Fluorescence spectroscopy for the detection of tongue carcinoma - validation in an animal model

The efficacy of fluorescence spectroscopy to detect squamous cell carcinoma is evaluated in an animal model following laser excitation at 442 and 532 nm. Lesions are chemically induced with a topical DMBA application at the left lateral tongue of Golden Syrian hamsters. The animals are investigated every 2 weeks after the 4th week of induction until a total of 26 weeks. The right lateral tongue of each animal is considered as a control site (normal contralateral tissue) and the induced lesions are analyzed as a set of points covering the entire clinically detectable area. Based on fluorescence spectral differences, four indices are determined to discriminate normal and carcinoma tissues, based on intraspectral analysis. The spectral data are also analyzed using a multivariate data analysis and the results are compared with histology as the diagnostic gold standard. The best result achieved is for blue excitation using the KNN (K-nearest neighbor, a interspectral analysis) algorithm with a sensitivity of 95.7% and a specificity of 91.6%. These high indices indicate that fluorescence spectroscopy may constitute a fast noninvasive auxiliary tool for diagnostic of cancer within the oral cavity. (C) 2008 Society of Photo-Optical Instrumentation Engineers.

Statistics of opinion domains of the majority-vote model on a square lattice

The existence of juxtaposed regions of distinct cultures in spite of the fact that people's beliefs have a tendency to become more similar to each other's as the individuals interact repeatedly is a puzzling phenomenon in the social sciences. Here we study an extreme version of the frequency-dependent bias model of social influence in which an individual adopts the opinion shared by the majority of the members of its extended neighborhood, which includes the individual itself. This is a variant of the majority-vote model in which the individual retains its opinion in case there is a tie among the neighbors' opinions. We assume that the individuals are fixed in the sites of a square lattice of linear size L and that they interact with their nearest neighbors only. Within a mean-field framework, we derive the equations of motion for the density of individuals adopting a particular opinion in the single-site and pair approximations. Although the single-site approximation predicts a single opinion domain that takes over the entire lattice, the pair approximation yields a qualitatively correct picture with the coexistence of different opinion domains and a strong dependence on the initial conditions. Extensive Monte Carlo simulations indicate the existence of a rich distribution of opinion domains or clusters, the number of which grows with L(2) whereas the size of the largest cluster grows with ln L(2). The analysis of the sizes of the opinion domains shows that they obey a power-law distribution for not too large sizes but that they are exponentially distributed in the limit of very large clusters. In addition, similarly to other well-known social influence model-Axelrod's model-we found that these opinion domains are unstable to the effect of a thermal-like noise.

LIMIT THEOREMS FOR A GENERAL STOCHASTIC RUMOUR MODEL

We study a general stochastic rumour model in which an ignorant individual has a certain probability of becoming a stifler immediately upon hearing the rumour. We refer to this special kind of stifler as an uninterested individual. Our model also includes distinct rates for meetings between two spreaders in which both become stiflers or only one does, so that particular cases are the classical Daley-Kendall and Maki-Thompson models. We prove a Law of Large Numbers and a Central Limit Theorem for the proportions of those who ultimately remain ignorant and those who have heard the rumour but become uninterested in it.

Antimicrobial mechanisms behind photodynamic effect in the presence of hydrogen peroxide

This study describes the use of methylene blue (MB) plus light (photodynamic inactivation, PDI) in the presence of hydrogen peroxide (H(2)O(2)) to kill Staphylococcus aureus, Escherichia coli, and Candida albicans. When H(2)O(2) was added to MB plus light there was an increased antimicrobial effect, which could be due to a change in the type of ROS generated or increased microbial uptake of MB. To clarify the mechanism, the production of ROS was investigated in the presence and absence of H(2)O(2). It was observed that ROS production was almost inhibited by the presence of H(2)O(2) when cells were not present. In addition, experiments using different sequence combinations of MB and H(2)O(2) were performed and MB optical properties inside the cell were analyzed. Spectroscopy experiments suggested that the amount of MB was higher inside the cells when H(2)O(2) was used before or simultaneously with PDI, and ROS formation inside C. albicans cells confirmed that ROS production is higher in the presence of H(2)O(2). Moreover enzymatic reduction of MB by E. coli during photosensitizer uptake to the photochemically inactive leucoMB could be reversed by the oxidative effects of hydrogen peroxide, increasing ROS formation inside the microorganism. Therefore, the combination of a photosensitizer such as MB and H(2)O(2) is an interesting approach to improve PDI efficiency.

