Increased rates of white matter hyperintensities in late-onset bipolar disorder

Objectives: Magnetic resonance imaging (MRI) studies have reported an increased frequency of white matter hyperintensities (WMH) in association with late-onset (LO) depression, and this has supported the notion that vascular-related mechanisms may be implicated in the pathophysiology of LO mood disorders. Recent clinical studies have also suggested a link between LO bipolar disorder (LO-BD) and cerebrovascular risk factors, but this has been little investigated with neuroimaging techniques. In order to ascertain whether there could be a specific association between WMH and LO-BD, we directly compared WMH rates between LO-BD subjects (illness onset 60 years), early-onset BD subjects (EO-BD, illness onset < 60 years), and elderly healthy volunteers. Methods: T2-weighted MRI data were acquired in LO-BD subjects (n = 10, age = 73.60 +/- 4.09), EO-BD patients (n = 49, age = 67.78 +/- 4.44), and healthy subjects (n = 24, age = 69.00 +/- 7.22). WMH rates were assessed using the Scheltens scale. Results: There was a greater prevalence of WMH in LO-BD patients relative to the two other groups in the deep parietal region (p = 0.018) and basal ganglia (p < 0.045). When between-group comparisons of mean WMH scores were conducted taking account of age differences (ANCOVA), there were more severe scores in LO-BD patients relative to the two other groups in deep frontal and parietal regions, as well as in the putamen (p < 0.05). Conclusions: Our results provide empirical support to the proposed link between vascular risk factors and LO-BD. If extended in future studies with larger samples, these. findings may help to clarify the pathophysiological distinctions between bipolar disorder emerging at early and late stages of life.

White-matter hyperintensities in first-episode psychosis

Background White-matter hyperintensities have been associated with both schizophrenia and mood disorders, particularly bipolar disorder, but results are inconsistent across studies. Aims To examine whether white-matter hyperintensities are a vulnerability marker for psychosis or are specifically associated with bipolar disorder. Method T-2-weighted magnetic resonance imaging data were acquired in 129 individuals with first-episode psychosis (either affective or non-affective psychoses) and 102 controls who were randomly selected from the same geographical areas. visual white-matter hyperintensity ratings were used for group and subgroup comparisons. Results There were no statistically significant between-group differences in white-matter hyperintensity frequency or severity scores. No significant correlations were found between white-matter hyperintensity scores and duration of illness, duration of untreated psychosis, or severity of psychotic, manic or depressive symptoms. Conclusions White-matter hyperintensities are not associated with vulnerability to psychosis in general, or specifically with affective psychoses. Further, first-episode psychosis investigations using more quantitative methods are warranted to confirm these findings. Declaration of interest None. Funding detailed in Acknowledgements.

Vascular diseases and old age mental disorders: an update of neuroimaging findings

Purpose of review To review neuroimaging findings that have been reported in samples of patients with cardiovascular disorders and their association with the onset of Alzheimer`s disease, vascular dementia, depression and bipolar disorder in the elderly and to highlight the implications of these findings to the knowledge about the pathophysiology of psychiatric disorders in old age, as well as their potential clinical implications. Recent findings Vascular risk factors, such as hypertension, diabetes, dyslipidemia, smoking habits and heart failure, have all been associated with signs of cerebrovascular dysfunction, including structural MRI findings of signal hyperintensities, lacunes and stroke and functional imaging findings of brain regional hypoperfusion and hypometabolism. Such brain abnormalities have been found to increase the risk of onset of psychiatric disorder (depression, bipolar and dementia) in old age. Summary As vascular risk factors are potentially modifiable when detected in midlife, the early characterization of brain changes associated with the presence of cardiovascular diseases holds promise to afford clinical applications in psychiatry, providing new perspectives for the prevention of old age psychiatric disorders.

