A simple, robust and rapid approach to detect carbapenemases in Gram-negative isolates by MALDI-TOF mass spectrometry: validation with triple quadripole tandem mass spectrometry, microarray and PCR.

Carbapenemases should be accurately and rapidly detected, given their possible epidemiological spread and their impact on treatment options. Here, we developed a simple, easy and rapid matrix-assisted laser desorption ionization-time of flight (MALDI-TOF)-based assay to detect carbapenemases and compared this innovative test with four other diagnostic approaches on 47 clinical isolates. Tandem mass spectrometry (MS-MS) was also used to determine accurately the amount of antibiotic present in the supernatant after 1 h of incubation and both MALDI-TOF and MS-MS approaches exhibited a 100% sensitivity and a 100% specificity. By comparison, molecular genetic techniques (Check-MDR Carba PCR and Check-MDR CT103 microarray) showed a 90.5% sensitivity and a 100% specificity, as two strains of Aeromonas were not detected because their chromosomal carbapenemase is not targeted by probes used in both kits. Altogether, this innovative MALDI-TOF-based approach that uses a stable 10-μg disk of ertapenem was highly efficient in detecting carbapenemase, with a sensitivity higher than that of PCR and microarray.

Protein-ligand binding free energy estimation using molecular mechanics and continuum electrostatics. Application to HIV-1 protease inhibitors.

A method is proposed for the estimation of absolute binding free energy of interaction between proteins and ligands. Conformational sampling of the protein-ligand complex is performed by molecular dynamics (MD) in vacuo and the solvent effect is calculated a posteriori by solving the Poisson or the Poisson-Boltzmann equation for selected frames of the trajectory. The binding free energy is written as a linear combination of the buried surface upon complexation, SASbur, the electrostatic interaction energy between the ligand and the protein, Eelec, and the difference of the solvation free energies of the complex and the isolated ligand and protein, deltaGsolv. The method uses the buried surface upon complexation to account for the non-polar contribution to the binding free energy because it is less sensitive to the details of the structure than the van der Waals interaction energy. The parameters of the method are developed for a training set of 16 HIV-1 protease-inhibitor complexes of known 3D structure. A correlation coefficient of 0.91 was obtained with an unsigned mean error of 0.8 kcal/mol. When applied to a set of 25 HIV-1 protease-inhibitor complexes of unknown 3D structures, the method provides a satisfactory correlation between the calculated binding free energy and the experimental pIC5o without reparametrization.

Robust accelerated failure time regression

Robust estimators for accelerated failure time models with asymmetric (or symmetric) error distribution and censored observations are proposed. It is assumed that the error model belongs to a log-location-scale family of distributions and that the mean response is the parameter of interest. Since scale is a main component of mean, scale is not treated as a nuisance parameter. A three steps procedure is proposed. In the first step, an initial high breakdown point S estimate is computed. In the second step, observations that are unlikely under the estimated model are rejected or down weighted. Finally, a weighted maximum likelihood estimate is computed. To define the estimates, functions of censored residuals are replaced by their estimated conditional expectation given that the response is larger than the observed censored value. The rejection rule in the second step is based on an adaptive cut-off that, asymptotically, does not reject any observation when the data are generat ed according to the model. Therefore, the final estimate attains full efficiency at the model, with respect to the maximum likelihood estimate, while maintaining the breakdown point of the initial estimator. Asymptotic results are provided. The new procedure is evaluated with the help of Monte Carlo simulations. Two examples with real data are discussed.

Does the physical disector method provide an accurate estimation of sensory neuron number in rat dorsal root ganglia?

The physical disector is a method of choice for estimating unbiased neuron numbers; nevertheless, calibration is needed to evaluate each counting method. The validity of this method can be assessed by comparing the estimated cell number with the true number determined by a direct counting method in serial sections. We reconstructed a 1/5 of rat lumbar dorsal root ganglia taken from two experimental conditions. From each ganglion, images of 200 adjacent semi-thin sections were used to reconstruct a volumetric dataset (stack of voxels). On these stacks the number of sensory neurons was estimated and counted respectively by physical disector and direct counting methods. Also, using the coordinates of nuclei from the direct counting, we simulate, by a Matlab program, disector pairs separated by increasing distances in a ganglion model. The comparison between the results of these approaches clearly demonstrates that the physical disector method provides a valid and reliable estimate of the number of sensory neurons only when the distance between the consecutive disector pairs is 60 microm or smaller. In these conditions the size of error between the results of physical disector and direct counting does not exceed 6%. In contrast when the distance between two pairs is larger than 60 microm (70-200 microm) the size of error increases rapidly to 27%. We conclude that the physical dissector method provides a reliable estimate of the number of rat sensory neurons only when the separating distance between the consecutive dissector pairs is no larger than 60 microm.

