Impact of Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry on the Clinical Management of Patients With Gram-negative Bacteremia: A Prospective Observational Study.

Background. Early identification of pathogens from blood cultures using matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry may optimize the choice of empirical antibiotic therapy in the setting of bloodstream infections. We aimed to assess the impact of this new technology on the use of antibiotic treatment in patients with gram-negative bacteremia. Methods. We conducted a prospective observational study from January to December 2010 to evaluate the sequential and separate impacts of Gram stain reporting and MALDI-TOF bacterial identification performed on blood culture pellets in patients with gram-negative bacteremia. The primary outcome was the impact of MALDI-TOF on empirical antibiotic choice. Results. Among 202 episodes of gram-negative bacteremia, Gram stain reporting had an impact in 42 cases (20.8%). MALDI-TOF identification led to a modification of empirical therapy in 71 of all 202 cases (35.1%), and in 16 of 27 cases (59.3%) of monomicrobial bacteremia caused by AmpC-producing Enterobacteriaceae. The most frequently observed impact was an early appropriate broadening of the antibiotic spectrum in 31 of 71 cases (43.7%). In total, 143 of 165 episodes (86.7%) of monomicrobial bacteremia were correctly identified at genus level by MALDI-TOF. Conclusions. In a low prevalence area for extended spectrum betalactamases (ESBL) and multiresistant gram-negative bacteria, MALDI-TOF performed on blood culture pellets had an impact on the clinical management of 35.1% of all gram-negative bacteremia cases, demonstrating a greater impact than Gram stain reporting. Thus, MALDI-TOF could become a vital second step beside Gram stain in guiding the empirical treatment of patients with bloodstream infection.

A filtering method to correct time-lapse 3D ERT data and improve imaging of natural aquifer dynamics

We have developed a processing methodology that allows crosshole ERT (electrical resistivity tomography) monitoring data to be used to derive temporal fluctuations of groundwater electrical resistivity and thereby characterize the dynamics of groundwater in a gravel aquifer as it is infiltrated by river water. Temporal variations of the raw ERT apparent-resistivity data were mainly sensitive to the resistivity (salinity), temperature and height of the groundwater, with the relative contributions of these effects depending on the time and the electrode configuration. To resolve the changes in groundwater resistivity, we first expressed fluctuations of temperature-detrended apparent-resistivity data as linear superpositions of (i) time series of riverwater-resistivity variations convolved with suitable filter functions and (ii) linear and quadratic representations of river-water-height variations multiplied by appropriate sensitivity factors; river-water height was determined to be a reliable proxy for groundwater height. Individual filter functions and sensitivity factors were obtained for each electrode configuration via deconvolution using a one month calibration period and then the predicted contributions related to changes in water height were removed prior to inversion of the temperature-detrended apparent-resistivity data. Applications of the filter functions and sensitivity factors accurately predicted the apparent-resistivity variations (the correlation coefficient was 0.98). Furthermore, the filtered ERT monitoring data and resultant time-lapse resistivity models correlated closely with independently measured groundwater electrical resistivity monitoring data and only weakly with the groundwater-height fluctuations. The inversion results based on the filtered ERT data also showed significantly less inversion artefacts than the raw data inversions. We observed resistivity increases of up to 10% and the arrival time peaks in the time-lapse resistivity models matched those in the groundwater resistivity monitoring data.

Time-lapse and probabilistic inversion strategies for plane-wave electromagnetic data.

