999 resultados para nonlinear resonance


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The objective of this study was to adapt a nonlinear model (Wang and Engel - WE) for simulating the phenology of maize (Zea mays L.), and to evaluate this model and a linear one (thermal time), in order to predict developmental stages of a field-grown maize variety. A field experiment, during 2005/2006 and 2006/2007 was conducted in Santa Maria, RS, Brazil, in two growing seasons, with seven sowing dates each. Dates of emergence, silking, and physiological maturity of the maize variety BRS Missões were recorded in six replications in each sowing date. Data collected in 2005/2006 growing season were used to estimate the coefficients of the two models, and data collected in the 2006/2007 growing season were used as independent data set for model evaluations. The nonlinear WE model accurately predicted the date of silking and physiological maturity, and had a lower root mean square error (RMSE) than the linear (thermal time) model. The overall RMSE for silking and physiological maturity was 2.7 and 4.8 days with WE model, and 5.6 and 8.3 days with thermal time model, respectively.

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OBJECTIVES: This study aimed to investigate post-mortem magnetic resonance imaging (pmMRI) for the assessment of myocardial infarction and hypointensities on post-mortem T2-weighted images as a possible method for visualizing the myocardial origin of arrhythmic sudden cardiac death. BACKGROUND: Sudden cardiac death has challenged clinical and forensic pathologists for decades because verification on post-mortem autopsy is not possible. pmMRI as an autopsy-supporting examination technique has been shown to visualize different stages of myocardial infarction. METHODS: In 136 human forensic corpses, a post-mortem cardiac MR examination was carried out prior to forensic autopsy. Short-axis and horizontal long-axis images were acquired in situ on a 3-T system. RESULTS: In 76 cases, myocardial findings could be documented and correlated to the autopsy findings. Within these 76 study cases, a total of 124 myocardial lesions were detected on pmMRI (chronic: 25; subacute: 16; acute: 30; and peracute: 53). Chronic, subacute, and acute infarction cases correlated excellently to the myocardial findings on autopsy. Peracute infarctions (age range: minutes to approximately 1 h) were not visible on macroscopic autopsy or histological examination. Peracute infarction areas detected on pmMRI could be verified in targeted histological investigations in 62.3% of cases and could be related to a matching coronary finding in 84.9%. A total of 15.1% of peracute lesions on pmMRI lacked a matching coronary finding but presented with severe myocardial hypertrophy or cocaine intoxication facilitating a cardiac death without verifiable coronary stenosis. CONCLUSIONS: 3-T pmMRI visualizes chronic, subacute, and acute myocardial infarction in situ. In peracute infarction as a possible cause of sudden cardiac death, it demonstrates affected myocardial areas not visible on autopsy. pmMRI should be considered as a feasible post-mortem investigation technique for the deceased patient if no consent for a clinical autopsy is obtained.

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A dual model with a nonlinear proton Regge trajectory in the missing mass (M_X^2) channel is constructed. A background based on a direct-channel exotic trajectory, developed and applied earlier for the inclusive electron-proton cross section description in the nucleon resonance region, is used. The parameters of the model are determined from the extrapolations to earlier experiments. Predictions for the low-mass (2 < M_X^2 < 8GeV^2) diffraction dissociation cross sections at the LHC energies are given.

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In (1) H magnetic resonance spectroscopy, macromolecule signals underlay metabolite signals, and knowing their contribution is necessary for reliable metabolite quantification. When macromolecule signals are measured using an inversion-recovery pulse sequence, special care needs to be taken to correctly remove residual metabolite signals to obtain a pure macromolecule spectrum. Furthermore, since a single spectrum is commonly used for quantification in multiple experiments, the impact of potential macromolecule signal variability, because of regional differences or pathologies, on metabolite quantification has to be assessed. In this study, we introduced a novel method to post-process measured macromolecule signals that offers a flexible and robust way of removing residual metabolite signals. This method was applied to investigate regional differences in the mouse brain macromolecule signals that may affect metabolite quantification when not taken into account. However, since no significant differences in metabolite quantification were detected, it was concluded that a single macromolecule spectrum can be generally used for the quantification of healthy mouse brain spectra. Alternatively, the study of a mouse model of human glioma showed several alterations of the macromolecule spectrum, including, but not limited to, increased mobile lipid signals, which had to be taken into account to avoid significant metabolite quantification errors.

