Stress generation in the tension wood of poplar is based on the lateral swelling power of the G-layer

The mechanism of active stress generation in tension wood is still not fully understood. To characterize the functional interdependency between the G-layer and the secondary cell wall, nanostructural characterization and mechanical tests were performed on native tension wood tissues of poplar (Populus nigra x Populus deltoids) and on tissues in which the G-layer was removed by an enzymatic treatment. In addition to the well-known axial orientation of the cellulose fibrils in the G-layer, it was shown that the microfibril angle of the S2-layer was very large (about 36 degrees). The removal of the G-layer resulted in an axial extension and a tangential contraction of the tissues. The tensile stress-strain curves of native tension wood slices showed a jagged appearance after yield that could not be seen in the enzyme-treated samples. The behaviour of the native tissue was modelled by assuming that cells deform elastically up to a critical strain at which the G-layer slips, causing a drop in stress. The results suggest that tensile stresses in poplar are generated in the living plant by a lateral swelling of the G-layer which forces the surrounding secondary cell wall to contract in the axial direction.

In vitro study on gas generation and prebiotic effects of some carbohydrates and their mixtures

This study was carried out to examine the effect or inulin (IN), fructooligosaccharide (FOS), polydextrose (POL) and isomaltooligosaccharides (ISO), alone and in combination, on gas production, gas composition and prebiotic effects. Static batch culture fermentation was performed with faecal samples from three healthy volunteers to study the volume and composition of gas generated and changes in bacterial populations. Four carbohydrates alone or mixed with one another (50:50) were examined. Prebiotic index (PI) was calculated and used to compare the prebiotic effect. The high amount of gas produced by IN was reduced by mixing it with FOS. No reduction in gas generation was observed when POL and ISO mixed with other substrates. It was found that the mixture of IN and FOS was effective in reducing the amount of gas produced while augmenting or maintaining their potential to Support the growth of bifidobacteria in Faecal batch culture as the highest PI was achieved with FOS alone and a mixture of FOS and IN. It was also found that high volume of gas was generated in presence of POL and ISO and they had lower prebiotic effect. The results of this study imply that a Mixture of prebiotics could prove effective in reducing the amount of gas generated by the gut microflora. (c) 2007 Elsevier Ltd. All rights reserved.

Kinetic modeling of the generation of 2-and 3-methylbutanal in a heated extract of beef liver

Quantitative control of aroma generation during the Maillard reaction presents great scientific and industrial interest. Although there have been many studies conducted in simplified model systems, the results are difficult to apply to complex food systems, where the presence of other components can have a significant impact. In this work, an aqueous extract of defatted beef liver was chosen as a simplified food matrix for studying the kinetics of the Mallard reaction. Aliquots of the extract were heated under different time and temperature conditions and analyzed for sugars, amino acids, and methylbutanals, which are important Maillard-derived aroma compounds formed in cooked meat. Multiresponse kinetic modeling, based on a simplified mechanistic pathway, gave a good fit with the experimental data, but only when additional steps were introduced to take into account the interactions of glucose and glucose-derived intermediates with protein and other amino compounds. This emphasizes the significant role of the food matrix in controlling the Maillard reaction.

Random number generation as an index of controlled processing

Random number generation (RNG) is a functionally complex process that is highly controlled and therefore dependent on Baddeley's central executive. This study addresses this issue by investigating whether key predictions from this framework are compatible with empirical data. In Experiment 1, the effect of increasing task demands by increasing the rate of the paced generation was comprehensively examined. As expected, faster rates affected performance negatively because central resources were increasingly depleted. Next, the effects of participants' exposure were manipulated in Experiment 2 by providing increasing amounts of practice on the task. There was no improvement over 10 practice trials, suggesting that the high level of strategic control required by the task was constant and not amenable to any automatization gain with repeated exposure. Together, the results demonstrate that RNG performance is a highly controlled and demanding process sensitive to additional demands on central resources (Experiment 1) and is unaffected by repeated performance or practice (Experiment 2). These features render the easily administered RNG task an ideal and robust index of executive function that is highly suitable for repeated clinical use.

Phase resetting as a mechanism of ERP generation: evidence from the power spectrum

A Neural Mass model is coupled with a novel method to generate realistic Phase reset ERPs. The power spectra of these synthetic ERPs are compared with the spectra of real ERPs and synthetic ERPs generated via the Additive model. Real ERP spectra show similarities with synthetic Phase reset ERPs and synthetic Additive ERPs.

Computer generation and quantitative morphometric analysis of virtual neurons

An important goal in computational neuroanatomy is the complete and accurate simulation of neuronal morphology. We are developing computational tools to model three-dimensional dendritic structures based on sets of stochastic rules. This paper reports an extensive, quantitative anatomical characterization of simulated motoneurons and Purkinje cells. We used several local and global algorithms implemented in the L-Neuron and ArborVitae programs to generate sets of virtual neurons. Parameters statistics for all algorithms were measured from experimental data, thus providing a compact and consistent description of these morphological classes. We compared the emergent anatomical features of each group of virtual neurons with those of the experimental database in order to gain insights on the plausibility of the model assumptions, potential improvements to the algorithms, and non-trivial relations among morphological parameters. Algorithms mainly based on local constraints (e.g., branch diameter) were successful in reproducing many morphological properties of both motoneurons and Purkinje cells (e.g. total length, asymmetry, number of bifurcations). The addition of global constraints (e.g., trophic factors) improved the angle-dependent emergent characteristics (average Euclidean distance from the soma to the dendritic terminations, dendritic spread). Virtual neurons systematically displayed greater anatomical variability than real cells, suggesting the need for additional constraints in the models. For several emergent anatomical properties, a specific algorithm reproduced the experimental statistics better than the others did. However, relative performances were often reversed for different anatomical properties and/or morphological classes. Thus, combining the strengths of alternative generative models could lead to comprehensive algorithms for the complete and accurate simulation of dendritic morphology.