Neuroimaging techniques in Alzheimer's disease

Neuroimaging techniques provide valuable tools for diagnosing Alzheimer's disease (AD), monitoring disease progression and evaluating responses to treatment. There is currently a wide array of techniques available including computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and, for recording electrical brain activity, electroencephalography (EEG). The choice of technique depends on the contrast between tissues of interest, spatial resolution, temporal resolution, requirements for functional data and the probable number of scans required. For example, while PET, CT and MRI can be used to differentiate between AD and other dementias, MRI is safer and provides better contrast of soft tissues. Neuroimaging is a technique spanning many disciplines and requires effective communication between doctors requesting a scan of a patient or group of patients and those with technical expertise. Consideration and discussion of the most suitable type of scan and the necessary settings to achieve the best results will help ensure appropriate techniques are chosen and used effectively. Neuroimaging techniques are currently expanding understanding of the structural and functional changes that occur in dementia. Further research may allow identification of early neurological signs ofAD, before clinical symptoms are evident, providing the opportunity to test preventative therapies. CombiningMRI and machine learning techniques may be a powerful approach to improve diagnosis ofAD and to predict clinical outcomes.

Oncology clinicians' defenses and adherence to communication skills training with simulated patients: an exploratory study.

The aim of this exploratory study was to assess the impact of clinicians' defense mechanisms-defined as self-protective psychological mechanisms triggered by the affective load of the encounter with the patient-on adherence to a communication skills training (CST). The population consisted of oncology clinicians (N = 31) who participated in a CST. An interview with simulated cancer patients was recorded prior and 6 months after CST. Defenses were measured before and after CST and correlated with a prototype of an ideally conducted interview based on the criteria of CST-teachers. Clinicians who used more adaptive defense mechanisms showed better adherence to communication skills after CST than clinicians with less adaptive defenses (F(1, 29) = 5.26, p = 0.03, d = 0.42). Improvement in communication skills after CST seems to depend on the initial levels of defenses of the clinician prior to CST. Implications for practice and training are discussed. Communication has been recognized as a central element of cancer care [1]. Ineffective communication may contribute to patients' confusion, uncertainty, and increased difficulty in asking questions, expressing feelings, and understanding information [2, 3], and may also contribute to clinicians' lack of job satisfaction and emotional burnout [4]. Therefore, communication skills trainings (CST) for oncology clinicians have been widely developed over the last decade. These trainings should increase the skills of clinicians to respond to the patient's needs, and enhance an adequate encounter with the patient with efficient exchange of information [5]. While CSTs show a great diversity with regard to their pedagogic approaches [6, 7], the main elements of CST consist of (1) role play between participants, (2) analysis of videotaped interviews with simulated patients, and (3) interactive case discussion provided by participants. As recently stated in a consensus paper [8], CSTs need to be taught in small groups (up to 10-12 participants) and have a minimal duration of at least 3 days in order to be effective. Several systematic reviews evaluated the impact of CST on clinicians' communication skills [9-11]. Effectiveness of CST can be assessed by two main approaches: participant-based and patient-based outcomes. Measures can be self-reported, but, according to Gysels et al. [10], behavioral assessment of patient-physician interviews [12] is the most objective and reliable method for measuring change after training. Based on 22 studies on participants' outcomes, Merckaert et al. [9] reported an increase of communication skills and participants' satisfaction with training and changes in attitudes and beliefs. The evaluation of CST remains a challenging task and variables mediating skills improvement remain unidentified. We recently thus conducted a study evaluating the impact of CST on clinicians' defenses by comparing the evolution of defenses of clinicians participating in CST with defenses of a control group without training [13]. Defenses are unconscious psychological processes which protect from anxiety or distress. Therefore, they contribute to the individual's adaptation to stress [14]. Perry refers to the term "defensive functioning" to indicate the degree of adaptation linked to the use of a range of specific defenses by an individual, ranging from low defensive functioning when he or she tends to use generally less adaptive defenses (such as projection, denial, or acting out) to high defensive functioning when he or she tends to use generally more adaptive defenses (such as altruism, intellectualization, or introspection) [15, 16]. Although several authors have addressed the emotional difficulties of oncology clinicians when facing patients and their need to preserve themselves [7, 17, 18], no research has yet been conducted on the defenses of clinicians. For example, repeated use of less adaptive defenses, such as denial, may allow the clinician to avoid or reduce distress, but it also diminishes his ability to respond to the patient's emotions, to identify and to respond adequately to his needs, and to foster the therapeutic alliance. Results of the above-mentioned study [13] showed two groups of clinicians: one with a higher defensive functioning and one with a lower defensive functioning prior to CST. After the training, a difference in defensive functioning between clinicians who participated in CST and clinicians of the control group was only showed for clinicians with a higher defensive functioning. Some clinicians may therefore be more responsive to CST than others. To further address this issue, the present study aimed to evaluate the relationship between the level of adherence to an "ideally conducted interview", as defined by the teachers of the CST, and the level of the clinician' defensive functioning. We hypothesized that, after CST, clinicians with a higher defensive functioning show a greater adherence to the "ideally conducted interview" than clinicians with a lower defensive functioning.

