Gary Golding

Public Health Risks from Heavy Metals and Metalloids Present in Traditional Chinese Medicines

Out of 247 traditional Chinese medicines (TCM) investigated, a proportion were contaminated with arsenic (5–15%), lead (∼5%), and mercury (∼65%). Some preparations exceeded the tolerable daily intake (TDI) for males and females for arsenic (4 and 5 products, respectively), lead (1 and 2 products), and mercury (5 and 7 products). These exceedances were as high as 2760-fold, which posed a potential danger to public health. As many users are known to self-prescribe, there is a substantial risk of poisoning from the consumption of these contaminated TCM.

Rapid Quantification of Methamphetamine: Using Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR) and Chemometrics

In Australia and increasingly worldwide, methamphetamine is one of the most commonly seized drugs analysed by forensic chemists. The current well-established GC/MS methods used to identify and quantify methamphetamine are lengthy, expensive processes, but often rapid analysis is requested by undercover police leading to an interest in developing this new analytical technique. Ninety six illicit drug seizures containing methamphetamine (0.1%–78.6%) were analysed using Fourier Transform Infrared Spectroscopy with an Attenuated Total Reflectance attachment and Chemometrics. Two Partial Least Squares models were developed, one using the principal Infrared Spectroscopy peaks of methamphetamine and the other a Hierarchical Partial Least Squares model. Both of these models were refined to choose the variables that were most closely associated with the methamphetamine % vector. Both of the models were excellent, with the principal peaks in the Partial Least Squares model having Root Mean Square Error of Prediction 3.8, R2 0.9779 and lower limit of quantification 7% methamphetamine. The Hierarchical Partial Least Squares model had lower limit of quantification 0.3% methamphetamine, Root Mean Square Error of Prediction 5.2 and R2 0.9637. Such models offer rapid and effective methods for screening illicit drug samples to determine the percentage of methamphetamine they contain.