Flow injection analysis of paracetamol using a biomimetic sensor as a sensitive and selective amperometric detector

This work describes the coupling of a biomimetic sensor to a flow injection system for the sensitive determination of paracetamol. The sensor was prepared as previously described in the literature (M. D. P. T. Sotomayor, A. Sigoli, M. R. V. Lanza, A. A. Tanaka and L. T. Kubota, J. Braz. Chem. Soc., 2008, 19, 734) by modifying a glassy carbon electrode surface with a Nafion (R) membrane doped with iron tetrapyridinoporphyrazine (FeTPyPz), a biomimetic catalyst of the P450 enzyme. The performance of the sensor for paracetamol detection was investigated and optimized in a flow injection system (FIA) using a wall jet electrochemical cell. Under optimized conditions a wide linear response range (1.0 x 10(-5) to 5.0 x 10(-2) mol L(-1)) was obtained, with a sensitivity of 2579 (+/- 129) mu A L mu mol(-1). The detection and quantification limits of the sensor for paracetamol in the FIA system were 1.0 and 3.5 mu mol L(-1), respectively. The analytical frequency was 51 samples h(-1), and over a period of five days (320 determinations) the biosensor maintained practically the same response. The system was successfully applied to paracetamol quantification in seven pharmaceutical formulations and in water samples from six rivers in Sao Paulo State, Brazil.

Learning Profile Identification Based on the Analysis of the User Context of Interaction

One of the e-learning environment goal is to attend the individual needs of students during the learning process. The adaptation of contents, activities and tools into different visualization or in a variety of content types is an important feature of this environment, bringing to the user the sensation that there are suitable workplaces to his profile in the same system. Nevertheless, it is important the investigation of student behaviour aspects, considering the context where the interaction happens, to achieve an efficient personalization process. The paper goal is to present an approach to identify the student learning profile analyzing the context of interaction. Besides this, the learning profile could be analyzed in different dimensions allows the system to deal with the different focus of the learning.

IEEE 802.15.4: a Federating Communication Protocol for Time-Sensitive Wireless Sensor Networks

Wireless Sensor Networks (WSNs) have been attracting increasing interests for developing a new generation of embedded systems with great potential for many applications such as surveillance, environment monitoring, emergency medical response and home automation. However, the communication paradigms in WSNs differ from the ones attributed to traditional wireless networks, triggering the need for new communication protocols. In this context, the recently standardised IEEE 802.15.4 protocol presents some potentially interesting features for deployment in wireless sensor network applications, such as power-efficiency, timeliness guarantees and scalability. Nevertheless, when addressing WSN applications with (soft/hard) timing requirements some inherent paradoxes emerge, such as power-efficiency versus timeliness, triggering the need of engineering solutions for an efficient deployment of IEEE 802.15.4 in WSNs. In this technical report, we will explore the most relevant characteristics of the IEEE 802.15.4 protocol for wireless sensor networks and present the most important challenges regarding time-sensitive WSN applications. We also provide some timing performance and analysis of the IEEE 802.15.4 that unveil some directions for resolving the previously mentioned paradoxes.

Artificial Intelligence in geospatial analysis: applications of self-organizing maps in the context of geographic information science.

A thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Information Systems.

Negotiation context analysis in electricity markets

Contextualization is critical in every decision making process. Adequate responses to problems depend not only on the variables with direct influence on the outcomes, but also on a correct contextualization of the problem regarding the surrounding environment. Electricity markets are dynamic environments with increasing complexity, potentiated by the last decades' restructuring process. Dealing with the growing complexity and competitiveness in this sector brought the need for using decision support tools. A solid example is MASCEM (Multi-Agent Simulator of Competitive Electricity Markets), whose players' decisions are supported by another multiagent system – ALBidS (Adaptive Learning strategic Bidding System). ALBidS uses artificial intelligence techniques to endow market players with adaptive learning capabilities that allow them to achieve the best possible results in market negotiations. This paper studies the influence of context awareness in the decision making process of agents acting in electricity markets. A context analysis mechanism is proposed, considering important characteristics of each negotiation period, so that negotiating agents can adapt their acting strategies to different contexts. The main conclusion is that context-dependant responses improve the decision making process. Suiting actions to different contexts allows adapting the behaviour of negotiating entities to different circumstances, resulting in profitable outcomes.

