High-throughput identification of RNA localization elements in neuronal cells.

Hundreds of RNAs are enriched in the projections of neuronal cells. For the vast majority of them, though, the sequence elements that regulate their localization are unknown. To identify RNA elements capable of directing transcripts to neurites, we deployed a massively parallel reporter assay that tested the localization regulatory ability of thousands of sequence fragments drawn from endogenous mouse 3' UTRs. We identified peaks of regulatory activity within several 3' UTRs and found that sequences derived from these peaks were both necessary and sufficient for RNA localization to neurites in mouse and human neuronal cells. The localization elements were enriched in adenosine and guanosine residues. They were at least tens to hundreds of nucleotides long as shortening of two identified elements led to significantly reduced activity. Using RNA affinity purification and mass spectrometry, we found that the RNA-binding protein Unk was associated with the localization elements. Depletion of Unk in cells reduced the ability of the elements to drive RNAs to neurites, indicating a functional requirement for Unk in their trafficking. These results provide a framework for the unbiased, high-throughput identification of RNA elements and mechanisms that govern transcript localization in neurons.

Quantification of pharmaceuticals in hospital effluent: Weighted ranking of environmental risk using a fuzzy hybrid multicriteria method.

An analytical method for quantification of seventeen pharmaceuticals and one metabolite was validated and applied in the analysis of hospital effluent samples. Two different sampling strategies were used: seasonal sampling, with 7 samples collected bimonthly; and hourly sampling, with 12 samples collected during 12 h. Thus, the variability was both seasonal and within the same day. High variability was observed in the measured concentrations of the pharmaceuticals and the metabolite. The quantification method, performed using weighted linear regression model, demonstrated results of average concentrations in seasonal samples ranged between 0.19 µgL-1 (carbamazepine) and higher than 61.56 µgL-1 (acetaminophen), while the hourly samples showed average concentrations between 0.07 µgL-1 (diazepam) and higher than 54.91 µgL-1 (acetaminophen). It is described as higher because the maximum concentration of the calibration curve took into account the dilution factor provided by DLLME. The diurnal results showed a trend towards higher concentrations in the first and last hours of sampling. The risk quotient (RQ) was calculated using organisms from three different trophic levels, for all the analytes quantified in the samples. Additionally, in order to understand the level of importance of each RQ, an expert panel was established, with contributions from 23 specialists in the area. The results were analyzed using a hybrid decision-making approach based on a Fuzzy Analytic Hierarchy Process (FAHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, in order to rank the compounds by environmental risk priority. The compounds of greatest concern were losartan, acetaminophen, 4-aminoantipyrine, sulfamethoxazole, and metoclopramide. Comparison of the environmental risk priority ranking with the potential human health risk was performed by applying the same multicriteria approach, with the prediction of endpoints using in silico (Q)SAR models. The results obtained suggested that sulfamethoxazole and acetaminophen were the most important analytes to be considered for monitoring.

Classifying micropollutants by environmental risk in groundwater using screening analysis associated to a hybrid multicriteria method combining (Q)SAR tools, fuzzy AHP and ELECTRE.

This study aimed to evaluate and monitor pesticides in groundwater of the Serra Geral aquifer, located in the Paraná Basin 3 (southern Brazil), using Liquid Chromatography coupled with a Quadrupole-Time-of-Flight Mass Spectrometer (LC-QTOF MS). A total of 117 samples, collected in three different moments, were analyzed over 36 months. Groundwater samples from 35 wells and four surface water points were monitored in each sampling campaign. A pesticide screening methodology was proposed with the tentative identification of 1607 pesticides and pesticide metabolites. The application of the proposed methodology resulted in the verification of 29 pesticides and pesticide metabolites, 7 as confirmed analytes and 22 as suspect compounds. (Q)SAR in silico predictions and GUS index calculation provided data on the potential environmental risk of the identified compounds, with eight endpoints considered. After in silico predictions, an alternative hybrid multicriteria method was applied, combining the weighting of endpoints of fuzzy AHP and micropollutants classification by environmental risk using ELECTRE. The fuzzy AHP results indicated the greatest importance of mutagenicity among the eight evaluated indicators, while the scarce influence of the physicochemical properties on the environmental risk suggested their exclusion from the model. Accordingly, the ELECTRE results highlighted the prevalence of thiamethoxam and carbendazim as the most dangerous for the environment. The application of the proposed method enabled the selection of the compounds that must be monitored, considering mutagenicity and toxicity predictions for environmental risk analysis.

Qualitative evaluation of pharmaceuticals and metabolites in hospital effluent: Influence of sample preparation technique and outranking by environmental risk using the ELECTRE method.

