Malaria entomological inoculation rates in gold mining areas of Southern Venezuela

A longitudinal study of malaria vectors aiming to describe the intensity of transmission was carried out in five villages of Southern Venezuela between January 1999-April 2000. The man-biting, sporozoite and entomological inoculation rates (EIR) were calculated based on 121 all-night collections of anophelines landing on humans, CDC light traps and ultra violet up-draft traps. A total of 6,027 female mosquitoes representing seven species were collected. The most abundant species were Anopheles marajoara Galvão & Damasceno (56.7%) and Anopheles darlingi Root (33%), which together accounted for 89.7% of the total anophelines collected. The mean biting rate for An. marajoara was 1.27 (SD + 0.81); it was 0.74 (SD + 0.91) for An. darlingand 0.11 (SD + 0.10) for Anopheles neomaculipalpus Curry and the overall biting rate was 2.29 (SD + 1.06). A total of 5,886 mosquitoes collected by all three methods were assayed by ELISA and 28 pools, equivalent to 28 mosquitoes, yielded positive results for Plasmodium spp. CS protein. An. neomaculipalpus had the highest sporozoite rate 0.84% (3/356), followed by An. darlingi 0.82% (16/1,948) and An. marajoara 0.27% (9/3,332). The overall sporozoite rate was 0.48% (28/5,886). The rates of infection by Plasmodium species in mosquitoes were 0.37% (22/5,886) for Plasmodium vivax(Grassi & Feletti) and 0.10% (6/5,886) for Plasmodium falciparum (Welch). The estimated overall EIR for An. darling was 2.21 infective bites/person/year, 1.25 for An. marajoara and 0.34 for An. neomaculipalpus. The overall EIR was four infective bites/person/year. The biting rate, the sporozoite rate and the EIR are too low to be indicators of the efficacy of control campaigns in this area.

Municipal distribution of bladder cancer mortality in Spain: Possible role of mining and industry

BACKGROUND Spain shows the highest bladder cancer incidence rates in men among European countries. The most important risk factors are tobacco smoking and occupational exposure to a range of different chemical substances, such as aromatic amines. METHODS This paper describes the municipal distribution of bladder cancer mortality and attempts to "adjust" this spatial pattern for the prevalence of smokers, using the autoregressive spatial model proposed by Besag, York and Molliè, with relative risk of lung cancer mortality as a surrogate. RESULTS It has been possible to compile and ascertain the posterior distribution of relative risk for bladder cancer adjusted for lung cancer mortality, on the basis of a single Bayesian spatial model covering all of Spain's 8077 towns. Maps were plotted depicting smoothed relative risk (RR) estimates, and the distribution of the posterior probability of RR>1 by sex. Towns that registered the highest relative risks for both sexes were mostly located in the Provinces of Cadiz, Seville, Huelva, Barcelona and Almería. The highest-risk area in Barcelona Province corresponded to very specific municipal areas in the Bages district, e.g., Suría, Sallent, Balsareny, Manresa and Cardona. CONCLUSION Mining/industrial pollution and the risk entailed in certain occupational exposures could in part be dictating the pattern of municipal bladder cancer mortality in Spain. Population exposure to arsenic is a matter that calls for attention. It would be of great interest if the relationship between the chemical quality of drinking water and the frequency of bladder cancer could be studied.

Regulation of the expression of components of the exocytotic machinery of insulin-secreting cells by microRNAs