The Spanish cadet in the European military context a comparative analysis of the professional socialisation

Research on the attitudes, motivations and social and political behavior of European cadets have been made throughout the last decade. Nowadays Spain also joins those surveys. Thru the analysis of polling data, we can consider the different attitudes of Spanish cadets in relation with the other European ones. The conclusion is that although the Spanish political transition to democracy has not ended already in the military teaching system, there are a lot of similarities among Spanish and European cadets.

Activation of the heat shock response in plants by chlorophenols: transgenic Physcomitrella patens as a sensitive biosensor for organic pollutants.

The ability to detect early molecular responses to various chemicals is central to the understanding of biological impact of pollutants in a context of varying environmental cues. To monitor stress responses in a model plant, we used transgenic moss Physcomitrella patens expressing the beta-glucuronidase reporter (GUS) under the control of the stress-inducible promoter hsp17.3B. Following exposure to pollutants from the dye and paper industry, GUS activity was measured by monitoring a fluorescent product. Chlorophenols, heavy metals and sulphonated anthraquinones were found to specifically activate the hsp17.3B promoter (within hours) in correlation with long-term toxicity effects (within days). At mildly elevated physiological temperatures, the chemical activation of this promoter was strongly amplified, which considerably increased the sensitivity of the bioassay. Together with the activation of hsp17.3B promoter, chlorophenols induced endogenous chaperones that transiently protected a recombinant thermolabile luciferase (LUC) from severe heat denaturation. This sensitive bioassay provides an early warning molecular sensor to industrial pollutants under varying environments, in anticipation to long-term toxic effects in plants. Because of the strong cross-talk between abiotic and chemical stresses that we find, this P. patens line is more likely to serve as a direct toxicity bioassay for pollutants combined with environmental cues, than as an indicator of absolute toxicity thresholds for various pollutants. It is also a powerful tool to study the role of heat shock proteins (HSPs) in plants exposed to combined chemical and environmental stresses.

DIP-STR: Highly Sensitive Markers for the Analysis of Unbalanced Genomic Mixtures.

Samples containing highly unbalanced DNA mixtures from two individuals commonly occur both in forensic mixed stains and in peripheral blood DNA microchimerism induced by pregnancy or following organ transplant. Because of PCR amplification bias, the genetic identification of a DNA that contributes trace amounts to a mixed sample represents a tremendous challenge. This means that standard genetic markers, namely microsatellites, also referred as short tandem repeats (STR), and single-nucleotide polymorphism (SNP) have limited power in addressing common questions of forensic and medical genetics. To address this issue, we developed a molecular marker, named DIP-STR that relies on pairing deletion-insertion polymorphisms (DIP) with STR. This novel analytical approach allows for the unambiguous genotyping of a minor component in the presence of a major component, where DIP-STR genotypes of the minor were successfully procured at ratios up to 1:1,000. The compound nature of this marker generates a high level of polymorphism that is suitable for identity testing. Here, we demonstrate the power of the DIP-STR approach on an initial set of nine markers surveyed in a Swiss population. Finally, we discuss the limitations and potential applications of our new system including preliminary tests on clinical samples and estimates of their performance on simulated DNA mixtures.

Cluster analysis of behavioural and event-related potentials during a contingent negative variation paradigm in remitting-relapsing and benign forms of multiple sclerosis

