A new approach to amino acid racemization in enamel: testing of a less destructive sampling methodology

Aspartic acid racemization has been found to be an accurate measure of age at death for recent forensic material. This paper examines the practicality of using acid etching of the tooth surface to extract amino acids from the enamel for racemization analysis. By serial etching of the tooth and contamination of the teeth with bovine serum albumin prior to etching, the ability of etching to remove contamination was assessed. The destructiveness of the method was visualized and quantified using micro-computed tomography (micro-CT). By bleaching the teeth and by deeper etching it was possible to obtain more consistent values. While etching had little effect on the enamel at the macroscale, it did have an impact at the microscale. The quantities of enamel removed varied depending upon the tooth morphology, but were not large. Acid etching of enamel thus appears to be a promising new method for extracting proteins for amino acid racemization age estimation noninvasively.     

Further investigation of findings reported for the Minnesota sex offender screening tool-revised

Among a number of widely used risk assessment instruments with adult sexual offenders, the Minnesota Sex Offender Screening Tool-Revised (MnSOST-R) has been subject to relatively few evaluation studies. Only two independent research groups have published replication studies in the peer-reviewed literature with data not provided by the MnSOST-R's developers, and the results regarding the accuracy of predicting sexual recidivism have been mixed. In this article, important differences between the Barbaree et al. and Langton et al. studies are presented. Analyses reported for the various subsets comprising these two samples indicate that coding discrepancies in the Barbaree et al. study account for the different findings, with a moderate level of predictive accuracy using the Receiver Operating Characteristic curve ultimately found for the MnSOST-R in both data sets.