Identifying reliable ions for the statistical differentiation of structurally similar fentanyl analogs.

Definitive identification of fentanyl analogs based on mass spectral comparison is challenging given the high degree of structural and, hence, spectral similarity. To address this, a statistical method was previously developed in which two electron-ionization (EI) mass spectra are compared using the unequal variance t-test. Normalized intensities of corresponding ions are compared, testing the null hypothesis (H0 ) that the difference in intensity is equal to zero. If H0 is accepted at all m/z values, the two spectra are statistically equivalent at the specified confidence level. If H0 is not accepted at any m/z value, then there is a significant difference in intensity at that m/z value between the two spectra. In this work, the statistical comparison method is applied to distinguish EI spectra of valeryl fentanyl, isovaleryl fentanyl, and pivaloyl fentanyl. Spectra of the three analogs were collected over a 9-month period and at different concentrations. At the 99.9% confidence level, the spectra of corresponding isomers were statistically associated. Spectra of different isomers were statistically distinct, and ions responsible for discrimination were identified in each comparison. To account for inherent instrument variations, discriminating ions for each pairwise comparison were ranked based on the magnitude of the calculated t-statistic (tcalc ) value. For a given comparison, ions with higher tcalc values are those with the greatest difference in intensity between the two spectra and, therefore, are considered more reliable for discrimination. Using these methods, objective discrimination among the spectra was achieved and ions considered most reliable for discrimination of these isomers were identified.

Measuring evaporation rate constants of highly volatile compounds for use in predictive kinetic models.

A kinetic model was previously developed in our laboratory to predict evaporation of compounds as a function of gas chromatographic retention index (IT). To define the initial model, evaporation rate constants were experimentally determined for compounds in the range IT = 800-1400 at temperatures from 5 to 35 °C. While the predictive accuracy was demonstrated, broader application of the model requires extension of the IT range to include more volatile compounds. However, such extension requires experimental determination of rate constants, which is challenging due to the explosive hazard and rapid evaporation of volatile compounds. In this work, rate constants of highly volatile compounds were experimentally determined and used to extend the kinetic model to predict evaporation. Prior to experimental evaporations, theoretical calculations were performed to optimize experimental parameters and to ensure that the vapor generated remained below the lower flammability limit for each compound. Compounds were then experimentally evaporated at three different temperatures (10, 20, and 30 °C) and analyzed by gas chromatography-mass spectrometry. The evaporation rate constants for each compound, corrected for condensation, were determined by regression to a first-order rate equation. These rate constants were combined with previously collected data to extend the kinetic model at each temperature. Comparison of predicted and experimentally determined chromatograms of an evaporated validation mixture indicated good model performance, with correlation coefficients ranging from 0.955 to 0.997 and mean absolute percent errors in predicting abundance ranging from 3 to 26%.

Statistical comparison of mass spectra for identification of amphetamine-type stimulants.

A method for the statistical comparison of mass spectral data is demonstrated for applications in controlled substance analysis. The method uses an unequal variance t-test at each mass-to-charge ratio in the scan range to determine if two spectra are statistically associated or discriminated. If the two spectra are associated, a random-match probability is calculated to estimate the likelihood that the mass spectral fragmentation pattern in question occurs by random chance alone. If the two spectra are discriminated, the fragment ions responsible for the discrimination are determined. In this work, mass spectral data from case samples containing amphetamine, methamphetamine, 3,4-methylenedioxyamphetamine (MDA), 3,4-methylenedioxymethamphetamine (MDMA), phentermine, and psilocin were investigated. All spectra were collected in an accredited forensic laboratory using routine methods for controlled substance analysis. Using the statistical method, spectra of case samples were statistically associated to the corresponding reference standard at the 99.9% confidence level. In these instances, random-match probabilities ranged from 10-39 to 10-29, indicating the probability that the characteristic fragmentation pattern occurred by random chance is extremely small. Further, spectra of case samples were discriminated from other reference standards at the 99.9% or 99.0% confidence level, with 1-26 ions responsible for discrimination in each comparison.

Assessing the effect of data pretreatment procedures for principal components analysis of chromatographic data.