The presence of pharmaceuticals and metabolites in effluents has become a serious environmental problem, so it is essential to be able to monitor these microcontaminants using qualitative approaches, as well as to assess the potential environmental risks that such compounds may present. Therefore, in this study, suspect screening analysis was performed of 2030 pharmaceuticals and metabolites in hospital effluent samples, applying different sample preparation techniques. Additionally, a pioneering association of (Q)SAR assessment of identified contaminants with the ELECTRE multi-criteria decision analysis technique made it possible to prioritize analytes according to their environmental risk, in order to enable their inclusion in environmental monitoring programs. The results showed that the most advantageous alternative sample preparation technique consisted of cleanup (100 mg of silica/alumina sorbent) + dispersive liquid-liquid microextraction (7.5 of aqueous matrix, 325 µL of chloroform (extracting solvent), and 500 µL of acetonitrile as dispersing solvent). This procedure resulted in the identification of 70 pharmaceuticals and metabolites in the composite sample tested. The suspect screening analysis found a total of 105 microcontaminants, 28 of them being "confirmed compounds" and 77 being "suspect compounds". Of the compounds identified, 87% were pharmaceuticals and 13% were metabolites. The compounds identified were subsequently evaluated using different open access software packages, considering eight endpoints: mobility, persistence, estrogen receptor binding, wastewater treatment plant total removal, biodegradability, PBT (persistent, bioaccumulation and toxic), mutagenicity, and carcinogenicity. The (Q)SAR prediction results were used as input data for the ELECTRE outranking method. Categorization of the identified compounds by ELECTRE resulted in the kernel (priority compounds) and a further 19 groups. ELECTRE sensitivity evaluation indicated that for all the cases, the kernel and the following two groups coincided. The categorization provided by the ELECTRE method constitutes a highly intuitive decision and choice tool, which can assist in the selection of compounds if subsequent quantitative analysis is to be carried out.

Multi-criteria decision-making techniques associated with (Q)SAR risk assessment for ranking surface water microcontaminants identified using LC-QTOF MS.

Contaminants of emerging concern (CECs) have been a focus of study for years, with investigations revealing the contamination of different environmental matrices (surface water, soil, air, and sediment) by diverse classes of microcontaminants. Understanding the contamination profiles requires identification and risk assessment of the microcontaminants. In the present work, analysis was made of the presence of 3250 compounds in 27 samples from the Conceição River (Rio Grande do Sul State, Brazil), using an SPE-LC-QTOF MS method. In total, 150 microcontaminants (confirmed and suspected) of different classes, especially pesticides and pharmaceuticals, were identified by an initial qualitative analysis. Subsequently, in silico predictions of eight endpoints, using quantitative structure-activity relationship ((Q)SAR) models, were employed to determine the risk of each previously screened microcontaminant. This large amount of (Q)SAR data, frequently with conflicting information in relation to the responses of the different endpoints, makes it difficult to define which microcontaminants should be prioritized for analysis. Therefore, in order to rank the identified microcontaminants by risk assessment, two multi-criteria decision-making (MCDM) ranking techniques (ToxPi and TOPSIS), associated with a weighting method, were performed to establish the order of priority for further quantitative analysis of the most hazardous microcontaminants. The two rankings were statistically similar, especially for the 20 highest priority microcontaminants. Nonetheless, sensitivity tests carried out for the ToxPi and TOPSIS outputs showed higher performance robustness of TOPSIS, compared to ToxPi. This is the first time that such an approach (screening/(Q)SAR/MCDM methods) has been performed in the context of microcontaminant environmental risk evaluation and demonstrated to be an available strategy to help rank the most concern microcontaminants identified in aqueous environment samples.

Chemical and toxicological evaluation along with unprecedented transformation products during photolysis and heterogeneous photocatalysis of chloramphenicol in different aqueous matrices.

As the presence of antibiotics in environmental waters enhances antimicrobial resistance, photolysis and heterogeneous photocatalysis of chloramphenicol (CAP) were evaluated in deionized water (DW) and in sewage treatment plant (STP) effluent under black light and solar irradiation. Processes were compared in terms of CAP degradation, reaction kinetics, and electrical energy per order, as well as regarding theoretical toxicity, biodegradability, carcinogenicity, and mutagenicity of transformation products (TPs). Rate constants obtained under photolysis (0.008 min-1) and heterogeneous photocatalysis (0.18 min-1) only differed in DW. This is due to the generation of photo-active reactive oxygen species (HO· and HO2·-/O2·-) under photolysis in STP effluent, as verified by experiments in the presence of 2-propanol and chloroform. Natural organic matter and HCO3- were the main responsible for reducing CAP degradation in STP effluent. Fifteen TPs were identified during both processes in DW, 13 of which are unprecedented. TPs were formed mainly via HO· preferential attack on the aromatic ring and on the α-carbon, and some of them were classified as persistent and toxic, genotoxic, or carcinogenic by Toxtree software. Results confirm that solar photocatalysis is less costly than to photocatalysis under black light for wastewater treatment.

Economically feasible strategy for confirmation of pharmaceuticals in hospital effluent using screening analysis.

