Magnesium and iron deficiencies alter Cd accumulation in Salix viminalis L.

Evidence exists that Cd and certain nutrient elements, such as Fe and Mg, could share similar mechanisms of plant uptake and accumulation. Here we report that Mg and Fe deficiency in mature plants of Salix viminalis, grown in hydroponic solutions containing 5 µg ml(-1) of Cd, caused a significant increase in Cd accumulation in roots, stems and leaves. Cd (µg g(-1) dry weight) was determined following three treatments: 1) Cd treatment in complete nutrient solution; 2) Cd treatment with Fe deficiency; and 3) Cd treatment with Mg deficiency, yielding, respectively: in young leaves (65.3, 76.1, and 92.2), mature leaves (51.5 to 76.3 and 87.1), upper stems (80.6, 116.8, and 130.6) lower stems (67.2, 119, and 102.3), roots (377.1, 744.8, and 442,5). Our results suggest that Cd utilizes the same uptake and transport pathways as Mg and Fe. Evidence exists that Mg and Fe uptake and translocation could be further facilitated by plants as an adaptive response to deficiency of these elements. Such physiological reaction could additionally stimulate Cd accumulation. Although Cd uptake was mostly confined in roots, high Cd content in aerial plant parts (51.5-130.6 µg g(-1)) indicates that the analysed Salix viminalis genotype is suitable for phytoextraction.

Role of myelin plasticity in oscillations and synchrony of neuronal activity.

Conduction time is typically ignored in computational models of neural network function. Here we consider the effects of conduction delays on the synchrony of neuronal activity and neural oscillators, and evaluate the consequences of allowing conduction velocity (CV) to be regulated adaptively. We propose that CV variation, mediated by myelin, could provide an important mechanism of activity-dependent nervous system plasticity. Even small changes in CV, resulting from small changes in myelin thickness or nodal structure, could have profound effects on neuronal network function in terms of spike-time arrival, oscillation frequency, oscillator coupling, and propagation of brain waves. For example, a conduction delay of 5ms could change interactions of two coupled oscillators at the upper end of the gamma frequency range (∼100Hz) from constructive to destructive interference; delays smaller than 1ms could change the phase by 30°, significantly affecting signal amplitude. Myelin plasticity, as another form of activity-dependent plasticity, is relevant not only to nervous system development but also to complex information processing tasks that involve coupling and synchrony among different brain rhythms. We use coupled oscillator models with time delays to explore the importance of adaptive time delays and adaptive synaptic strengths. The impairment of activity-dependent myelination and the loss of adaptive time delays may contribute to disorders where hyper- and hypo-synchrony of neuronal firing leads to dysfunction (e.g., dyslexia, schizophrenia, epilepsy).

Patient-centered yes/no prognosis using learning machines.

In the last 15 years several machine learning approaches have been developed for classification and regression. In an intuitive manner we introduce the main ideas of classification and regression trees, support vector machines, bagging, boosting and random forests. We discuss differences in the use of machine learning in the biomedical community and the computer sciences. We propose methods for comparing machines on a sound statistical basis. Data from the German Stroke Study Collaboration is used for illustration. We compare the results from learning machines to those obtained by a published logistic regression and discuss similarities and differences.

Water diffusion changes in Wallerian degeneration and their dependence on white matter architecture.

This study investigates water diffusion changes in Wallerian degeneration. We measured indices derived from the diffusion tensor (DT) and T2-weighted signal intensities in the descending motor pathways of patients with small chronic lacunar infarcts of the posterior limb of the internal capsule on one side. We compared these measurements in the healthy and lesioned sides at different levels in the brainstem caudal to the primary lesion. We found that secondary white matter degeneration is revealed by a large reduction in diffusion anisotropy only in regions where fibers are arranged in isolated bundles of parallel fibers, such as in the cerebral peduncle. In regions where the degenerated pathway crosses other tracts, such as in the rostral pons, paradoxically there is almost no change in diffusion anisotropy, but a significant change in the measured orientation of fibers. The trace of the diffusion tensor is moderately increased in all affected regions. This allows one to differentiate secondary and primary fiber loss where the increase in trace is considerably higher. We show that DT-MRI is more sensitive than T2-weighted MRI in detecting Wallerian degeneration. Significant diffusion abnormalities are observed over the entire trajectory of the affected pathway in each patient. This finding suggests that mapping degenerated pathways noninvasively with DT-MRI is feasible. However, the interpretation of water diffusion data is complex and requires a priori information about anatomy and architecture of the pathway under investigation. In particular, our study shows that in regions where fibers cross, existing DT-MRI-based fiber tractography algorithms may lead to erroneous conclusion about brain connectivity.

