70 resultados para SOURCE-MASS-SPECTROMETRY


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Field deployments of the Aerodyne Aerosol Mass Spectrometer (AMS) have significantly advanced real-time measurements and source apportionment of non-refractory particulate matter. However, the cost and complex maintenance requirements of the AMS make its deployment at sufficient sites to determine regional characteristics impractical. Furthermore, the negligible transmission efficiency of the AMS inlet for supermicron particles significantly limits the characterization of their chemical nature and contributing sources. In this study, we utilize the AMS to characterize the water-soluble organic fingerprint of ambient particles collected onto conventional quartz filters, which are routinely sampled at many air quality sites. The method was applied to 256 particulate matter (PM) filter samples (PM1, PM2:5, and PM10, i.e., PM with aerodynamic diameters smaller than 1, 2.5, and 10 μm, respectively), collected at 16 urban and rural sites during summer and winter. We show that the results obtained by the present technique compare well with those from co-located online measurements, e.g., AMS or Aerosol Chemical Speciation Monitor (ACSM). The bulk recoveries of organic aerosol (60–91 %) achieved using this technique, together with low detection limits (0.8 μg of organic aerosol on the analyzed filter fraction) allow its application to environmental samples. We will discuss the recovery variability of individual hydrocarbon ions, ions containing oxygen, and other ions. The performance of such data in source apportionment is assessed in comparison to ACSM data. Recoveries of organic components related to different sources as traffic, wood burning, and secondary organic aerosol are presented. This technique, while subjected to the limitations inherent to filter-based measurements (e.g., filter artifacts and limited time resolution) may be used to enhance the AMS capabilities in measuring size-fractionated, spatially resolved longterm data sets.

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Moraxella catarrhalis is a major mucosal pathogen of the human respiratory tract both in children and in adults. Two subpopulations of this organism have been described that differ in 16S rRNA gene sequence and virulence traits. Three 16S rRNA types have been defined. 2-DE followed by protein identification by MS revealed significant differences in the outer membrane protein (OMP) patterns of each M. catarrhalis 16S rRNA type. Approximately 130 features were detected on the 2-DE map of each M. catarrhalis 16S rRNA type. However, only 50 features were expressed by all strains. Furthermore, direct profiling of isolated OMP using MALDI-TOF MS resulted in a characteristic spectral fingerprint for each 16S rRNA type. Fingerprints remained identical when intact cells instead of isolated OMP were analyzed. This finding suggests that the source of desorbed ions is the outer membrane. Based on the fingerprint we were able to assign 18 well-characterized clinical M. catarrhalis isolates to the correct subpopulation. Therefore, MALDI-TOF of intact M. catarrhalis provides a rapid and robust tool for M. catarrhalis strain typing that could be applied in epidemiological studies.

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Abstract Radiation metabolomics employing mass spectral technologies represents a plausible means of high-throughput minimally invasive radiation biodosimetry. A simplified metabolomics protocol is described that employs ubiquitous gas chromatography-mass spectrometry and open source software including random forests machine learning algorithm to uncover latent biomarkers of 3 Gy gamma radiation in rats. Urine was collected from six male Wistar rats and six sham-irradiated controls for 7 days, 4 prior to irradiation and 3 after irradiation. Water and food consumption, urine volume, body weight, and sodium, potassium, calcium, chloride, phosphate and urea excretion showed major effects from exposure to gamma radiation. The metabolomics protocol uncovered several urinary metabolites that were significantly up-regulated (glyoxylate, threonate, thymine, uracil, p-cresol) and down-regulated (citrate, 2-oxoglutarate, adipate, pimelate, suberate, azelaate) as a result of radiation exposure. Thymine and uracil were shown to derive largely from thymidine and 2'-deoxyuridine, which are known radiation biomarkers in the mouse. The radiation metabolomic phenotype in rats appeared to derive from oxidative stress and effects on kidney function. Gas chromatography-mass spectrometry is a promising platform on which to develop the field of radiation metabolomics further and to assist in the design of instrumentation for use in detecting biological consequences of environmental radiation release.

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Because of the large variability in the pharmacokinetics of anti-HIV drugs, therapeutic drug monitoring in patients may contribute to optimize the overall efficacy and safety of antiretroviral therapy. An LC–MS/MS method for the simultaneous assay in plasma of the novel antiretroviral agents rilpivirine (RPV) and elvitegravir (EVG) has been developed to that endeavor. Plasma samples (100 μL) extraction is performed by protein precipitation with acetonitrile, and the supernatant is subsequently diluted 1:1 with 20-mM ammonium acetate/MeOH 50:50. After reverse-phase chromatography, quantification of RPV and EVG, using matrix-matched calibration samples, is performed by electrospray ionization–triple quadrupole mass spectrometry by selected reaction monitoring detection using the positive mode. The stable isotopic-labeled compounds RPV-13C6 and EVG-D6 were used as internal standards. The method was validated according to FDA recommendations, including assessment of extraction yield, matrix effects variability (<6.4%), as well as EVG and RPV short and long-term stability in plasma. Calibration curves were validated over the clinically relevant concentrations ranging from 5 to 2500 ng/ml for RPV and from 50 to 5000 ng/ml for EVG. The method is precise (inter-day CV%: 3–6.3%) and accurate (3.8–7.2%). Plasma samples were found to be stable (<15%) in all considered conditions (RT/48 h, +4°C/48 h, −20°C/3 months and 60°C/1 h). Selected metabolite profiles analysis in patients' samples revealed the presence of EVG glucuronide, that was well separated from parent EVG, allowing to exclude potential interferences through the in-source dissociation of glucuronide to parent drug. This new, rapid and robust LCMS/MS assay for the simultaneous quantification of plasma concentrations of these two major new anti-HIV drugs EVG and RPV offers an efficient analytical tool for clinical pharmacokinetics studies and routine therapeutic drug monitoring service.

