the resources employed. For a fixed effort on Alice\u2019s part, Bob increases his resources on the basis of the results for each round (victory, tie or defeat) with the aim of reducing the probability of defeat to below a given threshold. We read this goal in terms of computing a confidence interval for the probability of losing and realize that the moves in some contests may bring in an indeterminacy trap: in certain games Bob cannot simultaneously have both a low probability-of-defeat measure and a narrow confidence interval. We use the inferential mechanism called twisting argument to compute the above interval on the basis of two joint statistics. Careful use of such statistics allows us to avoid indeterminac

Playing monotone games to understand learning behaviors

We deal with a special class of games against nature which correspond to subsymbolic learning problems where we know a local descent direction in the error landscape but not the amount gained at each step of the learning procedure. Namely, Alice and Bob play a game where the probability of victory grows monotonically by unknown amounts with the resources each employs. For a fixed effort on Alice\u2019s part Bob increases his resources on the basis of the results of the individual contests (victory, tie or defeat). Quite unlike the usual ones in game theory, his aim is to stop as soon as the defeat probability goes under a given threshold with high confidence. We adopt such a game policy as an archetypal remedy to the general overtraining threat of learning algorithms. Namely, we deal with the original game in a computational learning framework analogous to the Probably Approximately Correct formulation. Therein, a wise use of a special inferential mechanism (known as twisting argument) highlights relevant statistics for managing different trade-offs between observability and controllability of the defeat probability. With similar statistics we discuss an analogous trade-off at the basis of the stopping criterion of subsymbolic learning procedures. As a conclusion, we propose a principled stopping rule based solely on the behavior of the training session, hence without distracting examples into a test set

Mining complex networks: A new challenge for supporting diagnostic decisions

New technologies are multiplying at an enormous speed and the produced data is not only massive but also complex. In fact, despite the abundance of tools to capture, process and share information (e.g. data) one cannot broadly assume the standard hypothesis that such data are identically and independently distributed (i.i.d.). As a result, proper handling of data is fundamental in order to convert the available observation in to useful information that leads to knowledge and suitable decision making. In this paper, we focus on network data. That is, we introduce the reader to a theoretical perspective concerning the knowledge mining of huge amount of relational information collected in all the network systems which are ubiquitous in our life. In this context, following a numerical evaluation we show the reader how different kind of information can provide a benefit for a typical machine learning problem i.e. classification. The main issue of our investigation is to provide a case where the accuracy of a classification model benefits when considering the additional information given by both network and dissimilarity features. Moreover, we treat a clinical example that will serve as running case for our analysis

DIABESITY: Design of mHealth integrated solutions for empowering diabetic and obese citizens in self-monitoring and self-management using mobile devices, apps, social media and web-based technologies

Obesity is one of the most important medical and public health problems of our time: it increases the risk of many health complications such as type 2 diabetes, needs long-lasting treatment for effective results and involves high public and private costs. Therefore, it is imperative that enduring and low-cost clinical programs are developed and evaluated. As reported in several studies, ICT may be valid alternatives to reduce costs and improve adherence to prescribed treatment. Nevertheless few studies have tested a long-term intervention addressed to the behavior change and to measure the weight loss of obese subjects. For this reason, we developed the DIABESITY study, the design of a mHealth integrated platform for empowering diabetic and obese citizens in self-monitoring, and self-management through the use of mobile devices, monitors and treatment protocols. In this paper we focus on the following three important aspects of DIABESITY. i) Dietary mHealth tools for home-patients; ii) Application and analysis of psychological factors and processes which mediate change of behavior and affect initiation and maintenance phases; iii) Employment of social networks for patients and clinicians. Currently, this study involves 14 international partners chosen amongst hospitals, universities and ICT companies which will strictly collaborate by contributing with their own specific skills. The effectiveness of DIABESITY compared with usual care (hospital-based treatment) will be provided in a randomized controlled trial with a 24-month follow-up. In particular, here we report primary and secondary clinical outcomes with the basic statistical procedures which will be used for this evaluation

Social media and mobile applications in chronic disease prevention and management

Social media and mobile applications in chronic disease prevention and managemen