Photic driving in the electroencephalogram of children and adolescents: harmonic structure and relation to the resting state

In order to identify latent bioelectrical oscillators, 15 normal subjects (aged 9-17 years, 8 males, 7 females) were subjected to intermittent photic stimulation. The EEG amplitude spectra corresponding to the 11 fixed frequencies of stimulation presented (3-24 Hz) were combined to form "profiles" of the driving reaction in the right occipital area. The driving response varied with frequency, and was demonstrable in 70-100% of cases (using as criterion peak amplitudes 20% larger than those of the neighbors). The strongest responses were observed at the frequency closest to the alpha peak of the resting EEG. A secondary profile maximum was in the theta band. In 10 subjects, this maximum exceeded half the alpha peak (with an average of 72.4% of the alpha peak), while in the resting spectra, theta amplitudes were much lower than the alpha maxima. This responsiveness in theta activity seems to be characteristic of prepubertal and pubertal subjects. The profiles and resting EEG spectra showed a highly significant Pearson's correlation, with the peak in the theta band of the profiles being the main difference observed between them. The correlation coefficient was significantly correlated with the ratio of the maxima in the theta and alpha bands (R = -0.77, P<0.001). The correlation coefficient between profile and resting spectrum may be a useful indicator in screening methods used to reveal latent cerebral oscillators. Profiles for the second and third harmonics were correlated with those of the first harmonic (fundamental frequency), when considering the corresponding EEG frequencies. Peak frequencies in all three profiles were close to those of the individual's background alpha rhythm, and peak amplitudes in higher harmonics were not much lower than those of the fundamental frequency (mean values of 84 and 63%, for second and third harmonics, respectively).

Local Binary Patterns in Focal-Plane Processing. Analysis and Applications

Feature extraction is the part of pattern recognition, where the sensor data is transformed into a more suitable form for the machine to interpret. The purpose of this step is also to reduce the amount of information passed to the next stages of the system, and to preserve the essential information in the view of discriminating the data into different classes. For instance, in the case of image analysis the actual image intensities are vulnerable to various environmental effects, such as lighting changes and the feature extraction can be used as means for detecting features, which are invariant to certain types of illumination changes. Finally, classification tries to make decisions based on the previously transformed data. The main focus of this thesis is on developing new methods for the embedded feature extraction based on local non-parametric image descriptors. Also, feature analysis is carried out for the selected image features. Low-level Local Binary Pattern (LBP) based features are in a main role in the analysis. In the embedded domain, the pattern recognition system must usually meet strict performance constraints, such as high speed, compact size and low power consumption. The characteristics of the final system can be seen as a trade-off between these metrics, which is largely affected by the decisions made during the implementation phase. The implementation alternatives of the LBP based feature extraction are explored in the embedded domain in the context of focal-plane vision processors. In particular, the thesis demonstrates the LBP extraction with MIPA4k massively parallel focal-plane processor IC. Also higher level processing is incorporated to this framework, by means of a framework for implementing a single chip face recognition system. Furthermore, a new method for determining optical flow based on LBPs, designed in particular to the embedded domain is presented. Inspired by some of the principles observed through the feature analysis of the Local Binary Patterns, an extension to the well known non-parametric rank transform is proposed, and its performance is evaluated in face recognition experiments with a standard dataset. Finally, an a priori model where the LBPs are seen as combinations of n-tuples is also presented

Association between the -174 G/C promoter polymorphism of the interleukin-6 gene and cardiovascular disease risk factors in Brazilian older women

In worldwide studies, interleukin-6 (IL-6) is implicated in age-related disturbances. The aim of the present report was to determine the possible association of IL-6 -174 C/G promoter polymorphism with the cytokine profile as well as with the presence of selected cardiovascular risk features. This was a cross-sectional study on Brazilian women aged 60 years or older. A sample of 193 subjects was investigated for impaired glucose regulation, diabetes, hypertension, and dyslipidemia. Genotyping was done by direct sequencing of PCR products. IL-6 and C-reactive protein were quantified by high-sensitivity assays. General linear regression models or the Student t-test were used to compare continuous variables among genotypes, followed by adjustments for confounding variables. The chi-square test was used to compare categorical variables. The genotypes were consistent with Hardy-Weinberg equilibrium proportions. In a recessive model, mean waist-to-hip ratio, serum glycated hemoglobin and serum glucose were markedly lower in C homozygotes (P = 0.001, 0.028, and 0.047, respectively). In a dominant hypothesis, G homozygotes displayed a trend towards higher levels of circulating IL-6 (P = 0.092). Non-parametric analysis revealed that impaired fasting glucose and hypertension were findings approximately 2-fold more frequent among G homozygous subjects (P = 0.042 and 0.043, respectively). Taken together, our results show that the IL-6 -174 G-allele is implicated in a greater cardiovascular risk. To our knowledge, this is the first investigation of IL-6 promoter variants and age-related disturbances in the Brazilian elderly population.

