Patients' prediction of extubation success.

The spontaneous breathing trial (SBT)-relying on objective criteria assessed by the clinician-is the major diagnostic tool to determine if patients can be successfully extubated. However, little is known regarding the patient's subjective perception of autonomous breathing. We performed a prospective observational study in 211 mechanically ventilated adult patients successfully completing a SBT. Patients were randomly assigned to be interviewed during this trial regarding their prediction of extubation success. We compared post-extubation outcomes in three patient groups: patients confident (confidents; n = 115) or not (non-confidents; n = 38) of their extubation success and patients not subjected to interview (control group; n = 58). Extubation success was more frequent in confidents than in non-confidents (90 vs. 45%; p < 0.001/positive likelihood ratio = 2.00) or in the control group (90 vs. 78%; p = 0.04). On the contrary, extubation failure was more common in non-confidents than in confidents (55 vs. 10%; p < 0.001/negative likelihood ratio = 0.19). Logistic regression analysis showed that extubation success was associated with patient's prediction [OR (95% CI): 9.2 (3.74-22.42) for confidents vs.non-confidents] as well as to age [0.72 (0.66-0.78) for age 75 vs. 65 and 1.31 (1.28-1.51) for age 55 vs. 65]. Our data suggest that at the end of a sustained SBT, extubation success might be correlated to the patients' subjective perception of autonomous breathing. The results of this study should be confirmed by a large multicenter trial.

Regularity and mass conservation for discrete coagulation-fragmentation equations with diffusion

We present a new a-priori estimate for discrete coagulation fragmentation systems with size-dependent diffusion within a bounded, regular domain confined by homogeneous Neumann boundary conditions. Following from a duality argument, this a-priori estimate provides a global L2 bound on the mass density and was previously used, for instance, in the context of reaction-diffusion equations. In this paper we demonstrate two lines of applications for such an estimate: On the one hand, it enables to simplify parts of the known existence theory and allows to show existence of solutions for generalised models involving collision-induced, quadratic fragmentation terms for which the previous existence theory seems difficult to apply. On the other hand and most prominently, it proves mass conservation (and thus the absence of gelation) for almost all the coagulation coefficients for which mass conservation is known to hold true in the space homogeneous case.

A mixed finite element method for nonlinear diffusion equations

We propose a mixed finite element method for a class of nonlinear diffusion equations, which is based on their interpretation as gradient flows in optimal transportation metrics. We introduce an appropriate linearization of the optimal transport problem, which leads to a mixed symmetric formulation. This formulation preserves the maximum principle in case of the semi-discrete scheme as well as the fully discrete scheme for a certain class of problems. In addition solutions of the mixed formulation maintain exponential convergence in the relative entropy towards the steady state in case of a nonlinear Fokker-Planck equation with uniformly convex potential. We demonstrate the behavior of the proposed scheme with 2D simulations of the porous medium equations and blow-up questions in the Patlak-Keller-Segel model.

Stable stationary states of non-local interaction equations

"Vegeu el resum a l'inici del document del fitxer adjunt."

Psychoses a l'adolescence, les neurosciences ameliorent-elles la prediction? [Adolescent psychosis, can neuroscience improve prediction?]

Developments in the field of neuroscience have created a high level of interest in the subject of adolescent psychosis, particularly in relation to prediction and prevention. As the medical practice of adolescent psychosis and its treatment is characterised by a heterogeneity which is both symptomatic and evolutive, the somewhat poor prognosis of chronic development justifies the research performed: apparent indicators of schizophrenic disorders on the one hand and specific endophenotypes on the other are becoming increasingly important. The significant progresses made on the human genome show that the genetic predetermination in current psychiatric pathologies is complex and subject to moderating effects and there is therefore significant potential for nature-nurture interactions (between the environment and the genes). The road to be followed in researching the phenotypic expression of a psychosis gene is long and winding and is susceptible to many external influences at various levels with different effects. Neurobiological, neurophysiological, neuropsychological and neuroanatomical studies help to identify endophenotypes, which allow researchers to create identifying "markers" along this winding road. The endophenotypes could make it possible to redefine the nosological categories and enhance understanding of the physiopathology of schizophrenia. In a predictive approach, large-scale retrospective and prospective studies make it possible to identify risk factors, which are compatible with the neurodevelopmental hypothesis of schizophrenia. However, the predictive value of such markers or risk indicators is not yet sufficiently developed to offer a reliable early-detection method or possible schizophrenia prevention measures. Nonetheless, new developments show promise against the background of a possible future nosographic revolution, based on a paradigm shift. It is perhaps on the basis of homogeneous endophenotypes in particular that we will be able to understand what protects against, or indeed can trigger, psychosis irrespective of the clinical expression or attempts to isolate the common genetic and biological bases according to homogeneous clinical characteristics, which have to date, proved unsuccessful

Equations of hyperelliptic Shimura curves

We describe an algorithm that computes explicit models of hyperelliptic Shimura curves attached to an indefinite quaternion algebra over Q and Atkin-Lehner quotients of them. It exploits Cerednik-Drinfeld’s nonarchimedean uniformisation of Shimura curves, a formula of Gross and Zagier for the endomorphism ring of Heegner points over Artinian rings and the connection between Ribet’s bimodules and the specialization of Heegner points, as introduced in [21]. As an application, we provide a list of equations of Shimura curves and quotients of them obtained by our algorithm that had been conjectured by Kurihara.