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MRI has evolved into an important diagnostic technique in medical imaging. However, reliability of the derived diagnosis can be degraded by artifacts, which challenge both radiologists and automatic computer-aided diagnosis. This work proposes a fully-automatic method for measuring image quality of three-dimensional (3D) structural MRI. Quality measures are derived by analyzing the air background of magnitude images and are capable of detecting image degradation from several sources, including bulk motion, residual magnetization from incomplete spoiling, blurring, and ghosting. The method has been validated on 749 3D T(1)-weighted 1.5T and 3T head scans acquired at 36 Alzheimer's Disease Neuroimaging Initiative (ADNI) study sites operating with various software and hardware combinations. Results are compared against qualitative grades assigned by the ADNI quality control center (taken as the reference standard). The derived quality indices are independent of the MRI system used and agree with the reference standard quality ratings with high sensitivity and specificity (>85%). The proposed procedures for quality assessment could be of great value for both research and routine clinical imaging. It could greatly improve workflow through its ability to rule out the need for a repeat scan while the patient is still in the magnet bore.

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BACKGROUND: Stem cell labeling with iron oxide (ferumoxide) particles allows labeled cells to be detected by magnetic resonance imaging (MRI) and is commonly used to track stem cell engraftment. However, the validity of MRI for distinguishing surviving ferumoxide-labeled cells from other sources of MRI signal, for example, macrophages containing ferumoxides released from nonsurviving cells, has not been thoroughly investigated. We sought to determine the relationship between the persistence of iron-dependent MRI signals and cell survival 3 weeks after injection of syngeneic or xenogeneic ferumoxides-labeled stem cells (cardiac-derived stem cells) in rats. METHODS AND RESULTS: We studied nonimmunoprivileged human and rat cardiac-derived stem cells and human mesenchymal stem cells doubly labeled with ferumoxides and beta-galactosidase and injected intramyocardially into immunocompetent Wistar-Kyoto rats. Animals were imaged at 2 days and 3 weeks after stem cell injection in a clinical 3-T MRI scanner. At 2 days, injection sites of xenogeneic and syngeneic cells (cardiac-derived stem cells and mesenchymal stem cells) were identified by MRI as large intramyocardial signal voids that persisted at 3 weeks (50% to 90% of initial signal). Histology (at 3 weeks) revealed the presence of iron-containing macrophages at the injection site, identified by CD68 staining, but very few or no beta-galactosidase-positive stem cells in the animals transplanted with syngeneic or xenogeneic cells, respectively. CONCLUSIONS: The persistence of significant iron-dependent MRI signal derived from ferumoxide-containing macrophages despite few or no viable stem cells 3 weeks after transplantation indicates that MRI of ferumoxide-labeled cells does not reliably report long-term stem cell engraftment in the heart.

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We present a novel scheme for the appearance of stochastic resonance when the dynamics of a Brownian particle takes place in a confined medium. The presence of uneven boundaries, giving rise to an entropic contribution to the potential, may upon application of a periodic driving force result in an increase of the spectral amplification at an optimum value of the ambient noise level. The entropic stochastic resonance, characteristic of small-scale systems, may constitute a useful mechanism for the manipulation and control of single molecules and nanodevices.

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PURPOSE: To evaluate gadocoletic acid (B-22956), a gadolinium-based paramagnetic blood pool agent, for contrast-enhanced coronary magnetic resonance angiography (MRA) in a Phase I clinical trial, and to compare the findings with those obtained using a standard noncontrast T2 preparation sequence. MATERIALS AND METHODS: The left coronary system was imaged in 12 healthy volunteers before B-22956 application and 5 (N = 11) and 45 (N = 7) minutes after application of 0.075 mmol/kg of body weight (BW) of B-22956. Additionally, imaging of the right coronary system was performed 23 minutes after B-22956 application (N = 6). A three-dimensional gradient echo sequence with T2 preparation (precontrast) or inversion recovery (IR) pulse (postcontrast) with real-time navigator correction was used. Assessment of the left and right coronary systems was performed qualitatively (a 4-point visual score for image quality) and quantitatively in terms of signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), vessel sharpness, visible vessel length, maximal luminal diameter, and the number of visible side branches. RESULTS: Significant (P < 0.01) increases in SNR (+42%) and CNR (+86%) were noted five minutes after B-22956 application, compared to precontrast T2 preparation values. A significant increase in CNR (+40%, P < 0.05) was also noted 45 minutes postcontrast. Vessels (left anterior descending artery (LAD), left coronary circumflex (LCx), and right coronary artery (RCA)) were also significantly (P < 0.05) sharper on postcontrast images. Significant increases in vessel length were noted for the LAD (P < 0.05) and LCx and RCA (both P < 0.01), while significantly more side branches were noted for the LAD and RCA (both P < 0.05) when compared to precontrast T2 preparation values. CONCLUSION: The use of the intravascular contrast agent B-22956 substantially improves both objective and subjective parameters of image quality on high-resolution three-dimensional coronary MRA. The increase in SNR, CNR, and vessel sharpness minimizes current limitations of coronary artery visualization with high-resolution coronary MRA.

