A modification of the microplate method for reverse ABO typing of bloodstains and additional validation studies

The results of additional validation studies of a sensitive microplate hemagglutination assay for ABO reverse grouping of bloodstains are presented. The results of the validation study demonstrate the reliability of the microplate assay for use in routine serological casework. Based on these studies, the microplate assay has now replaced the Lattes crust test for ABO reverse grouping of bloodstains in the FBI Laboratory.     

Acidic and neutral drugs screen in blood with quantitation using microbore high-performance liquid chromatography–diode array detection and capillary gas chromatography–flame ionization detection

Blood previously acidified with aqueous saturated ammonium chloride solution was extracted with ethyl acetate. The dried extract was subjected to acetonitrile–hexane partition. The acetonitrile portion was analysed for the presence of acidic and neutral drugs by HPLC–DAD (200 mm×2.1 mm I.D. microbore ODS-Hypersil column) and GC–FID (25 m narrow-bore×0.25 mm I.D. HP-5 column with 0.33 μm film thickness). The protocol was found to be suitable for both clinical toxicology (including emergency toxicology) and postmortem toxicology. At least 66 drugs of interest were unequivocally identified by RRTs (HPLC) and UV spectra (DAD) match while another 12 were unequivocally identified by double RRTs match (HPLC and GC). Quantitation was facilitated by incorporating calibration blood standards in each assay batch. The five drugs most commonly encountered in clinical blood specimens (1150 cases) were: paracetamol (47.4% of the cases); chlormezanone (6.6%), theophylline (1.74%), naproxen (1.65%) and mefenamic acid (1.56%). The following drugs were detected in toxicologically significant quantities in postmortem blood specimens (245 cases): phenobarbitone (1.22% of the cases), naproxen (0.82%), chlormezanone (0.82%), theophylline (0.82%), carbamazepine (0.41%) and paracetamol (0.41%).     

Understanding Recreation and Sport as a Rehabilitative Tool Within Juvenile Justice Programs

This article discusses relevant literature on the potential benefits of sport, recreation, and leisure, and how these benefits relate to rehabilitation of juveniles. Many professionals involved in juvenile rehabilitation believe sport and recreation are beneficial adjuncts to treatment programming; however, it can be difficult to structure sport and recreation in ways that directly correspond to treatment goals. The purpose of this article is to provide insights for professionals working with juveniles on how sport and recreation programming can be an effective means of helping to achieve rehabilitation goals. Attention is given to approaches, particularly the Teaching Games for Understanding model (Bunker & Thorpe, 1982), which can be used to effectively link recreation and sport to the rehabilitation process.     

Evolving Market Efficiency with an Application to Some Bulgarian Shares

With new technically advanced methods and computers at our disposal, the efficient market hypothesis is once again being debated. At the same time, we are witnessing an unprecedented growth in both existing and new financial markets. These new markets are often in economies which have just recently embraced free market economics; we term these stock markets infant markets. Such stock markets are obviously not efficient in allocating the supply of savings to productive capital. We do not test whether or not these infant markets are informationally efficient, but instead examine whether and how they are becoming more efficient. We propose modelling the excess returns of individual securities using a multi-factor model with time-varying coefficients and generalised auto-regressive conditional heteroskedastic (GARCH) errors. If the markets are becoming more informationally efficient or the agents are learning, we would expect this to manifest itself as the time-varying coefficients becoming more stable as time increases. We test our model using data on four Bulgarian shares. First, we estimate an AR(2) model and a GARCH-M(1,1) model for the shares. Then, we estimated our AR(2) model with time varying coefficients and GARCH type errors. We find varying levels of efficiency and varying speeds of movement towards efficiency within our sample of four shares.