Examining chemical compound biodegradation at low concentrations through bacterial cell proliferation.

We show proof of principle for assessing compound biodegradation at 1-2 mg C per L by measuring microbial community growth over time with direct cell counting by flow cytometry. The concept is based on the assumption that the microbial community will increase in cell number through incorporation of carbon from the added test compound into new cells in the absence of (as much as possible) other assimilable carbon. We show on pure cultures of the bacterium Pseudomonas azelaica that specific population growth can be measured with as low as 0.1 mg 2-hydroxybiphenyl per L, whereas in mixed community 1 mg 2-hydroxybiphenyl per L still supported growth. Growth was also detected with a set of fragrance compounds dosed at 1-2 mg C per L into diluted activated sludge and freshwater lake communities at starting densities of 10(4) cells per ml. Yield approximations from the observed community growth was to some extent in agreement with standard OECD biodegradation test results for all, except one of the examined compounds.

Biases of the ordinary least squares and instrumental variables estimators of the intergenerational earnings elasticity : revisited in the light of panel data

The OLS estimator of the intergenerational earnings correlation is biased towards zero, while the instrumental variables estimator is biased upwards. The first of these results arises because of measurement error, while the latter rests on the presumption that the education of the parent family is an invalid instrument. We propose a panel data framework for quantifying the asymptotic biases of these estimators, as well as a mis-specification test for the IV estimator. [Author]

Improving the prediction of plant species distribution and community composition by adding edaphic to topo-climatic variables

Questions Soil properties have been widely shown to influence plant growth and distribution. However, the degree to which edaphic variables can improve models based on topo-climatic variables is still unclear. In this study, we tested the roles of seven edaphic variables, namely (1) pH; (2) the content of nitrogen and of (3) phosphorus; (4) silt; (5) sand; (6) clay and (7) carbon-to-nitrogen ratio, as predictors of species distribution models in an edaphically heterogeneous landscape. We also tested how the respective influence of these variables in the models is linked to different ecological and functional species characteristics. Location The Western Alps, Switzerland. Methods With four different modelling techniques, we built models for 115 plant species using topo-climatic variables alone and then topo-climatic variables plus each of the seven edaphic variables, one at a time. We evaluated the contribution of each edaphic variable by assessing the change in predictive power of the model. In a second step, we evaluated the importance of the two edaphic variables that yielded the largest increase in predictive power in one final set of models for each species. Third, we explored the change in predictive power and the importance of variables across plant functional groups. Finally, we assessed the influence of the edaphic predictors on the prediction of community composition by stacking the models for all species and comparing the predicted communities with the observed community. Results Among the set of edaphic variables studied, pH and nitrogen content showed the highest contributions to improvement of the predictive power of the models, as well as the predictions of community composition. When considering all topo-climatic and edaphic variables together, pH was the second most important variable after degree-days. The changes in model results caused by edaphic predictors were dependent on species characteristics. The predictions for the species that have a low specific leaf area, and acidophilic preferences, tolerating low soil pH and high humus content, showed the largest improvement by the addition of pH and nitrogen in the model. Conclusions pH was an important predictor variable for explaining species distribution and community composition of the mountain plants considered in our study. pH allowed more precise predictions for acidophilic species. This variable should not be neglected in the construction of species distribution models in areas with contrasting edaphic conditions.

Using flow cytometry for in situ monitoring of antimicrobial compound production in the biocontrol bacterium Pseudomonas fluorescens CHA0

Pseudomonas fluorescens strain CHA0 is able to protect plants against a variety of pathogens, notably by producing the two antimicrobial compounds 2,4-diacetylphloroglucinol (DAPG) and pyoluteorin (PLT). The regulation of the expression of these compounds is affected by many biotic factors, such as fungal pathogens, rhizosphere bacteria as well as plant species. Therefore, the influence of some plant phenolic compounds on the expression of DAPG and PLT biosynthetic genes has been tested using GFP-based reporter, monitored by standard fluometry and flow cytometry. In situ experiments were also performed with cucumber plants. We found that several plant metabolites such as IAA and umbelliferone are able to modify significantly the expression of DAPG and PLT. The use of flow cytometry with autofluorescents proteins seems to be a promising method to study rhizobacteria-plant interactions.

