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.

Nonempirical hyper-generalized-gradient functionals constructed from the Lieb-Oxford bound

A simple and completely general representation of the exact exchange-correlation functional of density-functional theory is derived from the universal Lieb-Oxford bound, which holds for any Coulomb-interacting system. This representation leads to an alternative point of view on popular hybrid functionals, providing a rationale for why they work and how they can be constructed. A similar representation of the exact correlation functional allows to construct fully nonempirical hyper-generalized-gradient approximations (HGGAs), radically departing from established paradigms of functional construction. Numerical tests of these HGGAs for atomic and molecular correlation energies and molecular atomization energies show that even simple HGGAs match or outperform state-of-the-art correlation functionals currently used in solid-state physics and quantum chemistry.

Inference of gene regulatory networks from time series by Tsallis entropy

Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

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.

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

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.

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.

THE IMPORTANCE OF DISAGREEING: CONTRARIANS AND EXTREMISM IN THE CODA MODEL

In this paper, we study the effects of introducing contrarians in a model of Opinion Dynamics where the agents have internal continuous opinions, but exchange information only about a binary choice that is a function of their continuous opinion, the CODA model. We observe that the hung election scenario that arises when contrarians are introduced in discrete opinion models still happens. However, it is weaker and it should not be expected in every election. Finally, we also show that the introduction of contrarians make the tendency towards extremism of the original model weaker, indicating that the existence of agents that prefer to disagree might be an important aspect and help society to diminish extremist opinions.

Association Between Urinary Incontinence in Elderly Patients and Caregiver Burden in the City of Sao Paulo/Brazil: Health, Wellbeing, and Ageing Study

Aim: Some elderly patients with incontinence require the care of third parties, known as caregivers. Such care can occur on a daily basis leaving little opportunity for the caregiver to take care of himself/herself. The aims are to assess the association between urinary incontinence in elderly patients and caregiver burden and identify independent factors for caregiver`s burden in the city of Sao Paulo, Brazil. Methods: The Pan-American Health Organization and World Health Organization coordinated a multicenter study named Health, Wellbeing and Aging (SABE Study) in elderly people living in seven countries of Latin America and the Caribbean. In Brazil, the study population carried out in Sao Paulo in the year 2000 and reassessed in 2006 (COHORT A). Urinary incontinence was assessed by ICIQ-SF and caregiver burden by means of Zarit Burden Scale. Results: A total of 327 patients with caregivers were included in the study. The general prevalence of urinary incontinence was 25.8%, higher among the women. There was a significant positive association between caregiver burden and incontinent patients, demonstrating that urinary incontinence in elderly patients produced greater caregiver burden. In the present study, the variables with significant correlations were assessed using the multivariate logistic regression model. Category 2 of the ICIQ-SF (incontinent patients) increased the chances of caregiver burden 1.96-fold in comparison to Category 1 (continent patients). Likewise, the category of impaired cognition increased the chances of caregiver burden 2.34-fold. Conclusions: Urinary incontinence and cognitive impairment in elderly patients were associated to an increase in caregiver burden. Neurourol. Urodynam. 30:1281-1285, 2011. (C) 2011 Wiley-Liss, Inc.

Risk factors for neonatal transfers from the Sapopemba free-standing birth centre to a hospital in Sao Paulo, Brazil

Objective: to identify risk factors associated with neonatal transfers from a free-standing birth centre to a hospital. Design: epidemiological case-control study. Setting: midwifery-led free-standing birth centre in Sao Paulo, Brazil. Participants: 96 newborns were selected from 2840 births between September 1998 and August 2005. Cases were defined as all new borns transferred from the birth centre to a hospital (n = 32), and controls were defined as new borns delivered at the same birth centre, during the same time period, and who had not been transferred to a hospital (n = 64). Measurements and findings: data were collected from medical records available at the birth centre. Univariate and multivariate analyses were performed using logistic regression. The multivariate analysis included outcomes with p<0.25, specifically: smoking during pregnancy, prenatal care appointments, labour complications, weight in relation to gestational age, and one-minute Apgar score. Of the foregoing outcomes, those that remained in the full regression model as a risk factor associated with neonatal transfer were: smoking during pregnancy [p = 0.009, odds ratio (OR) = 4.1,95% confidence interval (CI) 1.03-16.33], labour complications (p<0.001, OR = 5.5, 95% CI 1.06-28.26) and one-minute Apgar score <= 7 (p<0.001, OR = 7.8,95% CI 1.62-37.03). Key conclusions and implications for practice: smoking during pregnancy, labour complications and one-minute Apgar score <= 7 were confirmed as risk factors for neonatal transfer from the birth centre to a hospital. The identified risk factors can help to improve institutional protocols and formulate hypotheses for other studies. (C) 2009 Elsevier Ltd. All rights reserved.