Evaluation of a characterization method of Egyptian human mummy balms by chemometric treatments of infrared data

Rethinking the Process of Animal Mummification in Ancient Egypt: Molecular Characterization of Embalming Material and the Use of Brassicaceae Seed Oil in the Mummification of Gazelle Mummies from Kom Mereh, Egypt

The study of animal mummification in ancient Egypt has recently received increasing attention from a number of modern scholars given the fact that this part of ancient Egyptian funerary and religious history is a practice yet to be fully understood. In this study, nine samples of embalming matter were extracted from six gazelle mummies from the archaeological site of Kom Mereh (modern village of Komir), dated to the Roman period of dominance in ancient Egypt. All samples were analyzed for the presence of inorganic and organic matter applying a multi-analytical approach based on Fourier transform infrared spectroscopy (FT-IR) and gas chromatography–mass spectrometry (GC-MS). Furthermore, in order to identify more specific compounds such as bitumen and beeswax in studied balms, each sample was subjected to a solid phase extraction (SPE) and saponification separation process, respectively. The results of this study revealed that the majority of the analyzed embalming substances sampled from six gazelle mummies from Kom Mereh were complex mixtures of plant oils, animal fats, conifer resin, and beeswax. In this regard, this study was able to report a practice until now unmentioned in the scientific literature, namely, the use of cruciferous oil, derived from seeds of Brassicaceae plants, in animal mummification.

An innovative spectroscopic approach for qualitative and quantitative evaluation of Mb-CO from myoglobin carbonylation reaction through chemometrics methods

In this work, an innovative approach using K-means and multivariate curve resolution-purity based algorithm (MCR-Purity) for the evaluation and quantification of carboxymyoglobin (Mb-CO) formation from Deoxy-Myoglobin (Deoxy-Mb) was presented. Through a multilevel multifactor experimental design, samples with different concentrations of Mb-CO were created. The UV-Vis spectra of these samples were submitted to K-means analysis, finding 3 clusters. The mean spectra of the clusters were extracted and it was possible to detect 2 totally differentiable groups through peaks 423 and 434 nm, which are wavelengths related to the Mb-CO and Deoxy-Mb components, respectively. The spectral data were subjected to MCR-Purity analysis. The MCR-Purity result successfully described the analyzed reaction, explaining more than 99.9% of the variance (R²) with a LOF of 1.43%. Then, a predictive model of MbCO was created through the linear relationship between MCR-Purity contributions and known concentrations of MbCO. The performance parameters of the created predictive model were R²CV = 0.98, RMSECV = 0.58 and RPDcv = 7.8 for the training set, and R²P = 0.98, RMSEP = 0.7 and RPDp = 6.8 for the test set. Thus, the predictive model presented an excellent performance considering that the Mb-CO variation is comprised between 0 and 21 µM. Therefore, these results demonstrate that the application of the proposed strategy to the analysis of spectral data presenting overlapping bands is feasible and robust.