Fine-tuning of insulin secretion from pancreatic beta-cells participates in blood glucose homeostasis. Defects in this process can lead to chronic hyperglycemia and diabetes mellitus. Several proteins controlling insulin exocytosis have been identified, but the mechanisms regulating their expression remain poorly understood. Here, we show that two non-coding microRNAs, miR124a and miR96, modulate the expression of proteins involved in insulin exocytosis and affect secretion of the beta-cell line MIN6B1. miR124a increases the levels of SNAP25, Rab3A and synapsin-1A and decreases those of Rab27A and Noc2. Inhibition of Rab27A expression is mediated by direct binding to the 3'-untranslated region of Rab27A mRNA. The effect on the other genes is indirect and linked to changes in mRNA levels. Over-expression of miR124a leads to exaggerated hormone release under basal conditions and a reduction in glucose-induced secretion. miR96 increases mRNA and protein levels of granuphilin, a negative modulator of insulin exocytosis, and decreases the expression of Noc2, resulting in lower capacity of MIN6B1 cells to respond to secretagogues. Our data identify miR124a and miR96 as novel regulators of the expression of proteins playing a critical role in insulin exocytosis and in the release of other hormones and neurotransmitters

Histology-driven data mining of lipid signatures from multiple imaging mass spectrometry analyses: application to human colorectal cancer liver metastasis biopsies.

Imaging mass spectrometry (IMS) represents an innovative tool in the cancer research pipeline, which is increasingly being used in clinical and pharmaceutical applications. The unique properties of the technique, especially the amount of data generated, make the handling of data from multiple IMS acquisitions challenging. This work presents a histology-driven IMS approach aiming to identify discriminant lipid signatures from the simultaneous mining of IMS data sets from multiple samples. The feasibility of the developed workflow is evaluated on a set of three human colorectal cancer liver metastasis (CRCLM) tissue sections. Lipid IMS on tissue sections was performed using MALDI-TOF/TOF MS in both negative and positive ionization modes after 1,5-diaminonaphthalene matrix deposition by sublimation. The combination of both positive and negative acquisition results was performed during data mining to simplify the process and interrogate a larger lipidome into a single analysis. To reduce the complexity of the IMS data sets, a sub data set was generated by randomly selecting a fixed number of spectra from a histologically defined region of interest, resulting in a 10-fold data reduction. Principal component analysis confirmed that the molecular selectivity of the regions of interest is maintained after data reduction. Partial least-squares and heat map analyses demonstrated a selective signature of the CRCLM, revealing lipids that are significantly up- and down-regulated in the tumor region. This comprehensive approach is thus of interest for defining disease signatures directly from IMS data sets by the use of combinatory data mining, opening novel routes of investigation for addressing the demands of the clinical setting.

Using free data mining software and clustering algorithms to find predictors from student qualifications

In this project a research both in finding predictors via clustering techniques and in reviewing the Data Mining free software is achieved. The research is based in a case of study, from where additionally to the KDD free software used by the scientific community; a new free tool for pre-processing the data is presented. The predictors are intended for the e-learning domain as the data from where these predictors have to be inferred are student qualifications from different e-learning environments. Through our case of study not only clustering algorithms are tested but also additional goals are proposed.

Oxidative stress enhances the expression of sulfur assimilation genes: preliminary insights on the Enterococcus faecalis iron-sulfur cluster machinery regulation

The Firmicutes bacteria participate extensively in virulence and pathological processes. Enterococcus faecalis is a commensal microorganism; however, it is also a pathogenic bacterium mainly associated with nosocomial infections in immunocompromised patients. Iron-sulfur [Fe-S] clusters are inorganic prosthetic groups involved in diverse biological processes, whose in vivo formation requires several specific protein machineries. Escherichia coli is one of the most frequently studied microorganisms regarding [Fe-S] cluster biogenesis and encodes the iron-sulfur cluster and sulfur assimilation systems. In Firmicutes species, a unique operon composed of the sufCDSUB genes is responsible for [Fe-S] cluster biogenesis. The aim of this study was to investigate the potential of the E. faecalis sufCDSUB system in the [Fe-S] cluster assembly using oxidative stress and iron depletion as adverse growth conditions. Quantitative real-time polymerase chain reaction demonstrated, for the first time, that Gram-positive bacteria possess an OxyR component responsive to oxidative stress conditions, as fully described for E. coli models. Likewise, strong expression of the sufCDSUB genes was observed in low concentrations of hydrogen peroxide, indicating that the lowest concentration of oxygen free radicals inside cells, known to be highly damaging to [Fe-S] clusters, is sufficient to trigger the transcriptional machinery for prompt replacement of [Fe-S] clusters.