Prediction of the economic cost of individual long-term care in the Spanish population

Pensions together with savings and investments during active life are key elements of retirement planning. Motivation for personal choices about the standard of living, bequest and the replacement ratio of pension with respect to last salary income must be considered. This research contributes to the financial planning by helping to quantify long-term care economic needs. We estimate life expectancy from retirement age onwards. The economic cost of care per unit of service is linked to the expected time of needed care and the intensity of required services. The expected individual cost of long-term care from an onset of dependence is estimated separately for men and women. Assumptions on the mortality of the dependent people compared to the general population are introduced. Parameters defining eligibility for various forms of coverage by the universal public social care of the welfare system are addressed. The impact of the intensity of social services on individual predictions is assessed, and a partial coverage by standard private insurance products is also explored. Data were collected by the Spanish Institute of Statistics in two surveys conducted on the general Spanish population in 1999 and in 2008. Official mortality records and life table trends were used to create realistic scenarios for longevity. We find empirical evidence that the public long-term care system in Spain effectively mitigates the risk of incurring huge lifetime costs. We also find that the most vulnerable categories are citizens with moderate disabilities that do not qualify to obtain public social care support. In the Spanish case, the trends between 1999 and 2008 need to be further explored.

In silico prediction of human carboxylesterase-1 (hCES1) metabolism combining docking analyses and MD simulations.

Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted in developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas little has been done to predict the hydrolytic activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES1. The study involves both docking analyses of known substrates to develop predictive models, and molecular dynamics (MD) simulations to reveal the in situ behavior of substrates and products, with particular attention being paid to the influence of their ionization state. The results emphasize some crucial properties of the hCES1 catalytic cavity, confirming that as a trend with several exceptions, hCES1 prefers substrates with relatively smaller and somewhat polar alkyl/aryl groups and larger hydrophobic acyl moieties. The docking results underline the usefulness of the hydrophobic interaction score proposed here, which allows a robust prediction of hCES1 catalysis, while the MD simulations show the different behavior of substrates and products in the enzyme cavity, suggesting in particular that basic substrates interact with the enzyme in their unprotonated form.

Stabilized Petrov-Galerkin methods for the convection-diffusion-reaction and the Helmholtz equations

We present two new stabilized high-resolution numerical methods for the convection–diffusion–reaction (CDR) and the Helmholtz equations respectively. The work embarks upon a priori analysis of some consistency recovery procedures for some stabilization methods belonging to the Petrov–Galerkin framework. It was found that the use of some standard practices (e.g. M-Matrices theory) for the design of essentially non-oscillatory numerical methods is not feasible when consistency recovery methods are employed. Hence, with respect to convective stabilization, such recovery methods are not preferred. Next, we present the design of a high-resolution Petrov–Galerkin (HRPG) method for the 1D CDR problem. The problem is studied from a fresh point of view, including practical implications on the formulation of the maximum principle, M-Matrices theory, monotonicity and total variation diminishing (TVD) finite volume schemes. The current method is next in line to earlier methods that may be viewed as an upwinding plus a discontinuity-capturing operator. Finally, some remarks are made on the extension of the HRPG method to multidimensions. Next, we present a new numerical scheme for the Helmholtz equation resulting in quasi-exact solutions. The focus is on the approximation of the solution to the Helmholtz equation in the interior of the domain using compact stencils. Piecewise linear/bilinear polynomial interpolation are considered on a structured mesh/grid. The only a priori requirement is to provide a mesh/grid resolution of at least eight elements per wavelength. No stabilization parameters are involved in the definition of the scheme. The scheme consists of taking the average of the equation stencils obtained by the standard Galerkin finite element method and the classical finite difference method. Dispersion analysis in 1D and 2D illustrate the quasi-exact properties of this scheme. Finally, some remarks are made on the extension of the scheme to unstructured meshes by designing a method within the Petrov–Galerkin framework.

Structural prediction of peptides bound to MHC class I.

An ab initio structure prediction approach adapted to the peptide-major histocompatibility complex (MHC) class I system is presented. Based on structure comparisons of a large set of peptide-MHC class I complexes, a molecular dynamics protocol is proposed using simulated annealing (SA) cycles to sample the conformational space of the peptide in its fixed MHC environment. A set of 14 peptide-human leukocyte antigen (HLA) A0201 and 27 peptide-non-HLA A0201 complexes for which X-ray structures are available is used to test the accuracy of the prediction method. For each complex, 1000 peptide conformers are obtained from the SA sampling. A graph theory clustering algorithm based on heavy atom root-mean-square deviation (RMSD) values is applied to the sampled conformers. The clusters are ranked using cluster size, mean effective or conformational free energies, with solvation free energies computed using Generalized Born MV 2 (GB-MV2) and Poisson-Boltzmann (PB) continuum models. The final conformation is chosen as the center of the best-ranked cluster. With conformational free energies, the overall prediction success is 83% using a 1.00 Angstroms crystal RMSD criterion for main-chain atoms, and 76% using a 1.50 Angstroms RMSD criterion for heavy atoms. The prediction success is even higher for the set of 14 peptide-HLA A0201 complexes: 100% of the peptides have main-chain RMSD values &lt; or =1.00 Angstroms and 93% of the peptides have heavy atom RMSD values &lt; or =1.50 Angstroms. This structure prediction method can be applied to complexes of natural or modified antigenic peptides in their MHC environment with the aim to perform rational structure-based optimizations of tumor vaccines.