Evaluation of the compliance with recommended procedures in newborns exposed to HBsAg-positive mothers: a multicenter collaborative study.

BACKGROUND: Maternal-infant transmission of hepatitis B virus (HBV) during birth carries a high risk for chronic HBV infection in infants with frequent subsequent development of chronic disease. This can be efficiently prevented by early immunization of exposed newborns. The purpose of this study was to determine the compliance with official recommendations for prevention of perinatal HBV transmission in hepatitis B surface antigen (HBsAg) exposed infants. METHODS: Records of pregnant women at 4 sites in Switzerland, admitted for delivery in 2005 and 2006, were screened for maternal HBsAg testing. In HBsAg-exposed infants, recommended procedures (postnatal active and passive immunization, completion of immunization series, and serological success control) were checked. RESULTS: Of 27,131 women tested for HBsAg, 194 (0.73%) were positive with 196 exposed neonates. Of these neonates, 143 (73%) were enrolled and 141 (99%) received simultaneous active and passive HBV immunization within 24 hours of birth. After discharge, the HBV immunization series was completed in 83%. Only 38% of children were tested for anti-HBs afterwards and protective antibody values (>100 U/L) were documented in 27% of the study cohort. No chronically infected child was identified. Analysis of hospital discharge letters revealed significant quality problems. CONCLUSIONS: Intensified efforts are needed to improve the currently suboptimal medical care in HBsAg-exposed infants. We propose standardized discharge letters, as well as reminders to primary care physicians with precise instructions on the need to complete the immunization series in HBsAg-exposed infants and to evaluate success by determination of anti-HBs antibodies after the last dose.

Evolution of Coordination in Social Networks: A Numerical Study

Coordination games are important to explain efficient and desirable social behavior. Here we study these games by extensive numerical simulation on networked social structures using an evolutionary approach. We show that local network effects may promote selection of efficient equilibria in both pure and general coordination games and may explain social polarization. These results are put into perspective with respect to known theoretical results. The main insight we obtain is that clustering, and especially community structure in social networks has a positive role in promoting socially efficient outcomes.

Learning about Bayesian networks for forensic interpretation : An example based on the "the problem of multiple propositions"

Both, Bayesian networks and probabilistic evaluation are gaining more and more widespread use within many professional branches, including forensic science. Notwithstanding, they constitute subtle topics with definitional details that require careful study. While many sophisticated developments of probabilistic approaches to evaluation of forensic findings may readily be found in published literature, there remains a gap with respect to writings that focus on foundational aspects and on how these may be acquired by interested scientists new to these topics. This paper takes this as a starting point to report on the learning about Bayesian networks for likelihood ratio based, probabilistic inference procedures in a class of master students in forensic science. The presentation uses an example that relies on a casework scenario drawn from published literature, involving a questioned signature. A complicating aspect of that case study - proposed to students in a teaching scenario - is due to the need of considering multiple competing propositions, which is an outset that may not readily be approached within a likelihood ratio based framework without drawing attention to some additional technical details. Using generic Bayesian networks fragments from existing literature on the topic, course participants were able to track the probabilistic underpinnings of the proposed scenario correctly both in terms of likelihood ratios and of posterior probabilities. In addition, further study of the example by students allowed them to derive an alternative Bayesian network structure with a computational output that is equivalent to existing probabilistic solutions. This practical experience underlines the potential of Bayesian networks to support and clarify foundational principles of probabilistic procedures for forensic evaluation.

EEG-based functional networks in schizophrenia.

Schizophrenia is often considered as a dysconnection syndrome in which, abnormal interactions between large-scale functional brain networks result in cognitive and perceptual deficits. In this article we apply the graph theoretic measures to brain functional networks based on the resting EEGs of fourteen schizophrenic patients in comparison with those of fourteen matched control subjects. The networks were extracted from common-average-referenced EEG time-series through partial and unpartial cross-correlation methods. Unpartial correlation detects functional connectivity based on direct and/or indirect links, while partial correlation allows one to ignore indirect links. We quantified the network properties with the graph metrics, including mall-worldness, vulnerability, modularity, assortativity, and synchronizability. The schizophrenic patients showed method-specific and frequency-specific changes especially pronounced for modularity, assortativity, and synchronizability measures. However, the differences between schizophrenia patients and normal controls in terms of graph theory metrics were stronger for the unpartial correlation method.

