Whole-cell antigenicity data support sequence-based kinetoplastid taxonomy

Early immunological data, obtained by immunodiffusion and immunoelectrophoresis, on the whole-cell antigenicity of kinetoplastid protozoa were retrieved and used to construct a dendrogram of antigenic distances. Remarkably, they supported the same taxonomic conclusions as analyses based on DNA and protein sequence data.

Uncertainty Quantification Of A Semi-Supervised Support Vector Regression Reservoir Model

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. Recent advances in machine learning offer a novel approach to model spatial distribution of petrophysical properties in complex reservoirs alternative to geostatistics. The approach is based of semisupervised learning, which handles both ?labelled? observed data and ?unlabelled? data, which have no measured value but describe prior knowledge and other relevant data in forms of manifolds in the input space where the modelled property is continuous. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic geological features and describe stochastic variability and non-uniqueness of spatial properties. On the other hand, it is able to capture and preserve key spatial dependencies such as connectivity of high permeability geo-bodies, which is often difficult in contemporary petroleum reservoir studies. Semi-supervised SVR as a data driven algorithm is designed to integrate various kind of conditioning information and learn dependences from it. The semi-supervised SVR model is able to balance signal/noise levels and control the prior belief in available data. In this work, stochastic semi-supervised SVR geomodel is integrated into Bayesian framework to quantify uncertainty of reservoir production with multiple models fitted to past dynamic observations (production history). Multiple history matched models are obtained using stochastic sampling and/or MCMC-based inference algorithms, which evaluate posterior probability distribution. Uncertainty of the model is described by posterior probability of the model parameters that represent key geological properties: spatial correlation size, continuity strength, smoothness/variability of spatial property distribution. The developed approach is illustrated with a fluvial reservoir case. The resulting probabilistic production forecasts are described by uncertainty envelopes. The paper compares the performance of the models with different combinations of unknown parameters and discusses sensitivity issues.

Desenvolupament d'algorismes biològicament inspirats basats en Support Vector Machines

L'objectiu d'aquest projecte ha estat el desenvolupament d'algorismes biològicament inspirats per a l'olfacció artificial. Per a assolir-lo ens hem basat en el paradigma de les màquines amb suport vectorial. Hem construit algoritmes que imitaven els processos computacionals dels diferents sistemes que formen el sistema olfactiu dels insectes, especialment de la llagosta Schistocerca gregaria. Ens hem centrat en el lòbuls de les antenes, i en el cos fungiforme. El primer està considerat un dispositiu de codificació de les olors, que a partir de la resposta temporal dels receptors olfactius a les antenes genera un patró d'activació espaial i temporal. Quant al cos fungiforme es considera que la seva funció és la d'una memòria per als olors, així com un centre per a la integració multi-sensorial. El primer pas ha estat la construcció de models detallats dels dos sistemes. A continuació, hem utilitzat aquests models per a processar diferents tipus de senyals amb l'objectiu de abstraure els principis computacionals subjacents. Finalment, hem avaluat les capacitats d'aquests models abstractes, i els hem utilitzat per al processat de dades provinents de sensors de gasos. Els resultats mostren que el models abstractes tenen millor comportament front el soroll i més capacitat d'emmagatzematge de records que altres models més clàssics, com ara les memòries associatives de Hopfield o fins i tot en determinades circumstàncies que les mateixes Support Vector Machines.

The EPAGE internet guideline as a decision support tool for determining the appropriateness of colonoscopy

