Transfer of Metal(loid)s from Soil to Leaves and Trunk Xylem Sap of Medicinal Plants and Possible Health Risk Assessment.

The objective of the present study was to investigate metal(loid)s in soils, in the trunk xylem sap and in the leaves of the Dipteryx alata plant located near the highway with high vehicle traffic in agricultural regions and near landfills, and to assess the transfer of metal(loid)s from soil to plant and possible health risk assessment. Trunk xylem sap, leaves and soil samples were collected at three sites near the highway. The analysis of trace elements was carried out using inductively coupled plasma optical emission spectroscopy (ICP OES). In the three soil sampling sites far from the highway edge, 15 elements were quantified. The concentrations of elements in the soil presented in greater proportions in the distance of 5 m in relation to 20 and 35 m. The metal(loid)s content in the study soil was higher than in other countries. The concentrations of Al, Cu, Fe, Mg, Mn, P, Se and Zn in the xylem sap were much higher than the leaves. The values of transfer factor of P, Mg and Mn from soil to the xylem sap and transfer factor of P from soil to leaf were greater than 1, indicating that the specie have a significant phytoremediation and phytoextraction potential. This plant has a tendency to accumulate As, Cd and Cr in its leaf tissues. The chronic hazard index (HI) values recorded in this study were above 1 for adults and adolescents. It is concluded that the soil, the trunk xylem sap and leaves of this plant are contaminated by heavy metals. Ingestion of the trunk xylem sap of this plant can cause toxicity in humans if ingested in large quantities and in the long term; therefore, its consumption should be avoided.

New consensus multivariate models based on PLS and ANN studies of sigma-1 receptor antagonists.

The treatment of neuropathic pain is very complex and there are few drugs approved for this purpose. Among the studied compounds in the literature, sigma-1 receptor antagonists have shown to be promising. In order to develop QSAR studies applied to the compounds of 1-arylpyrazole derivatives, multivariate analyses have been performed in this work using partial least square (PLS) and artificial neural network (ANN) methods. A PLS model has been obtained and validated with 45 compounds in the training set and 13 compounds in the test set (r2training = 0.761, q2 = 0.656, r2test = 0.746, MSEtest = 0.132 and MAEtest = 0.258). Additionally, multi-layer perceptron ANNs (MLP-ANNs) were employed in order to propose non-linear models trained by gradient descent with momentum backpropagation function. Based on MSEtest values, the best MLP-ANN models were combined in a MLP-ANN consensus model (MLP-ANN-CM; r2test = 0.824, MSEtest = 0.088 and MAEtest = 0.197). In the end, a general consensus model (GCM) has been obtained using PLS and MLP-ANN-CM models (r2test = 0.811, MSEtest = 0.100 and MAEtest = 0.218). Besides, the selected descriptors (GGI6, Mor23m, SRW06, H7m, MLOGP, and µ) revealed important features that should be considered when one is planning new compounds of the 1-arylpyrazole class. The multivariate models proposed in this work are definitely a powerful tool for the rational drug design of new compounds for neuropathic pain treatment. Graphical abstract Main scaffold of the 1-arylpyrazole derivatives and the selected descriptors.

Pattern recognition techniques applied to the study of leishmanial glyceraldehyde-3-phosphate dehydrogenase inhibition.

Chemometric pattern recognition techniques were employed in order to obtain Structure-Activity Relationship (SAR) models relating the structures of a series of adenosine compounds to the affinity for glyceraldehyde 3-phosphate dehydrogenase of Leishmania mexicana (LmGAPDH). A training set of 49 compounds was used to build the models and the best ones were obtained with one geometrical and four electronic descriptors. Classification models were externally validated by predictions for a test set of 14 compounds not used in the model building process. Results of good quality were obtained, as verified by the correct classifications achieved. Moreover, the results are in good agreement with previous SAR studies on these molecules, to such an extent that we can suggest that these findings may help in further investigations on ligands of LmGAPDH capable of improving treatment of leishmaniasis.