L'utilisation efficace des systèmes géothermaux, la séquestration du CO2 pour limiter le changement climatique et la prévention de l'intrusion d'eau salée dans les aquifères costaux ne sont que quelques exemples qui démontrent notre besoin en technologies nouvelles pour suivre l'évolution des processus souterrains à partir de la surface. Un défi majeur est d'assurer la caractérisation et l'optimisation des performances de ces technologies à différentes échelles spatiales et temporelles. Les méthodes électromagnétiques (EM) d'ondes planes sont sensibles à la conductivité électrique du sous-sol et, par conséquent, à la conductivité électrique des fluides saturant la roche, à la présence de fractures connectées, à la température et aux matériaux géologiques. Ces méthodes sont régies par des équations valides sur de larges gammes de fréquences, permettant détudier de manières analogues des processus allant de quelques mètres sous la surface jusqu'à plusieurs kilomètres de profondeur. Néanmoins, ces méthodes sont soumises à une perte de résolution avec la profondeur à cause des propriétés diffusives du champ électromagnétique. Pour cette raison, l'estimation des modèles du sous-sol par ces méthodes doit prendre en compte des informations a priori afin de contraindre les modèles autant que possible et de permettre la quantification des incertitudes de ces modèles de façon appropriée. Dans la présente thèse, je développe des approches permettant la caractérisation statique et dynamique du sous-sol à l'aide d'ondes EM planes. Dans une première partie, je présente une approche déterministe permettant de réaliser des inversions répétées dans le temps (time-lapse) de données d'ondes EM planes en deux dimensions. Cette stratégie est basée sur l'incorporation dans l'algorithme d'informations a priori en fonction des changements du modèle de conductivité électrique attendus. Ceci est réalisé en intégrant une régularisation stochastique et des contraintes flexibles par rapport à la gamme des changements attendus en utilisant les multiplicateurs de Lagrange. J'utilise des normes différentes de la norme l2 pour contraindre la structure du modèle et obtenir des transitions abruptes entre les régions du model qui subissent des changements dans le temps et celles qui n'en subissent pas. Aussi, j'incorpore une stratégie afin d'éliminer les erreurs systématiques de données time-lapse. Ce travail a mis en évidence l'amélioration de la caractérisation des changements temporels par rapport aux approches classiques qui réalisent des inversions indépendantes à chaque pas de temps et comparent les modèles. Dans la seconde partie de cette thèse, j'adopte un formalisme bayésien et je teste la possibilité de quantifier les incertitudes sur les paramètres du modèle dans l'inversion d'ondes EM planes. Pour ce faire, je présente une stratégie d'inversion probabiliste basée sur des pixels à deux dimensions pour des inversions de données d'ondes EM planes et de tomographies de résistivité électrique (ERT) séparées et jointes. Je compare les incertitudes des paramètres du modèle en considérant différents types d'information a priori sur la structure du modèle et différentes fonctions de vraisemblance pour décrire les erreurs sur les données. Les résultats indiquent que la régularisation du modèle est nécessaire lorsqu'on a à faire à un large nombre de paramètres car cela permet d'accélérer la convergence des chaînes et d'obtenir des modèles plus réalistes. Cependent, ces contraintes mènent à des incertitudes d'estimations plus faibles, ce qui implique des distributions a posteriori qui ne contiennent pas le vrai modèledans les régions ou` la méthode présente une sensibilité limitée. Cette situation peut être améliorée en combinant des méthodes d'ondes EM planes avec d'autres méthodes complémentaires telles que l'ERT. De plus, je montre que le poids de régularisation des paramètres et l'écart-type des erreurs sur les données peuvent être retrouvés par une inversion probabiliste. Finalement, j'évalue la possibilité de caractériser une distribution tridimensionnelle d'un panache de traceur salin injecté dans le sous-sol en réalisant une inversion probabiliste time-lapse tridimensionnelle d'ondes EM planes. Etant donné que les inversions probabilistes sont très coûteuses en temps de calcul lorsque l'espace des paramètres présente une grande dimension, je propose une stratégie de réduction du modèle ou` les coefficients de décomposition des moments de Legendre du panache de traceur injecté ainsi que sa position sont estimés. Pour ce faire, un modèle de résistivité de base est nécessaire. Il peut être obtenu avant l'expérience time-lapse. Un test synthétique montre que la méthodologie marche bien quand le modèle de résistivité de base est caractérisé correctement. Cette méthodologie est aussi appliquée à un test de trac¸age par injection d'une solution saline et d'acides réalisé dans un système géothermal en Australie, puis comparée à une inversion time-lapse tridimensionnelle réalisée selon une approche déterministe. L'inversion probabiliste permet de mieux contraindre le panache du traceur salin gr^ace à la grande quantité d'informations a priori incluse dans l'algorithme. Néanmoins, les changements de conductivités nécessaires pour expliquer les changements observés dans les données sont plus grands que ce qu'expliquent notre connaissance actuelle des phénomenès physiques. Ce problème peut être lié à la qualité limitée du modèle de résistivité de base utilisé, indiquant ainsi que des efforts plus grands devront être fournis dans le futur pour obtenir des modèles de base de bonne qualité avant de réaliser des expériences dynamiques. Les études décrites dans cette thèse montrent que les méthodes d'ondes EM planes sont très utiles pour caractériser