Quantitative analysis of multiple illicit drugs in preserved oral fluid by solid-phase extraction and liquid chromatography–tandem mass spectrometry

We present a validated method for the simultaneous analysis of basic drugs which comprises a sample clean-up step, using mixed-mode solid-phase extraction (SPE), followed by LC–MS/MS analysis. Deuterated analogues for all of the analytes of interest were used for quantitation. The applied HPLC gradient ensured the elution of all the drugs examined within 14 min and produced chromatographic peaks of acceptable symmetry. Selectivity of the method was achieved by a combination of retention time, and two precursor-product ion transitions for the non-deuterated analogues. Oral fluid was collected with the Intercept^®, a FDA approved sampling device that is used on a large scale in the US for workplace drug testing. However, this collection system contains some ingredients (stabilizers and preservatives) that can cause substantial interferences, e.g. ion suppression or enhancement during LC–MS/MS analysis, in the absence of suitable sample pre-treatment. The use of the SPE was demonstrated to be highly effective and led to significant decreases in the interferences. Extraction was found to be both reproducible and efficient with recoveries >76% for all of the analytes. Furthermore, the processed samples were demonstrated to be stable for 48 h, except for cocaine and benzoylecgonine, where a slight negative trend was observed, but did not compromise the quantitation. In all cases the method was linear over the range investigated (2–200 μg/L) with an excellent intra-assay and inter-assay precision (coefficients of variation <10% in most cases) for QC samples spiked at a concentration of 4, 12 and 100 μg/L. Limits of quantitation were estimated to be at 2 μg/L with limits of detection ranging from 0.2 to 0.5 μg/L, which meets the requirements of SAMHSA for oral fluid testing in the workplace. The method was subsequently applied to the analysis of Intercept^® samples collected at the roadside by the police, and to determine MDMA and MDA levels in oral fluid samples from a controlled study.     

Comparing Experimental and Matching Methods Using a Large-Scale Voter Mobilization Experiment

Alan S. Gerber and Donald P. Green Yale University, Institution for Social and Policy Studies, P.O. Box 208209, 77 Prospect Street, New Haven, CT 06520 e-mail: kevin.arceneaux{at}temple.edu (corresponding author) e-mail: alan.gerber{at}yale.edu e-mail: donald.green{at}yale.edu In the social sciences, randomized experimentation is the optimalresearch design for establishing causation. However, for a numberof practical reasons, researchers are sometimes unable to conductexperiments and must rely on observational data. In an effortto develop estimators that can approximate experimental resultsusing observational data, scholars have given increasing attentionto matching. In this article, we test the performance of matchingby gauging the success with which matching approximates experimentalresults. The voter mobilization experiment presented here comprisesa large number of observations (60,000 randomly assigned tothe treatment group and nearly two million assigned to the controlgroup) and a rich set of covariates. This study is analyzedin two ways. The first method, instrumental variables estimation,takes advantage of random assignment in order to produce consistentestimates. The second method, matching estimation, ignores randomassignment and analyzes the data as though they were nonexperimental.Matching is found to produce biased results in this applicationbecause even a rich set of covariates is insufficient to controlfor preexisting differences between the treatment and controlgroup. Matching, in fact, produces estimates that are no moreaccurate than those generated by ordinary least squares regression.The experimental findings show that brief paid get-out-the-votephone calls do not increase turnout, while matching and regressionshow a large and significant effect.     

Cross-validation of the risk matrix 2000 sexual and violent scales

The predictive accuracy of the newly developed actuarial risk measures Risk Matrix 2000 Sexual/Violence (RMS, RMV) were cross validated and compared with two risk assessment measures (SVR-20 and Static-99) in a sample of sexual (n= 85) and nonsex violent (n= 46) offenders. The sexual offense reconviction rate for the sex offender group was 18% at 10 years follow-up, compared with 2% for the violent offenders. Survival analyses revealed the violent offenders were reconvicted at twice the rate compared to sexual offenders. The RMV significantly predicted violent recidivism in the sex and combined sex/violent offender groups. Although the RMS obtained marginal accuracy in predicting sexual reconviction in the sex offender group, none of the scales significantly predicted sexual reconviction. An item analysis revealed four factors not included in the risk scales that were significantly correlated with sexual and violent reconviction. Combining these factors with Static-99, RMV, and RMS increased the accuracy in predicting sexual reconviction.     

Characterization of human control region sequences of the African American SWGDAM forensic mtDNA data set

The scientific working group on DNA analysis Methods (SWGDAM) mitochondrial DNA (mtDNA) population data set is used to infer the relative rarity of control region mtDNA profiles obtained from evidence samples and of profiles used for identification of missing persons. In this study, the African American haplogroup patterns in the SWGDAM data were analyzed in a phylogenetic context to determine relevant single nucleotide polymorphisms (SNPs) and to describe haplogroup distributions for Africans observed in these data sets. Over 200 SNPs (n=217) were observed in the African American data set (n=1148). These SNPs ranged from having 1-39 changes in the phylogenetic tree, with sites 152 and 16519 being the most variable. On average there were 5.8 changes for a character on the tree. The most variable sites (with 19 or more changes each) observed included 16093, 16129, 16189, 16311, 16362, 16519, 146, 150, 152, 189, and 195. These rapidly changing sites are consistent with other published analyses. Only 34 SNPs are needed to identify all clusters containing 10 or more individuals in the African American data set. The results show that the African American SWGDAM mtDNA data set contains variation consistent with that described in continental African populations. Thirteen of the 18 haplogroups previously observed in African populations were observed and include: L1a, L1b, L1c, L2a, L2b, L2c, L3b, L3d, L3e1, L3e2, L3e3, L3e4 and L3f. Haplogroup L2a is the most commonly observed cluster (18.8%) in the African American data set. The next most common haplogroups in the African American data set include the clusters L1c (11.0%), L1b (9.1%), L3e2 (9.0%) and L3b (8.1%). Approximately 8% of the haplogroups observed within African Americans were common in European Caucasians or East Asians; these were H (n=32), J (n=4), K (n=5), T (n=2), U5 (n=6), U6 (n=9 also known from North Africa), A (n=12), B (n=7), C (n=4), and M (n=16), respectively. The European Caucasian and East Asian haplogroups are expected due to admixture between individuals with recent ancestry in Western Eurasia and sub-Saharan Africa. The genetic characterization of these relevant data sets is fully consistent with other published mtDNA genetic variation. The sequence diversity observed in this data set makes it a valuable tool for forensic applications.