Contact and communication with healthcare providers regarding influenza vaccination during the 2009-2010 H1N1 pandemic.

Objective. The existence of two vaccines seasonal and pandemic-created the potential for confusion and misinformation among consumers during the 2009-2010 vaccination season. We measured the frequency and nature of influenza vaccination communication between healthcare providers and adults for both seasonal and 2009 influenza A(H1N1) vaccination and quantified its association with uptake of the two vaccines.Methods. We analyzed data from 4040 U.S. adult members of a nationally representative online panel surveyed between March 4th and March 24th, 2010. We estimated prevalence rates and adjusted associations between vaccine uptake and vaccination-related communication between patients and healthcare providers using bivariate probit models.Results. 64.1% (95%-CI: 61.5%-66.6%) of adults did not receive any provider-issued influenza vaccination recommendation. Adults who received a provider-issued vaccination recommendation were 14.1 (95%-CI: -2.4 to 30.6) to 32.1 (95%-CI: 24.3-39.8) percentage points more likely to be vaccinated for influenza than adults without a provider recommendation, after adjusting for other characteristics associated with vaccination.Conclusions. Influenza vaccination communication between healthcare providers and adults was relatively uncommon during the 2009-2010 pandemic. Increased communication could significantly enhance influenza vaccination rates. (C) 2011 Elsevier Inc. All rights reserved.

Extreme Precipitation Modelling Using Geostatistics and Machine Learning Algorithms

The paper presents an approach for mapping of precipitation data. The main goal is to perform spatial predictions and simulations of precipitation fields using geostatistical methods (ordinary kriging, kriging with external drift) as well as machine learning algorithms (neural networks). More practically, the objective is to reproduce simultaneously both the spatial patterns and the extreme values. This objective is best reached by models integrating geostatistics and machine learning algorithms. To demonstrate how such models work, two case studies have been considered: first, a 2-day accumulation of heavy precipitation and second, a 6-day accumulation of extreme orographic precipitation. The first example is used to compare the performance of two optimization algorithms (conjugate gradients and Levenberg-Marquardt) of a neural network for the reproduction of extreme values. Hybrid models, which combine geostatistical and machine learning algorithms, are also treated in this context. The second dataset is used to analyze the contribution of radar Doppler imagery when used as external drift or as input in the models (kriging with external drift and neural networks). Model assessment is carried out by comparing independent validation errors as well as analyzing data patterns.