Estimation of jump-diffusion processes via empirical characteristic functions

Preface The starting point for this work and eventually the subject of the whole thesis was the question: how to estimate parameters of the affine stochastic volatility jump-diffusion models. These models are very important for contingent claim pricing. Their major advantage, availability T of analytical solutions for characteristic functions, made them the models of choice for many theoretical constructions and practical applications. At the same time, estimation of parameters of stochastic volatility jump-diffusion models is not a straightforward task. The problem is coming from the variance process, which is non-observable. There are several estimation methodologies that deal with estimation problems of latent variables. One appeared to be particularly interesting. It proposes the estimator that in contrast to the other methods requires neither discretization nor simulation of the process: the Continuous Empirical Characteristic function estimator (EGF) based on the unconditional characteristic function. However, the procedure was derived only for the stochastic volatility models without jumps. Thus, it has become the subject of my research. This thesis consists of three parts. Each one is written as independent and self contained article. At the same time, questions that are answered by the second and third parts of this Work arise naturally from the issues investigated and results obtained in the first one. The first chapter is the theoretical foundation of the thesis. It proposes an estimation procedure for the stochastic volatility models with jumps both in the asset price and variance processes. The estimation procedure is based on the joint unconditional characteristic function for the stochastic process. The major analytical result of this part as well as of the whole thesis is the closed form expression for the joint unconditional characteristic function for the stochastic volatility jump-diffusion models. The empirical part of the chapter suggests that besides a stochastic volatility, jumps both in the mean and the volatility equation are relevant for modelling returns of the S&P500 index, which has been chosen as a general representative of the stock asset class. Hence, the next question is: what jump process to use to model returns of the S&P500. The decision about the jump process in the framework of the affine jump- diffusion models boils down to defining the intensity of the compound Poisson process, a constant or some function of state variables, and to choosing the distribution of the jump size. While the jump in the variance process is usually assumed to be exponential, there are at least three distributions of the jump size which are currently used for the asset log-prices: normal, exponential and double exponential. The second part of this thesis shows that normal jumps in the asset log-returns should be used if we are to model S&P500 index by a stochastic volatility jump-diffusion model. This is a surprising result. Exponential distribution has fatter tails and for this reason either exponential or double exponential jump size was expected to provide the best it of the stochastic volatility jump-diffusion models to the data. The idea of testing the efficiency of the Continuous ECF estimator on the simulated data has already appeared when the first estimation results of the first chapter were obtained. In the absence of a benchmark or any ground for comparison it is unreasonable to be sure that our parameter estimates and the true parameters of the models coincide. The conclusion of the second chapter provides one more reason to do that kind of test. Thus, the third part of this thesis concentrates on the estimation of parameters of stochastic volatility jump- diffusion models on the basis of the asset price time-series simulated from various "true" parameter sets. The goal is to show that the Continuous ECF estimator based on the joint unconditional characteristic function is capable of finding the true parameters. And, the third chapter proves that our estimator indeed has the ability to do so. Once it is clear that the Continuous ECF estimator based on the unconditional characteristic function is working, the next question does not wait to appear. The question is whether the computation effort can be reduced without affecting the efficiency of the estimator, or whether the efficiency of the estimator can be improved without dramatically increasing the computational burden. The efficiency of the Continuous ECF estimator depends on the number of dimensions of the joint unconditional characteristic function which is used for its construction. Theoretically, the more dimensions there are, the more efficient is the estimation procedure. In practice, however, this relationship is not so straightforward due to the increasing computational difficulties. The second chapter, for example, in addition to the choice of the jump process, discusses the possibility of using the marginal, i.e. one-dimensional, unconditional characteristic function in the estimation instead of the joint, bi-dimensional, unconditional characteristic function. As result, the preference for one or the other depends on the model to be estimated. Thus, the computational effort can be reduced in some cases without affecting the efficiency of the estimator. The improvement of the estimator s efficiency by increasing its dimensionality faces more difficulties. The third chapter of this thesis, in addition to what was discussed above, compares the performance of the estimators with bi- and three-dimensional unconditional characteristic functions on the simulated data. It shows that the theoretical efficiency of the Continuous ECF estimator based on the three-dimensional unconditional characteristic function is not attainable in practice, at least for the moment, due to the limitations on the computer power and optimization toolboxes available to the general public. Thus, the Continuous ECF estimator based on the joint, bi-dimensional, unconditional characteristic function has all the reasons to exist and to be used for the estimation of parameters of the stochastic volatility jump-diffusion models.