Engagement of multifocal neural circuits during recall of autobiographical happy events

Happy emotional states have not been extensively explored in functional magnetic resonance imaging studies using autobiographic recall paradigms. We investigated the brain circuitry engaged during induction of happiness by standardized script-driven autobiographical recall in 11 healthy subjects (6 males), aged 32.4 ± 7.2 years, without physical or psychiatric disorders, selected according to their ability to vividly recall personal experiences. Blood oxygen level-dependent (BOLD) changes were recorded during auditory presentation of personal scripts of happiness, neutral content and negative emotional content (irritability). The same uniform structure was used for the cueing narratives of both emotionally salient and neutral conditions, in order to decrease the variability of findings. In the happiness relative to the neutral condition, there was an increased BOLD signal in the left dorsal prefrontal cortex and anterior insula, thalamus bilaterally, left hypothalamus, left anterior cingulate gyrus, and midportions of the left middle temporal gyrus (P < 0.05, corrected for multiple comparisons). Relative to the irritability condition, the happiness condition showed increased activity in the left insula, thalamus and hypothalamus, and in anterior and midportions of the inferior and middle temporal gyri bilaterally (P < 0.05, corrected), varying in size between 13 and 64 voxels. Findings of happiness-related increased activity in prefrontal and subcortical regions extend the results of previous functional imaging studies of autobiographical recall. The BOLD signal changes identified reflect general aspects of emotional processing, emotional control, and the processing of sensory and bodily signals associated with internally generated feelings of happiness. These results reinforce the notion that happiness induction engages a wide network of brain regions.

Theory of small-signal ac response of a dielectric liquid containing two groups of ions

The analysis of Macdonald for electrolytes is generalized to the case in which two groups of ions are present. We assume that the electrolyte can be considered as a dispersion of ions in a dielectric liquid, and that the ionic recombination can be neglected. We present the differential equations governing the ionic redistribution when the liquid is subjected to an external electric field, describing the simultaneous diffusion of the two groups of ions in the presence of their own space charge fields. We investigate the influence of the ions on the impedance spectroscopy of an electrolytic cell. In the analysis, we assume that each group of ions have equal mobility, the electrodes perfectly block and that the adsorption phenomena can be neglected. In this framework, it is shown that the real part of the electrical impedance of the cell has a frequency dependence presenting two plateaux, related to a type of ambipolar and free diffusion coefficients. The importance of the considered problem on the ionic characterization performed by means of the impedance spectroscopy technique was discussed. (c) 2008 American Institute of Physics.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

Noise reduction in biomedical speech signal processing based on time and frequency Kalman filtering combined with spectral subtraction

The goal of this paper is to study and propose a new technique for noise reduction used during the reconstruction of speech signals, particularly for biomedical applications. The proposed method is based on Kalman filtering in the time domain combined with spectral subtraction. Comparison with discrete Kalman filter in the frequency domain shows better performance of the proposed technique. The performance is evaluated by using the segmental signal-to-noise ratio and the Itakura-Saito`s distance. Results have shown that Kalman`s filter in time combined with spectral subtraction is more robust and efficient, improving the Itakura-Saito`s distance by up to four times. (C) 2007 Elsevier Ltd. All rights reserved.

Void fraction measurement and signal analysis from multiple-electrode impedance sensors

Void fraction sensors are important instruments not only for monitoring two-phase flow, but for furnishing an important parameter for obtaining flow map pattern and two-phase flow heat transfer coefficient as well. This work presents the experimental results obtained with the analysis of two axially spaced multiple-electrode impedance sensors tested in an upward air-water two-phase flow in a vertical tube for void fraction measurements. An electronic circuit was developed for signal generation and post-treatment of each sensor signal. By phase shifting the electrodes supplying the signal, it was possible to establish a rotating electric field sweeping across the test section. The fundamental principle of using a multiple-electrode configuration is based on reducing signal sensitivity to the non-uniform cross-section void fraction distribution problem. Static calibration curves were obtained for both sensors, and dynamic signal analyses for bubbly, slug, and turbulent churn flows were carried out. Flow parameters such as Taylor bubble velocity and length were obtained by using cross-correlation techniques. As an application of the void fraction tested, vertical flow pattern identification could be established by using the probability density function technique for void fractions ranging from 0% to nearly 70%.

Ultrasonic Viscosity Measurement Using the Shear-Wave Reflection Coefficient with a Novel Signal Processing Technique

