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.

Frequency Domain Connectivity Identification: An Application of Partial Directed Coherence in fMRI

Functional magnetic resonance imaging (fMRI) has become an important tool in Neuroscience due to its noninvasive and high spatial resolution properties compared to other methods like PET or EEG. Characterization of the neural connectivity has been the aim of several cognitive researches, as the interactions among cortical areas lie at the heart of many brain dysfunctions and mental disorders. Several methods like correlation analysis, structural equation modeling, and dynamic causal models have been proposed to quantify connectivity strength. An important concept related to connectivity modeling is Granger causality, which is one of the most popular definitions for the measure of directional dependence between time series. In this article, we propose the application of the partial directed coherence (PDC) for the connectivity analysis of multisubject fMRI data using multivariate bootstrap. PDC is a frequency domain counterpart of Granger causality and has become a very prominent tool in EEG studies. The achieved frequency decomposition of connectivity is useful in separating interactions from neural modules from those originating in scanner noise, breath, and heart beating. Real fMRI dataset of six subjects executing a language processing protocol was used for the analysis of connectivity. Hum Brain Mapp 30:452-461, 2009. (C) 2007 Wiley-Liss, Inc.

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.

Renal Cell Carcinoma: T1 and T2 Signal Intensity Characteristics of Papillary and Clear Cell Types Correlated with Pathology

OBJECTIVE. The objective of our study was to describe the T1 and T2 signal intensity characteristics of papillary renal cell carcinoma (RCC) and clear cell RCC with pathologic correlation. MATERIALS AND METHODS. Of 539 RCCs, 49 tumors (21 papillary RCCs and 28 clear cell RCCs) in 45 patients were examined with MRI. Two radiologists retrospectively and independently assessed each tumor`s T1 and T2 signal intensity qualitatively and quantitatively (i.e., the signal intensity [SI] ratio [tumor SI/renal cortex SI]). Of the 49 tumors, 37 (76%) were assessed for pathology features including tumor architecture and the presence of hemosiderin, ferritin, necrosis, and fibrosis. MRI findings and pathology features were correlated. Statistical methods included summary statistics and Wilcoxon`s rank sum test for signal intensity, contingency tables for assessing reader agreement, concordance rate between the two readers with 95% CIs, and Fisher`s exact test for independence, all stratified by RCC type. RESULTS. Papillary RCCs and clear cell RCCs had a similar appearance and signal intensity ratio on T1-weighted images. On T2-weighted images, most papillary RCCs were hypointense (reader 1, 13/21; reader 2, 14/21), with an average mean signal intensity ratio for both readers of 0.67 +/- 0.2, and none was hyperintense, whereas most clear cell RCCs were hyperintense (reader 1, 21/28; reader 2, 17/28), with an average mean signal intensity ratio for both readers of 1.41 +/- 0.4 (p < 0.05). A tumor T2 signal intensity ratio of <= 0.66 had a specificity of 100% and sensitivity of 54% for papillary RCC. Most T2 hypointense tumors exhibited predominant papillary architecture; most T2 hyperintense tumors had a predominant nested architecture (p < 0.05). CONCLUSION. On T2-weighted images, most papillary RCCs are hypointense and clear cell RCCs, hyperintense. The T2 hypointense appearance of papillary RCCs correlated with a predominant papillary architecture at pathology.

Evaluating SVM and MLDA in the extraction of discriminant regions for mental state prediction

Pattern recognition methods have been successfully applied in several functional neuroimaging studies. These methods can be used to infer cognitive states, so-called brain decoding. Using such approaches, it is possible to predict the mental state of a subject or a stimulus class by analyzing the spatial distribution of neural responses. In addition it is possible to identify the regions of the brain containing the information that underlies the classification. The Support Vector Machine (SVM) is one of the most popular methods used to carry out this type of analysis. The aim of the current study is the evaluation of SVM and Maximum uncertainty Linear Discrimination Analysis (MLDA) in extracting the voxels containing discriminative information for the prediction of mental states. The comparison has been carried out using fMRI data from 41 healthy control subjects who participated in two experiments, one involving visual-auditory stimulation and the other based on bimanual fingertapping sequences. The results suggest that MLDA uses significantly more voxels containing discriminative information (related to different experimental conditions) to classify the data. On the other hand, SVM is more parsimonious and uses less voxels to achieve similar classification accuracies. In conclusion, MLDA is mostly focused on extracting all discriminative information available, while SVM extracts the information which is sufficient for classification. (C) 2009 Elsevier Inc. All rights reserved.