Inferences about the global scenario of human T-cell lymphotropic virus type 1 infection using data mining of viral sequences

Human T-cell lymphotropic virus type 1 (HTLV-1) is mainly associated with two diseases: tropical spastic paraparesis/HTLV-1-associated myelopathy (TSP/HAM) and adult T-cell leukaemia/lymphoma. This retrovirus infects five-10 million individuals throughout the world. Previously, we developed a database that annotates sequence data from GenBank and the present study aimed to describe the clinical, molecular and epidemiological scenarios of HTLV-1 infection through the stored sequences in this database. A total of 2,545 registered complete and partial sequences of HTLV-1 were collected and 1,967 (77.3%) of those sequences represented unique isolates. Among these isolates, 93% contained geographic origin information and only 39% were related to any clinical status. A total of 1,091 sequences contained information about the geographic origin and viral subtype and 93% of these sequences were identified as subtype “a”. Ethnicity data are very scarce. Regarding clinical status data, 29% of the sequences were generated from TSP/HAM and 67.8% from healthy carrier individuals. Although the data mining enabled some inferences about specific aspects of HTLV-1 infection to be made, due to the relative scarcity of data of available sequences, it was not possible to delineate a global scenario of HTLV-1 infection.

From the “Mining Triangle” to the “Greater Region“ (“Großregion”/”Grande Région”). The Institutionalisation of the “SaarLorLux” Euroregion

Gairebé 182 milions d'ciutadans de la Unió Europea (= 37,5% de la població total) viuen en aproximadament 130 regions frontereres i transfrontereres. Aquestes regions contribueixen significativament al procés d'integració europea. Aquesta importància es documenta pel paquet dels Fons Estructurals 2007-2013, que ha estat presentat per la Comissió Europea i que va ser aprovat recentment pel Parlament Europeu. Considerant que la UE ha gastat uns 4875 € milions per a la cooperació transfronterera, transnacional i interregional en el marc de la iniciativa Interreg per al període 2000-2006, la cooperació territorial europea es convertirà en un dels tres objectius dels fons estructurals i rebrà € 7750000000 (5,57 milions d'euros per a la cooperació transfronterera només) per al període 2007-2013 (Comissió Europea, 2006a, 2006b). A part d'això, un nou conjunt de normes per a l'establiment d'una "agrupació europea de cooperació territorial" (AECT) ha estat adoptat i que facilitarà la cooperació transboundray, transnacional i interregional a la UE. Aquest treball s'ocuparà de les estructures de la institucionalització, la presa de decisions i l'execució i les polítiques de la "Gran Regió" / "Großregion" (d'ara endavant: GR o Gran Regió).

Fungal sex: meiosis machinery in ancient symbiotic fungi.

Arbuscular mycorrhizal fungi are important symbionts that enhance plant growth. They were thought to have been asexual for hundreds of millions of years. A new study reveals that the fungi actually possess highly conserved genetic machinery for completion of meiosis.

Malaria in gold-mining areas in Colombia

Gold-mining may play an important role in the maintenance of malaria worldwide. Gold-mining, mostly illegal, has significantly expanded in Colombia during the last decade in areas with limited health care and disease prevention. We report a descriptive study that was carried out to determine the malaria prevalence in gold-mining areas of Colombia, using data from the public health surveillance system (National Health Institute) during the period 2010-2013. Gold-mining was more prevalent in the departments of Antioquia, Córdoba, Bolívar, Chocó, Nariño, Cauca, and Valle, which contributed 89.3% (270,753 cases) of the national malaria incidence from 2010-2013 and 31.6% of malaria cases were from mining areas. Mining regions, such as El Bagre, Zaragoza, and Segovia, in Antioquia, Puerto Libertador and Montelíbano, in Córdoba, and Buenaventura, in Valle del Cauca, were the most endemic areas. The annual parasite index (API) correlated with gold production (R2 0.82, p < 0.0001); for every 100 kg of gold produced, the API increased by 0.54 cases per 1,000 inhabitants. Lack of malaria control activities, together with high migration and proliferation of mosquito breeding sites, contribute to malaria in gold-mining regions. Specific control activities must be introduced to control this significant source of malaria in Colombia.

