A call for mtDNA data quality control in forensic science

There is increasing evidence that many of the mitochondrial DNA (mtDNA) databases published in the fields of forensic science and molecular anthropology are flawed. An a posteriori phylogenetic analysis of the sequences could help to eliminate most of the errors and thus greatly improve data quality. However, previously published caveats and recommendations along these lines were not yet picked up by all researchers. Here we call for stringent quality control of mtDNA data by haplogroup-directed database comparisons. We take some problematic databases of East Asian mtDNAs, published in the Journal of Forensic Sciences and Forensic Science International, as examples to demonstrate the process of pinpointing obvious errors. Our results show that data sets are not only notoriously plagued by base shifts and artificial recombination but also by lab-specific phantom mutations, especially in the second hypervariable region (HVR-II). (C) 2003 Elsevier Ireland Ltd. All rights reserved.

Fingerprinting quality control of Qianghuo by high-performance liquid chromatography-photodiode array detection

A novel, simple and accurate fingerprint method was developed using high-performance liquid chromatography-photodiode array detection (HPLC-DAD) for the quality control of Qianghuo, a Tibetan folk and Chinese herbal medicine used as a diaphoretic, an antifebrile and an anodyne. For the first time, the feasibility and advantages of employing chromatographic fingerprint were investigated and demonstrated for the evaluation of Qianghuo by systematically comparing chromatograms of aqueous extracts with the professional analytical software recommended by State Food and Drug Administration (SFDA). Our results revealed that the chromatographic fingerprint combing similarity evaluation could efficiently identify and distinguish raw herbs of Qianghno from different sources and different species. The effects on Notopterygium forbesii Boiss (Apiaceae) chromatographic fingerprints resulted from collecting locations, harvesting time were also examined. (c) 2006 Elsevier lrelanc Ltd. All rights reserved.

Spatial distribution of soil heavy metal pollution estimated by different interpolation methods: Accuracy and uncertainty analysis

Mapping the spatial distribution of contaminants in soils is the basis of pollution evaluation and risk control. Interpolation methods are extensively applied in the mapping processes to estimate the heavy metal concentrations at unsampled sites. The performances of interpolation methods (inverse distance weighting, local polynomial, ordinary kriging and radial basis functions) were assessed and compared using the root mean square error for cross validation. The results indicated that all interpolation methods provided a high prediction accuracy of the mean concentration of soil heavy metals. However, the classic method based on percentages of polluted samples, gave a pollution area 23.54-41.92% larger than that estimated by interpolation methods. The difference in contaminated area estimation among the four methods reached 6.14%. According to the interpolation results, the spatial uncertainty of polluted areas was mainly located in three types of region: (a) the local maxima concentration region surrounded by low concentration (clean) sites, (b) the local minima concentration region surrounded with highly polluted samples; and (c) the boundaries of the contaminated areas. (C) 2010 Elsevier Ltd. All rights reserved.