Towards the utilization of EEG as a brain imaging tool.

Recent advances in signal analysis have engendered EEG with the status of a true brain mapping and brain imaging method capable of providing spatio-temporal information regarding brain (dys)function. Because of the increasing interest in the temporal dynamics of brain networks, and because of the straightforward compatibility of the EEG with other brain imaging techniques, EEG is increasingly used in the neuroimaging community. However, the full capability of EEG is highly underestimated. Many combined EEG-fMRI studies use the EEG only as a spike-counter or an oscilloscope. Many cognitive and clinical EEG studies use the EEG still in its traditional way and analyze grapho-elements at certain electrodes and latencies. We here show that this way of using the EEG is not only dangerous because it leads to misinterpretations, but it is also largely ignoring the spatial aspects of the signals. In fact, EEG primarily measures the electric potential field at the scalp surface in the same way as MEG measures the magnetic field. By properly sampling and correctly analyzing this electric field, EEG can provide reliable information about the neuronal activity in the brain and the temporal dynamics of this activity in the millisecond range. This review explains some of these analysis methods and illustrates their potential in clinical and experimental applications.

How local excitation-inhibition ratio impacts the whole brain dynamics.

The spontaneous activity of the brain shows different features at different scales. On one hand, neuroimaging studies show that long-range correlations are highly structured in spatiotemporal patterns, known as resting-state networks, on the other hand, neurophysiological reports show that short-range correlations between neighboring neurons are low, despite a large amount of shared presynaptic inputs. Different dynamical mechanisms of local decorrelation have been proposed, among which is feedback inhibition. Here, we investigated the effect of locally regulating the feedback inhibition on the global dynamics of a large-scale brain model, in which the long-range connections are given by diffusion imaging data of human subjects. We used simulations and analytical methods to show that locally constraining the feedback inhibition to compensate for the excess of long-range excitatory connectivity, to preserve the asynchronous state, crucially changes the characteristics of the emergent resting and evoked activity. First, it significantly improves the model's prediction of the empirical human functional connectivity. Second, relaxing this constraint leads to an unrealistic network evoked activity, with systematic coactivation of cortical areas which are components of the default-mode network, whereas regulation of feedback inhibition prevents this. Finally, information theoretic analysis shows that regulation of the local feedback inhibition increases both the entropy and the Fisher information of the network evoked responses. Hence, it enhances the information capacity and the discrimination accuracy of the global network. In conclusion, the local excitation-inhibition ratio impacts the structure of the spontaneous activity and the information transmission at the large-scale brain level.

Inventory and description of disease management programs in Switzerland

Background: Disease management, a system of coordinated health care interventions for populations with chronic diseases in which patient self-care is a key aspect, has been shown to be effective for several conditions. Little is known on the supply of disease management programs in Switzerland. Objectives: To systematically search, record and evaluate data on existing disease management programs in Switzerland. Methods: Programs met our operational definition of disease management if their interventions targeted a chronic disease, included a multidisciplinary team and lasted at least 6 months. To find existing programs, we searched Swiss official websites, Swiss web-pages using Google, medical electronic database (Medline), and checked references from selected documents. We also contacted personally known individuals, those identified as possibly working in the field, individuals working in major Swiss health insurance companies and people recommended by previously contacted persons (snow ball strategy). We developed an extraction grid and collected information pertaining to the following 8 domains: patient population, intervention recipient, intervention content, delivery personnel, method of communication, intensity and complexity, environment and clinical outcomes (measures?). Results: We identified 8 programs fulfilling our operational definition of disease management. Programs targeted patients with diabetes, hypertension, heart failure, obesity, alcohol dependence, psychiatric disorders or breast cancer, and were mainly directed towards patients. The interventions were multifaceted and included education in almost all cases. Half of the programs included regularly scheduled follow-up, by phone in 3 instances. Healthcare professionals involved were physicians, nurses, case managers, social workers, psychologists and dietitians. None fulfilled the 6 criteria established by the Disease Management Association of America. Conclusions: Our study shows that disease management programs, in a country with universal health insurance coverage and little incentive to develop new healthcare strategies, are scarce, although we may have missed existing programs. Nonetheless, those already implemented are very interesting and rather comprehensive. Appropriate evaluation of these programs should be performed in order to build upon them and try to design a generic disease management framework suited to the Swiss healthcare system.

