Fast-convergent iterative scheme for filtering velocity signals and finding Kolmogorov scales

The present fundamental knowledge of fluid turbulence has been established primarily from hot- and cold-wire measurements. Unfortunately, however, these measurements necessarily suffer from contamination by noise since no certain method has previously been available to optimally filter noise from the measured signals. This limitation has impeded our progress of understanding turbulence profoundly. We address this limitation by presenting a simple, fast-convergent iterative scheme to digitally filter signals optimally and find Kolmogorov scales definitely. The great efficacy of the scheme is demonstrated by its application to the instantaneous velocity measured in a turbulent jet.

Ultraviolet signals ultra-aggression in a lizard

Understanding the role of multiple colour signals during sexual signalling is a central theme in animal communication. We quantified the role of multiple colour signals (including ultraviolet, UV), measures of body size and testosterone levels in settling disputes between male rivals in an elaborately ornamented, African lizard, played out in a large 'tournament' in the wild. The hue and brightness (total reflectance) of the UV throat in Augrabies flat lizards, Platysaurus broadleyi, as well as body size, were consistent and strong predictors of 'fighting ability'. Males with high fighting ability were larger and displayed a UV throat with low total reflectance. In contrast, males with low fighting ability were smaller and had violet throats with broader spectral reflectance curves (higher total reflectance). As fighting ability is associated with alternative reproductive tactics in this system (territorial versus floater), we also examined the role of colour signals in predicting male reproductive tactic. Territorial males had UV throats with higher chroma but had poorer body condition than floater males, probably because of the energetic costs of maintaining a territory. Although testosterone was not a significant predictor of fighting ability or reproductive tactic, it was correlated with the hue of the UV throat, suggesting that testosterone may impose some constraint on signal expression. Lastly, we show that within the context of the natural signalling environment, UV-reflective throats constitute a conspicuous, effective signal that male Augrabies flat lizards use to advertise their status honestly to rivals. (c) 2006 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

Germline mutations in TMEM127 confer susceptibility to pheochromocytoma

Pheochromocytomas, which are catecholamine-secreting tumors of neural crest origin, are frequently hereditary(1). However, the molecular basis of the majority of these tumors is unknown(2). We identified the transmembrane-encoding gene TMEM127 on chromosome 2q11 as a new pheochromocytoma susceptibility gene. In a cohort of 103 samples, we detected truncating germline TMEM127 mutations in approximately 30% of familial tumors and about 3% of sporadic-appearing pheochromocytomas without a known genetic cause. The wild-type allele was consistently deleted in tumor DNA, suggesting a classic mechanism of tumor suppressor gene inactivation. Pheochromocytomas with mutations in TMEM127 are transcriptionally related to tumors bearing NF1 mutations and, similarly, show hyperphosphorylation of mammalian target of rapamycin (mTOR) effector proteins. Accordingly, in vitro gain-of-function and loss-of-function analyses indicate that TMEM127 is a negative regulator of mTOR. TMEM127 dynamically associates with the endomembrane system and colocalizes with perinuclear (activated) mTOR, suggesting a subcompartmental-specific effect. Our studies identify TMEM127 as a tumor suppressor gene and validate the power of hereditary tumors to elucidate cancer pathogenesis.

Ramp and constant power trials produce equivalent critical power estimates

The standard critical power test protocol on the cycle prescribes a series of trials to exhaustion, each at a different but constant power setting. Recently the protocol has been modified and applied to a series of trials to exhaustion each at a different ramp incremental rate. This study was undertaken to compare critical power and anaerobic work capacity estimates in the same group of subjects when derived from the two protocols. Ten male subjects of mixed athletic ability cycled to exhaustion on eight occasions in randomized order over a 3-wk period. Four trials were performed at differing constant power settings and four trials on differing ramp incremental rates. Both critical power and anaerobic work capacity were estimated for each subject by curve fitting of the ramp model and of three versions of the constant power model. After adjusting for inter-subject variability, no significant differences were detected between critical power estimates or between anaerobic work capacity estimates from any model formulation or from the two protocols. It is concluded that both the ramp and constant power protocols produce equivalent estimates for critical power and anaerobic work capacity.

Wavelet correlation between subjects: A time-scale data driven analysis for brain mapping using fMRI

Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

From EEG to BOLD: Brain mapping and estimating transfer functions in simultaneous EEG-fMRI acquisitions

Simultaneous acquisition of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) aims to disentangle the description of brain processes by exploiting the advantages of each technique. Most studies in this field focus on exploring the relationships between fMRI signals and the power spectrum at some specific frequency bands (alpha, beta, etc.). On the other hand, brain mapping of EEG signals (e.g., interictal spikes in epileptic patients) usually assumes an haemodynamic response function for a parametric analysis applying the GLM, as a rough approximation. The integration of the information provided by the high spatial resolution of MR images and the high temporal resolution of EEG may be improved by referencing them by transfer functions, which allows the identification of neural driven areas without strong assumptions about haemodynamic response shapes or brain haemodynamic`s homogeneity. The difference on sampling rate is the first obstacle for a full integration of EEG and fMRI information. Moreover, a parametric specification of a function representing the commonalities of both signals is not established. In this study, we introduce a new data-driven method for estimating the transfer function from EEG signal to fMRI signal at EEG sampling rate. This approach avoids EEG subsampling to fMRI time resolution and naturally provides a test for EEG predictive power over BOLD signal fluctuations, in a well-established statistical framework. We illustrate this concept in resting state (eyes closed) and visual simultaneous fMRI-EEG experiments. The results point out that it is possible to predict the BOLD fluctuations in occipital cortex by using EEG measurements. (C) 2010 Elsevier Inc. All rights reserved.

Quantitative Analysis of Placental Vasculature by Three-Dimensional Power Doppler Ultrasonography in Normal Pregnancies From 12 to 40 Weeks of Gestation

Evaluate the distribution and variation of placental vascular indices according to gestational age and placental volume. From March to November 2007, three-dimensional (3D)-power Doppler ultrasound was performed in 295 normal pregnancies from 12 to 40 weeks of gestation. Using the same preestablished settings for all patients, power Doppler was applied to the placenta and placental Volume was obtained by the rotational technique (VOCAL(TM)). The 3D-power histogram was used to determine the placental vascular indices: vascularization index (VI), flow index (FI) and vascularization-flow index (VFI). The placental vascular indices were then plotted against gestational age and placental volume. All placental vascular indices showed constant distribution throughout gestation. A tendency for a reduction in placental vascular indices with increased placental volume was observed, but was only statistically significant when placental FI was considered (p < 0.05). All placental vascular indices estimated by 3D-power Doppler ultrasonography presented constant distribution throughout gestation, despite the increase in placental volume according to gestational age. (C) 2008 Elsevier Ltd. All rights reserved.