Characterization and source apportionment of organic aerosol using offline aerosol mass spectrometry

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.

MONITORING ENZYME REACTIONS BY FAST ATOM BOMBARDMENT MASS SPECTROMETRY

The potential for the direct analysis of enzyme reactions by fast atom bombardment (FAB) mass spectrometry has been investigated. Conditions are presented for the maintenance of enzymatic activity under FAB conditions along with FAB mass spectrometric data showing that these conditions can be applied to solutions of enzyme and substrate to follow enzymatic reactions inside the mass spectrometer in real-time. In addition, enzyme kinetic behavior under FAB mass spectrometric conditions is characterized using trypsin and its assay substrate, TAME, as an enzyme-substrate reaction model. These results show that two monitoring methods can be utilized to follow reactions by FAB mass spectrometry. The advantages of each method are discussed and illustrated by obtaining kinetic parameters from the direct analysis of enzyme reactions with assay or peptide substrates. ^

Development of combined micro -preparation, separation, and mass spectrometry methods and application in the microdialysis study of neuropeptide metabolism

Two sets of mass spectrometry-based methods were developed specifically for the in vivo study of extracellular neuropeptide biochemistry. First, an integrated micro-concentration/desalting/matrix-addition device was constructed for matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) to achieve attomole sensitivity for microdialysis samples. Second, capillary electrophoresis (CE) was incorporated into the above micro-liquid chromatography (LC) and MALDI MS system to provide two-dimensional separation and identification (i.e. electrophoretic mobility and molecular mass) for the analysis of complex mixtures. The latter technique includes two parts of instrumentation: (1) the coupling of a preconcentration LC column to the inlet of a CE capillary, and (2) the utilization of a matrix-precoated membrane target for continuous CE effluent deposition and for automatic MALDI MS analysis (imaging) of the CE track.^ Initial in vivo data reveals a carboxypeptidase A (CPA) activity in rat brain involved in extracellular neurotensin metabolism. Benzylsuccinic acid, a CPA inhibitor, inhibited neurotensin metabolite NT1-12 formation by 70%, while inhibitors of other major extracellular peptide metabolizing enzymes increased NT1-12 formation. CPA activity has not been observed in previous in vitro experiments. Next, the validity of the methodology was demonstrated in the detection and structural elucidation of an endogenous neuropeptide, (L)VV-hemorphin-7, in rat brain upon ATP stimulation. Finally, the combined micro-LC/CE/MALDI MS was used in the in vivo metabolic study of peptide E, a mu-selective opioid peptide with 25 amino acid residues. Profiles of 88 metabolites were obtained, their identity being determined by their mass-to-charge ratio and electrophoretic mobility. The results indicate that there are several primary cleavage sites in vivo for peptide E in the release of its enkephalin-containing fragments. ^

Rare earth elements determined in Antarctic ice by inductively coupled plasma

Inductively coupled plasma mass spectrometry (ICP-MS) is a suitable tool for multi-element analysis at low concentration levels. Rare earth element (REE) determinations in standard reference materials and small volumes of molten ice core samples from Antarctica have been performed with an ICP-time of flight-MS (ICP-TOF-MS) system. Recovery rates for REE in e.g. SPS-SW1 amounted to not, vert, similar ~103%, and the relative standard deviations were 3.4% for replicate analysis at REE concentrations in the lower ng/l range. Analyses of REE concentrations in Antarctic ice core samples showed that the ICP-TOF-MS technique meets the demands of restricted sample mass. The data obtained are in good agreement with ICP-Quadrupole-MS (ICP-Q-MS) and ICP-Sector Field-MS (ICP-SF-MS) results. The ICP-TOF-MS system determines accurately and precisely REE concentrations exceeding 5 ng/l while between 0.5 and 5 ng/l accuracy and precision are element dependent.

Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data

Mass spectrometry (MS) data provide a promising strategy for biomarker discovery. For this purpose, the detection of relevant peakbins in MS data is currently under intense research. Data from mass spectrometry are challenging to analyze because of their high dimensionality and the generally low number of samples available. To tackle this problem, the scientific community is becoming increasingly interested in applying feature subset selection techniques based on specialized machine learning algorithms. In this paper, we present a performance comparison of some metaheuristics: best first (BF), genetic algorithm (GA), scatter search (SS) and variable neighborhood search (VNS). Up to now, all the algorithms, except for GA, have been first applied to detect relevant peakbins in MS data. All these metaheuristic searches are embedded in two different filter and wrapper schemes coupled with Naive Bayes and SVM classifiers.

Multiresidue Analysis of Insecticides and Other Selected Environmental Contaminants in Poultry Manure by Gas Chromatography/Mass Spectrometry

An analytical method was developed for the simultaneous determination in poultry manure of 41 organic contaminants belonging to different chemical classes: pesticides, polycyclic aromatic hydrocarbons, polychlorinated biphenyls, and polybrominated diphenyl ethers. Poultry manure was extracted with a modified QuEChERS method, and the extracts were analyzed by isotope dilution GC/MS. Recovery of these contaminants from samples spiked at levels ranging from 25 to 100 ng/g was satisfactory for all the compounds. The developed procedure provided LODs from 0.8 to 9.6 ng/g. The analysis of poultry manure samples collected on different farms confirmed the presence of some of the studied contaminants. Pyrethroids and polycyclic aromatic hydrocarbons were the main contaminants detected.