The use of light-emitting diodes to stimulate mitochondrial function and liver regeneration of partially hepatectomized rats

The biostimulating effect of laser radiation has been observed in many areas of Medicine. However, there are still several questions to be answered, among them the importance of light coherence in the stimulatory process. In the present study, we used light-emitting diodes (LED) to promote the stimulation of liver regeneration after partial hepatectomy in rats. Fourteen male Wistar rats weighing 200-250 g were submitted to partial hepatectomy (70%) followed by LED light irradiation (630 nm) of the remaining part of the liver at two doses, i.e., 10 (N = 7) and 140 (N = 7) J/cm². A group irradiated with laser, 590 nm (N = 7, 15 J/cm²) was performed for the study of proliferating cell nuclear antigen-labeling index. Data are reported as mean ± SEM. Statistical comparisons of the groups were performed by analysis of variance for parametric measurements followed by the Bonferroni post-test, with the level of significance set at P < 0.05. Respiratory mitochondrial activity was increased in the irradiated groups (states 3 and 4; P < 0.05), with better results for the group exposed to the lower LED dose (10 J/cm²). The proliferating cell nuclear antigen-labeling index, by immunohistochemical staining, was similar for both LED-exposed groups (P > 0.05) and higher than for the control group (P < 0.05). The cell proliferation index obtained with LED and laser were similar (P > 0.05). In conclusion, the present results suggest that LED irradiation promotes biological stimulatory effects during the early stage of liver regeneration and that LED is as effective as laser light, independent of the coherence, divergence and cromaticity.

Effect of air pollution on diabetes and cardiovascular diseases in São Paulo, Brazil

Type 2 diabetes increases the risk of cardiovascular mortality and these patients, even without previous myocardial infarction, run the risk of fatal coronary heart disease similar to non-diabetic patients surviving myocardial infarction. There is evidence showing that particulate matter air pollution is associated with increases in cardiopulmonary morbidity and mortality. The present study was carried out to evaluate the effect of diabetes mellitus on the association of air pollution with cardiovascular emergency room visits in a tertiary referral hospital in the city of São Paulo. Using a time-series approach, and adopting generalized linear Poisson regression models, we assessed the effect of daily variations in PM10, CO, NO2, SO2, and O3 on the daily number of emergency room visits for cardiovascular diseases in diabetic and non-diabetic patients from 2001 to 2003. A semi-parametric smoother (natural spline) was adopted to control long-term trends, linear term seasonal usage and weather variables. In this period, 45,000 cardiovascular emergency room visits were registered. The observed increase in interquartile range within the 2-day moving average of 8.0 µg/m³ SO2 was associated with 7.0% (95%CI: 4.0-11.0) and 20.0% (95%CI: 5.0-44.0) increases in cardiovascular disease emergency room visits by non-diabetic and diabetic groups, respectively. These data indicate that air pollution causes an increase of cardiovascular emergency room visits, and that diabetic patients are extremely susceptible to the adverse effects of air pollution on their health conditions.

Critical analysis of autoregressive and fast Fourier transform markers of cardiovascular variability in rats and humans

The autonomic nervous system plays an important role in physiological and pathological conditions, and has been extensively evaluated by parametric and non-parametric spectral analysis. To compare the results obtained with fast Fourier transform (FFT) and the autoregressive (AR) method, we performed a comprehensive comparative study using data from humans and rats during pharmacological blockade (in rats), a postural test (in humans), and in the hypertensive state (in both humans and rats). Although postural hypotension in humans induced an increase in normalized low-frequency (LFnu) of systolic blood pressure, the increase in the ratio was detected only by AR. In rats, AR and FFT analysis did not agree for LFnu and high frequency (HFnu) under basal conditions and after vagal blockade. The increase in the LF/HF ratio of the pulse interval, induced by methylatropine, was detected only by FFT. In hypertensive patients, changes in LF and HF for systolic blood pressure were observed only by AR; FFT was able to detect the reduction in both blood pressure variance and total power. In hypertensive rats, AR presented different values of variance and total power for systolic blood pressure. Moreover, AR and FFT presented discordant results for LF, LFnu, HF, LF/HF ratio, and total power for pulse interval. We provide evidence for disagreement in 23% of the indices of blood pressure and heart rate variability in humans and 67% discordance in rats when these variables are evaluated by AR and FFT under physiological and pathological conditions. The overall disagreement between AR and FFT in this study was 43%.