Following publication of the National Academy of Sciences report "Strengthening Forensic Science in the United States: A Path Forward", there has been increasing interest in the application of multivariate statistical procedures for the evaluation of forensic evidence. However, prior to statistical analysis, variance from sources other than the sample must be minimized through application of data pretreatment procedures. This is necessary to ensure that subsequent statistical analysis of the data provides meaningful results. The purpose of this work was to evaluate the effect of pretreatment procedures on multivariate statistical analysis of chromatographic data obtained for a reference set of diesel fuels. Diesel was selected due to its chemical complexity and forensic relevance, both for fire debris and environmental forensic applications. Principal components analysis (PCA) was applied to the untreated chromatograms to assess association of replicates and discrimination among the different diesel samples. The chromatograms were then pretreated by sequentially applying the following procedures: background correction, smoothing, retention-time alignment, and normalization. The effect of each procedure on association and discrimination was evaluated based on the association of replicates in the PCA scores plot. For these data, background correction and smoothing offered minimal improvement, whereas alignment and normalization offered the greatest improvement in the association of replicates and discrimination among highly similar samples. Further, prior to pretreatment, the first principal component accounted for only non-sample sources of variance. Following pretreatment, these sources were minimized and the first principal component accounted for significant chemical differences among the diesel samples. These results highlight the need for pretreatment procedures and provide a metric to assess the effect of pretreatment on subsequent multivariate statistical analysis of complex data.

Gas chromatographic retention index as a basis for predicting evaporation rates of complex mixtures.

Models that predict the fate of petroleum fuels in the environment are often required for effective remediation of fuel-contaminated sites. In this research, an environmental fuel spill was simulated by means of a diesel/water microcosm, in which the temporal changes in composition were assessed during evaporation by gas chromatography-mass spectrometry (GC-MS). First-order kinetic rate constants were calculated for 51 selected compounds and utilized to develop predictive models for evaporation rate constants, using GC retention indices on a nonpolar stationary phase. Models were initially developed to predict rates of evaporation of compounds from individual classes (normal alkane, branched alkane, alkyl benzene, and polycyclic hydrocarbon) and then expanded to include all compounds (comprehensive model). Using the comprehensive model, the rate constants were predicted with a mean absolute percent error (MAPE) of 10%, whereas the class-specific models resulted in less error (4-8%). These models were employed to predict the fraction remaining of the total fuel (6% error) as well as the fraction remaining of individual compounds (13% MAPE). Accurate models such as these will facilitate remediation of environmental releases of petroleum products.

Effect of substrate interferences from high-density polyethylene on association of simulated ignitable liquid residues with the corresponding liquid.

The effect of substrate interferences from high-density polyethylene (HDPE) on the ability to associate an ignitable liquid residue with the corresponding liquid standard, using statistical procedures, is demonstrated. Gasoline, kerosene, and lighter fluid, at three different evaporation levels, were spiked onto HDPE and subsequently burned to generate simulated ignitable liquid residues (ILRs). Samples were extracted using a passive headspace procedure and analyzed by gas chromatography-mass spectrometry. The total ion chromatograms were subjected to data pretreatment procedures prior to principal components analysis and Pearson product moment correlation. Using the combination of these statistical procedures, simulated ILRs were successfully associated with the corresponding liquid type, despite the presence of compounds inherent to the HDPE substrate, as well as those resulting from pyrolysis of the substrate.

Statistical approach to establish equivalence of unabbreviated mass spectra.

RATIONALE: In many legal and regulatory applications, mass spectral comparison of an unknown or questioned sample to a reference standard or database is used for identification; however, no statistical confidence level or error rate is determined. Therefore, a simple and rapid method to establish the statistical equivalence of mass spectra is needed. METHODS: The standard deviation of the abundance at each m/z ratio was determined from replicate measurements or from a statistical model. These standard deviations were used in an unequal variance t-test to compare two spectra at every m/z ratio over the entire scan range. If determined to be statistically indistinguishable at every m/z ratio, the random-match probability (RMP) that the specific mass spectral fragmentation pattern occurred by chance was calculated. RESULTS: n-Alkane and alkylbenzene standards of varying concentrations were analyzed on the same instrument at different ionization voltages. Using the proposed method, replicate spectra were successfully associated at the 99.9% confidence level, with RMP values less than 10(-29). Despite the similarity in fragmentation patterns, spectra were distinguished from others in the homologous series. Moreover, the n-alkane spectra were appropriately associated to and discriminated from those in a standard reference database at the 99.9% confidence level. CONCLUSIONS: A simple and rapid method to assign statistical significance to the comparison of mass spectra was developed and validated. This method may be useful for legal and regulatory applications, such as the identification of controlled substances, environmental pollutants, and food and drug contaminants.