et suivre les variations temporelles du sous-sol sur de larges échelles. Les présentes approches améliorent l'évaluation des modèles obtenus, autant en termes d'incorporation d'informations a priori, qu'en termes de quantification d'incertitudes a posteriori. De plus, les stratégies développées peuvent être appliquées à d'autres méthodes géophysiques, et offrent une grande flexibilité pour l'incorporation d'informations additionnelles lorsqu'elles sont disponibles. -- The efficient use of geothermal systems, the sequestration of CO2 to mitigate climate change, and the prevention of seawater intrusion in coastal aquifers are only some examples that demonstrate the need for novel technologies to monitor subsurface processes from the surface. A main challenge is to assure optimal performance of such technologies at different temporal and spatial scales. Plane-wave electromagnetic (EM) methods are sensitive to subsurface electrical conductivity and consequently to fluid conductivity, fracture connectivity, temperature, and rock mineralogy. These methods have governing equations that are the same over a large range of frequencies, thus allowing to study in an analogous manner processes on scales ranging from few meters close to the surface down to several hundreds of kilometers depth. Unfortunately, they suffer from a significant resolution loss with depth due to the diffusive nature of the electromagnetic fields. Therefore, estimations of subsurface models that use these methods should incorporate a priori information to better constrain the models, and provide appropriate measures of model uncertainty. During my thesis, I have developed approaches to improve the static and dynamic characterization of the subsurface with plane-wave EM methods. In the first part of this thesis, I present a two-dimensional deterministic approach to perform time-lapse inversion of plane-wave EM data. The strategy is based on the incorporation of prior information into the inversion algorithm regarding the expected temporal changes in electrical conductivity. This is done by incorporating a flexible stochastic regularization and constraints regarding the expected ranges of the changes by using Lagrange multipliers. I use non-l2 norms to penalize the model update in order to obtain sharp transitions between regions that experience temporal changes and regions that do not. I also incorporate a time-lapse differencing strategy to remove systematic errors in the time-lapse inversion. This work presents improvements in the characterization of temporal changes with respect to the classical approach of performing separate inversions and computing differences between the models. In the second part of this thesis, I adopt a Bayesian framework and use Markov chain Monte Carlo (MCMC) simulations to quantify model parameter uncertainty in plane-wave EM inversion. For this purpose, I present a two-dimensional pixel-based probabilistic inversion strategy for separate and joint inversions of plane-wave EM and electrical resistivity tomography (ERT) data. I compare the uncertainties of the model parameters when considering different types of prior information on the model structure and different likelihood functions to describe the data errors. The results indicate that model regularization is necessary when dealing with a large number of model parameters because it helps to accelerate the convergence of the chains and leads to more realistic models. These constraints also lead to smaller uncertainty estimates, which imply posterior distributions that do not include the true underlying model in regions where the method has limited sensitivity. This situation can be improved by combining planewave EM methods with complimentary geophysical methods such as ERT. In addition, I show that an appropriate regularization weight and the standard deviation of the data errors can be retrieved by the MCMC inversion. Finally, I evaluate the possibility of characterizing the three-dimensional distribution of an injected water plume by performing three-dimensional time-lapse MCMC inversion of planewave EM data. Since MCMC inversion involves a significant computational burden in high parameter dimensions, I propose a model reduction strategy where the coefficients of a Legendre moment decomposition of the injected water plume and its location are estimated. For this purpose, a base resistivity model is needed which is obtained prior to the time-lapse experiment. A synthetic test shows that the methodology works well when the base resistivity model is correctly characterized. The methodology is also applied to an injection experiment performed in a geothermal system in Australia, and compared to a three-dimensional time-lapse inversion performed within a deterministic framework. The MCMC inversion better constrains the water plumes due to the larger amount of prior information that is included in the algorithm. The conductivity changes needed to explain the time-lapse data are much larger than what is physically possible based on present day understandings. This issue may be related to the base resistivity model used, therefore indicating that more efforts should be given to obtain high-quality base models prior to dynamic experiments. The studies described herein give clear evidence that plane-wave EM methods are useful to characterize and monitor the subsurface at a wide range of scales. The presented approaches contribute to an improved appraisal of the obtained models, both in terms of the incorporation of prior information in the algorithms and the posterior uncertainty quantification. In addition, the developed strategies can be applied to other geophysical methods, and offer great flexibility to incorporate additional information when available.