An fMRI Normative Database for Connectivity Networks Using One-Class Support Vector Machines

The application of functional magnetic resonance imaging (fMRI) in neuroscience studies has increased enormously in the last decade. Although primarily used to map brain regions activated by specific stimuli, many studies have shown that fMRI can also be useful in identifying interactions between brain regions (functional and effective connectivity). Despite the widespread use of fMRI as a research tool, clinical applications of brain connectivity as studied by fMRI are not well established. One possible explanation is the lack of normal pattern, and intersubject variability-two variables that are still largely uncharacterized in most patient populations of interest. In the current study, we combine the identification of functional connectivity networks extracted by using Spearman partial correlation with the use of a one-class support vector machine in order construct a normative database. An application of this approach is illustrated using an fMRI dataset of 43 healthy Subjects performing a visual working memory task. In addition, the relationships between the results obtained and behavioral data are explored. Hum Brain Mapp 30:1068-1076, 2009. (C) 2008 Wiley-Liss. Inc.

The impact of functional connectivity changes on support vector machines mapping of fMRI data

Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.

The relationship between prevalent medial meniscal intrasubstance signal changes and incident medial meniscal tears in women over a 1-year period assessed with 3.0 T MRI

Objective Intrasubstance meniscal signal changes not reaching the articular surface on fast spin echo (FSE) sequences are considered to represent mucoid degeneration on MRI. The aim of this study was to evaluate the association of prevalent intrasubstance signal changes with incident tears of the medial meniscus detected on 3.0 T MRI over a 1-year period. Materials and methods A total of 161 women aged a parts per thousand yen40 years participated in a longitudinal 1-year observational study of knee osteoarthritis. MRI (3.0 T) was performed at baseline and 12-month follow-up. The anterior horn, body, and posterior horn of the medial meniscus were scored by two experienced musculoskeletal radiologists using the Boston-Leeds Osteoarthritis Knee Score (BLOKS) system. Four grades were used to describe the meniscal morphology: grade 0 (normal), grade 1 (intrasubstance signal changes not reaching the articular surface), grade 2 (single tears), and grade 3 (complex tears and maceration). Fisher`s exact test and the Cochran-Armitage trend test were performed to evaluate whether baseline intrasubstance signal changes (grade 1) predict incident meniscal tears/maceration (grades 2 and/or 3) in the same subregion of the medial meniscus, when compared to subregions without pathology as the reference group (grade 0). Results Medial meniscal intrasubstance signal changes at baseline did not predict tears at follow-up when evaluating the anterior and posterior horns (left-sided p-values 0.06 and 0.59, respectively). No incident tears were detected in the body. Conclusion We could not demonstrate an association between prevalent medial meniscal intrasubstance signal changes with incident tears over a 1-year period.

Cysteinyl-leukotriene type 1 receptors transduce a critical signal for the up-regulation of eosinophilopoiesis by interleukin-13 and eotaxin in murine bone marrow

IL-13 and eotaxin play important, inter-related roles in asthma models. In the lungs, CysLT, produced by the 5-LO-LTC4S pathway, mediate some local responses to IL-13 and eotaxin; in bone marrow, CysLT enhance IL-5-dependent eosinophil differentiation. We examined the effects of IL-13 and eotaxin on eosinophil differentiation. Semi-solid or liquid cultures were established from murine bone marrow with GM-CSF or IL-5, respectively, and the effects of IL-13, eotaxin, or CysLT on eosinophil colony formation and on eosinophil differentiation in liquid culture were evaluated, in the absence or presence of: a) the 5-LO inhibitor zileuton, the FLAP inhibitor MK886, or the CysLT1R antagonists, montelukast and MK571; b) mutations that inactivate 5-LO, LTC4S, or CysLT1R; and c) neutralizing mAb against eotaxin and its CCR3 receptor. Both cytokines enhanced GM-CSF-dependent eosinophil colony formation and IL-5-stimulated eosinophil differentiation. Although IL-13 did not induce eotaxin production, its effects were abolished by anti-eotaxin and anti-CCR3 antibodies, suggesting up-regulation by IL-13 of responses to endogenous eotaxin. Anti-CCR3 blocked eotaxin completely. The effects of both cytokines were prevented by zileuton, MK886, montelukast, and MK571, as well as by inactivation of the genes coding for 5-LO, LTC4S, and CysLT1R. In the absence of either cytokine, these treatments or mutations had no effect. These findings provide evidence for: a) a novel role of eotaxin and IL-13 in regulating eosinophilopoiesis; and b) a role for CysLTRs in bone marrow cells in transducing cytokine regulatory signals. J. Leukoc. Biol. 87: 885-893; 2010.