Interference with Hemozoin Formation Represents an Important Mechanism of Schistosomicidal Action of Antimalarial Quinoline Methanols

Background: The parasitic trematode Schistosoma mansoni is one of the major causative agents of human schistosomiasis, which afflicts 200 million people worldwide. Praziquantel remains the main drug used for schistosomiasis treatment, and reliance on the single therapy has been prompting the search for new therapeutic compounds against this disease. Our group has demonstrated that heme crystallization into hemozoin (Hz) within the S. mansoni gut is a major heme detoxification route with lipid droplets involved in this process and acting as a potential chemotherapeutical target. In the present work, we investigated the effects of three antimalarial compounds, quinine (QN), quinidine (QND) and quinacrine (QCR) in a murine schistosomiasis model by using a combination of biochemical, cell biology and molecular biology approaches. Methodology/Principal Findings: Treatment of S. mansoni-infected female Swiss mice with daily intraperitoneal injections of QN, and QND (75 mg/kg/day) from the 11(th) to 17(th) day after infection caused significant decreases in worm burden (39%-61%) and egg production (42%-98%). Hz formation was significantly inhibited (40%-65%) in female worms recovered from QN- and QND-treated mice and correlated with reduction in the female worm burden. We also observed that QN treatment promoted remarkable ultrastructural changes in male and female worms, particularly in the gut epithelium and reduced the granulomatous reaction to parasite eggs trapped in the liver. Microarray gene expression analysis indicated that QN treatment increased the expression of transcripts related to musculature, protein synthesis and repair mechanisms. Conclusions: The overall significant reduction in several disease burden parameters by the antimalarial quinoline methanols indicates that interference with Hz formation in S. mansoni represents an important mechanism of schistosomicidal action of these compounds and points out the heme crystallization process as a valid chemotherapeutic target to treat schistosomiasis.

Mechanism and model of the oscillatory electro-oxidation of methanol

A mechanism for the kinetic instabilities observed in the galvanostatic electro-oxidation of methanol is suggested and a model developed. The model is investigated using stoichiometric network analysis as well as concepts from algebraic geometry (polynomial rings and ideal theory) revealing the occurrence of a Hopf and a saddle-node bifurcation. These analytical solutions are confirmed by numerical integration of the system of differential equations. (C) 2010 American Institute of Physics

Shelf and estuarine transport mechanisms affecting the supply of competent larvae in a suite of brachyuran crabs with different life histories

Supply of competent larvae to the benthic habitat is a major determinant of population dynamics in coastal and estuarine invertebrates with an indirect life cycle. Larval delivery may depend not only on physical transport mechanisms, but also on larval behavior and physiological progress to the competent stage. Yet, the combined analysis of such factors has seldom been attempted. We used time-series analyses to examine tide- and wind-driven mechanisms responsible for the supply of crab megalopae to an estuarine river under a major marine influence in SW Spain, and monitored the vertical distribution of upstream moving megalopae, their net flux and competent state. The species Panopeus africanus (estuarine), Brachynotus sexdentatus (euryhaline) and Nepinnotheres pinnotheres (coastal) comprised 80% of the whole sample, and responded in a similar way to tide and wind forcing. Tidal range was positively correlated to supply, with maxima 0 to 1 d after spring tides, suggesting selective tidal stream transport. Despite being extensively subjected to upwelling, downwind drift under the effect of westerlies, not Ekman transport, explained residual supply variation at our sampling area. Once in the estuary, net flux and competence state matched the expected trends. Net upstream flux increased from B. sexdentatus to P. africanus, favoring transport to a sheltered coastal habitat (N. pinnotheres), or to the upper estuary (P. africanus). Competence state was highest in N. pinnotheres, intermediate in B. sexdentatus and lowest in P. africanus, as expected if larvae respond to cues from adequate benthic habitat. P. africanus megalopae were found close to the bottom, not above, rendering slower upstream transport than anticipated.

