Ultra-high pressure liquid chromatography-mass spectrometry for plant metabolomics: a systematic comparison of high-resolution quadrupole-time-of-flight and single stage Orbitrap mass spectrometers.

The response of Arabidopsis to stress caused by mechanical wounding was chosen as a model to compare the performances of high resolution quadrupole-time-of-flight (Q-TOF) and single stage Orbitrap (Exactive Plus) mass spectrometers in untargeted metabolomics. Both instruments were coupled to ultra-high pressure liquid chromatography (UHPLC) systems set under identical conditions. The experiment was divided in two steps: the first analyses involved sixteen unwounded plants, half of which were spiked with pure standards that are not present in Arabidopsis. The second analyses compared the metabolomes of mechanically wounded plants to unwounded plants. Data from both systems were extracted using the same feature detection software and submitted to unsupervised and supervised multivariate analysis methods. Both mass spectrometers were compared in terms of number and identity of detected features, capacity to discriminate between samples, repeatability and sensitivity. Although analytical variability was lower for the UHPLC-Q-TOF, generally the results for the two detectors were quite similar, both of them proving to be highly efficient at detecting even subtle differences between plant groups. Overall, sensitivity was found to be comparable, although the Exactive Plus Orbitrap provided slightly lower detection limits for specific compounds. Finally, to evaluate the potential of the two mass spectrometers for the identification of unknown markers, mass and spectral accuracies were calculated on selected identified compounds. While both instruments showed excellent mass accuracy (<2.5ppm for all measured compounds), better spectral accuracy was recorded on the Q-TOF. Taken together, our results demonstrate that comparable performances can be obtained at acquisition frequencies compatible with UHPLC on Q-TOF and Exactive Plus MS, which may thus be equivalently used for plant metabolomics.

Multilayer perceptron with local constraint as an emerging method in spatial data analysis

The use of Geographic Information Systems has revolutionalized the handling and the visualization of geo-referenced data and has underlined the critic role of spatial analysis. The usual tools for such a purpose are geostatistics which are widely used in Earth science. Geostatistics are based upon several hypothesis which are not always verified in practice. On the other hand, Artificial Neural Network (ANN) a priori can be used without special assumptions and are known to be flexible. This paper proposes to discuss the application of ANN in the case of the interpolation of a geo-referenced variable.

Feasibility and electromagnetic compatibility study of the ClearPEM front-end electronics for simultaneous PET-MR imaging

In this work we present a first feasibility study of the ClearPEM technology for simultaneous PET-MR imaging. The mutual electromagnetic interference (EMI) effects between both systems were evaluated on a 7 T magnet by characterizing the response behavior of the ClearPEM detectors and front-end electronics to pulsed RF power and switched magnetic field gradients; and by analyzing the MR system performance degradation from noise pickup into the RF receiver chain, and from magnetic susceptibility artifacts caused by PET front-end materials.

Incremental neural networks for function approximation

A new strategy for incremental building of multilayer feedforward neural networks is proposed in the context of approximation of functions from R-p to R-q using noisy data. A stopping criterion based on the properties of the noise is also proposed. Experimental results for both artificial and real data are performed and two alternatives of the proposed construction strategy are compared.

A steroidomic approach for biomarkers discovery in doping control.

Anti-doping authorities have high expectations of the athlete steroidal passport (ASP) for anabolic-androgenic steroids misuse detection. However, it is still limited to the monitoring of known well-established compounds and might greatly benefit from the discovery of new relevant biomarkers candidates. In this context, steroidomics opens the way to the untargeted simultaneous evaluation of a high number of compounds. Analytical platforms associating the performance of ultra-high pressure liquid chromatography (UHPLC) and the high mass-resolving power of quadrupole time-of-flight (QTOF) mass spectrometers are particularly adapted for such purpose. An untargeted steroidomic approach was proposed to analyse urine samples from a clinical trial for the discovery of relevant biomarkers of testosterone undecanoate oral intake. Automatic peak detection was performed and a filter of reference steroid metabolites mass-to-charge ratio (m/z) values was applied to the raw data to ensure the selection of a subset of steroid-related features. Chemometric tools were applied for the filtering and the analysis of UHPLC-QTOF-MS(E) data. Time kinetics could be assessed with N-way projections to latent structures discriminant analysis (N-PLS-DA) and a detection window was confirmed. Orthogonal projections to latent structures discriminant analysis (O-PLS-DA) classification models were evaluated in a second step to assess the predictive power of both known metabolites and unknown compounds. A shared and unique structure plot (SUS-plot) analysis was performed to select the most promising unknown candidates and receiver operating characteristic (ROC) curves were computed to assess specificity criteria applied in routine doping control. This approach underlined the pertinence to monitor both glucuronide and sulphate steroid conjugates and include them in the athletes passport, while promising biomarkers were also highlighted.