Analysis of psychoactive substances and metabolites in sludges, soils, sediments and biota: a review

The use of psychoactive substances, including illegal drugs, drugs of abuse and psychiatric pharmaceuticals, is a major health and environmental issue. In particular, drugs are found in urban sewage and water ecosystems. The analysis of drugs in wastewater is challenging because drugs occur at trace levels in complex organo-mineral media, calling for advanced analytical methods. Here we review recent methods developped to analyze drugs in sludge, sediments, soils and biota. Extraction methods include solid–liquid extraction, sonication, microwave, and quick, easy, cheap, efective, rugged and safe extraction (QuEChERS). We compare and discuss advantages and disadvantages of each analytical step for various sample types.Funding for open access publishing: Universidad de Cádiz/CBUA. Sergio Santana-Viera thanks the University of Cádiz for his research contract (FEDER-UCA18-107036)

Distribución por tamaños de la materia particulada en Las Palmas de Gran Canaria

En este trabajo se presenta la distribución por tamaños de la materia particulada (MP)en la ciudad de Las Palmas de Gran Canaria. La experiencia se llevó a cabo entre junio de 2002 y marzo de 2003. A tal efecto se han utilizado captadores de alto volumen equipados con impactadores en cascada, que permiten una separación, en filtros de fibra de vidrio, de la materia recogida en seis fracciones de tamaño. Al final del muestreo se dispuso de 42 muestras válidas para el análisis. La materia particulada se determinó gravimétricamente. Se establecióla distribución de la concentración másica en función de los diámetros de corte. Se utilizan los diagramas de Lundgreen para establecer la distribución por tamaños y la evolución estacional e histórica. Se estudian las fracciones fina y gruesa del aerosol así como su evolución temporal e histórica

A data mining framework based on boundary-points for gene selection from DNA-microarrays: Pancreatic Ductal Adenocarcinoma as a case study

[EN] Gene selection (or feature selection) from DNA-microarray data can be focused on different techniques, which generally involve statistical tests, data mining and machine learning. In recent years there has been an increasing interest in using hybrid-technique sets to face the problem of meaningful gene selection; nevertheless, this issue remains a challenge. In an effort to address the situation, this paper proposes a novel hybrid framework based on data mining techniques and tuned to select gene subsets, which are meaningfully related to the target disease conducted in DNA-microarray experiments. For this purpose, the framework above deals with approaches such as statistical significance tests, cluster analysis, evolutionary computation, visual analytics and boundary points. The latter is the core technique of our proposal, allowing the framework to define two methods of gene selection. Another novelty of this work is the inclusion of the age of patients as an additional factor in our analysis, which can leading to gaining more insight into the disease. In fact, the results reached in this research have been very promising and have shown their biological validity. Hence, our proposal has resulted in a methodology that can be followed in the gene selection process from DNA-microarray data

An Ensemble Framework Coping with Instability in the Gene Selection Process

[EN] This paper proposes an ensemble framework for gene selection, which is aimed at addressing instability problems presented in the gene filtering task. The complex process of gene selection from gene expression data faces different instability problems from the informative gene subsets found by different filter methods. This makes the identification of significant genes by the experts difficult. The instability of results can come from filter methods, gene classifier methods, different datasets of the same disease and multiple valid groups of biomarkers. Even though there is a wide number of proposals, the complexity imposed by this problem remains a challenge today. This work proposes a framework involving five stages of gene filtering to discover biomarkers for diagnosis and classification tasks. This framework performs a process of stable feature selection, facing the problems above and, thus, providing a more suitable and reliable solution for clinical and research purposes. Our proposal involves a process of multistage gene filtering, in which several ensemble strategies for gene selection were added in such a way that different classifiers simultaneously assess gene subsets to face instability. Firstly, we apply an ensemble of recent gene selection methods to obtain diversity in the genes found (stability according to filter methods). Next, we apply an ensemble of known classifiers to filter genes relevant to all classifiers at a time (stability according to classification methods). The achieved results were evaluated in two different datasets of the same disease (pancreatic ductal adenocarcinoma), in search of stability according to the disease, for which promising results were achieved