Quantitative three-dimensional power Doppler angiography: a flow-free phantom experiment to evaluate the relationship between color gain, depth and signal artifact

Objectives To evaluate the presence of false flow three-dimensional (3D) power Doppler signals in `flow-free` models. Methods 3D power Doppler datasets were acquired from three different flow-free phantoms (muscle, air and water) with two different transducers and Virtual Organ Computer-aided AnaLysis was used to generate a sphere that was serially applied through the 3D dataset. The vascularization flow index was used to compare artifactual signals at different depths (from 0 to 6 cm) within the different phantoms and at different gain and pulse repetition frequency (PR F) settings. Results Artifactual Doppler signals were seen in all phantoms despite these being flow-free. The pattern was very similar and the degree of artifact appeared to be dependent on the gain and distance from the transducer. False signals were more evident in the far field and increased as the gain was increased, with false signals first appearing with a gain of 1 dB in the air and muscle phantoms. False signals were seen at a lower gain with the water phantom (-15 dB) and these were associated with vertical lines of Doppler artifact that were related to PRF, and disappeared when reflections were attenuated. Conclusions Artifactual Doppler signals are seen in flow-free phantoms and are related to the gain settings and the distance from the transducer. In the in-vivo situation, the lowest gain settings that allow the detection of blood flow and adequate definition of vessel architecture should be used, which invariably means using a setting near or below the middle of the range available. Additionally, observers should be aware of vertical lines when evaluating cystic or liquid-containing structures. Copyright (C) 2010 ISUOC. Published by John Wiley & Sons, Ltd.

Effect of image analysis software on neurofunctional activation during processing of emotional human faces

Functional brain imaging techniques such as functional MRI (fMRI) that allow the in vivo investigation of the human brain have been exponentially employed to address the neurophysiological substrates of emotional processing. Despite the growing number of fMRI studies in the field, when taken separately these individual imaging studies demonstrate contrasting findings and variable pictures, and are unable to definitively characterize the neural networks underlying each specific emotional condition. Different imaging packages, as well as the statistical approaches for image processing and analysis, probably have a detrimental role by increasing the heterogeneity of findings. In particular, it is unclear to what extent the observed neurofunctional response of the brain cortex during emotional processing depends on the fMRI package used in the analysis. In this pilot study, we performed a double analysis of an fMRI dataset using emotional faces. The Statistical Parametric Mapping (SPM) version 2.6 (Wellcome Department of Cognitive Neurology, London, UK) and the XBAM 3.4 (Brain Imaging Analysis Unit, Institute of Psychiatry, Kings College London, UK) programs, which use parametric and non-parametric analysis, respectively, were used to assess our results. Both packages revealed that processing of emotional faces was associated with an increased activation in the brain`s visual areas (occipital, fusiform and lingual gyri), in the cerebellum, in the parietal cortex, in the cingulate cortex (anterior and posterior cingulate), and in the dorsolateral and ventrolateral prefrontal cortex. However, blood oxygenation level-dependent (BOLD) response in the temporal regions, insula and putamen was evident in the XBAM analysis but not in the SPM analysis. Overall, SPM and XBAM analyses revealed comparable whole-group brain responses. Further Studies are needed to explore the between-group compatibility of the different imaging packages in other cognitive and emotional processing domains. (C) 2009 Elsevier Ltd. All rights reserved.

Opposite Effects of Delta-9-Tetrahydrocannabinol and Cannabidiol on Human Brain Function and Psychopathology

Delta-9-tetrahydrocannabinol (Delta-9-THC) and Cannabidiol (CBD), the two main ingredients of the Cannabis sativa plant have distinct symptomatic and behavioral effects. We used functional magnetic resonance imaging (fMRI) in healthy volunteers to examine whether Delta-9-THC and CBD had opposite effects on regional brain function. We then assessed whether pretreatment with CBD can prevent the acute psychotic symptoms induced by Delta-9-THC. Fifteen healthy men with minimal earlier exposure to cannabis were scanned while performing a verbal memory task, a response inhibition task, a sensory processing task, and when viewing fearful faces. Subjects were scanned on three occasions, each preceded by oral administration of Delta-9-THC, CBD, or placebo. BOLD responses were measured using fMRI. In a second experiment, six healthy volunteers were administered Delta-9-THC intravenously on two occasions, after placebo or CBD pretreatment to examine whether CBD could block the psychotic symptoms induced by Delta-9-THC. Delta-9-THC and CBD had opposite effects on activation relative to placebo in the striatum during verbal recall, in the hippocampus during the response inhibition task, in the amygdala when subjects viewed fearful faces, in the superior temporal cortex when subjects listened to speech, and in the occipital cortex during visual processing. In the second experiment, pretreatment with CBD prevented the acute induction of psychotic symptoms by Delta-9-tetrahydrocannabinol. Delta-9-THC and CBD can have opposite effects on regional brain function, which may underlie their different symptomatic and behavioral effects, and CBD`s ability to block the psychotogenic effects of Delta-9-THC. Neuropsychopharmacology (2010) 35, 764-774; doi:10.1038/npp.2009.184; published online 18 November 2009