Real-time viscosity measurement remains a necessity for highly automated industry. To resolve this problem, many studies have been carried out using an ultrasonic shear wave reflectance method. This method is based on the determination of the complex reflection coefficient`s magnitude and phase at the solid-liquid interface. Although magnitude is a stable quantity and its measurement is relatively simple and precise, phase measurement is a difficult task because of strong temperature dependence. A simplified method that uses only the magnitude of the reflection coefficient and that is valid under the Newtonian regimen has been proposed by some authors, but the obtained viscosity values do not match conventional viscometry measurements. In this work, a mode conversion measurement cell was used to measure glycerin viscosity as a function of temperature (15 to 25 degrees C) and corn syrup-water mixtures as a function of concentration (70 to 100 wt% of corn syrup). Tests were carried out at 1 MHz. A novel signal processing technique that calculates the reflection coefficient magnitude in a frequency band, instead of a single frequency, was studied. The effects of the bandwidth on magnitude and viscosity were analyzed and the results were compared with the values predicted by the Newtonian liquid model. The frequency band technique improved the magnitude results. The obtained viscosity values came close to those measured by the rotational viscometer with percentage errors up to 14%, whereas errors up to 96% were found for the single frequency method.

An In-Depth Study of the Barkhausen Emission Signal Properties of the Plastically Deformed Fe-2%Si Alloy

This paper presents the results of the in-depth study of the Barkhausen effect signal properties for the plastically deformed Fe-2%Si samples. The investigated samples have been deformed by cold rolling up to plastic strain epsilon(p) = 8%. The first approach consisted of time-domain-resolved pulse and frequency analysis of the Barkhausen noise signals whereas the complementary study consisted of the time-resolved pulse count analysis as well as a total pulse count. The latter included determination of time distribution of pulses for different threshold voltage levels as well as the total pulse count as a function of both the amplitude and the duration time of the pulses. The obtained results suggest that the observed increase in the Barkhausen noise signal intensity as a function of deformation level is mainly due to the increase in the number of bigger pulses.

In silico analysis of candidate genes involved in light sensing and signal transduction pathways in soybean

Several aspects of photoperception and light signal transduction have been elucidated by studies with model plants. However, the information available for economically important crops, such as Fabaceae species, is scarce. In order to incorporate the existing genomic tools into a strategy to advance soybean research, we have investigated publicly available expressed sequence tag ( EST) sequence databases in order to identify Glycine max sequences related to genes involved in light-regulated developmental control in model plants. Approximately 38,000 sequences from open-access databases were investigated, and all bona fide and putative photoreceptor gene families were found in soybean sequence databases. We have identified G. max orthologs for several families of transcriptional regulators and cytoplasmic proteins mediating photoreceptor-induced responses, although some important Arabidopsis phytochrome-signaling components are absent. Moreover, soybean and Arabidopsis gene-family homologs appear to have undergone a distinct expansion process in some cases. We propose a working model of light perception, signal transduction and response-eliciting in G. max, based on the identified key components from Arabidopsis. These results demonstrate the power of comparative genomics between model systems and crop species to elucidate several aspects of plant physiology and metabolism.

SacRALF1, a peptide signal from the grass sugarcane (Saccharum spp.), is potentially involved in the regulation of tissue expansion

Rapid alkalinization factor (RALF) is part of a growing family of small peptides with hormone characteristics in plants. Initially isolated from leaves of tobacco plants, RALF peptides can be found throughout the plant kingdom and they are expressed ubiquitously in plants. We took advantage of the small gene family size of RALF genes in sugarcane and the ordered cellular growth of the grass sugarcane leaves to gain information about the function of RALF peptides in plants. Here we report the isolation of two RALF peptides from leaves of sugarcane plants using the alkalinization assay. SacRALF1 was the most abundant and, when added to culture media, inhibited growth of microcalli derived from cell suspension cultures at concentrations as low as 0.1 mu M. Microcalli exposed to exogenous SacRALF1 for 5 days showed a reduced number of elongated cells. Only four copies of SacRALF genes were found in sugarcane plants. All four SacRALF genes are highly expressed in young and expanding leaves and show a low or undetectable level of expression in expanded leaves. In half-emerged leaf blades, SacRALF transcripts were found at high levels at the basal portion of the leaf and at low levels at the apical portion. Gene expression analyzes localize SacRALF genes in elongation zones of roots and leaves. Mature leaves, which are devoid of expanding cells, do not show considerable expression of SacRALF genes. Our findings are consistent with SacRALF genes playing a role in plant development potentially regulating tissue expansion.