A CT-based study investigating the relationship between pedicle screw placement and stimulation threshold of compound muscle action potentials measured by intraoperative neurophysiological monitoring.

PURPOSE: Neurophysiological monitoring aims to improve the safety of pedicle screw placement, but few quantitative studies assess specificity and sensitivity. In this study, screw placement within the pedicle is measured (post-op CT scan, horizontal and vertical distance from the screw edge to the surface of the pedicle) and correlated with intraoperative neurophysiological stimulation thresholds. METHODS: A single surgeon placed 68 thoracic and 136 lumbar screws in 30 consecutive patients during instrumented fusion under EMG control. The female to male ratio was 1.6 and the average age was 61.3 years (SD 17.7). Radiological measurements, blinded to stimulation threshold, were done on reformatted CT reconstructions using OsiriX software. A standard deviation of the screw position of 2.8 mm was determined from pilot measurements, and a 1 mm of screw-pedicle edge distance was considered as a difference of interest (standardised difference of 0.35) leading to a power of the study of 75 % (significance level 0.05). RESULTS: Correct placement and stimulation thresholds above 10 mA were found in 71 % of screws. Twenty-two percent of screws caused cortical breach, 80 % of these had stimulation thresholds above 10 mA (sensitivity 20 %, specificity 90 %). True prediction of correct position of the screw was more frequent for lumbar than for thoracic screws. CONCLUSION: A screw stimulation threshold of >10 mA does not indicate correct pedicle screw placement. A hypothesised gradual decrease of screw stimulation thresholds was not observed as screw placement approaches the nerve root. Aside from a robust threshold of 2 mA indicating direct contact with nervous tissue, a secondary threshold appears to depend on patients' pathology and surgical conditions.

Stability and robustness of blood variables in an antidoping context.

Introduction:  With the setting up of the newly Athlete's Biological Passport antidoping programme, novel guidelines have been introduced to guarantee results beyond reproach. We investigated in this context, the effect of storage time on the variables commonly measured for the haematological passport. We also wanted to assess for these variables, the within and between analyzer variations. Methods:  Blood samples were obtained from top level male professional cyclists (27 samples for the first part of the study and 102 for the second part) taking part to major stage races. After collection, they were transported under refrigerated conditions (2 °C < T < 12 °C), delivered to the antidoping laboratory, analysed and then stored at approximately 4 °C to conduct analysis at different time points up to 72 h after delivery. A mixed-model procedure was used to determine the stability of the different variables. Results:  As expected haemoglobin concentration was not affected by storage and showed stability for at least 72 h. Under the conditions of our investigation, the reticulocytes percentage showed a much better stability than previous published data (> 48 h) and the technical comparison of the haematology analyzer demonstrated excellent results. Conclusion:  In conclusion, our data clearly demonstrate that as long as the World Anti-Doping Agency's guidelines are followed rigorously, all blood results reach the quality level required in the antidoping context.

Characterization of PhlG, a hydrolase that specifically degrades the antifungal compound 2,4-diacetylphloroglucinol in the biocontrol agent Pseudomonas fluorescens CHA0.