The contamination of aquatic systems by pharmaceuticals has received considerable attention in recent decades, because these substances are increasingly detected in the environment. This is due to the abundant use of pharmaceuticals by the population and, consequently, their constant introduction into aquatic systems through domestic, industrial, and hospital wastewaters. Hospital effluents have highly complex compositions and present potential toxicity towards the environment. In this work, a screening methodology was developed to evaluate the occurrence of pharmaceutical products in hospital wastewater, using a viable, easy, and economical strategy employing commercial pharmaceutical compounds for screening analysis. Six samplings of hospital wastewater were carried out monthly (from winter until summer). The samples were filtered and pre-concentrated/extracted using solid phase extraction (SPE). The pharmaceuticals screening procedure required the construction of two databases, one for each ionization mode (positive and negative), which contained information that allowed the identification of the presence of these pharmaceuticals in the studied samples. Commercial pharmaceutical compounds were used as analytical standards. Based on this strategy and, using liquid chromatography coupled to high resolution mass spectrometry, it was possible to screen 110 pharmaceuticals and, from these, to confirm the presence of 38 pharmaceuticals in analyzed samples. These results indicate the analytes that should be taken into account in the further development of quantitative methods for pharmaceutical analysis.

Proposal of a new, fast, cheap, and easy method using DLLME for extraction and preconcentration of diazepam and its transformation products generated by a solar photo-Fenton process.

This work evaluated the formation of transformation products (TPs) during the degradation of diazepam (DZP) by a solar photo-Fenton process. Six TPs were identified, three of them for the first time. After elucidation of the TPs, a new, cheap, fast, and easy method was employed to extract and preconcentrate DZP and its TPs, using dispersive liquid-liquid microextraction (DLLME). The method was optimized using factorial and Doehlert designs, with the best results obtained using acetonitrile as disperser solvent and chloroform as extraction solvent, with volumes of 1000 and 650 µL, respectively. When DZP degradation was performed in ultrapure water, the extraction/preconcentration of DZP and its TPs by DLLME was very similar to the results obtained using a traditional SPE method. However, when hospital wastewater was used as the matrix, more limited extraction efficiency was obtained using DLLME, compared to SPE. Meanwhile, all the TPs extracted by SPE were also extracted by the DLLME technique. Furthermore, DLLME was much less expensive than SPE, besides being faster, easier, and requiring only small amounts of organic solvents. This work reports a new and very important tool for the extraction and preconcentration of TPs formed during degradation using techniques such as advanced oxidation processes (AOPs), since without this step it would not be possible to identify all the TPs formed in some complex wastewater matrices.

Investigation of pharmaceuticals and their metabolites in Brazilian hospital wastewater by LC-QTOF MS screening combined with a preliminary exposure and in silico risk assessment.

This work evaluates the occurrence of pharmaceuticals, with special emphasis on their metabolites, in raw hospital wastewater (HWW) using wide-scope screening based on liquid chromatography coupled to high resolution mass spectrometry. The applied strategy uses an extended purpose-built database, containing >1000 pharmaceuticals and 250 metabolites. Raw HWW samples from a hospital located in south Brazil were collected over six months, with a monthly sampling frequency. Accurate-mass full-spectrum data provided by quadrupole-time of flight MS allowed the identification of 43 pharmaceuticals and up to 31 metabolites in the samples under study. Additionally, other four metabolites not included in the initial database could be identified using a complementary strategy based on the common fragmentation pathway between the parent compound and its metabolites. Nine metabolites derived from four pharmaceuticals were identified in the raw HWW samples, whereas their parent compounds were not found in these samples. The results of this work illustrate the importance of including not only parent pharmaceuticals but also their main metabolites in screening analysis. Besides, the inclusion of in silico QSAR predictions allowed assessing the environmental fate and effect of pharmaceuticals and metabolites in terms of biodegradability, as possible Persistent, Bioaccumulative and Toxic (PBT) compounds, and their potential hazard to the aquatic environment.

Degradation of pharmaceuticals in different water matrices by a solar homo/heterogeneous photo-Fenton process over modified alginate spheres.

A solar homo/heterogeneous photo-Fenton process using five materials (Fe(II), Fe(III), mining waste, Fe(II)/mining waste, and Fe(III)/mining waste) supported on sodium alginate was used as a strategy to iron dosage for the degradation of eight pharmaceuticals in three different water matrices (distilled water, simulated wastewater, and hospital wastewater). Experiments were carried out in a photoreactor with a capacity of 1 L, using 3 g of iron-alginate spheres and an initial hydrogen peroxide concentration of 25 mg L-1, at pH 5.0. All the materials prepared were characterized by different techniques. The Fe(III)-alginate spheres presented the best pharmaceutical degradation after a treatment time of 116 min. Nineteen transformation products generated during the solar photo-Fenton process were identified by liquid chromatography coupled to quadrupole time-of-flight mass spectrometry, using a purpose-built database developed for detecting these transformation products. Finally, the transformation products identified were classified according to their toxicity and predicted biodegradability.