Self-Organising Maps and Correlation Analysis as a Tool to Explore Patterns in Excitation-Emission Matrix Data Sets and to Discriminate Dissolved Organic Matter Fluorescence Components

Dissolved organic matter (DOM) is a complex mixture of organic compounds, ubiquitous in marine and freshwater systems. Fluorescence spectroscopy, by means of Excitation-Emission Matrices (EEM), has become an indispensable tool to study DOM sources, transport and fate in aquatic ecosystems. However the statistical treatment of large and heterogeneous EEM data sets still represents an important challenge for biogeochemists. Recently, Self-Organising Maps (SOM) has been proposed as a tool to explore patterns in large EEM data sets. SOM is a pattern recognition method which clusterizes and reduces the dimensionality of input EEMs without relying on any assumption about the data structure. In this paper, we show how SOM, coupled with a correlation analysis of the component planes, can be used both to explore patterns among samples, as well as to identify individual fluorescence components. We analysed a large and heterogeneous EEM data set, including samples from a river catchment collected under a range of hydrological conditions, along a 60-km downstream gradient, and under the influence of different degrees of anthropogenic impact. According to our results, chemical industry effluents appeared to have unique and distinctive spectral characteristics. On the other hand, river samples collected under flash flood conditions showed homogeneous EEM shapes. The correlation analysis of the component planes suggested the presence of four fluorescence components, consistent with DOM components previously described in the literature. A remarkable strength of this methodology was that outlier samples appeared naturally integrated in the analysis. We conclude that SOM coupled with a correlation analysis procedure is a promising tool for studying large and heterogeneous EEM data sets.

pH Sensitive surfactants from lysine: assessment of their cytotoxicity and environmental behavior

The toxicity and environmental behavior of new pH-sensitive surfactants from lysine are presented. Three different chemical structures are studied: surfactants with one amino acid and one alkyl chain, surfactants with two amino acids on the polar head and one alkyl chain, and gemini surfactants. The pH sensitivity of these compounds can be tuned by modifying their chemical structures. Cytotoxicity has been evaluated using erythrocytes and fibroblast cells. The toxic effects against these cells depend on the hydrophobicity of the molecules as well as their cationic charge density. The effect of hydrophobicity and cationic charge density on toxicity is different for each type of cells. For erythrocytes, the toxicity increases as hydrophobicity and charge density increases. Nevertheless, for fibroblasts cationic charge density affects cytotoxicity in the opposite way: the higher charge density, the lower the toxicity. The effect of the pH on hemolysis has been evaluated in detail. The aquatic toxicity was established using Daphnia magna. All surfactants yielded EC50 values considerably higher than that reported for cationic surfactants based on quaternary ammonium groups. Finally, their biodegradability was evaluated using the CO2 headspace test (ISO 14593). These lysine derivatives showed high levels of biodegradation under aerobic conditions and can be classified as"readily biodegradable compounds".