The potent antimicrobial compound 2,4-diacetylphloroglucinol (DAPG) is a major determinant of biocontrol activity of plant-beneficial Pseudomonas fluorescens CHA0 against root diseases caused by fungal pathogens. The DAPG biosynthetic locus harbors the phlG gene, the function of which has not been elucidated thus far. The phlG gene is located upstream of the phlACBD biosynthetic operon, between the phlF and phlH genes which encode pathway-specific regulators. In this study, we assigned a function to PhlG as a hydrolase specifically degrades DAPG to equimolar amounts of mildly toxic monoacetylphloroglucinol (MAPG) and acetate. DAPG added to cultures of a DAPG-negative DeltaphlA mutant of strain CHA0 was completely degraded, and MAPG was temporarily accumulated. In contrast, DAPG was not degraded in cultures of a DeltaphlA DeltaphlG double mutant. To confirm the enzymatic nature of PhlG in vitro, the protein was histidine tagged, overexpressed in Escherichia coli, and purified by affinity chromatography. Purified PhlG had a molecular mass of about 40 kDa and catalyzed the degradation of DAPG to MAPG. The enzyme had a kcat of 33 s(-1) and a Km of 140 microM at 30 degrees C and pH 7. The PhlG enzyme did not degrade other compounds with structures similar to DAPG, such as MAPG and triacetylphloroglucinol, suggesting strict substrate specificity. Interestingly, PhlG activity was strongly reduced by pyoluteorin, a further antifungal compound produced by the bacterium. Expression of phlG was not influenced by the substrate DAPG or the degradation product MAPG but was subject to positive control by the GacS/GacA two-component system and to negative control by the pathway-specific regulators PhlF and PhlH.

Optimal dividend strategies for a compound Poisson risk process under transaction costs and power utility

We characterize the value function of maximizing the total discounted utility of dividend payments for a compound Poisson insurance risk model when strictly positive transaction costs are included, leading to an impulse control problem. We illustrate that well known simple strategies can be optimal in the case of exponential claim amounts. Finally we develop a numerical procedure to deal with general claim amount distributions.

School burnout in adolescents : Differences in background variables and exploration of school-related stress at the end of compulsory schooling

The aim of this study is to contribute to a better understanding of the risk factors associated with school burnout, which has recently been described as a syndrome of emotional exhaustion due to school demands, cynical and detached attitude towards school and feelings of inadequacy as a student (Salmela-Aro, Kiuru, Pietikainen & Jokela, 2008a). The research focuses on students in the last years of compulsory schooling, period in which burnout has not received much attention yet. A total of 342 adolescents (Mean age = 14.84) were asked to complete questionnaires about school burnout, school-related stress and background variables. The results showed differences in school burnout by gender, grade level and school track, with girls, last grade of compulsory school and high-track classes, showing the highest scores. No difference was observed with respect to grade retention. Several types of school stress were identified, with stress type Success related to pressures to succeed and concerns about the academic future being the highest. Finally, stress and burnout were strongly and positively correlated, and the type of stress Success was the best predictor of overall Burnout, Exhaustion and Inadequacy dimension scores. The results are discussed in relation to their theoretical relevance and implications for the prevention of school burnout in adolescents.

Introduction of snow and geomorphic disturbance variables into predictive models of alpine plant distribution in the Western Swiss Alps

Indirect topographic variables have been used successfully as surrogates for disturbance processes in plant species distribution models (SDM) in mountain environments. However, no SDM studies have directly tested the performance of disturbance variables. In this study, we developed two disturbance variables: a geomorphic index (GEO) and an index of snow redistribution by wind (SNOW). These were developed in order to assess how they improved both the fit and predictive power of presenceabsence SDM based on commonly used topoclimatic (TC) variables for 91 plants in the Western Swiss Alps. The individual contribution of the disturbance variables was compared to TC variables. Maps of models were prepared to spatially test the effect of disturbance variables. On average, disturbance variables significantly improved the fit but not the predictive power of the TC models and their individual contribution was weak (5.6% for GEO and 3.3% for SNOW). However their maximum individual contribution was important (24.7% and 20.7%). Finally, maps including disturbance variables (i) were significantly divergent from TC models in terms of predicted suitable surfaces and connectivity between potential habitats, and (ii) were interpreted as more ecologically relevant. Disturbance variables did not improve the transferability of models at the local scale in a complex mountain system, and the performance and contribution of these variables were highly species-specific. However, improved spatial projections and change in connectivity are important issues when preparing projections under climate change because the future range size of the species will determine the sensitivity to changing conditions.