Comparison of novel and existing methods for detection of linkage disequilibrium using parent-child trios in the GAW12 genetic isolate simulated data.

A novel method for joint detection of association caused by linkage disequilibrium (LD) and estimation of both recombination fraction and linkage disequilibrium parameters was compared to several existing implementations of the transmission/disequilibrium test (TDT) and modifications of the TDT in the simulated genetic isolate data from Genetic Analysis Workshop 12. The first completely genotyped trio of affected child and parents was selected from each family in each replicate so that the TDT tests are valid tests of linkage and association, rather than being only valid as tests for linkage. In general, power to detect LD using the genome-wide scan markers was inadequate in the individual replicate samples, but the power was better when analyzing several SNP markers in candidate gene 1.

In vivo fiber tractography using DT-MRI data.

Fiber tract trajectories in coherently organized brain white matter pathways were computed from in vivo diffusion tensor magnetic resonance imaging (DT-MRI) data. First, a continuous diffusion tensor field is constructed from this discrete, noisy, measured DT-MRI data. Then a Frenet equation, describing the evolution of a fiber tract, was solved. This approach was validated using synthesized, noisy DT-MRI data. Corpus callosum and pyramidal tract trajectories were constructed and found to be consistent with known anatomy. The method's reliability, however, degrades where the distribution of fiber tract directions is nonuniform. Moreover, background noise in diffusion-weighted MRIs can cause a computed trajectory to hop from tract to tract. Still, this method can provide quantitative information with which to visualize and study connectivity and continuity of neural pathways in the central and peripheral nervous systems in vivo, and holds promise for elucidating architectural features in other fibrous tissues and ordered media.

Statistical artifacts in diffusion tensor MRI (DT-MRI) caused by background noise.

This work helps elucidate how background noise introduces statistical artifacts in the distribution of the sorted eigenvalues and eigenvectors in diffusion tensor MRI (DT-MRI) data. Although it was known that sorting eigenvalues (principal diffusivities) by magnitude introduces a bias in their sample mean within a homogeneous region of interest (ROI), here it is shown that magnitude sorting also introduces a significant bias in the variance of the sample mean eigenvalues. New methods are presented to calculate the mean and variance of the eigenvectors of the diffusion tensor, based on a dyadic tensor representation of eigenvalue-eigenvector pairs. Based on their use it is shown that sorting eigenvalues by magnitude also introduces a bias in the mean and the variance of the sample eigenvectors (principal directions). This required the development of new methods to calculate the mean and variance of the eigenvectors of the diffusion tensor, based on a dyadic tensor representation of eigenvalue-eigenvector pairs. Moreover, a new approach is proposed to order these pairs within an ROI. To do this, a correspondence between each principal axis of the diffusion ellipsoid, an eigenvalue-eigenvector pair, and a dyadic tensor constructed from it is exploited. A measure of overlap between principal axes of diffusion ellipsoids in different voxels is defined that employs projections between these dyadic tensors. The optimal eigenvalue assignment within an ROI maximizes this overlap. Bias in the estimate of the mean and of the variance of the eigenvalues and of their corresponding eigenvectors is reduced in DT-MRI experiments and in Monte Carlo simulations of such experiments. Improvement is most significant in isotropic regions, but some is also observed in anisotropic regions. This statistical framework should enhance our ability to characterize microstructure and architecture of healthy tissue, and help to assess its changes in development, disease, and degeneration. Mitigating these artifacts should also improve the characterization of diffusion anisotropy and the elucidation of fiber-tract trajectories in the brain and in other fibrous tissues. Magn Reson Med 44:41-50, 2000. Published 2000 Wiley-Liss, Inc.

Color schemes to represent the orientation of anisotropic tissues from diffusion tensor data: application to white matter fiber tract mapping in the human brain.