Cognate microRNA-Gene Regulatory Networks Mediating Glioblastoma Oncogenic Properties

Malignant gliomas, including the most common and fatal form glioblastoma (GBM, WHO grade IV astrocytoma), remain a challenge to treat. In the United States and Europe, more than 30,000 patients per year are newly diagnosed with GBM. Despite ongoing trials, the best currently available multimodal treatment approaches include surgical resection followed by concomitant and adjuvant radiation (RT) and temozolomide (TMZ) therapy, resulting in a low median overall survival (OS) rate ranging from 12.2 - 15.9 months. The important role of genetic and epigenetic changes in DNA, RNA, and protein alteration as well as epigenetic changes secondary to the tumor microenvironment and outside selection pressure (therapeutic interventions), are increasingly being recognized. In GBM treatment, the focus is shifting toward a more patient-centered (personalized) therapy. In this regard, in particular, microRNAs are being increasingly studied. MicroRNAs are non¬protein coding small RNAs that serve as negative gene regulators by binding to a specific sequence in the promoter region of a target gene, thus regulating gene expression. A single microRNA potentially targets hundreds of genes; thus, microRNAs and their cognate target genes have important roles as tumor suppressors and oncogenes as well as regulators of various cancer- specific cellular features, such as proliferation, apoptosis, invasion, and metastasis. The identification of distinct microRNA-gene regulatory networks in GBM patients can be expected to provide novel therapeutic insights by identifying candidate patients for targeted therapies. To this end, in this work we identified and validated clinically relevant and meaningful novel gene- microRNA regulatory networks that correlated with MR tumor phenotypes, histopathology, and patient survival and response rates to therapy. - Le traitement des gliomes malins, y compris sous leur forme la plus commune et meurtrière, le glioblastome (GBM, ou astrocytome de grade IV selon l'OMS), demeure à ce jour un défi. Aux États-Unis et en Europe, un nouveau diagnostic de GBM est prononcé dans plus de 30Ό00 cas par an. En dépit de tests en cours, les meilleures approches thérapeutiques combinées actuellement disponibles comprennent la résection chirurgicale de la tumeur, suivie d'une radiothérapie adjuvante ainsi que d'un traitement au temozolomide (RT/TMZ), thérapies dont résulte une médiane de survie globale basse (overall survival, OS), comprise entre 12.2 et 15.9 mois. On reconnaît de plus en plus le rôle majeur de l'ADN, de l'ARN et de l'altération des protéines ainsi que des modifications épigénétiques, secondaires par rapport au microenvironnement de la tumeur et à la pression de sélection extérieure (les interventions thérapeutiques). Dans le traitement du GBM, le centre d'intérêt se déplace vers une thérapie centrée sur le cas individuel du patient. Dans ce but, en particulier les microARN sont de plus en plus analysés. Les microARN sont de petits ARN non-codants (les protéines) qui servent de régulateurs négatifs de gènes en s'attachant à une séquence spécifique dans la région promotrice d'un gène-cible, régulant ainsi l'expression du gène. Un seul microARN cible potentiellement des centaines de gènes; on a ainsi découvert que les microARN et leurs gènes-cibles apparentés ont une fonction importante en tant que suppresseurs de tumeurs et d'oncogènes, ainsi que comme régulateurs de diverses caractéristiques cellulaires spécifiques du cancer, comme la prolifération, l'apoptose, l'invasion et la métastase. On peut s'attendre à ce que l'identification de réseaux microARN régulateurs de gènes, distincts selon les patients de GBM, fournisse une approche thérapeutique inédite par la détermination des patients susceptibles de réagir favorablement à des thérapies ciblées.