Evaluation des différentes formules de la loi de Gumbel pour l'estimation des précipitations journalières extrêmes en Suisse

Les précipitations journalières extrêmes centennales ont été estimées à partir d'analyses de Gumbel et de sept formule empiriques effectuées sur des séries de mesures pluviométriques à 151 endroits de la Suisse pour deux périodes de 50 ans. Ces estimations ont été comparées avec les valeurs journalières maximales mesurées durant les 100 dernières années (1911-2010) afin de tester l'efficacité de ces sept formules. Cette comparaison révèle que la formule de Weibull serait la meilleure pour estimer les précipitations journalières centennales à partir de la série de mesures pluviométriques 1961-2010, mais la moins bonne pour la série de mesures 1911-1960. La formule de Hazen serait la plus efficace pour cette dernière période. Ces différences de performances entre les formules empiriques pour les deux périodes étudiées résultent de l'augmentation des précipitations journalières maximales mesurées de 1911 à 2010 pour 90% des stations en Suisse. Mais les différences entre les pluies extrêmes estimées à partir des sept formules empiriques ne dépassent pas 6% en moyenne.

A detailed urinary excretion time course study of captan and folpet biomarkers in workers for the estimation of dose, main route-of-entry and most appropriate sampling and analysis strategies

Captan and folpet are two fungicides largely used in agriculture, but biomonitoring data are mostly limited to measurements of captan metabolite concentrations in spot urine samples of workers, which complicate interpretation of results in terms of internal dose estimation, daily variations according to tasks performed, and most plausible routes of exposure. This study aimed at performing repeated biological measurements of exposure to captan and folpet in field workers (i) to better assess internal dose along with main routes-of-entry according to tasks and (ii) to establish most appropriate sampling and analysis strategies. The detailed urinary excretion time courses of specific and non-specific biomarkers of exposure to captan and folpet were established in tree farmers (n = 2) and grape growers (n = 3) over a typical workweek (seven consecutive days), including spraying and harvest activities. The impact of the expression of urinary measurements [excretion rate values adjusted or not for creatinine or cumulative amounts over given time periods (8, 12, and 24 h)] was evaluated. Absorbed doses and main routes-of-entry were then estimated from the 24-h cumulative urinary amounts through the use of a kinetic model. The time courses showed that exposure levels were higher during spraying than harvest activities. Model simulations also suggest a limited absorption in the studied workers and an exposure mostly through the dermal route. It further pointed out the advantage of expressing biomarker values in terms of body weight-adjusted amounts in repeated 24-h urine collections as compared to concentrations or excretion rates in spot samples, without the necessity for creatinine corrections.

Analysis and spatial modeling of the indoor radon Swiss data

The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.

Pom1 regulates the assembly of Cdr2-Mid1 cortical nodes for robust spatial control of cytokinesis.

Proper division plane positioning is essential to achieve faithful DNA segregation and to control daughter cell size, positioning, or fate within tissues. In Schizosaccharomyces pombe, division plane positioning is controlled positively by export of the division plane positioning factor Mid1/anillin from the nucleus and negatively by the Pom1/DYRK (dual-specificity tyrosine-regulated kinase) gradients emanating from cell tips. Pom1 restricts to the cell middle cortical cytokinetic ring precursor nodes organized by the SAD-like kinase Cdr2 and Mid1/anillin through an unknown mechanism. In this study, we show that Pom1 modulates Cdr2 association with membranes by phosphorylation of a basic region cooperating with the lipid-binding KA-1 domain. Pom1 also inhibits Cdr2 interaction with Mid1, reducing its clustering ability, possibly by down-regulation of Cdr2 kinase activity. We propose that the dual regulation exerted by Pom1 on Cdr2 prevents Cdr2 assembly into stable nodes in the cell tip region where Pom1 concentration is high, which ensures proper positioning of cytokinetic ring precursors at the cell geometrical center and robust and accurate division plane positioning.