Nanoparticle usage and protection measures in the manufacturing industry : a representative survey

Addressing the risks of nanoparticles requires knowledge about release into the environment and occupational exposure. However, such information currently is not systematically collected; therefore, this risk assessment lacks quantitative data. The goal was to evaluate the current level of nanoparticle usage in Swiss industry as well as health, safety, and environmental measures, and the number of potentially exposed workers. A representative, stratified mail survey was conducted among 1626 clients of the Swiss National Accident Insurance Fund (SUVA), which insures 80,000 manufacturing firms, representing 84% of all Swiss manufacturing companies (947 companies answered the survey for a 58.3% response rate). The extrapolation to all Swiss manufacturing companies results in 1309 workers (95% confidence interval [CI]: 1073 to 1545) potentially exposed to nanoparticles in 586 companies (95% CI: 145 to 1027). This corresponds to 0.08% of workers (95% CI: 0.06% to 0.09%) and to 0.6% of companies (95% CI: 0.2% to 1.1%). The industrial chemistry sector showed the highest percentage of companies using nanoparticles (21.2%). Other important sectors also reported nanoparticles. Personal protection equipment was the predominant protection strategy. Only a few applied specific environmental protection measures. This is the first nationwide representative study on nanoparticle use in the manufacturing sector. The information gained can be used for quantitative risk assessment. It can also help policymakers design strategies to support companies developing a safer use of nanomaterial. Notingthe current low use of nanoparticles, there is still time to proactively introduce protective methods. If the predicted "nano-revolution" comes true, now is the time to take action. [Supplementary materials are available for this article. Go to the publisher's online edition of Journal of occupational and Environmental Hygiene for the following free supplemental resource: a pdf file containing a detailed description of the approach to statistical analyses, English translation of the questionnaire, additional information for Figure 1, and additional information for the SUVA-code.] [Authors]

Freedom of choice of specialist physicians is important to Swiss resident: a cross-sectional study.

QUESTION UNDER STUDY: To assess how important the possibility to choose specialist physicians is for Swiss residents and to determine which variables are associated with this opinion. METHODS: This cross-sectional study used data from the 2007 Swiss population-based health survey and included 13,642 non-institutionalised adults who responded to the telephone and paper questionnaires. The dependent variable included answers to the question "How important is it for you to be able to choose the specialist you would like to visit?" Independent variables included socio-demographics, health and past year healthcare use measures. Crude and adjusted logistic regressions for the importance of being able to choose specialist physicians were performed, accounting for the survey design. RESULTS: 45% of participants found it very important to be able to choose the specialist physician they wanted to visit. The answers "rather important", "rather not important" and "not important" were reported by 28%, 20% and 7% of respondents. Women, individuals in middle/high executive position, those with an ordinary insurance scheme, those reporting ≥2 chronic conditions or poorer subjective health, or those who had had ≥2 outpatient visits in the preceding year were more likely to find this choice very important. CONCLUSIONS: In 2007, almost half of all Swiss residents found it very important to be able to choose his/her specialist physician. The further development of physician networks or other chronic disease management initiatives in Switzerland, towards integrated care, need to pay attention to the freedom of choice of specialist physicians that Swiss residents value. Future surveys should provide information on access and consultations with specialist physicians.

Modeling stochasticity and robustness in gene regulatory networks.

MOTIVATION: Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. RESULTS: In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. AVAILABILITY: Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/ approximately garg/genysis.html.

Kinematics and dynamic complexity of postural transitions in frail elderly subjects.

The aim of this study was to propose a methodology allowing a detailed characterization of body sit-to-stand/stand-to-sit postural transition. Parameters characterizing the kinematics of the trunk movement during sit-to-stand (Si-St) postural transition were calculated using one initial sensor system fixed on the trunk and a data logger. Dynamic complexity of these postural transitions was estimated by fractal dimension of acceleration-angular velocity plot. We concluded that this method provides a simple and accurate tool for monitoring frail elderly and to objectively evaluate the efficacy of a rehabilitation program.

