Vascular endothelial growth factor induces contralesional corticobulbar plasticity and functional neurological recovery in the ischemic brain

Vascular endothelial growth factor (VEGF) is a potent angiogenic factor, which also has neuroprotective activity. In view of these dual actions on vessels and neurons, we were interested whether VEGF promotes long distance axonal plasticity in the ischemic brain. Herein, we show that VEGF promotes neurological stroke recovery in mice when delivered in a delayed way starting 3 days after middle cerebral artery occlusion. Using anterograde tract-tracing experiments that we combined with histochemical and molecular biological studies, we demonstrate that although VEGF promoted angiogenesis predominantly in the ischemic hemisphere, pronounced axonal sprouting was induced by VEGF in the contralesional, but not the ipsilesional corticobulbar system. Corticobulbar plasticity was accompanied by the deactivation of the matrix metalloproteinase MMP9 in the lesioned hemisphere and the transient downregulation of the axonal growth inhibitors NG2 proteoglycan and brevican and the guidance molecules ephrin B1/2 in the contralesional hemisphere. The regulation of matrix proteinases, growth inhibitors, and guidance molecules offers insights how brain plasticity is controlled in the ischemic brain.

On the Synthesis of Microarray Experiments

With many different investigators studying the same disease and with a strong commitment to publish supporting data in the scientific community, there are often many different datasets available for any given disease. Hence there is substantial interest in finding methods for combining these datasets to provide better and more detailed understanding of the underlying biology. We consider the synthesis of different microarray data sets using a random effects paradigm and demonstrate how relatively standard statistical approaches yield good results. We identify a number of important and substantive areas which require further investigation.

Augmenting the effective field of view of optical tracking cameras--a way to overcome difficulties during intraoperative camera alignment

An Internet survey demonstrated the existence of problems related to intraoperative tracking camera set-up and alignment. It is hypothesized that these problems are a result of the limited field of view of today's optoelectronic camera systems, which is usually insufficiently large to keep the entire site of surgical action in view during an intervention. A method is proposed to augment a camera's field of view by actively controlling camera orientation, enabling it to track instruments as they are used intraoperatively. In an experimental study, an increase of almost 300% was found in the effective volume in which instruments could be tracked.

Hexose-6-phosphate dehydrogenase modulates 11beta-hydroxysteroid dehydrogenase type 1-dependent metabolism of 7-keto- and 7beta-hydroxy-neurosteroids

BACKGROUND: The role of 11beta-hydroxysteroid dehydrogenase type 1 (11beta-HSD1) in the regulation of energy metabolism and immune system by locally reactivating glucocorticoids has been extensively studied. Experiments determining initial rates of enzyme activity revealed that 11beta-HSD1 can catalyze both the reductase and the dehydrogenase reaction in cell lysates, whereas it predominantly catalyzes the reduction of cortisone to cortisol in intact cells that also express hexose-6-phosphate dehydrogenase (H6PDH), which provides cofactor NADPH. Besides its role in glucocorticoid metabolism, there is evidence that 11beta-HSD1 is involved in the metabolism of 7-keto- and 7-hydroxy-steroids; however the impact of H6PDH on this alternative function of 11beta-HSD1 has not been assessed. METHODOLOGY: We investigated the 11beta-HSD1-dependent metabolism of the neurosteroids 7-keto-, 7alpha-hydroxy- and 7beta-hydroxy-dehydroepiandrosterone (DHEA) and 7-keto- and 7beta-hydroxy-pregnenolone, respectively, in the absence or presence of H6PDH in intact cells. 3D-structural modeling was applied to study the binding of ligands in 11beta-HSD1. PRINCIPAL FINDINGS: We demonstrated that 11beta-HSD1 functions in a reversible way and efficiently catalyzed the interconversion of these 7-keto- and 7-hydroxy-neurosteroids in intact cells. In the presence of H6PDH, 11beta-HSD1 predominantly converted 7-keto-DHEA and 7-ketopregnenolone into their corresponding 7beta-hydroxy metabolites, indicating a role for H6PDH and 11beta-HSD1 in the local generation of 7beta-hydroxy-neurosteroids. 3D-structural modeling offered an explanation for the preferred formation of 7beta-hydroxy-neurosteroids. CONCLUSIONS: Our results from experiments determining the steady state concentrations of glucocorticoids or 7-oxygenated neurosteroids suggested that the equilibrium between cortisone and cortisol and between 7-keto- and 7-hydroxy-neurosteroids is regulated by 11beta-HSD1 and greatly depends on the coexpression with H6PDH. Thus, the impact of H6PDH on 11beta-HSD1 activity has to be considered for understanding both glucocorticoid and neurosteroid action in different tissues.