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Radiation metabolomics can be defined as the global profiling of biological fluids to uncover latent, endogenous small molecules whose concentrations change in a dose-response manner following exposure to ionizing radiation. In response to the potential threat of nuclear or radiological terrorism, the Center for High-Throughput Minimally Invasive Radiation Biodosimetry was established to develop field-deployable biodosimeters based, in part, on rapid analysis by mass spectrometry of readily and easily obtainable biofluids. In this review, we briefly summarize radiation biology and key events related to actual and potential nuclear disasters, discuss the important contributions the field of mass spectrometry has made to the field of radiation metabolomics, and summarize current discovery efforts to use mass spectrometry-based metabolomics to identify dose-responsive urinary constituents, and ultimately to build and deploy a noninvasive high-throughput biodosimeter.

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A liquid chromatographic-mass spectrometric assay with atmospheric pressure chemical ionization for quantification of ondansetron and its main metabolite 8-hydroxyondansetron in human plasma was presented. The enantiomeric separation was achieved on a Chiralcel OD-R column containing cellulose tris-(3,5-dimethylphenylcarbamate). The validation data were within the required limits. The assay was successfully applied to authentic plasma samples. Quantitative results from postoperative patients receiving ondansetron demonstrated a great interindividual variability in postoperative plasma drug concentrations, the metabolites were not detected in their unconjugated form. A wide variation in the S-(+)-/R-(-)-ondansetron concentration ratio between 0.14 and 7.18 is indicative for a stereoselective disposition or metabolism. In further studies CYP2D6 and CYP3A4 genotype dependent metabolism of ondansetron enantiomers as well as of co-administered drugs and clinical efficacy of the medication should be tested.

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This paper describes informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography (GCxGC) and high-resolution mass spectrometry (HRMS). GCxGC-HRMS analysis produces large data sets that are rich with information, but highly complex. The size of the data and volume of information requires automated processing for comprehensive cross-sample analysis, but the complexity poses a challenge for developing robust methods. The approach developed here analyzes GCxGC-HRMS data from multiple samples to extract a feature template that comprehensively captures the pattern of peaks detected in the retention-times plane. Then, for each sample chromatogram, the template is geometrically transformed to align with the detected peak pattern and generate a set of feature measurements for cross-sample analyses such as sample classification and biomarker discovery. The approach avoids the intractable problem of comprehensive peak matching by using a few reliable peaks for alignment and peak-based retention-plane windows to define comprehensive features that can be reliably matched for cross-sample analysis. The informatics are demonstrated with a set of 18 samples from breast-cancer tumors, each from different individuals, six each for Grades 1-3. The features allow classification that matches grading by a cancer pathologist with 78% success in leave-one-out cross-validation experiments. The HRMS signatures of the features of interest can be examined for determining elemental compositions and identifying compounds.

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We describe here a new reversed-phase high-performance liquid chromatography with mass spectrometry detection method for quantifying intact cytokinin nucleotides in human K-562 leukemia cells. Tandem mass spectrometry was used to identify the intracellular metabolites (cytokinin monophosphorylated, diphosphorylated, and triphosphorylated nucleotides) in riboside-treated cells. For the protein precipitation and sample preparation, a trichloroacetic acid extraction method is used. Samples are then back-extracted with diethyl ether, lyophilized, reconstituted, and injected into the LC system. Analytes were quantified in negative selected ion monitoring mode using a single quadrupole mass spectrometer. The method was validated in terms of retention time stabilities, limits of detection, linearity, recovery, and analytical accuracy. The developed method was linear in the range of 1-1,000 pmol for all studied compounds. The limits of detection for the analytes vary from 0.2 to 0.6 pmol.

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A liquid chromatography tandem mass spectrometry (LC-MS/MS) confirmatory method for the simultaneous determination of nine corticosteroids in liver, including the four MRL compounds listed in Council Regulation 37/2010, was developed. After an enzymatic deconjugation and a solvent extraction of the liver tissue, the resulting solution was cleaned up through an SPE Oasis HLB cartridge. The analytes were then detected by liquid chromatography-negative-ion electrospray tandem mass spectrometry, using deuterium-labelled internal standards. The procedure was validated as a quantitative confirmatory method according to the Commission Decision 2002/657/EC criteria. The results showed that the method was suitable for statutory residue testing regarding the following performance characteristics: instrumental linearity, specificity, precision (repeatability and intra-laboratory reproducibility), recovery, decision limit (CCα), detection capability (CCβ) and ruggedness. All the corticosteroids can be detected at a concentration around 1 μg kg(-1); the recoveries were above 62% for all the analytes. Repeatability and reproducibility (within-laboratory reproducibility) for all the analytes were below 7.65% and 15.5%, respectively.