Imagerie cardiaque non invasive: apport spécifique en clinique des nouvelles modalités (I). Evaluation morphologique [Cardiac imaging: specific clinical role of newly developed non invasive techniques. Part 1: Morphological evaluation].

Echocardiography is the preferred initial test to assess cardiac morphology and ventricular function. Cardiac MRI enables an optimal visualisation of heart muscle without contrast injection, and precise measurement of the ventricular volumes and systolic function. It is therefore an ideal test for patients with poor echocardiographic windows or for the specific evaluation of right heart chambers. Heart CT also remarkably images heart muscle and precisely measures ventricular systolic function after intravenous injection of iodinated contrast. Coronary CT may also, in selected cases, avoid the need for diagnostic coronary angiography. Although very accurate, these imaging modalities are expensive and may be contra-indicated for a particular patient. Their use in clinical practice has to follow the accepted guidelines.

Implementing statistical learning methods through Bayesian networks (Part 2): bayesian evaluations for results of black toner analyses in forensic document examination

This paper presents and discusses the use of Bayesian procedures - introduced through the use of Bayesian networks in Part I of this series of papers - for 'learning' probabilities from data. The discussion will relate to a set of real data on characteristics of black toners commonly used in printing and copying devices. Particular attention is drawn to the incorporation of the proposed procedures as an integral part in probabilistic inference schemes (notably in the form of Bayesian networks) that are intended to address uncertainties related to particular propositions of interest (e.g., whether or not a sample originates from a particular source). The conceptual tenets of the proposed methodologies are presented along with aspects of their practical implementation using currently available Bayesian network software.

Adaptively weighted maximum likelihood estimation of discrete distributions

SummaryDiscrete data arise in various research fields, typically when the observations are count data.I propose a robust and efficient parametric procedure for estimation of discrete distributions. The estimation is done in two phases. First, a very robust, but possibly inefficient, estimate of the model parameters is computed and used to indentify outliers. Then the outliers are either removed from the sample or given low weights, and a weighted maximum likelihood estimate (WML) is computed.The weights are determined via an adaptive process such that if the data follow the model, then asymptotically no observation is downweighted.I prove that the final estimator inherits the breakdown point of the initial one, and that its influence function at the model is the same as the influence function of the maximum likelihood estimator, which strongly suggests that it is asymptotically fully efficient.The initial estimator is a minimum disparity estimator (MDE). MDEs can be shown to have full asymptotic efficiency, and some MDEs have very high breakdown points and very low bias under contamination. Several initial estimators are considered, and the performances of the WMLs based on each of them are studied.It results that in a great variety of situations the WML substantially improves the initial estimator, both in terms of finite sample mean square error and in terms of bias under contamination. Besides, the performances of the WML are rather stable under a change of the MDE even if the MDEs have very different behaviors.Two examples of application of the WML to real data are considered. In both of them, the necessity for a robust estimator is clear: the maximum likelihood estimator is badly corrupted by the presence of a few outliers.This procedure is particularly natural in the discrete distribution setting, but could be extended to the continuous case, for which a possible procedure is sketched.RésuméLes données discrètes sont présentes dans différents domaines de recherche, en particulier lorsque les observations sont des comptages.Je propose une méthode paramétrique robuste et efficace pour l'estimation de distributions discrètes. L'estimation est faite en deux phases. Tout d'abord, un estimateur très robuste des paramètres du modèle est calculé, et utilisé pour la détection des données aberrantes (outliers). Cet estimateur n'est pas nécessairement efficace. Ensuite, soit les outliers sont retirés de l'échantillon, soit des faibles poids leur sont attribués, et un estimateur du maximum de vraisemblance pondéré (WML) est calculé.Les poids sont déterminés via un processus adaptif, tel qu'asymptotiquement, si les données suivent le modèle, aucune observation n'est dépondérée.Je prouve que le point de rupture de l'estimateur final est au moins aussi élevé que celui de l'estimateur initial, et que sa fonction d'influence au modèle est la même que celle du maximum de vraisemblance, ce qui suggère que cet estimateur est pleinement efficace asymptotiquement.L'estimateur initial est un estimateur de disparité minimale (MDE). Les MDE sont asymptotiquement pleinement efficaces, et certains d'entre eux ont un point de rupture très élevé et un très faible biais sous contamination. J'étudie les performances du WML basé sur différents MDEs.Le résultat est que dans une grande variété de situations le WML améliore largement les performances de l'estimateur initial, autant en terme du carré moyen de l'erreur que du biais sous contamination. De plus, les performances du WML restent assez stables lorsqu'on change l'estimateur initial, même si les différents MDEs ont des comportements très différents.Je considère deux exemples d'application du WML à des données réelles, où la nécessité d'un estimateur robuste est manifeste : l'estimateur du maximum de vraisemblance est fortement corrompu par la présence de quelques outliers.La méthode proposée est particulièrement naturelle dans le cadre des distributions discrètes, mais pourrait être étendue au cas continu.

