Automated user modeling for personalized digital libraries

Digital libraries (DL) have become one of the most typical ways of accessing any kind of digitalized information. Due to this key role, users welcome any improvements on the services they receive from digital libraries. One trend used to improve digital services is through personalization. Up to now, the most common approach for personalization in digital libraries has been user-driven. Nevertheless, the design of efficient personalized services has to be done, at least in part, in an automatic way. In this context, machine learning techniques automate the process of constructing user models. This paper proposes a new approach to construct digital libraries that satisfy user’s necessity for information: Adaptive Digital Libraries, libraries that automatically learn user preferences and goals and personalize their interaction using this information

A Detailed Investigation into Low-Level Feature Detection in Spectrogram Images

Being the first stage of analysis within an image, low-level feature detection is a crucial step in the image analysis process and, as such, deserves suitable attention. This paper presents a systematic investigation into low-level feature detection in spectrogram images. The result of which is the identification of frequency tracks. Analysis of the literature identifies different strategies for accomplishing low-level feature detection. Nevertheless, the advantages and disadvantages of each are not explicitly investigated. Three model-based detection strategies are outlined, each extracting an increasing amount of information from the spectrogram, and, through ROC analysis, it is shown that at increasing levels of extraction the detection rates increase. Nevertheless, further investigation suggests that model-based detection has a limitation—it is not computationally feasible to fully evaluate the model of even a simple sinusoidal track. Therefore, alternative approaches, such as dimensionality reduction, are investigated to reduce the complex search space. It is shown that, if carefully selected, these techniques can approach the detection rates of model-based strategies that perform the same level of information extraction. The implementations used to derive the results presented within this paper are available online from http://stdetect.googlecode.com

A Bacterial Biosensor for Oxidative Stress Using the Constitutively Expressed Redox-Sensitive Protein roGFP2

A highly specific, high throughput-amenable bacterial biosensor for chemically induced cellular oxidation was developed using constitutively expressed redox-sensitive green fluorescent protein roGFP2 in E. coli (E. coli-roGFP2). Disulfide formation between two key cysteine residues of roGFP2 was assessed using a double-wavelength ratiometric approach. This study demonstrates that only a few minutes were required to detect oxidation using E. coli-roGFP2, in contrast to conventional bacterial oxidative stress sensors. Cellular oxidation induced by hydrogen peroxide, menadione, sodium selenite, zinc pyrithione, triphenyltin and naphthalene became detectable after 10 seconds and reached the maxima between 80 to 210 seconds, contrary to Cd2+, Cu2+, Pb2+, Zn2+ and sodium arsenite, which induced the oxidation maximum immediately. The lowest observable effect concentrations (in ppm) were determined as 1.0 × 10−7 (arsenite), 1.0 × 10−4 (naphthalene), 1.0 × 10−4 (Cu2+), 3.8 × 10−4 (H2O2), 1.0 × 10−3 (Cd2+), 1.0 × 10−3 (Zn2+), 1.0 × 10−2 (menadione), 1.0 (triphenyltin), 1.56 (zinc pyrithione), 3.1 (selenite) and 6.3 (Pb2+), respectively. Heavy metal-induced oxidation showed unclear response patterns, whereas concentration-dependent sigmoid curves were observed for other compounds. In vivo GSH content and in vitro roGFP2 oxidation assays together with E. coli-roGFP2 results suggest that roGFP2 is sensitive to redox potential change and thiol modification induced by environmental stressors. Based on redox-sensitive technology, E. coli-roGFP2 provides a fast comprehensive detection system for toxicants that induce cellular oxidation

Are luminescent bacteria suitable for online detection and monitoring of toxic compounds in drinking water and its sources?

Biosensors based on luminescent bacteria may be valuable tools to monitor the chemical quality and safety of surface and drinking water. In this review, an overview is presented of the recombinant strains available that harbour the bacterial luciferase genes luxCDABE, and which may be used in an online biosensor for water quality monitoring. Many bacterial strains have been described for the detection of a broad range of toxicity parameters, including DNA damage, protein damage, membrane damage, oxidative stress, organic pollutants, and heavy metals. Most lux strains have sensitivities with detection limits ranging from milligrams per litre to micrograms per litre, usually with higher sensitivities in compound-specific strains. Although the sensitivity of lux strains can be enhanced by various molecular manipulations, most reported detection thresholds are still too high to detect levels of individual contaminants as they occur nowadays in European drinking waters. However, lux strains sensing specific toxic effects have the advantage of being able to respond to mixtures of contaminants inducing the same effect, and thus could be used as a sensor for the sum effect, including the effect of compounds that are as yet not identified by chemical analysis. An evaluation of the suitability of lux strains for monitoring surface and drinking water is therefore provided

Distribution of mosquitoes in the South East of Argentina and first report on the analysis based on 18S rDNA and COI sequences

Although Mar del Plata is the most important city on the Atlantic coast of Argentina, mosquitoes inhabiting such area are almost uncharacterized. To increase our knowledge in their distribution, we sampled specimens of natural populations. After the morphological identification based on taxonomic keys, sequences of DNA from small ribosomal subunit (18S rDNA) and cytochrome c oxidase I (COI) genes were obtained from native species and the phylogenetic analysis of these sequences were done. Fourteen species from the genera Uranotaenia, Culex, Ochlerotatus and Psorophora were found and identified. Our 18S rDNA and COI-based analysis indicates the relationships among groups at the supra-species level in concordance with mosquito taxonomy. The introduction and spread of vectors and diseases carried by them are not known in Mar del Plata, but some of the species found in this study were reported as pathogen vectors

Human matrix metalloproteinases: An ubiquitarian class of enzymes involved in several pathological processes

Human matrix metalloproteinases (MMPs) belong to the M10 family of the MA clan of endopeptidases. They are ubiquitarian enzymes, structurally characterized by an active site where a Zn(2+) atom, coordinated by three histidines, plays the catalytic role, assisted by a glutamic acid as a general base. Various MMPs display different domain composition, which is very important for macromolecular substrates recognition. Substrate specificity is very different among MMPs, being often associated to their cellular compartmentalization and/or cellular type where they are expressed. An extensive review of the different MMPs structural and functional features is integrated with their pathological role in several types of diseases, spanning from cancer to cardiovascular diseases and to neurodegeneration. It emerges a very complex and crucial role played by these enzymes in many physiological and pathological processes

Ocrelizumab versus Interferon Beta-1a in Relapsing Multiple Sclerosis

Supported by F. Hoffmann–La Roche