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Magnetic resonance imaging (MRI) and spectroscopy (MRS) allow establishing theanatomical evolution and neurochemical profiles of ischemic lesions. However onlylimited MRS studies have been reported to-date in mice due to the challenges ofMRS in small organs. The aim of the current work was to study the neurochemicaland imaging sequelae of ischemic stroke in a mouse model in a horizontal bore14.1 Tesla system.ICR-CD1 mice were subjected to 30 minute transient middle cerebral artery occlusion.The extent of the lesion was determined by MRI. The neurochemical profileconsisting of the concentrations of 22 metabolites was measured longitudinallyfollowing the recovery from ischemia at 3, 8 and 24h in the striatum.Our model produced very reproducible striatal lesions which began to appear onT2-weighted images 8h after ischemia. At 24h, they were well established andtheir size correlated with lesions measured by histology. Profound changes couldbe observed in the neurochemical profiles of the core of the striatal lesions as earlyas 3h post-ischemia, in particular, we observed elevated lactate levels, decreases inthe putative neuronal marker N-acetyl-aspartate and in glutamate, and a transienttwo-fold glutamine increase, likely linked to excitotoxic release of glutamate andconversion to glutamine. With further ischemia evolution, other changes appearedat later time-points, mainly decreases of metabolites, consistent with disruption ofcellular function. It is interesting to note that glutamine tended to return to basallevels at 24h.We conclude that early changes in markers of energy metabolism, glutamate excitotoxicityand neuronal viability can be detected with high precision non-invasively inmice following stroke. Such investigations should lead to a better understanding andinsight into the sequential early changes in the brain parenchyma after ischemia,which could be used e.g. for identifying new targets for neuroprotection.

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OBJECTIVE: Gadolinium-enhanced pulmonary magnetic resonance angiography (MRA) can be an option in patients with a history of previous adverse reaction to iodinated contrast material and renal insufficiency. Radiation is also avoided. The aim of this study is to prospectively compare the diagnostic value of MRA with that of a diagnostic strategy, taking into account catheter angiography, computed tomography angiography (CTA), and lung scintigraphy [ventilation-perfusion (VQ)]. MATERIAL AND METHODS: Magnetic resonance angiography was done in 48 patients with clinically suspected pulmonary embolism (PE) using fast gradient echo coronal acquisition with gadolinium. Interpretation was done with native coronal images and multiplanar maximum intensity projection reconstructions. Results were compared to catheter angiography (n=15), CTA (n=34), VQ (n=45), as well as 6-12 months clinical follow-ups, according to a sequenced reference tree. RESULTS: The final diagnosis of PE was retained in 11 patients (23%). There were two false negatives and no false positive results with MRA. Computed tomography angiography resulted in no false negatives or false positives. Magnetic resonance angiography had a sensitivity of 82% and a specificity of 100%. CONCLUSION: In our study, pulmonary MRA had a sensitivity of 82% and a specificity of 100% for the diagnosis of PE, with slightly less sensitivity than CTA. In the diagnostic algorithm of PE, pulmonary MRA should be considered as an alternative to CTA when iodine contrast injection or radiation is a significant matter.

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To evaluate the efficacy of endorectal Magnetic Resonance Imaging (MRI) and Magnetic Resonance Spetroscopic Imaging (MRSI) combined with total prostate-specific antigen (tPSA) and free prostate-specific antigen (fPSA) in selecting candidates for biopsy. Subjects and Methods: 246 patients with elevated tPSA (median: 7.81 ng/ml) underwent endorectal MRI and MRSI before Transrectal Ultrasound (TRUS) biopsy (10 peripheral + 2 central cores); patients with positive biopsies were treated with radical intention; those with negative biopsies were followed up and underwent MRSI before each additional biopsy if tPSA rose persistently. Mean follow-up: 27.6 months. We compared MRI, MRSI, tPSA, and fPSA with histopathology by sextant and determined the association between the Gleason score and MRI and MRSI. We determined the most accurate combination to detect prostate cancer (PCa) using receiver operating curves; we estimated the odds ratios (OR) and calculated sensitivity, specificity, and positive and negative predictive values. Results: No difference in tPSA was found between patients with and without PCa (p = 0.551). In the peripheral zone, the risk of PCa increased with MRSI grade; patients with high-grade MRSI had the greatest risk of PCa over time (OR = 328.6); the model including MRI, MRSI, tPSA, and fPSA was more accurate (Area under Curve: AUC = 95.7%) than MRI alone (AUC = 85.1%) or fPSA alone (AUC = 78.1%), but not than MRSI alone (94.5%). In the transitional zone, the model was less accurate (AUC = 84.4%). The association (p = 0.005) between MRSI and Gleason score was significant in both zones. Conclusions: MRSI is useful in patients with elevated tPSA. High-grade MRSI lesions call for repeated biopsies. Men with negative MRSI may forgo further biopsies because a significantly high Gleason lesion is very unlikely