This paper investigates the use of color to represent the directional information contained in the diffusion tensor. Ideally, one wants to take into account both the properties of human color vision and of the given display hardware to produce a representation in which differences in the orientation of anisotropic structures are proportional to the perceived differences in color. It is argued here that such a goal cannot be achieved in general and therefore, empirical or heuristic schemes, which avoid some of the common artifacts of previously proposed approaches, are implemented. Directionally encoded color (DEC) maps of the human brain obtained using these schemes clearly show the main association, projection, and commissural white matter pathways. In the brainstem, motor and sensory pathways are easily identified and can be differentiated from the transverse pontine fibers and the cerebellar peduncles. DEC maps obtained from diffusion tensor imaging data provide a simple and effective way to visualize fiber direction, useful for investigating the structural anatomy of different organs. Magn Reson Med 42:526-540, 1999.

Noise characteristics of 3-D and 2-D PET images.

We analyzed the noise characteristics of two-dimensional (2-D) and three-dimensional (3-D) images obtained from the GE Advance positron emission tomography (PET) scanner. Three phantoms were used: a uniform 20-cm phantom, a 3-D Hoffman brain phantom, and a chest phantom with heart and lung inserts. Using gated acquisition, we acquired 20 statistically equivalent scans of each phantom in 2-D and 3-D modes at several activity levels. From these data, we calculated pixel normalized standard deviations (NSD's), scaled to phantom mean, across the replicate scans, which allowed us to characterize the radial and axial distributions of pixel noise. We also performed sequential measurements of the phantoms in 2-D and 3-D modes to measure noise (from interpixel standard deviations) as a function of activity. To compensate for the difference in axial slice width between 2-D and 3-D images (due to the septa and reconstruction effects), we developed a smoothing kernel to apply to the 2-D data. After matching the resolution, the ratio of image-derived NSD values (NSD2D/NSD3D)2 averaged throughout the uniform phantom was in good agreement with the noise equivalent count (NEC) ratio (NEC3D/NEC2D). By comparing different phantoms, we showed that the attenuation and emission distributions influence the spatial noise distribution. The estimates of pixel noise for 2-D and 3-D images produced here can be applied in the weighting of PET kinetic data and may be useful in the design of optimal dose and scanning requirements for PET studies. The accuracy of these phantom-based noise formulas should be validated for any given imaging situation, particularly in 3-D, if there is significant activity outside the scanner field of view.

Effects of time delay in cardiac blood flow measurements by bolus H2(15)O.

Myocardial blood flow (rMBF) can be measured using dynamic positron emission tomography (PET) and bolus injection of H2(15)O. Recent studies indicate that large errors in the estimates of flow (f) can be produced by time shifts between the true arterial input function and the measured input function [A(t)]. We have investigated this phenomenon further using A(t) derived from patient data, and using simulated myocardial time activity curves [M(t)]. We found that with judicious choice of scan parameters and region of interest (ROI) placement, these errors can be greatly reduced. In particular, when A(t) is measured from the left ventricular (LV) cavity, the bias in f is negligible over a wide range of circumstances. However, when A(t) is not measured from the LV cavity, the bias in flow can be large for short scans (< 2 min) or low flow values (f < 0.4 ml/g/min). We show that the bias is primarily due to the spill-over term in the model that is most commonly used to compute rMBF and suggest some correction methods. We conclude that it is possible to avoid errors in estimates of flow due to time delay.

Profound increase in viscosity and aggregation of pig gastric mucin at low pH.

Epithelial mucins are glycoproteins of very large molecular weight that provide viscoelastic and gel-forming properties to mucus, the jellylike protective layer covering epithelial organs. In the mammalian stomach the mucus gel layer protects the underlying epithelial cells from HCl in the lumen. We report here that pig gastric mucin undergoes a 100-fold increase in viscosity in vitro when pH is lowered from 7 to 2. Sedimentation velocity and dynamic light-scattering measurements revealed the formation of extremely large aggregates at low pH consistent with the observed increase in viscosity. Aggregation of mucin at low pH was prevented by increasing the ionic strength, suggesting the involvement of electrostatic interactions. Trypsin digestion and thiol reduction, but not enzymatic removal of neuraminic acid, prevented aggregation at low pH. This implies that the peptide core rather than the oligosaccharide side chains of the molecule is involved in the aggregation of mucin at low pH. Increased aggregation and viscosity at low pH were also observed in a solvent made to mimic the ionic composition of gastric juice, indicating the physiological relevance of our findings. Our observations suggest that one mechanism of gastric protection may be the ability of gastric mucin to undergo aggregation with a marked increase in viscosity at low pH.