Influence of oxygen therapy on glucose-lactate metabolism after diffuse brain injury

OBJECT: Severe traumatic brain injury (TBI) imposes a huge metabolic load on brain tissue, which can be summarized initially as a state of hypermetabolism and hyperglycolysis. In experiments O2 consumption has been shown to increase early after trauma, especially in the presence of high lactate levels and forced O2 availability. In recent clinical studies the effect of increasing O2 availability on brain metabolism has been analyzed. By their nature, however, clinical trauma models suffer from a heterogeneous injury distribution. The aim of this study was to analyze, in a standardized diffuse brain injury model, the effect of increasing the fraction of inspired O2 on brain glucose and lactate levels, and to compare this effect with the metabolism of the noninjured sham-operated brain. METHODS: A diffuse severe TBI model developed by Foda and Maramarou, et al., in which a 420-g weight is dropped from a height of 2 m was used in this study. Forty-one male Wistar rats each weighing approximately 300 g were included. Anesthesized rats were monitored by placing a femoral arterial line for blood pressure and blood was drawn for a blood gas analysis. Two time periods were defined: Period A was defined as preinjury and Period B as postinjury. During Period B two levels of fraction of inspired oxygen (FiO2) were studied: air (FiO2 0.21) and oxygen (FiO2 1). Four groups were studied including sham-operated animals: air-air-sham (AAS); air-O2-sham (AOS); air-air-trauma (AAT); and air-O2-trauma (AOT). In six rats the effect of increasing the FiO2 on serum glucose and lactate was analyzed. During Period B lactate values in the brain determined using microdialysis were significantly lower (p < 0.05) in the AOT group than in the AAT group and glucose values in the brain determined using microdialysis were significantly higher (p < 0.04). No differences were demonstrated in the other groups. Increasing the FiO2 had no significant effect on the serum levels of glucose and lactate. CONCLUSIONS: Increasing the FiO2 influences dialysate glucose and lactate levels in injured brain tissue. Using an FiO2 of 1 influences brain metabolism in such a way that lactate is significantly reduced and glucose significantly increased. No changes in dialysate glucose and lactate values were found in the noninjured brain.

Synthesis of computations and experiments for obtaining pulsatile gas flow rates from dynamic pressure difference measurements across an orifice-plate meter

The use of conventional orifice-plate meter is typically restricted to measurements of steady flows. This study proposes a new and effective computational-experimental approach for measuring the time-varying (but steady-in-the-mean) nature of turbulent pulsatile gas flows. Low Mach number (effectively constant density) steady-in-the-mean gas flows with large amplitude fluctuations (whose highest significant frequency is characterized by the value fF) are termed pulsatile if the fluctuations have a direct correlation with the time-varying signature of the imposed dynamic pressure difference and, furthermore, they have fluctuation amplitudes that are significantly larger than those associated with turbulence or random acoustic wave signatures. The experimental aspect of the proposed calibration approach is based on use of Coriolis-meters (whose oscillating arm frequency fcoriolis >> fF) which are capable of effectively measuring the mean flow rate of the pulsatile flows. Together with the experimental measurements of the mean mass flow rate of these pulsatile flows, the computational approach presented here is shown to be effective in converting the dynamic pressure difference signal into the desired dynamic flow rate signal. The proposed approach is reliable because the time-varying flow rate predictions obtained for two different orifice-plate meters exhibit the approximately same qualitative, dominant features of the pulsatile flow.

Dynamic modeling of active regeneration in catalyzed and non-catalyzed diesel particulate filters

Particulate matter (PM) emissions standards set by the US Environmental Protection Agency (EPA) have become increasingly stringent over the years. The EPA regulation for PM in heavy duty diesel engines has been reduced to 0.01 g/bhp-hr for the year 2010. Heavy duty diesel engines make use of an aftertreatment filtration device, the Diesel Particulate Filter (DPF). DPFs are highly efficient in filtering PM (known as soot) and are an integral part of 2010 heavy duty diesel aftertreatment system. PM is accumulated in the DPF as the exhaust gas flows through it. This PM needs to be removed by oxidation periodically for the efficient functioning of the filter. This oxidation process is also known as regeneration. There are 2 types of regeneration processes, namely active regeneration (oxidation of PM by external means) and passive oxidation (oxidation of PM by internal means). Active regeneration occurs typically in high temperature regions, about 500 - 600 °C, which is much higher than normal diesel exhaust temperatures. Thus, the exhaust temperature has to be raised with the help of external devices like a Diesel Oxidation Catalyst (DOC) or a fuel burner. The O2 oxidizes PM producing CO2 as oxidation product. In passive oxidation, one way of regeneration is by the use of NO2. NO2 oxidizes the PM producing NO and CO2 as oxidation products. The passive oxidation process occurs at lower temperatures (200 - 400 °C) in comparison to the active regeneration temperatures. Generally, DPF substrate walls are washcoated with catalyst material to speed up the rate of PM oxidation. The catalyst washcoat is observed to increase the rate of PM oxidation. The goal of this research is to develop a simple mathematical model to simulate the PM depletion during the active regeneration process in a DPF (catalyzed and non-catalyzed). A simple, zero-dimensional kinetic model was developed in MATLAB. Experimental data required for calibration was obtained by active regeneration experiments performed on PM loaded mini DPFs in an automated flow reactor. The DPFs were loaded with PM from the exhaust of a commercial heavy duty diesel engine. The model was calibrated to the data obtained from active regeneration experiments. Numerical gradient based optimization techniques were used to estimate the kinetic parameters of the model.