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Bradyrhizobium japonicum is a symbiotic nitrogen-fixing soil bacteria that induce root nodules formation in legume soybean (Glycine max.). Using (13)C- and (31)P-nuclear magnetic resonance (NMR) spectroscopy, we have analysed the metabolite profiles of cultivated B. japonicum cells and bacteroids isolated from soybean nodules. Our results revealed some quantitative and qualitative differences between the metabolite profiles of bacteroids and their vegetative state. This includes in bacteroids a huge accumulation of soluble carbohydrates such as trehalose, glutamate, myo-inositol and homospermidine as well as Pi, nucleotide pools and intermediates of the primary carbon metabolism. Using this novel approach, these data show that most of the compounds detected in bacteroids reflect the metabolic adaptation of rhizobia to the surrounding microenvironment with its host plant cells.

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Spatial data analysis mapping and visualization is of great importance in various fields: environment, pollution, natural hazards and risks, epidemiology, spatial econometrics, etc. A basic task of spatial mapping is to make predictions based on some empirical data (measurements). A number of state-of-the-art methods can be used for the task: deterministic interpolations, methods of geostatistics: the family of kriging estimators (Deutsch and Journel, 1997), machine learning algorithms such as artificial neural networks (ANN) of different architectures, hybrid ANN-geostatistics models (Kanevski and Maignan, 2004; Kanevski et al., 1996), etc. All the methods mentioned above can be used for solving the problem of spatial data mapping. Environmental empirical data are always contaminated/corrupted by noise, and often with noise of unknown nature. That's one of the reasons why deterministic models can be inconsistent, since they treat the measurements as values of some unknown function that should be interpolated. Kriging estimators treat the measurements as the realization of some spatial randomn process. To obtain the estimation with kriging one has to model the spatial structure of the data: spatial correlation function or (semi-)variogram. This task can be complicated if there is not sufficient number of measurements and variogram is sensitive to outliers and extremes. ANN is a powerful tool, but it also suffers from the number of reasons. of a special type ? multiplayer perceptrons ? are often used as a detrending tool in hybrid (ANN+geostatistics) models (Kanevski and Maignank, 2004). Therefore, development and adaptation of the method that would be nonlinear and robust to noise in measurements, would deal with the small empirical datasets and which has solid mathematical background is of great importance. The present paper deals with such model, based on Statistical Learning Theory (SLT) - Support Vector Regression. SLT is a general mathematical framework devoted to the problem of estimation of the dependencies from empirical data (Hastie et al, 2004; Vapnik, 1998). SLT models for classification - Support Vector Machines - have shown good results on different machine learning tasks. The results of SVM classification of spatial data are also promising (Kanevski et al, 2002). The properties of SVM for regression - Support Vector Regression (SVR) are less studied. First results of the application of SVR for spatial mapping of physical quantities were obtained by the authorsin for mapping of medium porosity (Kanevski et al, 1999), and for mapping of radioactively contaminated territories (Kanevski and Canu, 2000). The present paper is devoted to further understanding of the properties of SVR model for spatial data analysis and mapping. Detailed description of the SVR theory can be found in (Cristianini and Shawe-Taylor, 2000; Smola, 1996) and basic equations for the nonlinear modeling are given in section 2. Section 3 discusses the application of SVR for spatial data mapping on the real case study - soil pollution by Cs137 radionuclide. Section 4 discusses the properties of the modelapplied to noised data or data with outliers.

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The vascular properties of large vessels in the obese have not been adequately studied. We used cardiovascular magnetic resonance imaging to quantify the cross-sectional area and elastic properties of the ascending thoracic and abdominal aorta in 21 clinically healthy obese young adult men and 25 men who were age-matched lean controls. Obese subjects had greater maximal cross-sectional area of the ascending thoracic aorta (984 +/- 252 vs 786 +/- 109 mm(2), p <0.01) and of the abdominal aorta (415 +/- 71 vs 374 +/- 51 mm(2), p <0.05). When indexed for height the differences persisted, but when indexed for body surface area, a significant difference between groups was found only for the maximal abdominal aortic cross-sectional area. The obese subjects also had decreased abdominal aortic elasticity, characterized by 24% lower compliance (0.0017 +/- 0.0004 vs 0.0021 +/- 0.0005 mm(2)/kPa/mm, p <0.01), 22% higher stiffness index beta (6.0 +/- 1.5 vs 4.9 +/- 0.7, p <0.005), and 41% greater pressure-strain elastic modulus (72 +/- 25 vs 51 +/- 9, p <0.005). At the ascending thoracic aorta, only the pressure-strain elastic modulus was different between obese and lean subjects (85 +/- 42 vs 65 +/- 26 kPa, respectively; p <0.05), corresponding to a 31% difference-but arterial compliance and stiffness index were not significantly different between groups. In clinically healthy young adult obese men, obesity is associated with increased cross-sectional aortic area and decreased aortic elasticity.