Personality traits and psychiatric comorbidities in alcohol dependence

Non-adaptive personality traits may constitute risk factors for development of psychiatric disorders such as depression and anxiety. We aim to evaluate associations and the predictive value of personality traits among alcohol-dependent individuals, with or without psychiatric comorbidities. The convenience sample comprised two groups of males over 18 years of age: one with subjects who had an alcohol dependence diagnosis (AG, n=110), and a control group without abuse and/or alcohol dependence diagnosis (CG, n=110). The groups were assessed by means of the Structured Clinical Interview DSM-IV (SCID-IV). AG participants were recruited among outpatients from the university hospital, whereas CG participants were recruited from a primary healthcare program. Data collection was done individually with self-assessment instruments. Parametric statistics were performed, and a significance level of P=0.05 was adopted. A positive correlation was observed between openness and the length of time that alcohol has been consumed, as were significant and negative correlations between conscientiousness and both the length of time alcohol has been consumed and the number of doses. For alcoholics, extraversion emerged as a protective factor against depression development (P=0.008) and tobacco abuse (P=0.007), whereas openness worked as a protective factor against anxiety (P=0.02). The findings point to specific deficits presented by alcoholics in relation to personality traits with or without psychiatric comorbidities and to the understanding that therapeutic approaches should favor procedures and/or preventive measures that allow more refined awareness about the disorder.

Transplantation and survival of mouse inner ear progenitor/stem cells in the organ of Corti after cochleostomy of hearing-impaired guinea pigs: preliminary results

In mammals, damage to sensory receptor cells (hair cells) of the inner ear results in permanent sensorineural hearing loss. Here, we investigated whether postnatal mouse inner ear progenitor/stem cells (mIESCs) are viable after transplantation into the basal turns of neomycin-injured guinea pig cochleas. We also examined the effects of mIESC transplantation on auditory functions. Eight adult female Cavia porcellus guinea pigs (250-350g) were deafened by intratympanic neomycin delivery. After 7 days, the animals were randomly divided in two groups. The study group (n=4) received transplantation of LacZ-positive mIESCs in culture medium into the scala tympani. The control group (n=4) received culture medium only. At 2 weeks after transplantation, functional analyses were performed by auditory brainstem response measurement, and the animals were sacrificed. The presence of mIESCs was evaluated by immunohistochemistry of sections of the cochlea from the study group. Non-parametric tests were used for statistical analysis of the data. Intratympanic neomycin delivery damaged hair cells and increased auditory thresholds prior to cell transplantation. There were no significant differences between auditory brainstem thresholds before and after transplantation in individual guinea pigs. Some mIESCs were observed in all scalae of the basal turns of the injured cochleas, and a proportion of these cells expressed the hair cell marker myosin VIIa. Some transplanted mIESCs engrafted in the cochlear basilar membrane. Our study demonstrates that transplanted cells survived and engrafted in the organ of Corti after cochleostomy.

Non-parametric stability analyses of dough properties in wheat

AbstractLiterature has unveiled that a paper has not been published yet on using non-parametric stability statistics (NPSSs) for evaluating genotypic stability in dough properties of wheat. Accordingly, the effects of genotype (G), environment (E) and GE interaction (GEI) on alveograph parameters, i.e. dough baking strength (W) and its tenacity (P)/extensibility (L), of 18 wheat (T. aestivum L.) genotypes were studied under irrigated field conditions in an 8-year trial (2006-2014) in central Turkey. Furthermore, genotypic stability for W and P/L was determined using 8 NPSSs viz. RM-Rank mean, RSD-Rank’s standard deviation, RS-Rank Sum, TOP-Ranking, Si(1), Si(2), Si(3) and Si(6) rank statistics. The ANOVA revealed that W and P/L were primarily controlled by E, although G and GEI also had significant effects. Among the 8 NPSSs, only RM, RS and TOP statistics were suitable for detecting the genotypes with high stable and bread making quality (e.g. G1 and G17). In conclusion, using RM, RS and TOP statistics is advisable to select for dough quality in wheat under multi-environment trials (METs).