Soil Carbon Turnover Measurement by Physical Fractionation at a Forest-to-Pasture Chronosequence in the Brazilian Amazon

The effect of conversion from forest-to-pasture upon soil carbon stocks has been intensively discussed, but few studies focus on how this land-use change affects carbon (C) distribution across soil fractions in the Amazon basin. We investigated this in the 20 cm depth along a chronosequence of sites from native forest to three successively older pastures. We performed a physicochemical fractionation of bulk soil samples to better understand the mechanisms by which soil C is stabilized and evaluate the contribution of each C fraction to total soil C. Additionally, we used a two-pool model to estimate the mean residence time (MRT) for the slow and active pool C in each fraction. Soil C increased with conversion from forest-to-pasture in the particulate organic matter (> 250 mu m), microaggregate (53-250 mu m), and d-clay (< 2 mu m) fractions. The microaggregate comprised the highest soil C content after the conversion from forest-to-pasture. The C content of the d-silt fraction decreased with time since conversion to pasture. Forest-derived C remained in all fractions with the highest concentration in the finest fractions, with the largest proportion of forest-derived soil C associated with clay minerals. Results from this work indicate that microaggregate formation is sensitive to changes in management and might serve as an indicator for management-induced soil carbon changes, and the soil C changes in the fractions are dependent on soil texture.

Simulation of Soil Carbon Dynamics under Sugarcane with the CENTURY Model

Currently there is a trend for the expansion of the area cropped with sugarcane (Saccharum officinarum L.), driven by an increase in the world demand for biofuels, due to economical, environmental, and geopolitical issues. Although sugarcane is traditionally harvested by burning dried leaves and tops, the unburned, mechanized harvest has been progressively adopted. The use of process based models is useful in understanding the effects of plant litter in soil C dynamics. The objective of this work was to use the CENTURY model in evaluating the effect of sugarcane residue management in the temporal dynamics of soil C. The approach taken in this work was to parameterize the CENTURY model for the sugarcane crop, to simulate the temporal dynamics of soil C, validating the model through field experiment data, and finally to make predictions in the long term regarding soil C. The main focus of this work was the comparison of soil C stocks between the burned and unburned litter management systems, but the effect of mineral fertilizer and organic residue applications were also evaluated. The simulations were performed with data from experiments with different durations, from 1 to 60 yr, in Goiana and Timbauba, Pernambuco, and Pradopolis, Sao Paulo, all in Brazil; and Mount Edgecombe, Kwazulu-Natal, South Africa. It was possible to simulate the temporal dynamics of soil C (R(2) = 0.89). The predictions made with the model revealed that there is, in the long term, a trend for higher soil C stocks with the unburned management. This increase is conditioned by factors such as climate, soil texture, time of adoption of the unburned system, and N fertilizer management.

Multifractal regime transition in a modified minority game model

The search for more realistic modeling of financial time series reveals several stylized facts of real markets. In this work we focus on the multifractal properties found in price and index signals. Although the usual minority game (MG) models do not exhibit multifractality, we study here one of its variants that does. We show that the nonsynchronous MG models in the nonergodic phase is multifractal and in this sense, together with other stylized facts, constitute a better modeling tool. Using the structure function (SF) approach we detected the stationary and the scaling range of the time series generated by the MG model and, from the linear (non-linear) behavior of the SF we identified the fractal (multifractal) regimes. Finally, using the wavelet transform modulus maxima (WTMM) technique we obtained its multifractal spectrum width for different dynamical regimes. (C) 2009 Elsevier Ltd. All rights reserved.

