Effects of physical exercise training in DNA damage and repair - could the difference be in hOGG1 Ser326Cys polymorphism?

Acute physical exercise is associated with increased oxygen consumption, which could result in an increased formation of reactive oxygen species (ROS). ROS can react with several organic structures, namely DNA, causing strand breaks and a variety of modified bases in DNA. Physical exercise training seems to decrease the incidence of oxidative stress-associated diseases, and is considered as a key component of a healthy lifestyle. This is a result of exercise-induced adaptation, which has been associated with the possible increase in antioxidant activity and in oxidative damage repair enzymes, leading to an improved physiological function and enhanced resistance to oxidative stress (Radak et al. 2008). Human 8-oxoguanine DNA glycosylase 1 (hOGG1) is involved in the base excision repair (BER) pathway and encodes an enzyme responsible for removing the most common product of oxidative damage in DNA, 8-hydroxyguanine (8-OH-G). The genetic polymorphism of hOGG1 at codon 326 results in a serine (Ser) to cysteine (Cys) amino acid substitution (Ser326Cys). It has been suggested that the carriers of at least one hOGG1Cys variant allele exhibit lower 8-OH-G excision activity than the wild-type (Wilson et al. 2011). The aim of this study was to investigate the possible influence of hOGG1 Ser326Cys polymorphism on DNA damage and repair activity in response to 16 weeks of combined physical exercise training, in thirty healthy Caucasian men. Comet assay was carried out using peripheral blood lymphocytes and enabled the evaluation of DNA damage, both strand breaks and FPG-sensitive sites, and DNA repair activity. Genotypes were determined by PCR-RFLP analysis. The subjects with Ser/Ser genotype were considered as wild-type group (n=20), Ser/Cys and Cys/Cys genotype were analyzed together as mutant group (n=10). Regarding differences between pre and post-training in the wild-type group, the results showed a significant decrease in DNA strand breaks (DNA SBs) (p=0.002) and also in FPG-sensitive sites (p=0.017). No significant differences were observed in weight (p=0.389) and in lipid peroxidation (MDA) (p=0.102). A significant increase in total antioxidant capacity (evaluated by ABTS) was observed (p=0.010). Regarding mutant group, the results showed a significant decrease in DNA SBs (p=0.008) and in weight (p=0.028). No significant differences were observed in FPG-sensitive sites (p=0.916), in ABTS (p=0.074) and in MDA (p=0.086). No significant changes in DNA repair activity were observed in both genotype groups. This preliminary study suggests the possibility of different responses in DNA damage to physical exercise training, considering the hOGG1 Ser326Cys polymorphism.

Vertex component analysis: a fast algorithm to extract endmembers spectra from hyperspectral data

Chapter in Book Proceedings with Peer Review First Iberian Conference, IbPRIA 2003, Puerto de Andratx, Mallorca, Spain, JUne 4-6, 2003. Proceedings

Self-assembly in chains, rings, and branches: a single component system with two critical points

Agências financiadoras: FCT - PEstOE/FIS/UI0618/2011; PTDC/FIS/098254/2008 ERC-PATCHYCOLLOIDS e MIUR-PRIN

Application of continuous wavelet transform to the analysis of the modulus of the fractional Fourier transform bands for resolving two component mixture

In this paper, the fractional Fourier transform (FrFT) is applied to the spectral bands of two component mixture containing oxfendazole and oxyclozanide to provide the multicomponent quantitative prediction of the related substances. With this aim in mind, the modulus of FrFT spectral bands are processed by the continuous Mexican Hat family of wavelets, being denoted by MEXH-CWT-MOFrFT. Four modulus sets are obtained for the parameter a of the FrFT going from 0.6 up to 0.9 in order to compare their effects upon the spectral and quantitative resolutions. Four linear regression plots for each substance were obtained by measuring the MEXH-CWT-MOFrFT amplitudes in the application of the MEXH family to the modulus of the FrFT. This new combined powerful tool is validated by analyzing the artificial samples of the related drugs, and it is applied to the quality control of the commercial veterinary samples.