A new measurement of energy expenditure and physical activity in patients treated by maintenance hemodialysis

Purpose: The accurate estimation of total energy expenditure (TEE) is essential to allow the provision of nutritional requirements in patients treated by maintenance hemodialysis (MHD). The measurement of TEE and resting energy expenditure (REE) by direct or indirect calorimetry and doubly labeled water are complicated, timeconsuming and cumbersome in this population. Recently, a new system called SenseWear® armband (SWA) was developed to assess TEE, physical activity and REE. This device works by measurements of body acceleration in two axes, heat production and steps counts. REE measured by indirect calorimetry and SWA are well correlated. The aim of this study was to determine TEE, physical activity and REE on patients on MHD using this new device. Methods and materials: Daily TEE, REE, step count, activity time, intensity of activity and lying time were determined for 7 consecutive days in unselected stable patients on MHD and sex, age and weightmatched healthy controls (HC). Patients with malnutrition, cancer, use of immunosuppressive drugs, hypoalbumemia <35 g/L and those hospitalized in the last 3 months, were excluded. For MHD patients, separate analyses were conducted in dialysis and non-dialysis days. Relevant parameters known to affect REE, such as BMI, albumin, pre-albumin, hemoglobin, Kt/V, CRP, bicarbonate, PTH, TSH, were recorded. Results: Thirty patients on MHD and 30 HC were included. In MHD patients, there were 20 men and 10 women. Age was 60,13 years ± 14.97 (mean ± SD), BMI was 25.77 kg/m² ± 4.73 and body weight was 74.65 kg ± 16.16. There were no significant differences between the two groups. TEE was lower in MHD patients compared to HC (28.79 ± 5.51 SD versus 32.91 ± 5.75 SD kcal/kg/day; p <0.01). Activity time was significantly lower in patients on MHD (101.3 ± 12.6SD versus 50.7 ± 9.4 SD min; p = 0.0021). Energy expenditure during the time of activity was significantly lower in MHD patients. MHD patients walked 4543 ± 643 SD vs 8537 ± 744 SD steps per day (p <0.0001). Age was negatively correlated with TEE (r = -0.70) and intensity of activity (r = -0.61) in HC, but not in patients on MHD. TEE showed no difference between dialysis and non-dialysis days (29.92 ± 2.03 SD versus 28.44 ± 1.90 SD kcal/kg/day; p = NS), reflecting a lack of difference in activity (number of steps, time of physical activity) and REE. This finding was observed in MHD patients both older and younger than 60 years. However, age stratification appeared to have an influence on TEE, regardless of dialysis day, (29.92 ± 2.07 SD kcal/kg/day for <60 years-old versus 27.41 ± 1.04 SD kcal/kg/day for ≥60 years old), although failing to reach statistical significance. Conclusion: Using SWA, we have shown that stable patients on MHD have a lower TEE than matched HC. On average, a TEE of 28.79 kcal/kg/day, partially affected by age, was measured. This finding gives support to the clinical impression that it is difficult and probably unnecessary to provide an energy amount of 30-35 kcal/kg/day, as proposed by international guidelines for this population. In addition, we documented for the first time that MHD patients exert a reduced physical activity as compared to HC. There were surprisingly no differences in TEE, REE and physical activity parameters between dialysis and non-dialysis days. This observation might be due to the fact that patients on MHD produce a physical effort to reach the dialysis centre. Age per se did not influence physical activity in MHD patients, contrary to HC, reflecting the impact of co-morbidities on physical activity in this group of patients.

Implementing statistical learning methods through Bayesian networks. Part 1: a guide to Bayesian parameter estimation using forensic science data

As a thorough aggregation of probability and graph theory, Bayesian networks currently enjoy widespread interest as a means for studying factors that affect the coherent evaluation of scientific evidence in forensic science. Paper I of this series of papers intends to contribute to the discussion of Bayesian networks as a framework that is helpful for both illustrating and implementing statistical procedures that are commonly employed for the study of uncertainties (e.g. the estimation of unknown quantities). While the respective statistical procedures are widely described in literature, the primary aim of this paper is to offer an essentially non-technical introduction on how interested readers may use these analytical approaches - with the help of Bayesian networks - for processing their own forensic science data. Attention is mainly drawn to the structure and underlying rationale of a series of basic and context-independent network fragments that users may incorporate as building blocs while constructing larger inference models. As an example of how this may be done, the proposed concepts will be used in a second paper (Part II) for specifying graphical probability networks whose purpose is to assist forensic scientists in the evaluation of scientific evidence encountered in the context of forensic document examination (i.e. results of the analysis of black toners present on printed or copied documents).

