Multivariate curve resolution of wavelet and Fourier compressed spectra.

The multivariate curve resolution method SIMPLe to use Interactive Self-Modeling Mixture Analysis (SIMPLISMA) was applied to Fourier and wavelet compressed ion-mobility spectra. The spectra obtained from the SIMPLISMA model were transformed back to their original representation, that is, uncompressed format. SIMPULSMA was able to model the same pure variables for the partial wavelet transform, although for the Fourier and complete wavelet transforms, satisfactory pure variables and models were not obtained. Data were acquired from two samples and two different ion mobility spectrometry (IMS) sensors. The first sample was thermally desorbed sodium gamma-hydroxybutyrate (GHB), and the second sample was a liquid mixture of dicyclohexylamine (DCHA) and diethylmethylphosphonate (DEMP). The spectra were compressed to 6.3% of their original size. SIMPLISMA was applied to the compressed data in the Fourier and wavelet domains. An alternative method of normalizing SIMPLISMA spectra was devised that removes variation in scale between SIMPLISMA results obtained from uncompressed and compressed data. SIMPLISMA was able to accurately extract the spectral features and concentration profiles directly from daublet compressed IMS data at a compression ratio of 93.7% with root-mean-square errors of reconstruction < 3%. The daublet wavelet filters were selected, because they worked well when compared to coiflet and symmlet. The effects of the daublet filter width and compression ratio were evaluated with respect to reconstruction errors of the data sets and SIMPLISMA spectra. For these experiments, the daublet 14 filter performed well for the two data sets.

Prediction of substructure and toxicity of pesticides with temperature constrained-cascade correlation network from low-resolution mass spectra.

Artificial neural networks are trained to predict the toxicity or active substructures of organophosphorus pesticides and then are applied to screening GC/MS data for environmentally hazardous compounds. Every mass spectral scan in the chromatographic run is classified, and separate chromatograms are obtained for either toxicity or substructure classes. Classification of mass spectra allows the detection of chromatographic peaks from potentially hazardous compounds that may be missing from the reference database. The neural network models predict substructures and toxicity from mass spectra without first determining the complete configurational structure of the pesticides. Temperature constrained-cascade correlation networks (TCCCN) were used because they are self-configuring networks that train rapidly and robustly. The toxicity classes are defined by the World Health Organization, and the substructure classes are standard organophosphorus pesticide groupings. The TCCCN models are used to mathematically resolve peaks in the chromatograms by substructure and toxicity. Evaluations yielded classification rates of 97 and 84% for substructure and toxicity, respectively.

The analysis of methamphetamine hydrochloride by thermal desorption ion mobility spectrometry and SIMPLISMA.

Ion mobility spectrometry (IMS) has been successfully developed to yield an advanced portable instrument. Such instruments may detect trace quantities of regulated substances at the crime scene. The atmospheric ion chemistry that occurs within the instrument may hinder the determination of analytes in real-world samples. The use of temperature programming adds an extra dimension to the data that improves the selectivity of the IMS data when chemometric processing is applied. The SIMPLISMA (SIMPLe-to-use-Interactive Self-Modeling Mixture Analysis) method is demonstrated for modeling variances in IMS data that are introduced from the temperature program. Methamphetamine hydrochloride IMS peaks are obscured by chemical interferences that arise from cigarette smoke residue. Cigarette smoke residue is pervasive at crime scenes. The ability of SIMPLISMA to resolve the analyte peaks that correspond to methamphetamine hydrochloride from interfering cigarette smoke has been demonstrated. A reduced mobility of 1.62 cm2V-1s-1 was observed for a methamphetamine hydrochloride monomer. With the IMS drift tube at room temperature, a second peak was observed at 1.24 cm2V-1s-1, which is consistent with a dimer ion. This peak has not been previously reported.

Development of an expert system for amino acid sequence identification.

An expert system for amino acid sequence identification has been developed. The algorithm uses heuristic rules developed by human experts in protein sequencing. The system is applied to the chromatographic data of phenylthiohydantoin-amino acids acquired from an automated sequencer. The peak intensities in the current cycle are compared with those in the previous cycle, while the calibration and succeeding cycles are used as ancillary identification criteria when necessary. The retention time for each chromatographic peak in each cycle is corrected by the corresponding peak in the calibration cycle at the same run. The main improvement of our system compared with the onboard software used by the Applied Biosystems 477A Protein/Peptide Sequencer is that each peak in each cycle is assigned an identification name according to the corrected retention time to be used for the comparison with different cycles. The system was developed from analyses of ribonuclease A and evaluated by runs of four other protein samples that were not used in rule development. This paper demonstrates that rules developed by human experts can be automatically applied to sequence assignment. The expert system performed more accurately than the onboard software of the protein sequencer, in that the misidentification rates for the expert system were around 7%, whereas those for the onboard software were between 13 and 21%.