Performance of matrix-assisted laser desorption ionization-time of flight mass spectrometry for identification of bacterial strains routinely isolated in a clinical microbiology laboratory.

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has recently been introduced in diagnostic microbiology laboratories for the identification of bacterial and yeast strains isolated from clinical samples. In the present study, we prospectively compared MALDI-TOF MS to the conventional phenotypic method for the identification of routine isolates. Colonies were analyzed by MALDI-TOF MS either by direct deposition on the target plate or after a formic acid-acetonitrile extraction step if no valid result was initially obtained. Among 1,371 isolates identified by conventional methods, 1,278 (93.2%) were putatively identified to the species level by MALDI-TOF MS and 73 (5.3%) were identified to the genus level, but no reliable identification was obtained for 20 (1.5%). Among the 1,278 isolates identified to the species level by MALDI-TOF MS, 63 (4.9%) discordant results were initially identified. Most discordant results (42/63) were due to systematic database-related taxonomical differences, 14 were explained by poor discrimination of the MALDI-TOF MS spectra obtained, and 7 were due to errors in the initial conventional identification. An extraction step was required to obtain a valid MALDI-TOF MS identification for 25.6% of the 1,278 valid isolates. In conclusion, our results show that MALDI-TOF MS is a fast and reliable technique which has the potential to replace conventional phenotypic identification for most bacterial strains routinely isolated in clinical microbiology laboratories.

Extracellular matrix components in peripheral nerve repair: how to affect neural cellular response and nerve regeneration?

Peripheral nerve injury is a serious problem affecting significantly patients' life. Autografts are the "gold standard" used to repair the injury gap, however, only 50% of patients fully recover from the trauma. Artificial conduits are a valid alternative to repairing peripheral nerve. They aim at confining the nerve environment throughout the regeneration process, and providing guidance to axon outgrowth. Biocompatible materials have been carefully designed to reduce inflammation and scar tissue formation, but modifications of the inner lumen are still required in order to optimise the scaffolds. Biomicking the native neural tissue with extracellular matrix fillers or coatings showed great promises in repairing longer gaps and extending cell survival. In addition, extracellular matrix molecules provide a platform to further bind growth factors that can be released in the system over time. Alternatively, conduit fillers can be used for cell transplantation at the injury site, reducing the lag time required for endogenous Schwann cells to proliferate and take part in the regeneration process. This review provides an overview on the importance of extracellular matrix molecules in peripheral nerve repair.

Absorbance enhancement in microplate wells for improved-sensitivity biosensors

A generic optical biosensing strategy was developed that relies on the absorbance enhancement phenomenon occurring in a multiple scattering matrix. Experimentally, inserts made of glass fiber membrane were placed into microplate wells in order to significantly lengthen the trajectory of the incident light through the sample and therefore increase the corresponding absorbance. Enhancement factor was calculated by comparing the absorbance values measured for a given amount of dye with and without the absorbance-enhancing inserts in the wells. Moreover, the dilution of dye in solutions with different refractive indices (RI) clearly revealed that the enhancement factor increased with the ΔRI between the membrane and the surrounding medium, reaching a maximum value (EF>25) when the membranes were dried. On this basis, two H2O2-biosensing systems were developed based on the biofunctionalization of the glass fiber inserts either with cytochrome c or horseradish peroxidase (HRP) and the analytical performances were systematically compared with the corresponding bioassay in solution. The efficiency of the absorbance-enhancement approach was particularly clear in the case of the cytochrome c-based biosensor with a sensitivity gain of 40 folds and wider dynamic range. Therefore, the developed strategy represents a promising way to convert standard colorimetric bioassays into optical biosensors with improved sensitivity.

Qualités psychométriques de la version française de la TAS-20 et prévalence de l'alexithymie chez 264 adolescents tout-venant [The 20-item Toronto alexithymia scale: structural validity, internal consistency and prevalence of alexithymia in a Swiss adolescent sample]

L'objectif de cette étude est d'examiner la structure factorielle et la consistance interne de la TAS-20 sur un échantillon d'adolescents (n = 264), ainsi que de décrire la distribution des caractéristiques alexithymiques dans cet échantillon. La structure à trois facteurs de la TAS-20 a été confirmée par notre analyse factorielle confirmatoire. La consistance interne, mesurée à l'aide d'alpha de Cronbach, est acceptable pour le premier facteur (difficulté à identifier les sentiments (DIF)), bonne pour le second (difficulté à verbaliser les sentiments (DDF)), mais en revanche, faible pour le troisième facteur (pensées orientées vers l'extérieur (EOT)). Les résultats d'une Anova mettent en évidence une tendance linéaire indiquant que plus l'âge augmente plus le niveau d'alexithymie (score total TAS-20), la difficulté à identifier les sentiments et les pensées orientées vers l'extérieur diminuent. En ce qui concerne la prévalence de l'alexithymie, on remarque en effet que 38,5 % des adolescents de moins de 16 ans sont considérés comme alexithymiques, contre 30,1 % des 16-17 ans et 22 % des plus de 17 ans. Notre étude indique donc que la TAS-20 est un instrument adéquat pour évaluer l'alexithymie à l'adolescence, tout en suggérant quelques précautions étant donné l'aspect développemental de cette période.

