RESUMO
The reliability of Araucaria heterophylla needles as a biomonitor was evaluated by analyzing the concentration of metals in PM10 filters and in Araucaria heterophylla needles. The sampling campaign was carried out at two sites in the city of Quito, Ecuador, in 2017-2019. Concentrations of Cr, Cu, K, Mn, Pb, Zn, Ca, Fe, Al and Mg were determined in PM10 filters and in Araucaria heterophylla needles using an Inductively Coupled Plasma - Optical Emission Spectroscopy (ICP-OES). The annual mean concentrations of PM10 ranged between 24.9 and 26.3 µg m-3, exceeding the limit established by the World Health Organization (20 µg m-3). Statistical analyses, performed for the PM10 filters, showed that dust resuspension and anthropogenic activities were important sources for PM10 emissions in the city. Metals related to natural emissions (Ca, Mg, K, Al and Fe) dominated in both types of samples, while the minor metals were those related to anthropogenic emissions (Zn, Cu, Cr and Pb). The former were positively associated with the needle samples, while the latter were associated with PM10 filters. This work not only improved scientific knowledge on the concentrations of PM10 and metals in the Andean city of Quito, but also greatly contributed to the progress of research on the use of Araucaria heterophylla needles as a biomonitor.
RESUMO
Consensus scoring has become a commonly used strategy within structure-based virtual screening (VS) workflows with improved performance compared to those based in a single scoring function. However, no research has been devoted to analyze the worth of docking scoring functions components in consensus scoring. We implemented and tested a method that incorporates docking scoring functions components into the setting of high performance VS workflows. This method uses genetic algorithms for finding the combination of scoring components that maximizes the VS enrichment for any target. Our methodology was validated using a data set including ligands and decoys for 102 targets that have been widely used in VS validation studies. Results show that our approach outperforms other methods for all targets. It also boosts the initial enrichment performance of the traditional use of whole scoring functions in consensus scoring by an average of 45%. Our methodology showed to be outstandingly predictive when challenged to rescore external (previously unseen) data. Remarkably, CompScore was able not only to retain its performance after redocking with a different software, but also proved that the enrichment obtained was not artificial. CompScore is freely available at: http://bioquimio.udla.edu.ec/compscore/ .