On the path integral formulation and the evaluation of quantum statistical averages

Four problems of physical interest have been solved in this thesis using the path integral formalism. Using the trigonometric expansion method of Burton and de Borde (1955), we found the kernel for two interacting one dimensional oscillators• The result is the same as one would obtain using a normal coordinate transformation, We next introduced the method of Papadopolous (1969), which is a systematic perturbation type method specifically geared to finding the partition function Z, or equivalently, the Helmholtz free energy F, of a system of interacting oscillators. We applied this method to the next three problems considered• First, by summing the perturbation expansion, we found F for a system of N interacting Einstein oscillators^ The result obtained is the same as the usual result obtained by Shukla and Muller (1972) • Next, we found F to 0(Xi)f where A is the usual Tan Hove ordering parameter* The results obtained are the same as those of Shukla and Oowley (1971), who have used a diagrammatic procedure, and did the necessary sums in Fourier space* We performed the work in temperature space• Finally, slightly modifying the method of Papadopolous, we found the finite temperature expressions for the Debyecaller factor in Bravais lattices, to 0(AZ) and u(/K/ j,where K is the scattering vector* The high temperature limit of the expressions obtained here, are in complete agreement with the classical results of Maradudin and Flinn (1963) .

Simulation-Based Finite and Large Sample Tests in Multivariate Regressions.

In the context of multivariate linear regression (MLR) models, it is well known that commonly employed asymptotic test criteria are seriously biased towards overrejection. In this paper, we propose a general method for constructing exact tests of possibly nonlinear hypotheses on the coefficients of MLR systems. For the case of uniform linear hypotheses, we present exact distributional invariance results concerning several standard test criteria. These include Wilks' likelihood ratio (LR) criterion as well as trace and maximum root criteria. The normality assumption is not necessary for most of the results to hold. Implications for inference are two-fold. First, invariance to nuisance parameters entails that the technique of Monte Carlo tests can be applied on all these statistics to obtain exact tests of uniform linear hypotheses. Second, the invariance property of the latter statistic is exploited to derive general nuisance-parameter-free bounds on the distribution of the LR statistic for arbitrary hypotheses. Even though it may be difficult to compute these bounds analytically, they can easily be simulated, hence yielding exact bounds Monte Carlo tests. Illustrative simulation experiments show that the bounds are sufficiently tight to provide conclusive results with a high probability. Our findings illustrate the value of the bounds as a tool to be used in conjunction with more traditional simulation-based test methods (e.g., the parametric bootstrap) which may be applied when the bounds are not conclusive.

Semi-Parametric Weak Instrument Regressions with an Application to the Risk-Return Trade-off

Recent work shows that a low correlation between the instruments and the included variables leads to serious inference problems. We extend the local-to-zero analysis of models with weak instruments to models with estimated instruments and regressors and with higher-order dependence between instruments and disturbances. This makes this framework applicable to linear models with expectation variables that are estimated non-parametrically. Two examples of such models are the risk-return trade-off in finance and the impact of inflation uncertainty on real economic activity. Results show that inference based on Lagrange Multiplier (LM) tests is more robust to weak instruments than Wald-based inference. Using LM confidence intervals leads us to conclude that no statistically significant risk premium is present in returns on the S&P 500 index, excess holding yields between 6-month and 3-month Treasury bills, or in yen-dollar spot returns.

Monte Carlo Tests with Nuisance Parameters: A General Approach to Finite-Sample Inference and Nonstandard Asymptotics

The technique of Monte Carlo (MC) tests [Dwass (1957), Barnard (1963)] provides an attractive method of building exact tests from statistics whose finite sample distribution is intractable but can be simulated (provided it does not involve nuisance parameters). We extend this method in two ways: first, by allowing for MC tests based on exchangeable possibly discrete test statistics; second, by generalizing the method to statistics whose null distributions involve nuisance parameters (maximized MC tests, MMC). Simplified asymptotically justified versions of the MMC method are also proposed and it is shown that they provide a simple way of improving standard asymptotics and dealing with nonstandard asymptotics (e.g., unit root asymptotics). Parametric bootstrap tests may be interpreted as a simplified version of the MMC method (without the general validity properties of the latter).

Finite-Sample Simulation-Based Inference in VAR Models with Applications to Order Selection and Causality Testing

Statistical tests in vector autoregressive (VAR) models are typically based on large-sample approximations, involving the use of asymptotic distributions or bootstrap techniques. After documenting that such methods can be very misleading even with fairly large samples, especially when the number of lags or the number of equations is not small, we propose a general simulation-based technique that allows one to control completely the level of tests in parametric VAR models. In particular, we show that maximized Monte Carlo tests [Dufour (2002)] can provide provably exact tests for such models, whether they are stationary or integrated. Applications to order selection and causality testing are considered as special cases. The technique developed is applied to quarterly and monthly VAR models of the U.S. economy, comprising income, money, interest rates and prices, over the period 1965-1996.

Heterotachy and long-branch attraction in phylogenetics

Affiliation: Département de Biochimie, Faculté de médecine, Université de Montréal