Evaluating retraining rules for semi-supervised learning in neural network based cursive word recognition

Training a system to recognize handwritten words is a task that requires a large amount of data with their correct transcription. However, the creation of such a training set, including the generation of the ground truth, is tedious and costly. One way of reducing the high cost of labeled training data acquisition is to exploit unlabeled data, which can be gathered easily. Making use of both labeled and unlabeled data is known as semi-supervised learning. One of the most general versions of semi-supervised learning is self-training, where a recognizer iteratively retrains itself on its own output on new, unlabeled data. In this paper we propose to apply semi-supervised learning, and in particular self-training, to the problem of cursive, handwritten word recognition. The special focus of the paper is on retraining rules that define what data are actually being used in the retraining phase. In a series of experiments it is shown that the performance of a neural network based recognizer can be significantly improved through the use of unlabeled data and self-training if appropriate retraining rules are applied.

Learning Paradigms Exemplified by Virtual Experiments with Honey Bees

Learning is based on rules that can be elucidated by behavioural experiments. This article focuses on virtual experiments, in which non-associative learning (habituation, sensitization) and principles of associative learning (contiguity, inhibitory learning, generalization, overshadowing, positive and negative patterning) can be examined using 'virtual' honey bees in PER (Proboscis Reaction Extension) conditioning experiments. Users can develop experimental designs, simulate and document the experiments and find explanations and suggestions for the analysis of the learning experiments. The virtual experiments are based on video sequences and data from actual learning experiments. The bees' responses are determined by probability-based learning profiles.

Neoliberalism, the Third Way and Social Work: the UK experience

For most of the past two decades, the notion that there is no alternative to the market as a basis for organising society has constituted a kind of global 'common sense', accepted not only by the neo-liberal Right but also by social democratic thinkers and politicians, in the form of 'the Third Way'. This paper will critically assess the central claims of neoliberalism in the light of experience in the UK and internationally, evaluate the ways in which Third Way policies are shaping social work in the UK, and in the final section, begin to explore some of the ways in which the anti-capitalist movement which has emerged in recent years might contribute to the development of a new, engaged social work, based on social justice.

Quantile-Based Optimization of Noisy Computer Experiments with Tunable Precision

This article addresses the issue of kriging-based optimization of stochastic simulators. Many of these simulators depend on factors that tune the level of precision of the response, the gain in accuracy being at a price of computational time. The contribution of this work is two-fold: first, we propose a quantile-based criterion for the sequential design of experiments, in the fashion of the classical expected improvement criterion, which allows an elegant treatment of heterogeneous response precisions. Second, we present a procedure for the allocation of the computational time given to each measurement, allowing a better distribution of the computational effort and increased efficiency. Finally, the optimization method is applied to an original application in nuclear criticality safety. This article has supplementary material available online. The proposed criterion is available in the R package DiceOptim.

Designing forest biodiversity experiments: general considerations illustrated by a new large experiment in subtropical China

1. Biodiversity-ecosystem functioning (BEF) experiments address ecosystem-level consequences of species loss by comparing communities of high species richness with communities from which species have been gradually eliminated. BEF experiments originally started with microcosms in the laboratory and with grassland ecosystems. A new frontier in experimental BEF research is manipulating tree diversity in forest ecosystems, compelling researchers to think big and comprehensively. 2. We present and discuss some of the major issues to be considered in the design of BEF experiments with trees and illustrate these with a new forest biodiversity experiment established in subtropical China (Xingangshan, Jiangxi Province) in 2009/2010. Using a pool of 40 tree species, extinction scenarios were simulated with tree richness levels of 1, 2, 4, 8 and 16 species on a total of 566 plots of 25.8x25.8m each. 3. The goal of this experiment is to estimate effects of tree and shrub species richness on carbon storage and soil erosion; therefore, the experiment was established on sloped terrain. The following important design choices were made: (i) establishing many small rather than fewer larger plots, (ii) using high planting density and random mixing of species rather than lower planting density and patchwise mixing of species, (iii) establishing a map of the initial ecoscape' to characterize site heterogeneity before the onset of biodiversity effects and (iv) manipulating tree species richness not only in random but also in trait-oriented extinction scenarios. 4. Data management and analysis are particularly challenging in BEF experiments with their hierarchical designs nesting individuals within-species populations within plots within-species compositions. Statistical analysis best proceeds by partitioning these random terms into fixed-term contrasts, for example, species composition into contrasts for species richness and the presence of particular functional groups, which can then be tested against the remaining random variation among compositions. 5. We conclude that forest BEF experiments provide exciting and timely research options. They especially require careful thinking to allow multiple disciplines to measure and analyse data jointly and effectively. Achieving specific research goals and synergy with previous experiments involves trade-offs between different designs and requires manifold design decisions.

