Effective bioremediation of clarithromycin and diclofenac in wastewater by microbes and Arundo donax L

Bioremediation of pharmaceuticals has gained large research efforts, but there is still a need to improve the performance of bioremediation systems by selecting effective organisms. In this study, we characterized the capability to remove clarithromycin (CLA) and diclofenac (DCF) by the bacterium Streptomyces rochei, and the fungi Phanerochaete chrysosporium and Trametes versicolor. The macrolide antibiotic CLA and the non-steroid anti-inflammatory DCF were selected because these are two of the most frequently detected drugs in water bodies. Growth and content of the PhCs and a DCF metabolite (MET) by the energy crop Arundo donax L. were also evaluated under hydroponic conditions. The removal rate (RR) by S. rochei increased from 24 to 40% at 10 and 100 µg CLA L-1, respectively, averaged over incubation times. At 144 h, the RR by P. chrysosporium was 84%, while by T. versicolor was 70 and 45% at 10 and 100 CLA µg L-1. The RR by S. rochei did not exceed 30% at 1 mg DCF L-1 and reached 60% at 10 mg DCF L-1, whereas approached 95% and 63% by P. chrysosporium and T. versicolor, respectively, at both doses. Root biomass and length of A. donax were strongly affected at 100 µg CLA L-1. CLA concentration in roots and shoots increased with the increase of the dose and translocation factor (TF) was about 1. DCF severely affected both shoot fresh weight and root length at the highest dose and concentration in roots and shoots increased with the increase of the dose. DCF concentrations were 16-19 times higher in roots than in shoots, and TF was about 0.1. MET was detected only in roots and its proportion over the parent compound decreased with the increase of the DCF dose. This study highlights the potential contribution of A. donax and the tested microbial inoculants for improving the effectiveness of bioremediation systems for CLA and DCF removal.

Structural Elucidation of Relevant Gibberellic Acid Impurities and In Silico Investigation of Their Interaction with Soluble Gibberellin Receptor GID1

Gibberellin derivatives are a family of tetracyclic diterpenoid plant hormones used in agriculture as plant growth regulators included in the European Directive 91/414. In the pesticide peer review process and to assess their toxicological relevance and product chemical equivalence, the European Food Safety Authority (EFSA) highlighted data gaps such as the identification of hydrolysis products and unknown impurities. The aspect of impurity characterization and quantitation is challenging and requires the use of hyphenated analytical techniques. In this regard, we used an LC-QTOF/MS and NMR analysis for the characterization of gibberellic acid impurities found in technical products. Gibberellic acid impurities such as gibberellin A1 (GA ₁ ), 3-isolactone gibberellic acid (iso-GA ₃ ), gibberellenic acid, 1α,2α-epoxygibberellin A3 (2-epoxy- GA ₃ ), and (1α,2β,3α,4bβ,10β)-2,3,7-trihydroxy-1-methyl-8-methylenegibb-4-ene-1,10-dicarboxylic acid were identified and successfully characterized. Moreover, an in silico investigation on selected gibberellic acid impurities and derivatives and their interactions with a gibberellin insensitive dwarf1 (GID1) receptor has been carried out by means of induced fit docking (IFD), generalized-Born surface area (MM-GBSA), and metadynamics (MTD) experiments. A direct HPLC method with DAD and MS for the detection of gibberellic acid and its impurities in a technical sample has been developed. Moreover, by means of the in silico characterization of the GID1 receptor-binding pocket, we investigated the receptor affinity of the selected gibberellins, identifying compounds (2) and (4) as the most promising hit to lead compounds.

Pesticides groundwater modelling relies on input data characterised by a high intrinsic variability: Is the resulting risk for groundwater credible?

In the framework of Regulation (EC) 1107/2009, concerning the placing of plant protection products (PPP) on the market, FOCUS models are used to predict active substances concentration in groundwater. The predicted environmental concentration in groundwater (PEC_GW) are influenced by active substance specific parameters, namely DT₅₀, K_OM and Freundlich coefficient (1/n), whose minimal variation in certain combinations of intervals significantly affects PEC_GW output. Considering that minimal variation are intrinsic in all laboratory studies, this approach may lead to not acceptable variations in the results for regulatory purposes. In the present article, PEC_GW were calculated for all maize crop scenarios, using 808 dummy active substances with different combinations of DT₅₀, K_OM and 1/n values, in order to quantify the influence of each single parameter on the final result of PEARL and PELMO models. The results obtained were used to create a classification system for the input parameters K_OM and DT₅₀ in order to minimise the input uncertainty effects. Even if this approach is scientifically viable yet, due to its conservative nature, it cannot be considered suitable in the regulatory framework, where acceptability of an active substance is strictly related to the limit value of 0.1 μg/L. Nevertheless, this classification system could represent an important screening or preliminary assessment to plan pesticide monitoring programmes. Based on the results of this analysis, it is believed that the assessment of pesticide leaching into groundwater should be revised to take into account this variability. Considering that both PEARL and PELMO FOCUS models deal with interaction between a chemical and a complex system like soil and weather, the selection of input data cannot pretend to rely on single specific number. Considering that intrinsic uncertainty cannot be eliminated from experimental work, a revision of the criteria used to identify the proper input data and a thorough revision of the actual groundwater modelling is recommended.

Use of hydroxyacetophenones as matrices for the analysis of high molecular weight glutenin mixtures by matrix-assisted laser desorption/ionization mass spectrometry

A selection of hydroxyacetophenones has been investigated as matrices for the analysis, by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS), of high molecular weight (HMW) glutenin mixtures from three wheat varieties. Mass spectra were obtained directly from the HMW glutenin extracts without any preliminary purification and separation steps. According to the quality of the mass spectra, obtained using different hydroxyacetophenones, it has been possible to classify the matrices on the basis of their suitability for the analyte properties. Only two of the matrices considered showed to be compatible with the HMW glutenin mixtures analysis, although a large amount of other highly complex protein mixtures are present. This study indicates that MALDI-MS, as a stand-alone technique, is particularly useful for the direct determination of the complete HMW subunits profile and their molecular weights. Copyright 1999 John Wiley & Sons, Ltd.