Signal Transduction, Plasma Membrane Calcium Movements, and Pigment Translocation in Freshwater Shrimp Chromatophores

Crustacean color change results from the differential translocation of chromatophore pigments, regulated by neurosecretory peptides like red pigment concentrating hormone (RPCH) that, in the red ovarian chromatophores of the freshwater shrimp Macrobrachium olfersi, triggers pigment aggregation via increased cytosolic cGMP and Ca(2+) of both smooth endoplasmatic reticulum (SER) and extracellular origin. However, Ca(2+) movements during RPCH signaling and the mechanisms that regulate intracellular [Ca(2+)] are enigmatic. We investigate Ca(2+) transporters in the chromatophore plasma membrane and Ca(2+) movements that occur during RPCH signal transduction. Inhibition of the plasma membrane Ca(2+)-ATPase by La(3+) and indirect inhibition of the Na(+)/Ca(2+) exchanger by ouabain induce pigment aggregation, revealing a role for both in Ca(2+) extrusion. Ca(2+) channel blockade by La(3+) or Cd(2+) strongly inhibits slow-phase RPCH-triggered aggregation during which pigments disperse spontaneously. L-type Ca(2+) channel blockade by gabapentin markedly reduces rapid-phase translocation velocity; N- or P/Q-type blockade by omega-conotoxin MVIIC strongly inhibits RPCH-triggered aggregation and reduces velocity, effects revealing RPCH-signaled influx of extracellular Ca(2+). Plasma membrane depolarization, induced by increasing external K(+) from 5 to 50 mM, produces Ca(2+)-dependent pigment aggregation, whereas removal of K(+) from the perfusate causes pigment hyperdispersion, disclosing a clear correlation between membrane depolarization and pigment aggregation; K(+) channel blockade by Ba(2+) also partially inhibits RPCH action. We suggest that, during RPCH signal transduction, Ca(2+) released from the SER, together with K(+) channel closure, causes chromatophore membrane depolarization, leading to the opening of predominantly N- and/or P/Q-type voltage-gated Ca(2+) channels, and a Ca(2+)/cGMP cascade, resulting in pigment aggregation. J. Exp. Zool. 313A:605-617, 2010. (C) 2010 Wiley-Liss, Inc.

Use of SVM Methods with Surface-Based Cortical and Volumetric Subcortical Measurements to Detect Alzheimer`s Disease

Here, we examine morphological changes in cortical thickness of patients with Alzheimer`s disease (AD) using image analysis algorithms for brain structure segmentation and study automatic classification of AD patients using cortical and volumetric data. Cortical thickness of AD patients (n = 14) was measured using MRI cortical surface-based analysis and compared with healthy subjects (n = 20). Data was analyzed using an automated algorithm for tissue segmentation and classification. A Support Vector Machine (SVM) was applied over the volumetric measurements of subcortical and cortical structures to separate AD patients from controls. The group analysis showed cortical thickness reduction in the superior temporal lobe, parahippocampal gyrus, and enthorhinal cortex in both hemispheres. We also found cortical thinning in the isthmus of cingulate gyrus and middle temporal gyrus at the right hemisphere, as well as a reduction of the cortical mantle in areas previously shown to be associated with AD. We also confirmed that automatic classification algorithms (SVM) could be helpful to distinguish AD patients from healthy controls. Moreover, the same areas implicated in the pathogenesis of AD were the main parameters driving the classification algorithm. While the patient sample used in this study was relatively small, we expect that using a database of regional volumes derived from MRI scans of a large number of subjects will increase the SVM power of AD patient identification.

Improved detection of incipient vascular changes by a biotechnological platform combining post mortem MRI in situ with neuropathology

The histopathological counterpart of white matter hyperintensities is a matter of debate. Methodological and ethical limitations have prevented this question to be elucidated. We want to introduce a protocol applying state-of-the-art methods in order to solve fundamental questions regarding the neuroimaging-neuropathological uncertainties comprising the most common white matter hyperintensities [WMHs] seen in aging. By this protocol, the correlation between signal features in in situ, post mortem MRI-derived methods, including DTI and MTR and quantitative and qualitative histopathology can be investigated. We are mainly interested in determining the precise neuroanatomical substrate of incipient WMHs. A major issue in this protocol is the exact co-registration of small lesion in a tridimensional coordinate system that compensates tissue deformations after histological processing. The protocol is based on four principles: post mortem MRI in situ performed in a short post mortem interval, minimal brain deformation during processing, thick serial histological sections and computer-assisted 3D reconstruction of the histological sections. This protocol will greatly facilitate a systematic study of the location, pathogenesis, clinical impact, prognosis and prevention of WMHs. (C) 2009 Elsevier B.V. All rights reserved.