Responsiveness to a physiological regimen of GnRH therapy and relation to genotype in women with isolated hypogonadotropic hypogonadism.

CONTEXT: Isolated hypogonadotropic hypogonadism (IHH) is caused by defective GnRH secretion or action resulting in absent or incomplete pubertal development and infertility. Most women with IHH ovulate with physiological GnRH replacement, implicating GnRH deficiency as the etiology. However, a subset does not respond normally, suggesting the presence of defects at the pituitary or ovary. OBJECTIVES: The objective of the study was to unmask pituitary or ovarian defects in IHH women using a physiological regimen of GnRH replacement, relating these responses to genes known to cause IHH. DESIGN, SETTING, AND SUBJECTS: This study is a retrospective analysis of 37 IHH women treated with iv pulsatile GnRH (75 ng/kg per bolus). MAIN OUTCOME MEASURES: Serum gonadotropin and sex steroid levels were measured, and 14 genes implicated in IHH were sequenced. RESULTS: During their first cycle of GnRH replacement, normal cycles were recreated in 60% (22 of 37) of IHH women. Thirty percent of women (12 of 37) demonstrated an attenuated gonadotropin response, indicating pituitary resistance, and 10% (3 of 37) exhibited an exaggerated FSH response, consistent with ovarian resistance. Mutations in CHD7, FGFR1, KAL1, TAC3, and TACR3 were documented in IHH women with normal cycles, whereas mutations were identified in GNRHR, PROKR2, and FGFR1 in those with pituitary resistance. Women with ovarian resistance were mutation negative. CONCLUSIONS: Although physiological replacement with GnRH recreates normal menstrual cycle dynamics in most IHH women, hypogonadotropic responses in the first week of treatment identify a subset of women with pituitary dysfunction, only some of whom have mutations in GNRHR. IHH women with hypergonadotropic responses to GnRH replacement, consistent with an additional ovarian defect, did not have mutations in genes known to cause IHH, similar to our findings in a subset of IHH men with evidence of an additional testicular defect.

Dynamics of IS Adaptation in Multinational Corporations: A New Theoretical Lens

The specificities of multinational corporations (MNCs) have to date not been a focus area of IS research. Extant literature mostly proposes IS configurations for specific types of MNCs, following a static and prescriptive approach. Our research seeks to explain the dynamics of global IS design. It suggests a new theoretical lens for studying global IS design by applying the structural adjustment paradigm from organizational change theories. Relying on archetype theory, we conduct a longitudinal case study to theorize the dynamics of IS adaptation. We find that global IS design emerges as an organizational adaptation process to balance interpretative schemes (i.e. the organization's values and beliefs) and structural arrangements (i.e. strategic, organizational, and IS configurations). The resulting insights can be used as a basis to further explore alternative global IS designs and movements between them.

Monitoring of illicit pill distribution networks using an image collection exploration framework

This paper proposes a novel approach for the analysis of illicit tablets based on their visual characteristics. In particular, the paper concentrates on the problem of ecstasy pill seizure profiling and monitoring. The presented method extracts the visual information from pill images and builds a representation of it, i.e. it builds a pill profile based on the pill visual appearance. Different visual features are used to build different image similarity measures, which are the basis for a pill monitoring strategy based on both discriminative and clustering models. The discriminative model permits to infer whether two pills come from the same seizure, while the clustering models groups of pills that share similar visual characteristics. The resulting clustering structure allows to perform a visual identification of the relationships between different seizures. The proposed approach was evaluated using a data set of 621 Ecstasy pill pictures. The results demonstrate that this is a feasible and cost effective method for performing pill profiling and monitoring.