Associations between alcohol consumption and selected cytokines in a Swiss population-based sample (CoLaus study).

To assess the associations between alcohol consumption and cytokine levels (interleukin-1beta - IL-1β; interleukin-6 - IL-6 and tumor necrosis factor-α - TNF-α) in a Caucasian population. Population sample of 2884 men and 3201 women aged 35-75. Alcohol consumption was categorized as nondrinkers, low (1-6 drinks/week), moderate (7-13/week) and high (14+/week). No difference in IL-1β levels was found between alcohol consumption categories. Low and moderate alcohol consumption led to lower IL-6 levels: median (interquartile range) 1.47 (0.70-3.51), 1.41 (0.70-3.32), 1.42 (0.66-3.19) and 1.70 (0.83-4.39) pg/ml for nondrinkers, low, moderate and high drinkers, respectively, p<0.01, but this association was no longer significant after multivariate adjustment. Compared to nondrinkers, moderate drinkers had the lowest odds (Odds ratio=0.86 (0.71-1.03)) of being in the highest quartile of IL-6, with a significant (p<0.05) quadratic trend. Low and moderate alcohol consumption led to lower TNF-α levels: 2.92 (1.79-4.63), 2.83 (1.84-4.48), 2.82 (1.76-4.34) and 3.15 (1.91-4.73) pg/ml for nondrinkers, low, moderate and high drinkers, respectively, p<0.02, and this difference remained borderline significant (p=0.06) after multivariate adjustment. Moderate drinkers had a lower odds (0.81 [0.68-0.98]) of being in the highest quartile of TNF-α. No specific alcoholic beverage (wine, beer or spirits) effect was found. Moderate alcohol consumption is associated with lower levels of IL-6 and (to a lesser degree) of TNF-α, irrespective of the type of alcohol consumed. No association was found between IL-1β levels and alcohol consumption.

Evaluation of cumulative PCB exposure estimated by a job exposure matrix versus PCB serum concentrations.

Although polychlorinated biphenyls (PCBs) have been banned in many countries for more than three decades, exposures to PCBs continue to be of concern due to their long half-lives and carcinogenic effects. In National Institute for Occupational Safety and Health studies, we are using semiquantitative plant-specific job exposure matrices (JEMs) to estimate historical PCB exposures for workers (n = 24,865) exposed to PCBs from 1938 to 1978 at three capacitor manufacturing plants. A subcohort of these workers (n = 410) employed in two of these plants had serum PCB concentrations measured at up to four times between 1976 and 1989. Our objectives were to evaluate the strength of association between an individual worker's measured serum PCB levels and the same worker's cumulative exposure estimated through 1977 with the (1) JEM and (2) duration of employment, and to calculate the explained variance the JEM provides for serum PCB levels using (3) simple linear regression. Consistent strong and statistically significant associations were observed between the cumulative exposures estimated with the JEM and serum PCB concentrations for all years. The strength of association between duration of employment and serum PCBs was good for highly chlorinated (Aroclor 1254/HPCB) but not less chlorinated (Aroclor 1242/LPCB) PCBs. In the simple regression models, cumulative occupational exposure estimated using the JEMs explained 14-24% of the variance of the Aroclor 1242/LPCB and 22-39% for Aroclor 1254/HPCB serum concentrations. We regard the cumulative exposure estimated with the JEM as a better estimate of PCB body burdens than serum concentrations quantified as Aroclor 1242/LPCB and Aroclor 1254/HPCB.

The Importance of Revenue Sharing for the Local Economic Impacts of a Renewable Energy Project: A Social Accounting Matrix Approach

As demand for electricity from renewable energy sources grows, there is increasing interest, and public and financial support, for local communities to become involved in the development of renewable energy projects. In the UK, “Community Benefit” payments are the most common financial link between renewable energy projects and local communities. These are “goodwill” payments from the project developer for the community to spend as it wishes. However, if an ownership stake in the renewable energy project were possible, receipts to the local community would potentially be considerably higher. The local economic impacts of these receipts are difficult to quantify using traditional Input-Output techniques, but can be more appropriately handled within a Social Accounting Matrix (SAM) framework where income flows between agents can be traced in detail. We use a SAM for the Shetland Islands to evaluate the potential local economic and employment impact of a large onshore wind energy project proposed for the Islands. Sensitivity analysis is used to show how the local impact varies with: the level of Community Benefit payments; the portion of intermediate inputs being sourced from within the local economy; and the level of any local community ownership of the project. By a substantial margin, local ownership confers the greatest economic impacts for the local community.