Cinéma, machine à mondes : essai sur les films à univers multiples

Dans cet ouvrage, l'auteur propose une conceptualisation théorique de la coprésence en un même film de mondes multiples en abordant différents paramètres (hétérogénéité de la facture de l'image, pratiques du montage alterné, typologie des enchâssements, expansion sérielle, etc.) sur la base d'un corpus de films de fiction récents qui appartiennent pour la plupart au genre de la science-fiction (Matrix, Dark City, Avalon, Resident Evil, Avatar,...). Issue de la filmologie, la notion de « diégèse » y est développée à la fois dans le potentiel d'autonomisation dont témoigne la conception mondaine qui semble dominer aujourd'hui à l'ère des jeux vidéo, dans ses liens avec le récit et dans une perspective intermédiale. Les films discutés ont la particularité de mettre en scène des machines permettant aux personnages de passer d'un monde à l'autre : les modes de figuration de ces technologies sont investigués en lien avec les imaginaires du dispositif cinématographique et les potentialité du montage. La comparaison entre les films (Tron et son récent sequel, Totall Recall et son remake) et entre des oeuvres filmiques et littéraires (en particulier les nouvelles de Philip K. Dick et Simlacron 3 de Galouye) constitue un outil d'analyse permettant de saisir la contemporanéité de cette problématique, envisagée sur le plan esthétique dans le contexte de l'imagerie numérique.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

From Naples 1963 to Rome 2013 - A brief review of how the International Research Group on Ostracoda (IRGO) developed as a social communication system

The 1st International Symposium on Ostracoda (ISO) was held in Naples (1963). The philosophy behind this symposium and the logical outcome of what is now known as the International Research Group on Ostracoda (IRGO) is here reviewed, namely ostracodology over the last 50 years is sociologically analysed. Three different and important historic moments for the scientific achievements of this domain are recognised. The first one, between about 1963-1983, is related to applied research for the oil industry as well as to the great interest in the better description of the marine environment by both zoologists and palaeontologists. Another important aspect during this period was the work by researchers dealing with Palaeozoic ostracods, who had their own discussion group, IRGPO. Gradually, the merger of this latter group with those dealing with post-Palaeozoic ostracods at various meetings improved communication between the two groups of specialists. A second period was approximately delineated between 1983 and 2003. During this time-slice, more emphasis was addressed to environmental research with topics such as the study of global events and long-term climate change. Ostracodologists profited also from the research "politics" within national and international programmes. Large international research teams emerged using new research methods. During the third period (2003-2013), communication and collaborative research reached a global dimension. Amongst the topics of research we cite the reconstruction of palaeoclimate using transfer functions, the building of large datasets of ostracod distributions for regional and intercontinental studies, and the implementation of actions that should lead to taxonomic harmonisation. Projects within which molecular biological techniques are routinely used, combined with sophisticated morphological information, expanded now in their importance. The documentation of the ostracod description improved through new techniques to visualise morphological details, which stimulated also communication between ostracodologists. Efforts of making available ostracod information through newsletters and electronic media are evoked.

Espace public, médiations, reconnaissance : Eléments de reconstruction d'une théorie critique de la communication

Résumé en français Après un examen critique de la théorie des médias et de la culture développée par l'Ecole de Francfort, abordée ici principalement au travers des oeuvres de T.W. Adorno et de Jürgen Habeimas, ce travail en propose une reconstruction en s'inspirant de la théorie de la reconnaissance d'Axel Honneth. Envisagée sous un angle narratif, la communication publique est vue comme un processus engageant à la fois des relations de reconnaissance et leur négation sous la double forme de la réification et du mépris. La recherche développe une approche des médias sensible à ces tensions et conflits ainsi qu'aux luttes pour la reconnaissance qui travaillent la scène publique, y compris dans sa dimension esthétique. Title and abstract in english « Public sphere, mediations, recognition. Reconstruction elements of a critical theory of communication ». After a critical discussion of media and culture theory developped by the Frankfurt School presented here mainly through the works of T.W. Adorno and Jürgen Habermas, this research proposes to reconstruct it on the basis of the theory of recognition developed by Axel Honneth. Considered through the perspective of narrative, public communication in is seen as a process implying at the same time recognition relations and their negation through the double process of reification and disrespect. The research develops an approach of media which is attentive to those tensions and conflicts and to the struggles for recognition that forms public sphere, also in his aesthetic dimension.