The evaluation of the spatial and temporal distribution of pollutants is a crucial issue to assess the anthropogenic burden on the environment. Numerous chemometric approaches are available for data exploration and they have been applied for environmental health assessment purposes. Among the unsupervised methods, Self-Organizing Map (SOM) is an artificial neural network able to handle non-linear problems that can be used for exploratory data analysis, pattern recognition, and variable relationship assessment. Much more interpretation ability is gained when the SOM-based model is merged with clustering algorithms. This review comprises: (i) a description of the algorithm operation principle with a focus on the key parameters used for the SOM initialization; (ii) a description of the SOM output features and how they can be used for data mining; (iii) a list of available software tools for performing calculations; (iv) an overview of the SOM application for obtaining spatial and temporal pollution patterns in the environmental compartments with focus on model training and result visualization; (v) advice on reporting SOM model details in a paper to attain comparability and reproducibility among published papers as well as advice for extracting valuable information from the model results is presented.

Seven derivatives of plant-derived hydroxybenzoic acid (HBA)—including 2,3-dihydroxybenzoic (2,3-DHB, pyrocatechuic), 2,4-dihydroxybenzoic (2,4-DHB, β-resorcylic), 2,5-dihydroxybenzoic (2,5-DHB, gentisic), 2,6-dihydroxybenzoic (2,6-DHB, γ-resorcylic acid), 3,4-dihydroxybenzoic (3,4-DHB, protocatechuic), 3,5-dihydroxybenzoic (3,5-DHB, α-resorcylic), and 3,4,5-trihydroxybenzoic (3,4,5-THB, gallic) acids—were studied for their structural and biological properties. Anti-/pro-oxidant properties were evaluated by using DPPH^• (2,2-diphenyl-1-picrylhydrazyl), ABTS^•+ (2,2-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid), FRAP (ferric-reducing antioxidant power), CUPRAC (cupric-reducing antioxidant power), and Trolox oxidation assays. Lipophilicity was estimated by means of experimental (HPLC) and theoretical methods. The antimicrobial activity against Escherichia coli (E. coli), Pseudomonas aeruginosa (P. aeruginosa), Staphylococcus aureus (S. aureus), Bacillus subtilis (B. subtilis), Salmonella enteritidis (S. enteritidis), and Candida albicans (C. albicans) was studied. The cytotoxicity of HBAs in MCF-7 and MDA-MB-231 cell lines was estimated. Moreover, the structure of HBAs was studied by means of experimental (FTIR, ¹H, and ¹³C NMR) and quantum chemical DFT methods (the NBO and CHelpG charges, electrostatic potential maps, and electronic parameters based on the energy of HOMO and LUMO orbitals). The aromaticity of HBA was studied based on the calculated geometric and magnetic aromaticity indices (HOMA, Aj, BAC, I6, NICS). The biological activity of hydroxybenzoic acids was discussed in relation to their geometry, the electronic charge distribution in their molecules, their lipophilicity, and their acidity. Principal component analysis (PCA) was used in the statistical analysis of the obtained data and the discussion of the dependency between the structure and activity (SAR: structure–activity relationship) of HBAs. This work provides valuable information on the potential application of hydroxybenzoic acids as bioactive components in dietary supplements, functional foods, or even drugs.

High-performance ion chromatography and inductively coupled plasma–mass spectrometry methods have been applied to estimate the content of Cd, Co, Cu, Fe, Mn, Zn, and Ni in whole blood, plasma, and urine of obese and nonobese children. The study was conducted on a group of 81 Polish children of age 6–17 years (37 males, 44 females). Obese children were defined as those with body mass index (BMI) >95th percentile in each age–gender-specific group. Statistical testing was done by the use of nonparametric tests (Kruskal–Wallis's and Mann–Whitney's U) and Spearman's correlation coefficient. Significant correlations appeared for control group in plasma (Mn–Cd, Ni–Co), urine (Cu–Co), and blood (Fe–Cu), while for obese patients in plasma (Cd–Mn, Ni–Cu, Ni–Zn) and urine (Fe–Cd, Co–Mn). Sex criteria did not influence correlations between metals' content in plasma and urine of obese patients. Metals' abundance was correlated in non-corresponding combinations of body fluids. Rare significant differences between content of metals according to sex and the type of body fluids were discovered: Zn in plasma from obese patients of both sexes, and Zn, Co, and Mn in blood, Mn in plasma from healthy subjects. Negative correlations between BMI and Zn in blood, Cu in plasma, and Fe in urine were discovered for girls (control group). Positive correlation between Co content in plasma and BMI was discovered for obese boys. The changes in metals' content in body fluids may be indicators of obesity. Content of zinc, copper, and cobalt should be monitored in children with elevated BMI to avoid deficiency problems.