Influence of some processing and storage conditions on the mechanical properties of oat flakes

Flake breakage and texture are important quality, criteria in oat flakes. These properties are determined by the mechanical properties of the flakes, which may be influenced by process variables such as kilning and flake thickness. A pin deformation method was used to measure the rupture force of individual oat flakes at different water activities. The monolayer value of ground oat flakes ranged from 5.83 to 684 g/100 g dry matter Thick flakes were strongest, requiring 3.4 N to rupture the flake compared to 2.2 N for the thin flakes. Water softened the flakes, causing a decrease in rupture force from 3.6 N to 2.4 N as water activity; increased from 0.115 to 0.848. Kilning had a significant effect on flake thickness but not on the mechanical properties. This study suggests that oat flakes should be stored at water activity 0.4 or less as there is a sharp loss of flake strength above this point.

Atopostipes suicloacale gen. nov., sp. nov., isolated from an underground swine manure storage pit

Phenotypic and molecular genetic studies were performed on an unknown facultative anaerobic, catalase-negative, non-spore-forming, rod-shaped bacterium isolated from a pig manure storage pit. The unknown bacterium was nutritionally fastidious with growth enhanced by the addition of rumen fluid and was phenotypically initially identified as an Eubacterium species. Comparative 16S rRNA gene sequencing studies, however, revealed that the unknown bacterium was phylogenetically distant from Eubacterium limosum (the type species of the genus Eubacterium) and related organisms. Phylogenetically, the unknown species displayed a close association with an uncultured organism from human subgingival plaque and formed an unknown sub-line within a cluster of organisms which includes Alloioccoccus otitis, Alkalibacterium olivoapovliticus, Allofustis seminis, Dolosigranulum pigrum, and related organisms, within the low mol% G + C Gram-positive bacteria. Sequence divergence values of > 8% with all known taxonomically recognised taxa, however, clearly indicates the novel bacterium represents a hitherto unknown genus. Based on both phenotypic and phylogenetic considerations, it is proposed that the unknown bacterium from pig manure be classified in a new genus and species, as Atopostipes suicloacale gen. nov., sp. nov. The type strain of Atopostipes suicloacale is PPC79(T) = NRRL 23919(T) = DSM 15692(T). Crown Copyright (C) 2004 Published by Elsevier Ltd. All rights reserved.

The effects of low-temperature potato storage and washing and soaking pre-treatments on the acrylamide content of French fries

BACKGROUND: Since the discovery in 2002 of acrylamide in a wide range of foods, there has been much work done to explore mechanisms of formation and to reduce acrylamide in commercial products. This study aimed to investigate simple measures which could be used to reduce acrylamide formation in home-cooked French fries, using potatoes from three cultivars stored under controlled conditions and sampled at three time points. RESULTS: The reducing sugar content for all three cultivars increased during storage, which led to increased acrylamide levels in the French fries. Washing and soaking (30 min or 2 h) raw French fries before cooking led to reductions in acrylamide of up to 23, 38 and 48% respectively. Pre-treated fries were lighter in colour after cooking than the corresponding controls. CONCLUSION: Pre-treatments such as soaking or washing raw French fries in water reduce acrylamide and colour formation in the final product when cooking is stopped at a texture-determined endpoint. (c) 2008 Society of Chemical Industry.

Lag-1 sparing in the attentional blink: benefits and costs of integrating two events into a single episode

When people monitor a visual stream of rapidly presented stimuli for two targets (T1 and T2), they often miss T2 if it falls into a time window of about half a second after T1 onset-the attentional blink. However, if T2 immediately follows T1, performance is often reported being as good as that at long lags-the so-called Lag-1 sparing effect. Two experiments investigated the mechanisms underlying this effect. Experiment 1 showed that, at Lag 1, requiring subjects to correctly report both identity and temporal order of targets produces relatively good performance on T2 but relatively bad performance on T1. Experiment 2 confirmed that subjects often confuse target order at short lags, especially if the two targets are equally easy to discriminate. Results suggest that, if two targets appear in close succession, they compete for attentional resources. If the two competitors are of unequal strength the stronger one is more likely to win and be reported at the expense of the other. If the two are equally strong, however, they will often be integrated into the same attentional episode and thus get both access to attentional resources. But this comes with a cost, as it eliminates information about the targets' temporal order.

Integrative views on dual-task costs

In this paper, we introduce a special issue about unique and shared mechanisms underlying the performance limitations observed in dual tasks. In particular, the relationship between task-switching costs, the attentional-blink effect, and the psychological refractory period effect is reviewed. These costs are traditionally attributed to fixed and unique capacity limitations for task set reconfiguration, target identification, and response selection, respectively However, we argue that more global attentional processes play a role that cuts across these paradigms. This is reason for a more paradigm-independent approach to processing limitations in dual tasks.

Generation, description and storage of dendritic morphology data

It is generally assumed that the variability of neuronal morphology has an important effect on both the connectivity and the activity of the nervous system, but this effect has not been thoroughly investigated. Neuroanatomical archives represent a crucial tool to explore structure–function relationships in the brain. We are developing computational tools to describe, generate, store and render large sets of three–dimensional neuronal structures in a format that is compact, quantitative, accurate and readily accessible to the neuroscientist. Single–cell neuroanatomy can be characterized quantitatively at several levels. In computer–aided neuronal tracing files, a dendritic tree is described as a series of cylinders, each represented by diameter, spatial coordinates and the connectivity to other cylinders in the tree. This ‘Cartesian’ description constitutes a completely accurate mapping of dendritic morphology but it bears little intuitive information for the neuroscientist. In contrast, a classical neuroanatomical analysis characterizes neuronal dendrites on the basis of the statistical distributions of morphological parameters, e.g. maximum branching order or bifurcation asymmetry. This description is intuitively more accessible, but it only yields information on the collective anatomy of a group of dendrites, i.e. it is not complete enough to provide a precise ‘blueprint’ of the original data. We are adopting a third, intermediate level of description, which consists of the algorithmic generation of neuronal structures within a certain morphological class based on a set of ‘fundamental’, measured parameters. This description is as intuitive as a classical neuroanatomical analysis (parameters have an intuitive interpretation), and as complete as a Cartesian file (the algorithms generate and display complete neurons). The advantages of the algorithmic description of neuronal structure are immense. If an algorithm can measure the values of a handful of parameters from an experimental database and generate virtual neurons whose anatomy is statistically indistinguishable from that of their real counterparts, a great deal of data compression and amplification can be achieved. Data compression results from the quantitative and complete description of thousands of neurons with a handful of statistical distributions of parameters. Data amplification is possible because, from a set of experimental neurons, many more virtual analogues can be generated. This approach could allow one, in principle, to create and store a neuroanatomical database containing data for an entire human brain in a personal computer. We are using two programs, L–NEURON and ARBORVITAE, to investigate systematically the potential of several different algorithms for the generation of virtual neurons. Using these programs, we have generated anatomically plausible virtual neurons for several morphological classes, including guinea pig cerebellar Purkinje cells and cat spinal cord motor neurons. These virtual neurons are stored in an online electronic archive of dendritic morphology. This process highlights the potential and the limitations of the ‘computational neuroanatomy’ strategy for neuroscience databases.