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

Application of Continuous Wavelet Transform to the Analysis of the Modulus of the Fractional Fourier Transform Bands for Resolving Two Component Mixture

In this paper, the fractional Fourier transform (FrFT) is applied to the spectral bands of two component mixture containing oxfendazole and oxyclozanide to provide the multicomponent quantitative prediction of the related substances. With this aim in mind, the modulus of FrFT spectral bands are processed by the continuous Mexican Hat family of wavelets, being denoted by MEXH-CWT-MOFrFT. Four modulus sets are obtained for the parameter a of the FrFT going from 0.6 up to 0.9 in order to compare their effects upon the spectral and quantitative resolutions. Four linear regression plots for each substance were obtained by measuring the MEXH-CWT-MOFrFT amplitudes in the application of the MEXH family to the modulus of the FrFT. This new combined powerful tool is validated by analyzing the artificial samples of the related drugs, and it is applied to the quality control of the commercial veterinary samples.

Bait formulations of molluscicides and their effects on biochemical changes in the ovotestis of snail Lymnaea acuminata (Mollusca; Gastropoda:Lymnaeidae)

The effect of sub-lethal feeding of bait formulations containing molluscicidal component of Ferula asafoetida (ferulic acid, umbelliferone), Syzygium aromaticum (eugenol) and Carum carvi (limonene) on biochemical changes in the ovotestis of snail Lymnaea acuminata were studied. Bait formulations feeding to L. acuminata were studied in clear glass aquaria having diameter of 30 cm. Baits were prepared from different binary combinations of attractant amino acid (valine, aspartic acid, lysine and alanine 10 mM) in 100 mL of 2% agar solution + sub-lethal (20% and 60% of 24h LC50) doses of different molluscicides (ferulic acid, umbelliferone, eugenol and limonene). These baits caused maximum significant reduction in free amino acid, protein, DNA, RNA levels i.e. 41.37, 23.56, 48.36 and 14.29% of control in the ovotestis of the snail, respectively. Discontinuation of feeding after treatment of 60% of 96h LC50 of molluscicide containing bait for next 72h caused a significant recovery in free amino acid, protein, DNA and RNA levels in the ovotestis of L. acuminata.

EFFECTS OF SINGLE, BINARY AND TERTIARY COMBINATIONS WITH Jatropha gossypifolia AND OTHER PLANT-DERIVED MOLLUSCICIDES ON REPRODUCTION AND SURVIVAL OF THE SNAIL Lymnaea acuminata

The effect of sub-lethal doses (40% and 80% of LC50/24h) of plant derived molluscicides of singly, binary (1:1) and tertiary (1:1:1) combinations of the Rutin, Ellagic acid, Betulin and taraxerol with J. gossypifolia latex, leaf and stem bark powder extracts and their active component on the reproduction of freshwater snail Lymnaea acuminata have been studied. It was observed that the J. gossypifolia latex, stem bark, individual leaf and their combinations with other plant derived active molluscicidal components caused a significant reduction in fecundity, hatchability and survival of young snails. It is believed that sub-lethal exposure of these molluscicides on snail reproduction is a complex process involving more than one factor in reducing the reproductive capacity.

The effects Ishares IBovespa index fund creation on the liquidity of underlying stocks

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Integration of geometric consistency contributory factors in three-leg junctions collision prediction models of Portuguese two-lane national highways

This paper aims at developing a collision prediction model for three-leg junctions located in national roads (NR) in Northern Portugal. The focus is to identify factors that contribute for collision type crashes in those locations, mainly factors related to road geometric consistency, since literature is scarce on those, and to research the impact of three modeling methods: generalized estimating equations, random-effects negative binomial models and random-parameters negative binomial models, on the factors of those models. The database used included data published between 2008 and 2010 of 177 three-leg junctions. It was split in three groups of contributing factors which were tested sequentially for each of the adopted models: at first only traffic, then, traffic and the geometric characteristics of the junctions within their area of influence; and, lastly, factors which show the difference between the geometric characteristics of the segments boarding the junctionsâ area of influence and the segment included in that area were added. The choice of the best modeling technique was supported by the result of a cross validation made to ascertain the best model for the three sets of researched contributing factors. The models fitted with random-parameters negative binomial models had the best performance in the process. In the best models obtained for every modeling technique, the characteristics of the road environment, including proxy measures for the geometric consistency, along with traffic volume, contribute significantly to the number of collisions. Both the variables concerning junctions and the various national highway segments in their area of influence, as well as variations from those characteristics concerning roadway segments which border the already mentioned area of influence have proven their relevance and, therefore, there is a rightful need to incorporate the effect of geometric consistency in the three-leg junctions safety studies.