RÉSUMÉ Contexte : Peu d'études ont examiné la façon dont les médecins appréhendent les guidelines, et encore moins celle dont ils perçoivent de tels guidelines disponibles sur Internet. Cette étude évalue l'acceptation par les médecins d'un guideline électronique portant sur l'adéquation de la colonoscopie. Méthode : Des gastroentérologues participant à une étude observationnelle internationale ont consulté un guideline électronique pour une série consécutive de patients adressés pour une colonoscopie. Le guideline a été élaboré par le Panel Européen sur l'Adéquation de l'Endoscopie Gastro-intestinale (EPAGE en version anglaise), utilisant une méthode validée (RAND). Les opinions des médecins sur le guideline, sur le site Internet et sur les perspectives d'utilisation ont été recueillies au moyen de questionnaires. Résultats : 289 patients ont été inclus dans l'étude. Le temps moyen pour consulter le site Internet a été de 1.8 min et 86% des médecins l'ont considéré comme simple à utiliser. Les recommandations ont été facilement localisées pour 82% des patients et les médecins étaient d'accord avec l'adéquation de la colonoscopie dans 86% des cas. Selon les critères EPAGE, la colonoscopie était appropriée, incertaine et inappropriée, respectivement chez 59, 28 et 13% des patients. Conclusions : Le guideline EPAGE a été considéré comme acceptable et simple à utiliser. L'utilisation, l'utilité et la pertinence du site Internet a été jugée comme acceptable. Son utilisation effective dépendra cependant de la levée de certains obstacles au niveau organisationnel et culturel.

Claudin-19 mutations and clinical phenotype in Spanish patients with familial hypomagnesemia with hypercalciuria and nephrocalcinosis.

Familial hypomagnesemia with hypercalciuria and nephrocalcinosis is an autosomal recessive tubular disorder characterized by excessive renal magnesium and calcium excretion and chronic kidney failure. This rare disease is caused by mutations in the CLDN16 and CLDN19 genes. These genes encode the tight junction proteins claudin-16 and claudin-19, respectively, which regulate the paracellular ion reabsorption in the kidney. Patients with mutations in the CLDN19 gene also present severe visual impairment. Our goals in this study were to examine the clinical characteristics of a large cohort of Spanish patients with this disorder and to identify the disease causing mutations. We included a total of 31 patients belonging to 27 unrelated families and studied renal and ocular manifestations. We then analyzed by direct DNA sequencing the coding regions of CLDN16 and CLDN19 genes in these patients. Bioinformatic tools were used to predict the consequences of mutations. Clinical evaluation showed ocular defects in 87% of patients, including mainly myopia, nystagmus and macular colobomata. Twenty two percent of patients underwent renal transplantation and impaired renal function was observed in another 61% of patients. Results of the genetic analysis revealed CLDN19 mutations in all patients confirming the clinical diagnosis. The majority of patients exhibited the previously described p.G20D mutation. Haplotype analysis using three microsatellite markers showed a founder effect for this recurrent mutation in our cohort. We also identified four new pathogenic mutations in CLDN19, p.G122R, p.I41T, p.G75C and p.G75S. A strategy based on microsequencing was designed to facilitate the genetic diagnosis of this disease. Our data indicate that patients with CLDN19 mutations have a high risk of progression to chronic renal disease.

Statistical discrimination of steroid profiles in doping control with support vector machines.

Due to their performance enhancing properties, use of anabolic steroids (e.g. testosterone, nandrolone, etc.) is banned in elite sports. Therefore, doping control laboratories accredited by the World Anti-Doping Agency (WADA) screen among others for these prohibited substances in urine. It is particularly challenging to detect misuse with naturally occurring anabolic steroids such as testosterone (T), which is a popular ergogenic agent in sports and society. To screen for misuse with these compounds, drug testing laboratories monitor the urinary concentrations of endogenous steroid metabolites and their ratios, which constitute the steroid profile and compare them with reference ranges to detect unnaturally high values. However, the interpretation of the steroid profile is difficult due to large inter-individual variances, various confounding factors and different endogenous steroids marketed that influence the steroid profile in various ways. A support vector machine (SVM) algorithm was developed to statistically evaluate urinary steroid profiles composed of an extended range of steroid profile metabolites. This model makes the interpretation of the analytical data in the quest for deviating steroid profiles feasible and shows its versatility towards different kinds of misused endogenous steroids. The SVM model outperforms the current biomarkers with respect to detection sensitivity and accuracy, particularly when it is coupled to individual data as stored in the Athlete Biological Passport.