10th International Conference

The International Symposium on Distributed Computing and Artificial Intelligence 2013 (DCAI 2013) is a forum in which applications of innovative techniques for solving complex problems are presented. Artificial intelligence is changing our society. Its application in distributed environments, such as the internet, electronic commerce, environment monitoring, mobile communications, wireless devices, distributed computing, to mention only a few, is continuously increasing, becoming an element of high added value with social and economic potential, in industry, quality of life, and research. This conference is a stimulating and productive forum where the scientific community can work towards future cooperation in Distributed Computing and Artificial Intelligence areas. These technologies are changing constantly as a result of the large research and technical effort being undertaken in both universities and businesses. The exchange of ideas between scientists and technicians from both the academic and industry sector is essential to facilitate the development of systems that can meet the ever increasing demands of today's society. This edition of DCAI brings together past experience, current work, and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. This symposium is organized by the Bioinformatics, Intelligent System and Educational Technology Research Group (http://bisite.usal.es/) of the University of Salamanca. The present edition was held in Salamanca, Spain, from 22nd to 24th May 2013

Microwave Assisted Micellar Extraction Method Combined with Graphite Furnace Atomic Absorption Spectrometry For The Determination of Ni, Cr, Cu, Pb And Cd in Marine Sediments.

A new green method has been developed for the extraction of the pseudo-total content of the heavy metals Ni, Cu, Cr, Pb, and Cd from marine sediments using a mixture of biodegradable micellar media (SDS, Triton X-100) as extractants and graphite furnace atomic absorption spectrometry (GFAAS) for their determination. This work is the first one that uses only surfactants as extractants, without the addition of chelating agents to increase the extraction efficiency of the method, proving to be effective in the extraction of metals from this type of matrices. The proposed method has shown high recovery percentages for all the metals considered (>68%), good linearity and reproducibility (RSD<5.9%), as well as detection limits ranging from 0.06 to 2.78 µg g-1. The method was applied to the determination of the heavy metals under study in samples with different physicochemical properties. Finally, our results were compared with those obtained using microwave assisted extraction - furnace atomic absorption spectrometry (MAE/GFAAS) described in ISO 11047:1998 obtaining comparable results.Accepted ManuscriptsBiotecnologí

Deposition of chlorides in the concrete in the atmospheres of Tenerife Island- Spain

El efecto del viento sobre la superficie del mar y su oleaje cerca de la costa provoca la formación de un aerosol con un contenido de cloruros y sales que depende de su velocidad. Este aerosol penetra por la red de poros pudiendo provocar la corrosión de la armadura lo que ha sido estudiado en probetas de hormigón situadas al menos en dos atmósferas de Brasil. No existen en cambio estudios similares en España. En el presente trabajo se comunican los contenidos de cloruros que se han recogido con el método de la vela húmeda en cinco estaciones colocadas en diversos emplazamientos de la Isla de Tenerife en España.Postprint (published version

An agent-based clustering approach for gene selection in gene expression microarray

Gene selection is a major research area in microarray analysis, which seeks to discover differentially expressed genes for a particular target annotation. Such genes also often called informative genes are able to differentiate tissue samples belonging to different classes of the studied disease. Despite the fact that there is a wide number of proposals, the complexity imposed by this problem remains a challenge today. This research proposes a gene selection approach by means of a clustering-based multiagent system. This proposal manages different filter methods and gene clustering through coordinated agents to discover informative gene subsets. To assess the reliability of our approach, we have used four important and public gene expression datasets, two Lung cancer datasets, Colon and Leukemia cancer dataset. The achieved results have been validated through cluster validity measures, visual analytics, a classifier and compared with other gene selection methods, proving the reliability of our proposal

New opportunities for the study of organic films applied on metals for corrosion protection by means of alternating current scanning electrochemical microscopy

A new method for the investigation of the inhibition efficiency against corrosion by organic films adsorbed on metals based on the measurement of Z-approach curves by AC-SECM is proposed. Preliminary measurements conducted on four copper-inhibitor systems exposed to aqueous solutions support that a characteristic frequency can be defined, which corresponds to the frequency of the AC potential signal applied to the SECM tip for which a transition between negative- and positive-feedback behaviours is observed in the approach curves. From the shift of this characteristic frequency towards higher values, the enhancement of the corrosion protection efficiency of the inhibitor system can be established. Furthermore, the effects of inhibitor nature, concentration, and pre-treatment duration for the formation of the surface films, can be readily investigate