The enterprise face to the environmental challenge: straddling the fence between social responsibility and penal responsibility

This contribution aims to analyse how to incur companies' criminal liability when they violate environmental protection globally. In Switzerland, companies' criminal liability has already been provided for to fight against money launder- ing (Article 102 CP). Could a similar liability be incurred, in Switzerland, for companies that infringe environmental protection? This is what our contribution is all about. Since the company is at the heart of our subject, the point is to see to what extent criminal liability could be transposed to cases of violation by companies of the environmental principles promoted by the CSR concept.

Collaborative quality improvement to manage pain in acute care hospitals.

Objective. Collaborative quality improvement programs have been successfully used to manage chronic diseases in adults and acute lung complications in premature infants. Their effectiveness to improve pain management in acute care hospitals is currently unknown. The purpose of this study was to determine whether a collaborative quality improvement program implemented at hospital level could improve pain management and overall pain relief. Design.To assess the effectiveness of the program, we performed a before-after trial comparing patient's self-reported pain management and experience before and after program implementation. We included all adult patients hospitalized for more than 24 hours and discharged either to their home or to a nursing facility, between March 1, 2001 and March 31, 2001 (before program implementation) and between September 15, 2005 and October 15, 2005 (after program implementation). Setting.A teaching hospital of 2,096 beds in Geneva, Switzerland. Patients.All adult patients hospitalized for more than 24 hours and discharged between 1 to 31 March 2001 (before program) and 15 September to 15 October 2005 (after program implementation). Interventions.Implementation of a collaborative quality improvement program using multifaceted interventions (staff education, opinion leaders, patient education, audit, and feedback) to improve pain management at hospital level. Outcome Measures.Patient-reported pain experience, pain management, and overall hospital experience based on the Picker Patient Experience questionnaire, perceived health (SF-36 Health survey). Results.After implementation of the program only 2.3% of the patients reported having no pain relief during their hospital stay (vs 4.5% in 2001, P = 0.05). Among nonsurgical patients, improvements were observed for pain assessment (42.3% vs 27.9% of the patients had pain intensity measured with a visual analog scale, P = 0.012), pain management (staff did everything they could to help in 78.9% vs 67.9% of cases P = 0.003), and pain relief (70.4% vs 57.3% of patients reported full pain relief P = 0.008). In surgical patients, pain assessment also improved (53.7.3% vs 37.6%) as well as pain treatment. More patients received treatments to relieve pain regularly or intermittently after program implementation (95.1% vs 91.9% P = 0.046). Conclusion.Implementation of a collaborative quality improvement program at hospital level improved both pain management and pain relief in patients. Further studies are needed to determine the overall cost-effectiveness of such programs.

Key cognitive and collaborative aptitudes in ambulance people

The aim of our study was to identify and document some key cognitive aptitudes used by ambulance people in emergency situations. Better knowing such aptitudes is necessary for a school of ambulance people in order to improve the selection and education of students. The idea was to better consider real work activity requirements and characteristics, and to develop and implement genuine educational content and selection tools. We followed the work activity of ambulance professionals involved in real emergency situations. Some interventions were filmed and post-analyzed. We completed and validated our analysis by means of interviews with ambulance personnel. We selected some video sequences and used them as a support for the interviews. We identified and documented many different key aptitudes like orientation and spatial sense, the capacity to perform complex cognitive tasks and delicate manipulations in the context of divided attention, as well as diverse aptitudes relevant in collaborative work.