Infornut® Process; improves accessibility to diagnosis and nutritional support for the malnourished hospitalized patient; impact on management indicators; two-year assessment.

Introduction: The high prevalence of disease-related hospital malnutrition justifies the need for screening tools and early detection in patients at risk for malnutrition, followed by an assessment targeted towards diagnosis and treatment. At the same time there is clear undercoding of malnutrition diagnoses and the procedures to correct it Objectives: To describe the INFORNUT program/ process and its development as an information system. To quantify performance in its different phases. To cite other tools used as a coding source. To calculate the coding rates for malnutrition diagnoses and related procedures. To show the relationship to Mean Stay, Mortality Rate and Urgent Readmission; as well as to quantify its impact on the hospital Complexity Index and its effect on the justification of Hospitalization Costs. Material and methods: The INFORNUT® process is based on an automated screening program of systematic detection and early identification of malnourished patients on hospital admission, as well as their assessment, diagnoses, documentation and reporting. Of total readmissions with stays longer than three days incurred in 2008 and 2010, we recorded patients who underwent analytical screening with an alert for a medium or high risk of malnutrition, as well as the subgroup of patients in whom we were able to administer the complete INFORNUT® process, generating a report for each.

Soins palliatifs et soins de support: à la frontière de la toute-puissance médicale [Palliative and supportive care: at the frontiers of medical omnipotence].

Cancer patients have physical, social, spiritual and emotional needs. They may suffer from severe physical symptoms, from social isolation, spiritual abandonment, and emotions such as sadness and anxiety, or feelings of deception, helplessness, anger and guilt. In some of them, the disease is rapidly progressing and ultimately they die. Their demanding care evokes intense feelings in health care providers, the more since these incurable patients represent a challenge, which could be condensed under the heading "the challenge of medical omnipotence". We suppose that the way health care providers cope with these circumstances has a profound influence on the way these patients are cared for. The attitudes towards the emerging heterogeneous movement of palliative and supportive care and towards its different models of implementation can be viewed from this point of view. We try to demonstrate these interrelations and to discuss the danger that may arise if they remain obscure and unreflected.

Congenital heart disease affects local gyrification in 22q11.2 deletion syndrome.

22q11.2 deletion syndrome (22q11.2DS) is a common genetic condition associated with cognitive and learning impairments. In this study, we applied a three-dimensional method for quantifying gyrification at thousands of points over the cortical surface to imaging data from 44 children, adolescents, and young adults with 22q11.2DS (17 males, 27 females; mean age 17y 2mo [SD 9y 1mo], range 6-37y), and 53 healthy participants (21 males, 32 females; mean age 15y 4mo [SD 8y 6mo]; range 6-40y). Several clusters of reduced gyrification were observed, further substantiating the pattern of cerebral alterations presented by children with the syndrome. Comparisons within 22q11.2DS demonstrated an effect of congenital heart disease (CHD) on cortical gyrification, with reduced gyrification at the parieto-temporo-occipital junction in patients with CHD, as compared with patients without CHD. Reductions in gyrification can resemble mild polymicrogyria, suggesting early abnormal neuronal proliferation or migration and providing support for an effect of hemodynamic factors on brain development in 22q11.2DS. The results also shed light on the pathophysiology of acquired brain injury in other populations with CHD.

A Clinical Decision Support using a Terminology Server to improve Patient Safety.

Clinical Decision Support Systems (CDSS) are software applications that support clinicians in making healthcare decisions providing relevant information for individual patients about their specific conditions. The lack of integration between CDSS and Electronic Health Record (EHR) has been identified as a significant barrier to CDSS development and adoption. Andalusia Healthcare Public System (AHPS) provides an interoperable health information infrastructure based on a Service Oriented Architecture (SOA) that eases CDSS implementation. This paper details the deployment of a CDSS jointly with the deployment of a Terminology Server (TS) within the AHPS infrastructure. It also explains a case study about the application of decision support to thromboembolism patients and its potential impact on improving patient safety. We will apply the inSPECt tool proposal to evaluate the appropriateness of alerts in this scenario.