Background: Event-related potentials (ERPs) may be used as a highly sensitive way of detecting subtle degrees of cognitive dysfunction. On the other hand, impairment of cognitive skills is increasingly recognised as a hallmark of patients suffering from multiple sclerosis (MS). We sought to determine the psychophysiological pattern of information processing among MS patients with the relapsing-remitting form of the disease and low physical disability considered as two subtypes: 'typical relapsing-remitting' (RRMS) and 'benign MS' (BMS). Furthermore, we subjected our data to a cluster analysis to determine whether MS patients and healthy controls could be differentiated in terms of their psychophysiological profile.Methods: We investigated MS patients with RRMS and BMS subtypes using event-related potentials (ERPs) acquired in the context of a Posner visual-spatial cueing paradigm. Specifically, our study aimed to assess ERP brain activity in response preparation (contingent negative variation -CNV) and stimuli processing in MS patients. Latency and amplitude of different ERP components (P1, eN1, N1, P2, N2, P3 and late negativity -LN) as well as behavioural responses (reaction time -RT; correct responses -CRs; and number of errors) were analyzed and then subjected to cluster analysis. Results: Both MS groups showed delayed behavioural responses and enhanced latency for long-latency ERP components (P2, N2, P3) as well as relatively preserved ERP amplitude, but BMS patients obtained more important performance deficits (lower CRs and higher RTs) and abnormalities related to the latency (N1, P3) and amplitude of ERPs (eCNV, eN1, LN). However, RRMS patients also demonstrated abnormally high amplitudes related to the preparation performance period of CNV (cCNV) and post-processing phase (LN). Cluster analyses revealed that RRMS patients appear to make up a relatively homogeneous group with moderate deficits mainly related to ERP latencies, whereas BMS patients appear to make up a rather more heterogeneous group with more severe information processing and attentional deficits. Conclusions: Our findings are suggestive of a slowing of information processing for MS patients that may be a consequence of demyelination and axonal degeneration, which also seems to occur in MS patients that show little or no progression in the physical severity of the disease over time.

Sensitive headspace gas chromatography analysis of free and conjugated 1-methoxy-2-propanol in urine

Glycol ethers still continue to be a workplace hazard due to their important use on an industrial scale. Currently, chronic occupational exposures to low levels of xenobiotics become increasingly relevant. Thus, sensitive analytical methods for detecting biomarkers of exposure are of interest in the field of occupational exposure assessment. 1-Methoxy-2-propanol (1M2P) is one of the dominant glycol ethers and the unmetabolized urinary fraction has been identified to be a good biological indicator of exposure. An existing analytical method including a solid-phase extraction and derivatization before GC/FID analysis is available but presents some disadvantages. We present here an alternative method for the determination of urinary 1M2P based on the headspace gas chromatography technique. We determined the 1M2P values by the direct headspace method for 47 samples that had previously been assayed by the solid-phase extraction and derivatization gas chromatography procedure. An inter-method comparison based on a Bland-Altman analysis showed that both techniques can be used interchangeably. The alternative method showed a tenfold lower limit of detection (0.1 mg/L) as well as good accuracy and precision which were determined by several urinary 1M2P analyses carried out on a series of urine samples obtained from a human volunteer study. The within- and between-run precisions were generally about 10%, which corresponds to the usual injection variability. We observed that the differences between the results obtained with both methods are not clinically relevant in comparison to the current biological exposure index of urinary 1M2P. Accordingly, the headspace gas chromatography technique turned out to be a more sensitive, accurate, and simple method for the determination of urinary 1M2P.[Authors]

Thermodynamics and log–contrast analysis in fluid geochemistry

There are two principal chemical concepts that are important for studying the naturalenvironment. The first one is thermodynamics, which describes whether a system is atequilibrium or can spontaneously change by chemical reactions. The second main conceptis how fast chemical reactions (kinetics or rate of chemical change) take place wheneverthey start. In this work we examine a natural system in which both thermodynamics andkinetic factors are important in determining the abundance of NH+4 , NO−2 and NO−3 insuperficial waters. Samples were collected in the Arno Basin (Tuscany, Italy), a system inwhich natural and antrophic effects both contribute to highly modify the chemical compositionof water. Thermodynamical modelling based on the reduction-oxidation reactionsinvolving the passage NH+4 -& NO−2 -& NO−3 in equilibrium conditions has allowed todetermine the Eh redox potential values able to characterise the state of each sample and,consequently, of the fluid environment from which it was drawn. Just as pH expressesthe concentration of H+ in solution, redox potential is used to express the tendency of anenvironment to receive or supply electrons. In this context, oxic environments, as thoseof river systems, are said to have a high redox potential because O2 is available as anelectron acceptor.Principles of thermodynamics and chemical kinetics allow to obtain a model that oftendoes not completely describe the reality of natural systems. Chemical reactions may indeedfail to achieve equilibrium because the products escape from the site of the rectionor because reactions involving the trasformation are very slow, so that non-equilibriumconditions exist for long periods. Moreover, reaction rates can be sensitive to poorly understoodcatalytic effects or to surface effects, while variables as concentration (a largenumber of chemical species can coexist and interact concurrently), temperature and pressurecan have large gradients in natural systems. By taking into account this, data of 91water samples have been modelled by using statistical methodologies for compositionaldata. The application of log–contrast analysis has allowed to obtain statistical parametersto be correlated with the calculated Eh values. In this way, natural conditions in whichchemical equilibrium is hypothesised, as well as underlying fast reactions, are comparedwith those described by a stochastic approach