Leisure, work and gender: a sociological study of women's time in France

In this article, I address the question of the relationship between women's labour market position and their `objective' and `subjective' experience of leisure. With reference to a small-scale empirical study of the social time use of mothers in France, I argue that it is misleading to consider women's leisure experience as being determined by their labour market position. I attempt to show that it could prove more fruitful to examine the complex relationship between women's class and gender identities and their simultaneous experience of work, family and leisure.

Mass conservative three-dimensional water tracer distribution from Markov chain Monte Carlo inversion of time-lapse ground-penetrating radar data

Time-lapse geophysical measurements are widely used to monitor the movement of water and solutes through the subsurface. Yet commonly used deterministic least squares inversions typically suffer from relatively poor mass recovery, spread overestimation, and limited ability to appropriately estimate nonlinear model uncertainty. We describe herein a novel inversion methodology designed to reconstruct the three-dimensional distribution of a tracer anomaly from geophysical data and provide consistent uncertainty estimates using Markov chain Monte Carlo simulation. Posterior sampling is made tractable by using a lower-dimensional model space related both to the Legendre moments of the plume and to predefined morphological constraints. Benchmark results using cross-hole ground-penetrating radar travel times measurements during two synthetic water tracer application experiments involving increasingly complex plume geometries show that the proposed method not only conserves mass but also provides better estimates of plume morphology and posterior model uncertainty than deterministic inversion results.

Changes in leisure time and occupational physical activity over 8 years: The Cornellà health Interview Survey Follow-Up Study

Aim: To describe changes in leisure time and occupational physical activity status in an urban Mediterranean population-based cohort, and to evaluate sociodemographic, health-related and lifestyle correlates of such changes. Methods: Data for this study come from the Cornellè Health Interview Survey Follow-Up Study, a prospective cohort study of a representative sample (n¿=¿2500) of the population. Participants in the analysis reported here include 1246 subjects (567 men and 679 women) who had complete data on physical activity at the 1994 baseline survey and at the 2002 follow-up. We fitted Breslow-Cox regression models to assess the association between correlates of interest and changes in physical activity. Results: Regarding leisure time physical activity, 61.6% of cohort members with ¿sedentary¿ habits in 1994 changed their status to ¿light/moderate¿ physical activity in 2002, and 70% who had ¿light/moderate¿ habits in 1994 did not change their activity level. Regarding occupational physical activity, 74.4% of cohort members who were ¿active¿ did not change their level of activity, and 64.3% of participants with ¿sedentary¿ habits in 1994 changed to ¿active¿ occupational physical activity. No clear correlates of change in physical activity were identified in multivariate analyses. Conclusion: While changes in physical activity are evident in this population-based cohort, no clear determinants of such changes were recognised. Further longitudinal studies including other potential individual and contextual determinants are needed to better understand determinants of changes in physical activity at the population level.

Time-scale and other invariants of integrative mechanical behavior in living cells.

In dealing with systems as complex as the cytoskeleton, we need organizing principles or, short of that, an empirical framework into which these systems fit. We report here unexpected invariants of cytoskeletal behavior that comprise such an empirical framework. We measured elastic and frictional moduli of a variety of cell types over a wide range of time scales and using a variety of biological interventions. In all instances elastic stresses dominated at frequencies below 300 Hz, increased only weakly with frequency, and followed a power law; no characteristic time scale was evident. Frictional stresses paralleled the elastic behavior at frequencies below 10 Hz but approached a Newtonian viscous behavior at higher frequencies. Surprisingly, all data could be collapsed onto master curves, the existence of which implies that elastic and frictional stresses share a common underlying mechanism. Taken together, these findings define an unanticipated integrative framework for studying protein interactions within the complex microenvironment of the cell body, and appear to set limits on what can be predicted about integrated mechanical behavior of the matrix based solely on cytoskeletal constituents considered in isolation. Moreover, these observations are consistent with the hypothesis that the cytoskeleton of the living cell behaves as a soft glassy material, wherein cytoskeletal proteins modulate cell mechanical properties mainly by changing an effective temperature of the cytoskeletal matrix. If so, then the effective temperature becomes an easily quantified determinant of the ability of the cytoskeleton to deform, flow, and reorganize.

Analog circuit for real-time computation of respiratory mechanical impedance in sleep studies

The aim of this work was to develop a low-cost circuit for real-time analog computation of the respiratory mechanical impedance in sleep studies. The practical performance of the circuit was tested in six patients with obstructive sleep apnea. The impedance signal provided by the analog circuit was compared with the impedance calculated simultaneously with a conventional computerized system. We concluded that the low-cost analog circuit developed could be a useful tool for facilitating the real-time assessment of airway obstruction in routine sleep studies.