Constructing a Social Accounting Matrix for Libya

In this paper a Social Accounting Matrix is constructed for Libya for the year 2000. The procedure was divided into three steps. First, a macro SAM was constructed to consistently capture and represent the macroeconomic framework of the Libyan economy in 2000. Second, that macro SAM was disaggregated into a micro SAM incorporating the accounts for individual activities, primary factors and the main economic institutions. But the SAM obtained in this way was not balanced. So in thE final step we balanced the SAM using a cross-entropy procedure in General Algebraic Modelling System (GAMS). This SAM integrates national income, inputoutput, flow-of-funds, and foreign trade statistics into a comprehensive and consistent dataset. The lack of coherent time series data for Libya is a serious obstacle for applied research that uses econometric analysis. Our main intension in constructing this SAM has been one of providing benchmark data for economy-wide analysis using CGE modelling for Libya.

Disaggregating the Household Sector in a 2004 UK Input Output Table and Social Accounting Matrix by Income Quintiles

This paper disaggregates a UK Input-Output (IO) table for 2004 based on household income quintiles from published survey data. In addition to the Input-Output disaggregation, the household components of a UK Income Expenditure (I-E) account used to inform a Social Accounting Matrix (SAM),have also been disaggregated by household income quintile. The focus of this paper is on household expenditure on the UK energy sector.

Analytic approximation of matrix functions in Lp

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

Estimation of the Spatial Weights Matrix under Structural Constraints

While estimates of models with spatial interaction are very sensitive to the choice of spatial weights, considerable uncertainty surrounds de nition of spatial weights in most studies with cross-section dependence. We show that, in the spatial error model the spatial weights matrix is only partially identi ed, and is fully identifi ed under the structural constraint of symmetry. For the spatial error model, we propose a new methodology for estimation of spatial weights under the assumption of symmetric spatial weights, with extensions to other important spatial models. The methodology is applied to regional housing markets in the UK, providing an estimated spatial weights matrix that generates several new hypotheses about the economic and socio-cultural drivers of spatial di¤usion in housing demand.

Matrix-assisted laser desorption ionization-time of flight mass spectrometry for direct bacterial identification from positive blood culture pellets.

An ammonium chloride erythrocyte-lysing procedure was used to prepare a bacterial pellet from positive blood cultures for direct matrix-assisted laser desorption-ionization time of flight (MALDI-TOF) mass spectrometry analysis. Identification was obtained for 78.7% of the pellets tested. Moreover, 99% of the MALDI-TOF identifications were congruent at the species level when considering valid scores. This fast and accurate method is promising.

The role of career adaptability and work conditions on general and professional well-being.

This study, conducted with a representative sample of employed and unemployed adults living in Switzerland (N = 2002), focuses on work conditions (in terms of professional insecurity and job demands), career adaptability, and professional and general well-being. Analyses of covariance highlighted that both unemployed and employed participants with low job insecurity reported higher scores on career adaptability and several dimensions (notably on control) than employed participants with high job insecurity. Moreover, structural equation modeling for employed participants showed that, independent of work conditions, adaptability resources were positively associated both with general and professional well-being. As expected professional outcomes were strongly related to job strain and professional insecurity, emphasizing the central role of the work environment. Finally, career adaptability partially mediated the relationship between job strain and professional insecurity, and the outcome well-being.

Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.

Introduction: As part of the MicroArray Quality Control (MAQC)-II project, this analysis examines how the choice of univariate feature-selection methods and classification algorithms may influence the performance of genomic predictors under varying degrees of prediction difficulty represented by three clinically relevant endpoints. Methods: We used gene-expression data from 230 breast cancers (grouped into training and independent validation sets), and we examined 40 predictors (five univariate feature-selection methods combined with eight different classifiers) for each of the three endpoints. Their classification performance was estimated on the training set by using two different resampling methods and compared with the accuracy observed in the independent validation set. Results: A ranking of the three classification problems was obtained, and the performance of 120 models was estimated and assessed on an independent validation set. The bootstrapping estimates were closer to the validation performance than were the cross-validation estimates. The required sample size for each endpoint was estimated, and both gene-level and pathway-level analyses were performed on the obtained models. Conclusions: We showed that genomic predictor accuracy is determined largely by an interplay between sample size and classification difficulty. Variations on univariate feature-selection methods and choice of classification algorithm have only a modest impact on predictor performance, and several statistically equally good predictors can be developed for any given classification problem.

Comparing population distributions from bin-aggregated sample data: an application to historical height data from France

This paper develops a methodology to estimate the entire population distributions from bin-aggregated sample data. We do this through the estimation of the parameters of mixtures of distributions that allow for maximal parametric flexibility. The statistical approach we develop enables comparisons of the full distributions of height data from potential army conscripts across France's 88 departments for most of the nineteenth century. These comparisons are made by testing for differences-of-means stochastic dominance. Corrections for possible measurement errors are also devised by taking advantage of the richness of the data sets. Our methodology is of interest to researchers working on historical as well as contemporary bin-aggregated or histogram-type data, something that is still widely done since much of the information that is publicly available is in that form, often due to restrictions due to political sensitivity and/or confidentiality concerns.