Estimation of the noisy component of anatomical backgrounds.

The knowledge of the relationship that links radiation dose and image quality is a prerequisite to any optimization of medical diagnostic radiology. Image quality depends, on the one hand, on the physical parameters such as contrast, resolution, and noise, and on the other hand, on characteristics of the observer that assesses the image. While the role of contrast and resolution is precisely defined and recognized, the influence of image noise is not yet fully understood. Its measurement is often based on imaging uniform test objects, even though real images contain anatomical backgrounds whose statistical nature is much different from test objects used to assess system noise. The goal of this study was to demonstrate the importance of variations in background anatomy by quantifying its effect on a series of detection tasks. Several types of mammographic backgrounds and signals were examined by psychophysical experiments in a two-alternative forced-choice detection task. According to hypotheses concerning the strategy used by the human observers, their signal to noise ratio was determined. This variable was also computed for a mathematical model based on the statistical decision theory. By comparing theoretical model and experimental results, the way that anatomical structure is perceived has been analyzed. Experiments showed that the observer's behavior was highly dependent upon both system noise and the anatomical background. The anatomy partly acts as a signal recognizable as such and partly as a pure noise that disturbs the detection process. This dual nature of the anatomy is quantified. It is shown that its effect varies according to its amplitude and the profile of the object being detected. The importance of the noisy part of the anatomy is, in some situations, much greater than the system noise. Hence, reducing the system noise by increasing the dose will not improve task performance. This observation indicates that the tradeoff between dose and image quality might be optimized by accepting a higher system noise. This could lead to a better resolution, more contrast, or less dose.

Immunization with HIV Gag targeted to dendritic cells followed by recombinant New York vaccinia virus induces robust T-cell immunity in nonhuman primates.

Protein vaccines, if rendered immunogenic, would facilitate vaccine development against HIV and other pathogens. We compared in nonhuman primates (NHPs) immune responses to HIV Gag p24 within 3G9 antibody to DEC205 ("DEC-HIV Gag p24"), an uptake receptor on dendritic cells, to nontargeted protein, with or without poly ICLC, a synthetic double stranded RNA, as adjuvant. Priming s.c. with 60 μg of both HIV Gag p24 vaccines elicited potent CD4(+) T cells secreting IL-2, IFN-γ, and TNF-α, which also proliferated. The responses increased with each of three immunizations and recognized multiple Gag peptides. DEC-HIV Gag p24 showed better cross-priming for CD8(+) T cells, whereas the avidity of anti-Gag antibodies was ∼10-fold higher with nontargeted Gag 24 protein. For both protein vaccines, poly ICLC was essential for T- and B-cell immunity. To determine whether adaptive responses could be further enhanced, animals were boosted with New York vaccinia virus (NYVAC)-HIV Gag/Pol/Nef. Gag-specific CD4(+) and CD8(+) T-cell responses increased markedly after priming with both protein vaccines and poly ICLC. These data reveal qualitative differences in antibody and T-cell responses to DEC-HIV Gag p24 and Gag p24 protein and show that prime boost with protein and adjuvant followed by NYVAC elicits potent cellular immunity.

Estimation du degré de couverture d'un registre pour les cancers notifiés au décès [Evaluation of the comprehensiveness of a cancer register from death certificates].

The comparison of cancer prevalence with cancer mortality can lead under some hypotheses to an estimate of registration rate. A method is proposed, where the cases with cancer as a cause of death are divided into 3 categories: (1) cases already known by the registry (2) unknown cases having occured before the registry creation date (3) unknown cases occuring during the registry operates. The estimate is then the number of cases in the first category divided by the total of those in categories 1 and 3 (these only are to be registered). An application is performed on the data of the Canton de Vaud. Survival rates of the Norvegian Cancer Registry are used for computing the number of unknown cases to be included in second and third category, respectively. The discussion focusses on the possible determinants of the obtained comprehensiveness rates for various cancer sites.