7 research outputs found

    ProblÚmes médico-légaux posés par un préjudice sexuel déclaré aprÚs un dommage corporel

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    PARIS-BIUM (751062103) / SudocCentre Technique Livre Ens. Sup. (774682301) / SudocSudocFranceF

    Modeling incision profile in AWJM of Titanium alloys Ti6Al4V

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    Abrasive water jet milling (AWJM) is a new way to perform controlled depth milling especially for hard materials, but it’s not yet enough reliable because of large variety of process parameters and complex footprint geometries that are not well mastered. In order to master the milling device in AWJM, a deep study on the footprint of a single path of the cutting head should first be considered. The flow of the AWJ and the distribution of abrasive particles coming out of the jet are related to the profile measured on the footprint. In this study, experiments were made on titanium alloys specimen to compare several theoretical models to the measured profile of the footprint. This study establishes new models to fit the incision profile taking in consideration the behavior of the abrasive particles impacting the workpiece

    Energy Resolved Mass Spectrometry for Interoperable Non-resonant Collisional Spectra in Metabolomics

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    International audienceIn untargeted metabolomics, the unambiguous identification of metabolites remains a major challenge. This requires high-quality spectral libraries for reliable metabolite identification, which is essential for translating metabolomics data into meaningful biological information. Several attempts have been made to generate reproducible product ion spectra (PIS) under a low collision energy (E-Lab) regime and nonresonant collisional conditions but have not fully succeeded. We examined the ERMS (energy-resolved mass spectrometry) breakdown curves of two lipo-amino acids and showed the possibility to highlight "singular points", called descriptors hereafter (linked to respective E-Lab depending on the instrument), for each of the monomodal product ion profiles. Using several instruments based on different technologies, the PIS recorded at these specific E-Lab sites shows remarkable similarities. The descriptors appeared as being independent of the fragmentation mechanisms and can be used to overcome the main instrumental effects that limit the interoperability of spectral libraries. This proof-of-concept study, performed on two particular lipo-amino acids, demonstrates the high potential of ERMS-derived information to determine the instrument-specific E-Lab at which PIS recorded in nonresonant conditions become highly similar and instrument-independent, thus comparable across platforms. This innovative but straightforward approach could help remove some of the obstacles to metabolite identification in nontargeted metabolomics, putting an end to a challenging chimera

    Discovery and quantification of lipoamino acids in bacteria

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    International audienceImproving knowledge about metabolites produced by the microbiota is a key point to understand its role in human health and disease. Among them, lipoamino acid (LpAA) containing asparagine and their derivatives are bacterial metabolites which could have an impact on the host. In this study, our aim was to extend the characterization of this family. We developed a semi-targeted workflow to identify and quantify new candidates. First, the sample preparation and analytical conditions using liquid chromatography (LC) coupled to high resolution mass spectrometry (HRMS) were optimized. Using a theoretical homemade database, HRMS raw data were manually queried. This strategy allowed us to find 25 new LpAA conjugated to Asn, Gln, Asp, Glu, His, Leu, Ileu, Pro, Lys, Phe, Trp and Val amino acids. These metabolites were then fully characterized by MS2, and compared to the pure synthesized standards to validate annotation. Finally, a quantitative method was developed by LC coupled to a triple quadrupole instrument, and linearity and limit of quantification were determined. 14 new LpAA were quantified in gram positive bacteria, Lactobacilus animalis, and 12 LpAA in Escherichia coli strain Nissle 1917
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