Innovative Approaches for Estimating the Levels of Tobacco-Specific Nitrosamines in Cured Tobacco Samples

Dry tobacco leaves: an in vivo and in silico approach to the consequences of occupational exposure

Exposure of tobacco workers handling dried tobacco leaves has been linked to an increased risk of toxicity and respiratory illness due to the presence of nicotine and other chemicals. This study aimed to evaluate the DNA damage caused by the exposure of tobacco growers during the dry leaf classification process and the relation to cellular mechanisms. A total of 86 individuals participated in the study, divided into a group exposed to dry tobacco (n = 44) and a control group (n = 42). Genotoxicity was evaluated using the alkaline comet assay and lymphocyte micronucleus (MN) assay (CBMN-Cyt), and measurement of telomere length. The levels of oxidative and nitrosative stress were evaluated through the formation of thiobarbituric acid reactive species, and nitric oxide levels, respectively. The inorganic elements were measured in the samples using particle-induced X-ray emission method. The combination of variables was demonstrated through principal component analysis and the interactions were expanded through systems biology. Comet assay, MN, death cells, thiobarbituric acid reactive species, and nitrosative stress showed a significant increase for all exposed groups in relation to the control. Telomere length showed a significant decrease for exposed women and total exposed group in relation to men and control groups, respectively. Bromine (Br) and rubidium (Rb) in the exposed group presented higher levels than control groups. Correlations between nitrate and apoptosis; Br and MN and necrosis; and Rb and telomeres; besides age and DNA damage and death cells were observed. The systems biology analysis demonstrated that tobacco elements can increase the nuclear translocation of NFKB dimers inducing HDAC2 expression, which, associated with BRCA1 protein, can potentially repress transcription of genes that promote DNA repair. Dry tobacco workers exposed to dry leaves and their different agents showed DNA damage by different mechanisms, including redox imbalance.

Rapid evaporative ionization mass spectrometry (REIMS) combined with chemometrics for real-time beer analysis

The beer industry plays an important role in the economy since this is the third most consumed beverage worldwide. Efficient analytical methods must be developed to ensure the quality of the product. Rapid evaporative ionization mass spectrometry (REIMS) can provide molecular-level information, while enabling fast analysis. REIMS requires minimal sample preparation and it is ideal for the analysis of homogeneous liquid samples, such as beers, within only five seconds. In this article, 32 different beers were analyzed by REIMS in positive and negative ionization modes using a hybrid quadrupole time-of-flight mass spectrometer. The positive and negative MS spectrum blocks were augmented for data fusion. A predictive model by partial least squares discriminant analysis (PLS-DA) was used to discriminate the samples (i) by their brands and (ii) by the beer type (Premium and Standard American lagers). The results showed that REIMS provided a rich fingerprint of beers, which was successfully used to discriminate the brands and types with 96.9% and 97.9% accuracy, respectively. We believe that this proof-of-concept has great potential to be applied on a larger scale for industrial purposes due to its high-throughput.

Enter the Matrix: Improving the Interpretation of Separations Data Using Chemometrics in Analytical Investigations

This article describes a compendium of chemometrics applications in separation science to demonstrate the importance and synergy of data handling. We review the main points that must be raised when using multivariate techniques and list references for further reading. With examples in food science, the case studies comprise of applications of pattern recognition (principal component analysis, PCA), regression (partial least squares, PLS), and classification methods (soft independent modelling of class analogies, SIMCA).