Bioremediation of diesel contaminated soils : an investigation into the effects of biosurfactant and organic matter amendments

The aim of this study was to investigate the effects of biosurfactants and organic matter amendments on the bioremediation of diesel contaminated soil. Two strains of Pseudomonas aeruginosa with the ability to produce biosurfactant were isolated from a water and soil sample in Co. Sligo. The first strain, Isolate A, produced a biosurfactant which contained four rhamnose containing compounds, when grown in proteose peptone glucose ammonium salts medium with glucose as the carbon source. Two of the components were identified as rhamnolipid 1 and 2 whilst the other two components were unidentified. The second strain, Isolate GO, when grown in similar conditions produced a biosurfactant which contained only rhamnolipid 2. The type of aeration system used had a significant effect on the abiotic removal of diesel from soil. Forced aeration at a rate of 120L 02/kg soil/ hour resulted in the greatest removal. Over a 112 day incubation period this type o f aeration resulted in the removal o f 48% o f total hexane extractable material. In relation to bioremediation of the diesel contaminated sandy soil, amending the soil with two inorganic nutrients, KH2PO4 and NÜ4N03, significantly enhanced the removal of diesel, especially the «- alkanes, when compared to an unamended control. The biosurfactant from Isolate A and a biosurfactant produced by Pseudomonas aeruginosa NCIMB 8628 (a known biosurfactant producer), when applied at a concentration of three times their critical micelle concentration, had a neutral effect on the biodégradation o f diesel contaminated sandy soil, even in the presence o f inorganic nutrients. It was deduced that the main reason for this neutral effect was because they were both readily biodegraded by the indigenous microorganisms. The most significant removal of diesel occurred when the soils were amended with two organic materials plus the inorganic nutrients. Amendment of the diesel contaminated soil with spent brewery grain (SBG) removed significantly more diesel than amendment with dried molassed sugar beet pulp (DMSBP). After a 108 day incubation period, amendment of the diesel contaminated soil with DMSBP plus inorganic nutrients and SBG plus inorganic nutrients resulted in 72 and 89% removal of diesel range organics (DRO), in comparison to 41% removal of DRO in an inorganic nutrient amended control. The first order kinetic model described the degradation of the different diesel components with high correlation and was used to calculate Vi lives. The V2 life, of the total «-alkanes in the diesel was reduced from 40 days in the control to 8.5 and 5.1 days in the presence of DMSBP and SBG, respectively. The V2 life o f the unresolved complex mixture (UCM) in the diesel contaminated soil was also significantly reduced in the presence o f the two organics. DMSBP and SBG addition reduced UCM V2 life to 86 and 43 days, respectively, compared to 153 days in the control. The component of diesel whose removal was enhanced the greatest through the organic material amendments was the isoprenoid, pristane, a compound which until recently was thought to be nonbiodegradable and was used as an inert biomarker in oil degradation studies. The V2 life of pristane was reduced from 533 days in the nutrient amended control to 49.5 and 19.5 days in DMSBP and SBG amended soils. These results indicate that the addition o f the DMSBP and SBG to diesel contaminated soil stimulated diesel biodégradation, probably by enhancing the indigenous diesel degrading microbial population to degrade diesel hydrocarbons, whilst the addition o f biosurfactants had no enhanced effect on the bioremediation process.

Comparative Statics of Asset Prices: the effect of other assets' risk

Currently, financial economics is unable to predict changes in asset prices with respect to changes in the underlying risk factors, even when an asset's dividend is independent of a given factor. This paper takes steps towards addressing this issue by highlighting a crucial component of wealth effects on asset prices hitherto ignored by the literature. Changes in wealth do not only alter an agents risk aversion, but also her perceived 'riskiness' of a security. The latter enhances significantly the extent to which market- clearing leads to endogenously-generated correlation across asset prices, over and above that induced by correlation between payoffs, giving the appearance of 'contagion.'

Effects of anxiety on visuospatial pattern discrimination and decision-making processes: what can we learn from brain dynamics ?