An opinion dynamics model for the diffusion of innovations

We study the dynamics of the adoption of new products by agents with continuous opinions and discrete actions (CODA). The model is such that the refusal in adopting a new idea or product is increasingly weighted by neighbor agents as evidence against the product. Under these rules, we study the distribution of adoption times and the final proportion of adopters in the population. We compare the cases where initial adopters are clustered to the case where they are randomly scattered around the social network and investigate small world effects on the final proportion of adopters. The model predicts a fat tailed distribution for late adopters which is verified by empirical data. (C) 2009 Elsevier B.V. All rights reserved.

Multifractality in the random parameter model for multivariate time series

The Random Parameter model was proposed to explain the structure of the covariance matrix in problems where most, but not all, of the eigenvalues of the covariance matrix can be explained by Random Matrix Theory. In this article, we explore the scaling properties of the model, as observed in the multifractal structure of the simulated time series. We use the Wavelet Transform Modulus Maxima technique to obtain the multifractal spectrum dependence with the parameters of the model. The model shows a scaling structure compatible with the stylized facts for a reasonable choice of the parameter values. (C) 2009 Elsevier B.V. All rights reserved.

A Markovian model market-Akerlof`s lemons and the asymmetry of information

In this work we study an agent based model to investigate the role of asymmetric information degrees for market evolution. This model is quite simple and may be treated analytically since the consumers evaluate the quality of a certain good taking into account only the quality of the last good purchased plus her perceptive capacity beta. As a consequence, the system evolves according to a stationary Markov chain. The value of a good offered by the firms increases along with quality according to an exponent alpha, which is a measure of the technology. It incorporates all the technological capacity of the production systems such as education, scientific development and techniques that change the productivity rates. The technological level plays an important role to explain how the asymmetry of information may affect the market evolution in this model. We observe that, for high technological levels, the market can detect adverse selection. The model allows us to compute the maximum asymmetric information degree before the market collapses. Below this critical point the market evolves during a limited period of time and then dies out completely. When beta is closer to 1 (symmetric information), the market becomes more profitable for high quality goods, although high and low quality markets coexist. The maximum asymmetric information level is a consequence of an ergodicity breakdown in the process of quality evaluation. (C) 2011 Elsevier B.V. All rights reserved.

MODELING SCIENTIFIC AGENTS FOR A BETTER SCIENCE

Science is a fundamental human activity and we trust its results because it has several error-correcting mechanisms. It is subject to experimental tests that are replicated by independent parts. Given the huge amount of information available and the information asymetry between producers and users of knowledge, scientists have to rely on the reports of others. This makes it possible for social effects to influence the scientific community. Here, an Opinion Dynamics agent model is proposed to describe this situation. The influence of Nature through experiments is described as an external field that acts on the experimental agents. We will see that the retirement of old scientists can be fundamental in the acceptance of a new theory. We will also investigate the interplay between social influence and observations. This will allow us to gain insight in the problem of when social effects can have negligible effects in the conclusions of a scientific community and when we should worry about them.

Land planarians (Platyhelminthes) as a model organism for fine-scale phylogeographic studies: understanding patterns of biodiversity in the Brazilian Atlantic Forest hotspot

The Brazilian Atlantic Forest is one of the richest biodiversity hotspots of the world. Paleoclimatic models have predicted two large stability regions in its northern and central parts, whereas southern regions might have suffered strong instability during Pleistocene glaciations. Molecular phylogeographic and endemism studies show, nevertheless, contradictory results: although some results validate these predictions, other data suggest that paleoclimatic models fail to predict stable rainforest areas in the south. Most studies, however, have surveyed species with relatively high dispersal rates whereas taxa with lower dispersion capabilities should be better predictors of habitat stability. Here, we have used two land planarian species as model organisms to analyse the patterns and levels of nucleotide diversity on a locality within the Southern Atlantic Forest. We find that both species harbour high levels of genetic variability without exhibiting the molecular footprint of recent colonization or population expansions, suggesting a long-term stability scenario. The results reflect, therefore, that paleoclimatic models may fail to detect refugia in the Southern Atlantic Forest, and that model organisms with low dispersal capability can improve the resolution of these models.