Effect of evaporation and matrix interferences on the association of simulated ignitable liquid residues to the corresponding liquid standard.

Identification of an ignitable liquid in fire debris evidence can be complicated due to evaporation of the liquid, matrix interferences, and thermal degradation of both the liquid and the matrix. In this research, liquids extracted from simulated fire debris were compared to the original liquid using multivariate statistical procedures. Neat and evaporated gasoline and kerosene standards were spiked onto nylon carpet, which was subsequently burned. The ignitable liquid residues were extracted using a passive headspace procedure and analyzed by gas chromatography-mass spectrometry. Pearson product moment correlation coefficients, hierarchical cluster analysis, and principal components analysis were used to compare the liquids extracted from the carpet to the corresponding neat liquid. For each procedure, association of the extracts according to liquid type was possible, albeit not necessarily to the specific evaporation level. Of the three procedures investigated, principal components analysis offered the most promise since contributions from matrix interferences were essentially eliminated.

Forensic analysis of Salvia divinorum using multivariate statistical procedures. Part II: association of adulterated samples to S. divinorum.

Salvia divinorum is a plant material that is of forensic interest due to the hallucinogenic nature of the active ingredient, salvinorin A. In this study, S. divinorum was extracted and spiked onto four different plant materials (S. divinorum, Salvia officinalis, Cannabis sativa, and Nicotiana tabacum) to simulate an adulterated sample that might be encountered in a forensic laboratory. The adulterated samples were extracted and analyzed by gas chromatography-mass spectrometry, and the resulting total ion chromatograms were subjected to a series of pretreatment procedures that were used to minimize non-chemical sources of variance in the data set. The data were then analyzed using principal components analysis (PCA) to investigate association of the adulterated extracts to unadulterated S. divinorum. While association was possible based on visual assessment of the PCA scores plot, additional procedures including Euclidean distance measurement, hierarchical cluster analysis, Student's t tests, Wilcoxon rank-sum tests, and Pearson product moment correlation were also applied to the PCA scores to provide a statistical evaluation of the association observed. The advantages and limitations of each statistical procedure in a forensic context were compared and are presented herein.

Forensic analysis of Salvia divinorum using multivariate statistical procedures. Part I: discrimination from related Salvia species.

Salvia divinorum is a hallucinogenic herb that is internationally regulated. In this study, salvinorin A, the active compound in S. divinorum, was extracted from S. divinorum plant leaves using a 5-min extraction with dichloromethane. Four additional Salvia species (Salvia officinalis, Salvia guaranitica, Salvia splendens, and Salvia nemorosa) were extracted using this procedure, and all extracts were analyzed by gas chromatography-mass spectrometry. Differentiation of S. divinorum from other Salvia species was successful based on visual assessment of the resulting chromatograms. To provide a more objective comparison, the total ion chromatograms (TICs) were subjected to principal components analysis (PCA). Prior to PCA, the TICs were subjected to a series of data pretreatment procedures to minimize non-chemical sources of variance in the data set. Successful discrimination of S. divinorum from the other four Salvia species was possible based on visual assessment of the PCA scores plot. To provide a numerical assessment of the discrimination, a series of statistical procedures such as Euclidean distance measurement, hierarchical cluster analysis, Student's t tests, Wilcoxon rank-sum tests, and Pearson product moment correlation were also applied to the PCA scores. The statistical procedures were then compared to determine the advantages and disadvantages for forensic applications.

Association of ignitable liquid residues to neat ignitable liquids in the presence of matrix interferences using chemometric procedures.