Character Networks and Centrality

A character network represents relations between characters from a text; the relations are based on text proximity, shared scenes/events, quoted speech, etc. Our project sketches a theoretical framework for character network analysis, bringing together narratology, both close and distant reading approaches, and social network analysis. It is in line with recent attempts to automatise the extraction of literary social networks (Elson, 2012; Sack, 2013) and other studies stressing the importance of character- systems (Woloch, 2003; Moretti, 2011). The method we use to build the network is direct and simple. First, we extract co-occurrences from a book index, without the need for text analysis. We then describe the narrative roles of the characters, which we deduce from their respective positions in the network, i.e. the discourse. As a case study, we use the autobiographical novel Les Confessions by Jean-Jacques Rousseau. We start by identifying co-occurrences of characters in the book index of our edition (Slatkine, 2012). Subsequently, we compute four types of centrality: degree, closeness, betweenness, eigenvector. We then use these measures to propose a typology of narrative roles for the characters. We show that the two parts of Les Confessions, written years apart, are structured around mirroring central figures that bear similar centrality scores. The first part revolves around the mentor of Rousseau; a figure of openness. The second part centres on a group of schemers, depicting a period of deep paranoia. We also highlight characters with intermediary roles: they provide narrative links between the societies in the life of the author. The method we detail in this complete case study of character network analysis can be applied to any work documented by an index. Un réseau de personnages modélise les relations entre les personnages d'un récit : les relations sont basées sur une forme de proximité dans le texte, l'apparition commune dans des événements, des citations dans des dialogues, etc. Notre travail propose un cadre théorique pour l'analyse des réseaux de personnages, rassemblant narratologie, close et distant reading, et analyse des réseaux sociaux. Ce travail prolonge les tentatives récentes d'automatisation de l'extraction de réseaux sociaux tirés de la littérature (Elson, 2012; Sack, 2013), ainsi que les études portant sur l'importance des systèmes de personnages (Woloch, 2003; Moretti, 2011). La méthode que nous utilisons pour construire le réseau est directe et simple. Nous extrayons les co-occurrences d'un index sans avoir recours à l'analyse textuelle. Nous décrivons les rôles narratifs des personnages en les déduisant de leurs positions relatives dans le réseau, donc du discours. Comme étude de cas, nous avons choisi le roman autobiographique Les Confessions, de Jean- Jacques Rousseau. Nous déduisons les co-occurrences entre personnages de l'index présent dans l'édition Slatkine (Rousseau et al., 2012). Sur le réseau obtenu, nous calculons quatre types de centralité : le degré, la proximité, l'intermédiarité et la centralité par vecteur propre. Nous utilisons ces mesures pour proposer une typologie des rôles narratifs des personnages. Nous montrons que les deux parties des Confessions, écrites à deux époques différentes, sont structurées autour de deux figures centrales, qui obtiennent des mesures de centralité similaires. La première partie est construite autour du mentor de Rousseau, qui a symbolisé une grande ouverture. La seconde partie se focalise sur un groupe de comploteurs, et retrace une période marquée par la paranoïa chez l'auteur. Nous mettons également en évidence des personnages jouant des rôles intermédiaires, et de fait procurant un lien narratif entre les différentes sociétés couvrant la vie de l'auteur. La méthode d'analyse des réseaux de personnages que nous décrivons peut être appliquée à tout texte de fiction comportant un index.

The automatic selection of ventilation parameters during the initial phase of mechanical ventilation.

OBJECTIVE: To test a method that allows automatic set-up of the ventilator controls at the onset of ventilation. DESIGN: Prospective randomized crossover study. SETTING: ICUs in one adult and one children's hospital in Switzerland. PATIENTS: Thirty intubated stable, critically ill patients (20 adults and 10 children). INTERVENTIONS: The patients were ventilated during two 20-min periods using a modified Hamilton AMADEUS ventilator. During the control period the ventilator settings were chosen immediately prior to the study. During the other period individual settings were automatically determined by the ventilatior (AutoInit). MEASUREMENTS AND RESULTS: Pressure, flow, and instantaneous CO2 concentration were measured at the airway opening. From these measurements, series dead space (V(DS)), expiratory time constant (RC), tidal volume (VT, total respiratory frequency (f(tot), minute ventilation (MV), and maximal and mean airway pressure (Paw, max and Paw, mean) were calculated. Arterial blood gases were analyzed at the end of each period. Paw, max was significantly less with the AutoInit ventilator settings while f(tot) was significantly greater (P < 0.05). The other values were not statistically significant. CONCLUSIONS: The AutoInit ventilator settings, which were automatically derived, were acceptable for all patients for a period of 20 min and were not found to be inferior to the control ventilator settings. This makes the AutoInit method potentially useful as an automatic start-up procedure for mechanical ventilation.