Mining and exploiting domain-specific corpora in the PANACEA platform

The objective of the PANACEA ICT-2007.2.2 EU project is to build a platform that automates the stages involved in the acquisition,production, updating and maintenance of the large language resources required by, among others, MT systems. The development of a Corpus Acquisition Component (CAC) for extracting monolingual and bilingual data from the web is one of the most innovative building blocks of PANACEA. The CAC, which is the first stage in the PANACEA pipeline for building Language Resources, adopts an efficient and distributed methodology to crawl for web documents with rich textual content in specific languages and predefined domains. The CAC includes modules that can acquire parallel data from sites with in-domain content available in more than one language. In order to extrinsically evaluate the CAC methodology, we have conducted several experiments that used crawled parallel corpora for the identification and extraction of parallel sentences using sentence alignment. The corpora were then successfully used for domain adaptation of Machine Translation Systems.

Técnicas de Data e Text Mining Para Anotação de Um Arquivo Digital

O presente trabalho cujo Título é técnicas de Data e Text Mining para a anotação dum Arquivo Digital, tem como objectivo testar a viabilidade da utilização de técnicas de processamento automático de texto para a anotação das sessões dos debates parlamentares da Assembleia da República de Portugal. Ao longo do trabalho abordaram-se conceitos como tecnologias de descoberta do conhecimento (KDD), o processo da descoberta do conhecimento em texto, a caracterização das várias etapas do processamento de texto e a descrição de algumas ferramentas open souce para a mineração de texto. A metodologia utilizada baseou-se na experimentação de várias técnicas de processamento textual utilizando a open source R/tm. Apresentam-se, como resultados, a influência do pré-processamento, tamanho dos documentos e tamanhos dos corpora no resultado do processamento utilizando o algoritmo knnflex.

Intégration de méthodes de data mining dans le renseignement criminel : analyse par des structures issues de la théorie des graphes dans le profilage des stupéfiants

Data mining can be defined as the extraction of previously unknown and potentially useful information from large datasets. The main principle is to devise computer programs that run through databases and automatically seek deterministic patterns. It is applied in different fields of application, e.g., remote sensing, biometry, speech recognition, but has seldom been applied to forensic case data. The intrinsic difficulty related to the use of such data lies in its heterogeneity, which comes from the many different sources of information. The aim of this study is to highlight potential uses of pattern recognition that would provide relevant results from a criminal intelligence point of view. The role of data mining within a global crime analysis methodology is to detect all types of structures in a dataset. Once filtered and interpreted, those structures can point to previously unseen criminal activities. The interpretation of patterns for intelligence purposes is the final stage of the process. It allows the researcher to validate the whole methodology and to refine each step if necessary. An application to cutting agents found in illicit drug seizures was performed. A combinatorial approach was done, using the presence and the absence of products. Methods coming from the graph theory field were used to extract patterns in data constituted by links between products and place and date of seizure. A data mining process completed using graphing techniques is called ``graph mining''. Patterns were detected that had to be interpreted and compared with preliminary knowledge to establish their relevancy. The illicit drug profiling process is actually an intelligence process that uses preliminary illicit drug classes to classify new samples. Methods proposed in this study could be used \textit{a priori} to compare structures from preliminary and post-detection patterns. This new knowledge of a repeated structure may provide valuable complementary information to profiling and become a source of intelligence.