In fire debris analysis, weathering of ignitable liquids and matrix interferences can make the identification of ignitable liquid residues (ILRs) difficult. An objective method was developed to associate ILRs with the corresponding neat liquid with discrimination from matrix interferences using principal components analysis (PCA) and Pearson product moment correlation (PPMC) coefficients. Six ignitable liquids (gasoline, diesel, ultra pure paraffin lamp oil, adhesive remover, torch fuel, paint thinner) were spiked onto carpet, which was burned, then extracted using passive headspace extraction, and analyzed by gas chromatography-mass spectrometry. Both light and heavy burn conditions were investigated. In the PCA scores plot, ignitable liquids were discriminated based on alkane and aromatic content. All ILRs were successfully associated with the corresponding neat liquid using both PCA and PPMC coefficients, regardless of the extent of burning. The method developed in this research may make the association of ILRs with corresponding neat liquids more objective.

Thermodynamic and kinetic characterization of a bridged-ethylene hybrid C18 stationary phase.

In this study, a series of polycyclic aromatic hydrocarbons (PAHs) and nitrogen-containing polycyclic aromatic hydrocarbons (NPAHs) is separated on a hybrid stationary phase using methanol and acetonitrile mobile phases. Temperature is varied from 283 to 313 K in order to determine thermodynamic and kinetic parameters of the separation. Thermodynamic behavior is characterized by the retention factor and associated changes in molar enthalpy, whereas kinetic behavior is characterized by the rate constants and associated activation energies. In this study, the retention factors for the NPAHs are smaller than those for the parent PAHs in methanol, while they are more similar to the parent PAHs in acetonitrile. The changes in molar enthalpy are very similar for all solutes, yet are more negative in acetonitrile than in methanol. The rate constants for the NPAHs are smaller than those for their parent PAHs in both mobile phases. Moreover, the rate constants in acetonitrile are one to four orders of magnitude smaller than those in methanol. Based on these thermodynamic and kinetic results, the hybrid stationary phase is compared to traditional silica stationary phases. In addition, the relative contributions from the partition and adsorption mechanisms are discussed.

Thermodynamic and kinetic study of chiral separations of coumarin-based anticoagulants on derivatized amylose stationary phase.

Thermodynamic and kinetic studies are performed on amylose derivatized with tris-(3,5-dimethylphenyl carbamate) stationary phase for the chiral separation of coumarin-based anticoagulants. Polar-organic eluents that contain acetonitrile as bulk solvent with modifiers such as methanol, i-butanol, t-butanol, and tetrahydrofuran are used in the study. Temperature is varied from 5 to 45 degrees C at constant pressure of 1500psi. In general, both retention and enantioselectivity decrease as the temperature increases and as hydrogen bond donating ability of the modifiers increases. The van't Hoff plots are found to show both linear and non-linear behavior. The non-linear plots are believed to be the result of conformational changes in the derivatized amylose phase and are observed around room temperature. The retention behavior in acetonitrile mobile phase provides a linear enthalpy-entropy compensation plot, indicating that all coumarins may have a similar retention mechanism. In contrast, enthalpy-entropy compensation is not observed for warfarin and coumatetralyl enantiomers when separated with different organic modifiers in the mobile phase. The kinetic data indicate that the rate of sorption is always greater than the rate of desorption. An increase in the concentration of alcohol modifiers causes an increase in the desorption rate constant. In contrast, an increase in the concentration of tetrahydrofuran causes a decrease in the desorption rate constant. This effect is most significant for the second eluted enantiomer of coumatetralyl, for which the desorption rate is 36 times slower than the first eluted enantiomer.

Effect of gas chromatography temperature program on the association and discrimination of diesel samples.

Five diesel samples were analyzed by gas chromatography-mass spectrometry (GC-MS) using six GC temperature programs, aiming to investigate the effect of temperature program on association and discrimination of the samples. Temperature programs varied by ramp rate and incorporated one- or two-step temperature ramps. Pearson product moment correlation coefficients and principal components analysis were used to evaluate differences in discrimination among the diesel samples afforded by each temperature program, based on the total ion chromatogram (TIC) and selected extracted ion profiles (EIPs). Association of diesel replicates and discrimination among samples based on the TIC and aromatic EIP were similar for all temperature programs based on scores plots. The alkane EIP was not useful in discriminating samples regardless of temperature program, because of similar alkane content of the diesel samples. The association and discrimination of diesel samples was largely unaffected by temperature programs that incorporated one- or two-step temperature ramps.

Association and discrimination of diesel fuels using chemometric procedures.