Ab initio absorption spectrum of NiO combining molecular dynamics with the embedded cluster approach in a discrete reaction field

We developed a procedure that combines three complementary computational methodologies to improve the theoretical description of the electronic structure of nickel oxide. The starting point is a Car-Parrinello molecular dynamics simulation to incorporate vibrorotational degrees of freedom into the material model. By means ofcomplete active space self-consistent field second-order perturbation theory (CASPT2) calculations on embedded clusters extracted from the resulting trajectory, we describe localized spectroscopic phenomena on NiO with an efficient treatment of electron correlation. The inclusion of thermal motion into the theoretical description allowsus to study electronic transitions that, otherwise, would be dipole forbidden in the ideal structure and results in a natural reproduction of the band broadening. Moreover, we improved the embedded cluster model by incorporating self-consistently at the complete active space self-consistent field (CASSCF) level a discrete (or direct) reaction field (DRF) in the cluster surroundings. The DRF approach offers an efficient treatment ofelectric response effects of the crystalline embedding to the electronic transitions localized in the cluster. We offer accurate theoretical estimates of the absorption spectrum and the density of states around the Fermi level of NiO, and a comprehensive explanation of the source of the broadening and the relaxation of the charge transferstates due to the adaptation of the environment

Critical thinking and accuracy of nurses' diagnoses. Part I: risk of low accuracy diagnoses and new views of critical thinking

Interpretations of patient data are complex and diverse, contributing to a risk of low accuracy nursing diagnoses. This risk is confirmed in research findings that accuracy of nurses' diagnoses varied widely from high to low. Highly accurate diagnoses are essential, however, to guide nursing interventions for the achievement of positive health outcomes. Development of critical thinking abilities is likely to improve accuracy of nurses' diagnoses. Newer views of critical thinking serve as a basis for critical thinking in nursing. Seven cognitive skills and ten habits of mind are identified as dimensions of critical thinking for use in the diagnostic process.

Review of therapeutic drug monitoring of anticancer drugs part two - Targeted therapies.

Most of oral targeted therapies are tyrosine kinase inhibitors (TKIs). Oral administration generates a complex step in the pharmacokinetics (PK) of these drugs. Inter-individual PK variability is often large and variability observed in response is influenced not only by the genetic heterogeneity of drug targets, but also by the pharmacogenetic background of the patient (e.g. cytochome P450 and ABC transporter polymorphisms), patient characteristics such as adherence to treatment and environmental factors (drug-drug interactions). Retrospective studies have shown that targeted drug exposure, reflected in the area under the plasma concentration-time curve (AUC) correlates with treatment response (efficacy/toxicity) in various cancers. Nevertheless levels of evidence for therapeutic drug monitoring (TDM) are however heterogeneous among these agents and TDM is still uncommon for the majority of them. Evidence for imatinib currently exists, others are emerging for compounds including nilotinib, dasatinib, erlotinib, sunitinib, sorafenib and mammalian target of rapamycin (mTOR) inhibitors. Applications for TDM during oral targeted therapies may best be reserved for particular situations including lack of therapeutic response, severe or unexpected toxicities, anticipated drug-drug interactions and/or concerns over adherence treatment. Interpatient PK variability observed with monoclonal antibodies (mAbs) is comparable or slightly lower to that observed with TKIs. There are still few data with these agents in favour of TDM approaches, even if data showed encouraging results with rituximab, cetuximab and bevacizumab. At this time, TDM of mAbs is not yet supported by scientific evidence. Considerable effort should be made for targeted therapies to better define concentration-effect relationships and to perform comparative randomised trials of classic dosing versus pharmacokinetically-guided adaptive dosing.