Influence of a lifestyle intervention in preschool children on physiological and psychological parameters (Ballabeina): study design of a cluster randomized controlled trial.

Childhood obesity and physical inactivity are increasing dramatically worldwide. Children of low socioeconomic status and/or children of migrant background are especially at risk. In general, the overall effectiveness of school-based programs on health-related outcomes has been disappointing. A special gap exists for younger children and in high risk groups. This paper describes the rationale, design, curriculum, and evaluation of a multicenter preschool randomized intervention study conducted in areas with a high migrant population in two out of 26 Swiss cantons. Twenty preschool classes in the German (canton St. Gallen) and another 20 in the French (canton Vaud) part of Switzerland were separately selected and randomized to an intervention and a control arm by the use of opaque envelopes. The multidisciplinary lifestyle intervention aimed to increase physical activity and sleep duration, to reinforce healthy nutrition and eating behaviour, and to reduce media use. According to the ecological model, it included children, their parents and the teachers. The regular teachers performed the majority of the intervention and were supported by a local health promoter. The intervention included physical activity lessons, adaptation of the built infrastructure; promotion of regional extracurricular physical activity; playful lessons about nutrition, media use and sleep, funny homework cards and information materials for teachers and parents. It lasted one school year. Baseline and post-intervention evaluations were performed in both arms. Primary outcome measures included BMI and aerobic fitness (20 m shuttle run test). Secondary outcomes included total (skinfolds, bioelectrical impedance) and central (waist circumference) body fat, motor abilities (obstacle course, static and dynamic balance), physical activity and sleep duration (accelerometry and questionnaires), nutritional behaviour and food intake, media use, quality of life and signs of hyperactivity (questionnaires), attention and spatial working memory ability (two validated tests). Researchers were blinded to group allocation. The purpose of this paper is to outline the design of a school-based multicenter cluster randomized, controlled trial aiming to reduce body mass index and to increase aerobic fitness in preschool children in culturally different parts of Switzerland with a high migrant population. Trial Registration: (clinicaltrials.gov) NCT00674544.

Reconciliation of metabolites and biochemical reactions for metabolic networks.

Genome-scale metabolic network reconstructions are now routinely used in the study of metabolic pathways, their evolution and design. The development of such reconstructions involves the integration of information on reactions and metabolites from the scientific literature as well as public databases and existing genome-scale metabolic models. The reconciliation of discrepancies between data from these sources generally requires significant manual curation, which constitutes a major obstacle in efforts to develop and apply genome-scale metabolic network reconstructions. In this work, we discuss some of the major difficulties encountered in the mapping and reconciliation of metabolic resources and review three recent initiatives that aim to accelerate this process, namely BKM-react, MetRxn and MNXref (presented in this article). Each of these resources provides a pre-compiled reconciliation of many of the most commonly used metabolic resources. By reducing the time required for manual curation of metabolite and reaction discrepancies, these resources aim to accelerate the development and application of high-quality genome-scale metabolic network reconstructions and models.

Modeling the impact of lesions in the human brain.

Lesions of anatomical brain networks result in functional disturbances of brain systems and behavior which depend sensitively, often unpredictably, on the lesion site. The availability of whole-brain maps of structural connections within the human cerebrum and our increased understanding of the physiology and large-scale dynamics of cortical networks allow us to investigate the functional consequences of focal brain lesions in a computational model. We simulate the dynamic effects of lesions placed in different regions of the cerebral cortex by recording changes in the pattern of endogenous ("resting-state") neural activity. We find that lesions produce specific patterns of altered functional connectivity among distant regions of cortex, often affecting both cortical hemispheres. The magnitude of these dynamic effects depends on the lesion location and is partly predicted by structural network properties of the lesion site. In the model, lesions along the cortical midline and in the vicinity of the temporo-parietal junction result in large and widely distributed changes in functional connectivity, while lesions of primary sensory or motor regions remain more localized. The model suggests that dynamic lesion effects can be predicted on the basis of specific network measures of structural brain networks and that these effects may be related to known behavioral and cognitive consequences of brain lesions.