Bayesian networks and the evaluation of scientific evidence in forensic science

Résumé Ce travail de thèse étudie des moyens de formalisation permettant d'assister l'expert forensique dans la gestion des facteurs influençant l'évaluation des indices scientifiques, tout en respectant des procédures d'inférence établies et acceptables. Selon une vue préconisée par une partie majoritaire de la littérature forensique et juridique - adoptée ici sans réserve comme point de départ - la conceptualisation d'une procédure évaluative est dite 'cohérente' lors qu'elle repose sur une implémentation systématique de la théorie des probabilités. Souvent, par contre, la mise en oeuvre du raisonnement probabiliste ne découle pas de manière automatique et peut se heurter à des problèmes de complexité, dus, par exemple, à des connaissances limitées du domaine en question ou encore au nombre important de facteurs pouvant entrer en ligne de compte. En vue de gérer ce genre de complications, le présent travail propose d'investiguer une formalisation de la théorie des probabilités au moyen d'un environment graphique, connu sous le nom de Réseaux bayesiens (Bayesian networks). L'hypothèse principale que cette recherche envisage d'examiner considère que les Réseaux bayesiens, en concert avec certains concepts accessoires (tels que des analyses qualitatives et de sensitivité), constituent une ressource clé dont dispose l'expert forensique pour approcher des problèmes d'inférence de manière cohérente, tant sur un plan conceptuel que pratique. De cette hypothèse de travail, des problèmes individuels ont été extraits, articulés et abordés dans une série de recherches distinctes, mais interconnectées, et dont les résultats - publiés dans des revues à comité de lecture - sont présentés sous forme d'annexes. D'un point de vue général, ce travail apporte trois catégories de résultats. Un premier groupe de résultats met en évidence, sur la base de nombreux exemples touchant à des domaines forensiques divers, l'adéquation en termes de compatibilité et complémentarité entre des modèles de Réseaux bayesiens et des procédures d'évaluation probabilistes existantes. Sur la base de ces indications, les deux autres catégories de résultats montrent, respectivement, que les Réseaux bayesiens permettent également d'aborder des domaines auparavant largement inexplorés d'un point de vue probabiliste et que la disponibilité de données numériques dites 'dures' n'est pas une condition indispensable pour permettre l'implémentation des approches proposées dans ce travail. Le présent ouvrage discute ces résultats par rapport à la littérature actuelle et conclut en proposant les Réseaux bayesiens comme moyen d'explorer des nouvelles voies de recherche, telles que l'étude de diverses formes de combinaison d'indices ainsi que l'analyse de la prise de décision. Pour ce dernier aspect, l'évaluation des probabilités constitue, dans la façon dont elle est préconisée dans ce travail, une étape préliminaire fondamentale de même qu'un moyen opérationnel.

Probabilistic evidential assessment of gunshot residue particle evidence (Part I): likelihood ratio calculation and case pre-assessment using Bayesian networks

Well developed experimental procedures currently exist for retrieving and analyzing particle evidence from hands of individuals suspected of being associated with the discharge of a firearm. Although analytical approaches (e.g. automated Scanning Electron Microscopy with Energy Dispersive X-ray (SEM-EDS) microanalysis) allow the determination of the presence of elements typically found in gunshot residue (GSR) particles, such analyses provide no information about a given particle's actual source. Possible origins for which scientists may need to account for are a primary exposure to the discharge of a firearm or a secondary transfer due to a contaminated environment. In order to approach such sources of uncertainty in the context of evidential assessment, this paper studies the construction and practical implementation of graphical probability models (i.e. Bayesian networks). These can assist forensic scientists in making the issue tractable within a probabilistic perspective. The proposed models focus on likelihood ratio calculations at various levels of detail as well as case pre-assessment.

Bayesian Networks and the Value of the Evidence for the Forensic Two-Trace Transfer Problem

Forensic scientists face increasingly complex inference problems for evaluating likelihood ratios (LRs) for an appropriate pair of propositions. Up to now, scientists and statisticians have derived LR formulae using an algebraic approach. However, this approach reaches its limits when addressing cases with an increasing number of variables and dependence relationships between these variables. In this study, we suggest using a graphical approach, based on the construction of Bayesian networks (BNs). We first construct a BN that captures the problem, and then deduce the expression for calculating the LR from this model to compare it with existing LR formulae. We illustrate this idea by applying it to the evaluation of an activity level LR in the context of the two-trace transfer problem. Our approach allows us to relax assumptions made in previous LR developments, produce a new LR formula for the two-trace transfer problem and generalize this scenario to n traces.