New stakeholders, spaces and instruments of analysis in the context of energy relationships: Case studies from Kazakhstan and Turkmenistan

The disintegration of the USSR brought the emergence of a new geo-energy space in Central Asia. This space arose in the context of a global energy transition, which began in the late 1970s. Therefore, this new space in a changing energy world requires both new conceptual frameworks of analysis and the creation of new analytical tools. Taking into account this fact, our paper attempts to apply the theoretical framework of the Global Commodity Chain (GCC) to the case of natural resources in Central Asia. The aim of the paper is to check if there could be any Central Asia’s geo-energy space, assuming that this space would exist if natural resources were managed with regional criteria. The paper is divided into four sections. First an introduction that describes the new global energy context within natural resources of Central Asia would be integrated. Secondly, the paper justifies why the GCC methodology is suitable for the study of the value chains of energy products. Thirdly, we build up three cases studies (oil and uranium from Kazakhstan and gas from Turkmenistan) which reveal a high degree of uncertainty over the direction these chains will take. Finally, we present the conclusions of this study that state that the most plausible scenario would be the integration of energy resources of these countries in GCC where the core of the decision-making process will be far away from the region of Central Asia. Key words: Energy transition, geo-energy space, Global Commodity Chains, Central Asia

Clinicopathologic and molecular analysis of a choroidal pigmented schwannoma in the context of a PTEN hamartoma tumor syndrome.

PURPOSE: To report the first case of choroidal schwannoma in a patient affected by PTEN hamartoma tumor syndrome (PHTS) and investigate the molecular involvement of the phosphatase and tensin homolog (PTEN) and neurofibromin 2 (NF2) genes in this rare intraocular tumor. DESIGN: Observational case report. PARTICIPANT: A 10-year-old girl diagnosed with PHTS. METHODS: The enucleated specimen underwent histologic, immunohistochemical, and transmission electronic microscopy. The expression of PTEN and NF2 and their protein products were evaluated by reverse transcription-polymerase chain reaction and immunohistochemistry. Somatic mutations of PTEN and NF2, as well as allelic loss, were investigated by direct sequencing of DNA extracted from the tumor. PTEN epigenetic silencing was investigated by pyrosequencing. MAIN OUTCOME MEASURES: Histopathologic and molecular characterization of a choroidal pigmented schwannoma. RESULTS: Histopathologic, immunohistochemical, and electron microscopic analysis demonstrated features consistent with a pigmented cellular schwannoma of the choroid. We found no loss of heterozygosity at the genomic level for the PTEN germline mutation and no promoter hypermethylation or other somatic intragenic mutations. However, we observed an approximate 40% reduction of PTEN expression at both the mRNA and the protein level, indicating that the tumor was nonetheless functionally deficient for PTEN. Although DNA sequencing of NF2 failed to identify any pathologic variants, its expression was abolished within the tumor. CONCLUSIONS: We report the first description of a pigmented choroidal schwannoma in the context of a PHTS. This rare tumor showed a unique combination of reduction of PTEN and absence of NF2 expression.

Post-detection analysis for grating-based ultra-small angle X-ray scattering.

Until recently, the hard X-ray, phase-sensitive imaging technique called grating interferometry was thought to provide information only in real space. However, by utilizing an alternative approach to data analysis we demonstrated that the angular resolved ultra-small angle X-ray scattering distribution can be retrieved from experimental data. Thus, reciprocal space information is accessible by grating interferometry in addition to real space. Naturally, the quality of the retrieved data strongly depends on the performance of the employed analysis procedure, which involves deconvolution of periodic and noisy data in this context. The aim of this article is to compare several deconvolution algorithms to retrieve the ultra-small angle X-ray scattering distribution in grating interferometry. We quantitatively compare the performance of three deconvolution procedures (i.e., Wiener, iterative Wiener and Lucy-Richardson) in case of realistically modeled, noisy and periodic input data. The simulations showed that the algorithm of Lucy-Richardson is the more reliable and more efficient as a function of the characteristics of the signals in the given context. The availability of a reliable data analysis procedure is essential for future developments in grating interferometry.