Detection and discrimination of visuospatial input involve at least extracting, selecting and encoding relevant information and decision-making processes allowing selecting a response. These two operations are altered, respectively, by attentional mechanisms that change discrimination capacities, and by beliefs concerning the likelihood of uncertain events. Information processing is tuned by the attentional level that acts like a filter on perception, while decision-making processes are weighed by subjective probability of risk. In addition, it has been shown that anxiety could affect the detection of unexpected events through the modification of the level of arousal. Consequently, purpose of this study concerns whether and how decision-making and brain dynamics are affected by anxiety. To investigate these questions, the performance of women with either a high (12) or a low (12) STAI-T (State-Trait Anxiety Inventory, Spielberger, 1983) was examined in a decision-making visuospatial task where subjects have to recognize a target visual pattern from non-target patterns. The target pattern was a schematic image of furniture arranged in such a way as to give the impression of a living room. Non-target patterns were created by either the compression or the dilatation of the distances between objects. Target and non-target patterns were always presented in the same configuration. Preliminary behavioral results show no group difference in reaction time. In addition, visuo-spatial abilities were analyzed trough the signal detection theory for quantifying perceptual decisions in the presence of uncertainty (Green and Swets, 1966). This theory treats detection of a stimulus as a decision-making process determined by the nature of the stimulus and cognitive factors. Astonishingly, no difference in d' (corresponding to the distance between means of the distributions) and c (corresponds to the likelihood ratio) indexes was observed. Comparison of Event-related potentials (ERP) reveals that brain dynamics differ according to anxiety. It shows differences in component latencies, particularly a delay in anxious subjects over posterior electrode sites. However, these differences are compensated during later components by shorter latencies in anxious subjects compared to non-anxious one. These inverted effects seem indicate that the absence of difference in reaction time rely on a compensation of attentional level that tunes cortical activation in anxious subjects, but they have to hammer away to maintain performance.

Long-term effects of cannabis on brain structure.

The dose-dependent toxicity of the main psychoactive component of cannabis in brain regions rich in cannabinoid CB1 receptors is well known in animal studies. However, research in humans does not show common findings across studies regarding the brain regions that are affected after long-term exposure to cannabis. In the present study, we investigate (using Voxel-based Morphometry) gray matter changes in a group of regular cannabis smokers in comparison with a group of occasional smokers matched by the years of cannabis use. We provide evidence that regular cannabis use is associated with gray matter volume reduction in the medial temporal cortex, temporal pole, parahippocampal gyrus, insula, and orbitofrontal cortex; these regions are rich in cannabinoid CB1 receptors and functionally associated with motivational, emotional, and affective processing. Furthermore, these changes correlate with the frequency of cannabis use in the 3 months before inclusion in the study. The age of onset of drug use also influences the magnitude of these changes. Significant gray matter volume reduction could result either from heavy consumption unrelated to the age of onset or instead from recreational cannabis use initiated at an adolescent age. In contrast, the larger gray matter volume detected in the cerebellum of regular smokers without any correlation with the monthly consumption of cannabis may be related to developmental (ontogenic) processes that occur in adolescence.

Functional effects of Na+,K+-ATPase gene mutations linked to familial hemiplegic migraine.

Familial hemiplegic migraine type 2, an autosomal dominant form of migraine with aura, has been associated with four distinct mutations in the alpha2-subunit of the Na+,K+-ATPase. We have introduced these mutations in the alpha2-subunit of the human Na+,K+-ATPase and the corresponding mutations in the Bufo marinus alpha1-subunit and studied these mutants by expression in Xenopus oocyte. Metabolic labeling studies showed that the mutants were synthesized and associated with the beta-subunit, except for the alpha2HW887R mutant, which was poorly synthesized, and the alpha1BW890R, which was partially retained in the endoplasmic reticulum. [3H]ouabain binding showed the presence of the alpha2HR689Q and alpha2HM731T at the membrane, whereas the alpha2HL764P and alpha2HW887R could not be detected. Functional studies with the mutants of the B. marinus Na+,K+-ATPase showed a reduced or abolished electrogenic activity and a low K+ affinity for the alpha1BW890R mutant. Through different mechanisms, all these mutations result in a strong decrease of the functional expression of the Na+,K+-pump. The decreased activity in alpha2 isoform of the Na+,K+-pump expressed in astrocytes seems an essential component of hemiplegic migraine pathogenesis and may be responsible for the cortical spreading depression, which is one of the first events in migraine attacks.