Psychophysiology of prospective memory

Prospective memory involves the self-initiated retrieval of an intention upon an appropriate retrieval cue. Cue identification can be considered as an orienting reaction and may thus trigger a psychophysiological response. Here we present two experiments in which skin conductance responses (SCRs) elicited by prospective memory cues were compared to SCRs elicited by aversive stimuli to test whether a single prospective memory cue triggers a similar SCR as an aversive stimulus. In Experiment 2 we also assessed whether cue specificity had a differential influence on prospective memory performance and on SCRs. We found that detecting a single prospective memory cue is as likely to elicit a SCR as an aversive stimulus. Missed prospective memory cues also elicited SCRs. On a behavioural level, specific intentions led to better prospective memory performance. However, on a psychophysiological level specificity had no influence. More generally, the results indicate reliable SCRs for prospective memory cues and point to psychophysiological measures as valuable approach, which offers a new way to study one-off prospective memory tasks. Moreover, the findings are consistent with a theory that posits multiple prospective memory retrieval stages.

Flux and resident injection in gaseous advection experiments

The occurrence of gaseous pollutants in soils has stimulated many experimental activities, including forced ventilation in the field as well as laboratory transport experiments with gases. The dispersion coefficient in advective-dispersive gas phase transport is often dominated by molecular diffusion, which leads to a large overall dispersivity gamma. Under such conditions it is important to distinguish between flux and resident modes of solute injection and detection. The influence of the inlet type oil the macroscopic injection mode was tested in two series of column experiments with gases at different mean flow velocities nu. First we compared infinite resident and flux injections, and second, semi-infinite resident and flux injections. It is shown that the macroscopically apparent injection condition depends on the geometry of the inlet section. A reduction of the cross-sectional area of the inlet relative to that of the column is very effective in excluding the diffusive solute input, thus allowing us to use the solutions for a flux Injection also at rather low mean flow velocities nu. If the whole cross section of a column is exposed to a large reservoir like that of ambient air, a semi-infinite resident injection is established, which can be distinguished from a flux injection even at relatively high velocities nu, depending on the mechanical dispersivity of the porous medium.

Identifiability of diffusion and sorption parameters from in situ diffusion experiments by using simultaneously tracer dilution and claystone data

In situ diffusion experiments are performed in geological formations at underground research laboratories to overcome the limitations of laboratory diffusion experiments and investigate scale effects. Tracer concentrations are monitored at the injection interval during the experiment (dilution data) and measured from host rock samples around the injection interval at the end of the experiment (overcoring data). Diffusion and sorption parameters are derived from the inverse numerical modeling of the measured tracer data. The identifiability and the uncertainties of tritium and Na-22(+) diffusion and sorption parameters are studied here by synthetic experiments having the same characteristics as the in situ diffusion and retention (DR) experiment performed on Opalinus Clay. Contrary to previous identifiability analyses of in situ diffusion experiments, which used either dilution or overcoring data at approximate locations, our analysis of the parameter identifiability relies simultaneously on dilution and overcoring data, accounts for the actual position of the overcoring samples in the claystone, uses realistic values of the standard deviation of the measurement errors, relies on model identification criteria to select the most appropriate hypothesis about the existence of a borehole disturbed zone and addresses the effect of errors in the location of the sampling profiles. The simultaneous use of dilution and overcoring data provides accurate parameter estimates in the presence of measurement errors, allows the identification of the right hypothesis about the borehole disturbed zone and diminishes other model uncertainties such as those caused by errors in the volume of the circulation system and the effective diffusion coefficient of the filter. The proper interpretation of the experiment requires the right hypothesis about the borehole disturbed zone. A wrong assumption leads to large estimation errors. The use of model identification criteria helps in the selection of the best model. Small errors in the depth of the overcoring samples lead to large parameter estimation errors. Therefore, attention should be paid to minimize the errors in positioning the depth of the samples. The results of the identifiability analysis do not depend on the particular realization of random numbers. (C) 2012 Elsevier B.V. All rights reserved.