Analysis of TNF-antagonist switch over time and associated risk factors in the Swiss Inflammatory Bowel Disease Cohort

Abstract Background and aims. Limited data from large cohorts are available on tumor necrosis factor (TNF) antagonists (infliximab, adalimumab, certolizumab pegol) switch over time. We aimed to evaluate the prevalence of switching from one TNF antagonist to another and to identify associated risk factors. Methods. Data from the Swiss Inflammatory Bowel Diseases Cohort Study (SIBDCS) were analyzed. Results. Of 1731 patients included into the SIBDCS (956 with Crohn's disease [CD] and 775 with ulcerative colitis [UC]), 347 CD patients (36.3%) and 129 UC patients (16.6%) were treated with at least one TNF antagonist. A total of 53/347 (15.3%) CD patients (median disease duration 9 years) and 20/129 (15.5%) of UC patients (median disease duration 7 years) needed to switch to a second and/or a third TNF antagonist, respectively. Median treatment duration was longest for the first TNF antagonist used (CD 25 months; UC 14 months), followed by the second (CD 13 months; UC 4 months) and third TNF antagonist (CD 11 months; UC 15 months). Primary nonresponse, loss of response and side effects were the major reasons to stop and/or switch TNF antagonist therapy. A low body mass index, a short diagnostic delay and extraintestinal manifestations at inclusion were identified as risk factors for a switch of the first used TNF antagonist within 24 months of its use in CD patients. Conclusion. Switching of the TNF antagonist over time is a common issue. The median treatment duration with a specific TNF antagonist is diminishing with an increasing number of TNF antagonists being used.

Changes over time in risk factors for cardiovascular disease and use of lipid-lowering drugs in HIV-infected individuals and impact on myocardial infarction.

BACKGROUND: Because of the known relationship between exposure to combination antiretroviral therapy and cardiovascular disease (CVD), it has become increasingly important to intervene against risk of CVD in human immunodeficiency virus (HIV)-infected patients. We evaluated changes in risk factors for CVD and the use of lipid-lowering therapy in HIV-infected individuals and assessed the impact of any changes on the incidence of myocardial infarction. METHODS: The Data Collection on Adverse Events of Anti-HIV Drugs Study is a collaboration of 11 cohorts of HIV-infected patients that included follow-up for 33,389 HIV-infected patients from December 1999 through February 2006. RESULTS: The proportion of patients at high risk of CVD increased from 35.3% during 1999-2000 to 41.3% during 2005-2006. Of 28,985 patients, 2801 (9.7%) initiated lipid-lowering therapy; initiation of lipid-lowering therapy was more common for those with abnormal lipid values and those with traditional risk factors for CVD (male sex, older age, higher body mass index [calculated as the weight in kilograms divided by the square of the height in meters], family and personal history of CVD, and diabetes mellitus). After controlling for these, use of lipid-lowering drugs became relatively less common over time. The incidence of myocardial infarction (0.32 cases per 100 person-years [PY]; 95% confidence interval [CI], 0.29-0.35 cases per 100 PY) appeared to remain stable. However, after controlling for changes in risk factors for CVD, the rate decreased over time (relative rate in 2003 [compared with 1999-2000], 0.73 cases per 100 PY [95% CI, 0.50-1.05 cases per 100 PY]; in 2004, 0.64 cases per 100 PY [95% CI, 0.44-0.94 cases per 100 PY]; in 2005-2006, 0.36 cases per 100 PY [95% CI, 0.24-0.56 cases per 100 PY]). Further adjustment for lipid levels attenuated the relative rates towards unity (relative rate in 2003 [compared with 1999-2000], 1.06 cases per 100 PY [95% CI, 0.63-1.77 cases per 100 PY]; in 2004, 1.02 cases per 100 PY [95% CI, 0.61-1.71 cases per 100 PY]; in 2005-2006, 0.63 cases per 100 PY [95% CI, 0.36-1.09 cases per 100 PY]). CONCLUSIONS: Although the CVD risk profile among patients in the Data Collection on Adverse Events of Anti-HIV Drugs Study has decreased since 1999, rates have remained relatively stable, possibly as a result of a more aggressive approach towards managing the risk of CVD.

Suboptimal filtering and nonlinear time scale transformation for the analysis of multiexponential decays

Multiexponential decays may contain time-constants differing in several orders of magnitudes. In such cases, uniform sampling results in very long records featuring a high degree of oversampling at the final part of the transient. Here, we analyze a nonlinear time scale transformation to reduce the total number of samples with minimum signal distortion, achieving an important reduction of the computational cost of subsequent analyses. We propose a time-varying filter whose length is optimized for minimum mean square error

Effect of soil-spraying time on root-colonization ability of antagonistic Streptomyces griseoviridis

Selostus: Kasvualustan käsittelyajan vaikutus Streptomyces griseoviridis -antagonistin juurten asutuskykyyn