Critical thinking and accuracy of nurses' diagnoses. Part II: application of cognitive skills and guidelines for self-development

Part I of this article, the author explained the difficulties of achieving accuracy of nurses' diagnoses, the relevance of critical thinking to the achievement of accuracy, and newer views of critical thinking. In Part II, the critical thinking dimensions identified as important for nursing practice are applied in the diagnostic process using a case study of a 16 year old girl with type 1 diabetes. Application of seven cognitive skills and ten habits of mind illustrate the importance of using critical thinking for accuracy of nurses' diagnoses. Ten strategies are proposed for self-development of critical thinking abilities.

The biochemistry of drug metabolism--an introduction: part 5. Metabolism and bioactivity.

This review continues a general presentation of the metabolism of drugs and other xenobiotics begun in five recent issues of Chemistry & Biodiversity. The present Part is dedicated to the pharmacological and toxicological consequences of drug and xenobiotic metabolism. In other words, the key concepts here are activation vs. deactivation, toxification vs. detoxification, and their interplay. These concepts are illustrated with a number of medicinally, toxicologically, and environmentally relevant examples. But, far from being concerned only with individual cases, the review is based on broad classifications, global rationalizations, and synthetic hypotheses.

Forensic intelligence framework. Part II: study of the main generic building blocks and challenges through the examples of illicit drugs and false identity documents monitoring

The development of forensic intelligence relies on the expression of suitable models that better represent the contribution of forensic intelligence in relation to the criminal justice system, policing and security. Such models assist in comparing and evaluating methods and new technologies, provide transparency and foster the development of new applications. Interestingly, strong similarities between two separate projects focusing on specific forensic science areas were recently observed. These observations have led to the induction of a general model (Part I) that could guide the use of any forensic science case data in an intelligence perspective. The present article builds upon this general approach by focusing on decisional and organisational issues. The article investigates the comparison process and evaluation system that lay at the heart of the forensic intelligence framework, advocating scientific decision criteria and a structured but flexible and dynamic architecture. These building blocks are crucial and clearly lay within the expertise of forensic scientists. However, it is only part of the problem. Forensic intelligence includes other blocks with their respective interactions, decision points and tensions (e.g. regarding how to guide detection and how to integrate forensic information with other information). Formalising these blocks identifies many questions and potential answers. Addressing these questions is essential for the progress of the discipline. Such a process requires clarifying the role and place of the forensic scientist within the whole process and their relationship to other stakeholders.

Girl Connection, Girls & Sport-Part II, June 2004

Newsletter for professionals who work with girls involved in or at risk for involvement in the juvenile justice system.

Daughter of time: the postmodern midwife (Part 1)

This article presents the notion of the postmodern midwife, defining her as one who takes a relativistic stance toward bio-medicine and other knowledge systems, alternative and indigenous, moving fluidly between them to serve the women she attends. She is locally and globally aware, culturally competent, and politically engaged, working with the resources at hand to preserve midwifery in the interests of women. Her informed relativism is most accessible to professional midwives but is also beginning to characterize some savvy traditional midwives in various countries. Thus the concept of the postmodern midwife can serve as a bridge across the ethnic, racial, and status gaps that divide the professional from the traditional midwife, and as an analytical focal point for understanding how the members of each group negotiate their identities and their roles in a changing world.

Daughter of time: the postmodern midwife (Part 2)

Any effort to make sense of the complexities of contemporary midwifery must deal not only with biomedical and governmental power structures but also with the definitions such structures impose upon midwives and the ramifications of these definitions within and across national and cultural borders. The international definition of a midwife requires graduations from a government-recognized educational program. Those who have not are not considered midwives but are labeled traditional birth attendants. Since there are myriad local names for midwives in myriad languages, the impact of this naming at local levels can be hard to assess. But on the global scale, the ramifications of the distinction between midwives who meet the international definition and those who do not have been profound. Those who do are incorporated into the health care system. Those who do not remain outside of it, and suffer multiple forms of discrimination as a result.

EU cohesion aid to Spain: a data set. Part II: 1994-99 planning period

In this paper we construct a data set on EU cohesion aid to Spain during the planning period 1994-99. The data are disaggregated by region, year and function and attempt to approximate the timing of actual executed expenditure on assisted projects.