Five neat diesel samples were analyzed by gas chromatography-mass spectrometry and total ion chromatograms as well as extracted ion profiles of the alkane and aromatic compound classes were generated. A retention time alignment algorithm was employed to align chromatograms prior to peak area normalization. Pearson product moment correlation coefficients and principal components analysis were then employed to investigate association and discrimination among the diesel samples. The same procedures were also used to investigate the association of a diesel residue to its neat counterpart. Current limitations in the retention time alignment algorithm and the subsequent effect on the association and discrimination of the diesel samples are discussed. An understanding of these issues is crucial to ensure the accuracy of data interpretation based on such chemometric procedures.

Theoretical evaluation of methods for extracting retention factors and kinetic rate constants in liquid chromatography.

A three-dimensional stochastic simulation is used to provide a detailed understanding of mass transfer processes in liquid chromatography. In this simulation, the migration of individual molecules is established through diffusion and laminar convection within the mobile phase. The molecules interact with the stationary phase by a partition (absorption) mechanism. For these studies, the column length, linear velocity, stationary-phase diffusion coefficient, interfacial mass transfer coefficient, and equilibrium constant are varied in a system with a homogeneous surface. Heterogeneous surfaces are also investigated by having multiple types of interaction sites that are equally or unequally distributed. For each simulation, the molecular distribution is examined and characterized at specified times or column lengths. Five individual methods are then applied to extract the thermodynamic and kinetic information for transport between the mobile and stationary phases. In the first method, all of the molecules are initially distributed in the mobile phase and the fraction remaining is monitored as a function of time. These simulation data are fit to a single exponential decay by nonlinear regression to determine the "true" retention factors and rate constants. The other methods rely on evaluating the shape of the zone profiles along the column. The statistical moments of the profiles are used to calculate the mean and the variance, which are related to the retention factors and the rate constants, respectively. The profiles are also fit to the exponentially modified Gaussian equation, the Giddings equation, and the Thomas equation. The fitting parameters from these equations are then used to calculate the retention factors and rate constants. Comparisons of the accuracy relative to the "true" retention factors and "true" rate constants, as well as the advantages and limitations of each method are discussed.

Luminescence-based methods for sensing and detection of explosives.

The detection of explosives and related compounds is important in both forensic and environmental applications. Luminescence-based methods have been widely used for detecting explosives and their degradation products in complex matrices. Direct detection methods utilize the inherent fluorescence of explosive molecules or the luminescence generated from chemical reactions. Direct detection methods include high-energy excitation techniques such as gamma-ray and x-ray fluorescence, detection of decomposition products by fluorescence or chemiluminescence, and detection following reduction to amines or another reaction to produce fluorescent products from the explosive. Indirect detection methods utilize the interference caused by the presence of explosive compounds with traditional processes of fluorescence and fluorescence quenching. Indirect detection methods include quenching of solution-phase, immobilized, and solid-state fluorophores, displacement of fluorophores, fluorescence immunoassay, and reactions that produce fluorescent products other than the explosive. A comprehensive review of these methods is presented.

Investigation of common fluorophores for the detection of nitrated explosives by fluorescence quenching.

Previous studies have indicated that nitrated explosives may be detected by fluorescence quenching of pyrene and related compounds. The use of pyrene, however, invokes numerous health and waste disposal hazards. In the present study, ten safer fluorophores are identified for quenching detection of target nitrated compounds. Initially, Stern-Volmer constants are measured for each fluorophore with nitrobenzene and 4-nitrotoluene to determine the sensitivity of the quenching interaction. For quenching constants greater than 50 M(-1), sensitivity and selectivity are investigated further using an extended set of target quenchers. Nitromethane, nitrobenzene, 4-nitrotoluene, and 2,6-dinitrotoluene are chosen to represent nitrated explosives and their degradation products; aniline, benzoic acid, and phenol are chosen to represent potential interfering compounds. Among the fluorophores investigated, purpurin, malachite green, and phenol red demonstrate the greatest sensitivity and selectivity for nitrated compounds. Correlation of the quenching rate constants for these fluorophores to Rehm-Weller theory suggests an electron-transfer quenching mechanism. As a result of the large quenching constants, purpurin, malachite green, and phenol red are the most promising for future detection of nitrated explosives via fluorescence quenching.