Iodine-123 labelled nor-beta-CIT binds to the serotonin transporter in vivo as assessed by biodistribution studies in rats

Flavobacterium aurantiacum NRRL B-184 possesses the ability to degrade aflatoxin B1 in solution and in several food items. Aflatoxin B1 is a potent carcinogen that causes significant economic losses to the agricultural and food industry. The role of trace metal ions (Cu2+, Mn2+, Zn2+, and Co2+) were studied in an effort to understand the enzymatic system involved in aflatoxin B1 degradation by F aurantiacum. The effect of divalent chelators (EDTA and 1,10-phenanthroline [OPT]) in the presence of the trace metal ions was studied as well. Aflatoxin B1 (10 microg/ml) was added to 72-h cultures of F aurantiacum that had been washed and resuspended in phosphate buffer (pH 7.0). HPLC was used to determine aflatoxin B1 concentration in these cultures. Incubating cells at 30 degrees C with 1 and 10 mM Cu2+, Mn2+, and Zn2+ significantly decreased aflatoxin B degradation after 4 and 24 h (P < 0.05). Decreased degradation was also observed with 1 and 10 mM Cu2+ and Zn2+ after 48 h and with 0.1 mM Cu2+ after 24 and 48 h. Co2+ did not have a significant effect on aflatoxin B1 degradation. EDTA and OPT did not counter the inhibition in the presence of Cu2+. The addition of 1 mM EDTA countered the inhibition by 1 mM Mn2+ after 4 and 24 h, but 1 mM OPT did not counter the inhibition by 10 mM Mn2+ after 4 and 24 h. OPT countered the inhibition by 1 mM Zn2+ after 4 and 48 h. These trace elements inhibit aflatoxin B1 degradation by F aurantiacum. In addition, their presence necessitates higher concentrations (>1 mM) of EDTA and OPT for the removal of their inhibitory effect.     

Efficient data association for view based SLAM using connected dominating sets

Loop closing in vision based SLAM applications is a difficult task. Comparing new image data with all previously acquired image data is practically impossible because of the high computational costs. Most approaches therefore compare new data with only a subset of the old data, for example by sampling the data over time or over space by using a position estimate. In this paper, we propose a more natural approach, which dynamically determines a subset of images that best describes the complete image data in the space of all previously seen images. The actual problem of finding such a subset is called the “Connected Dominating Set” (CDS) problem, which is well studied in the field of graph theory. Application on large indoor datasets results in approximately the same map using only 13% of the computational resources with respect to comparing with all previous images. Also, it outperforms other sampling approaches. The proposed method is particularly beneficial for realistic mapping scenarios including moving objects and persons, motion blur and changing light conditions.¹     

Cognitive and serotonergic vulnerability to depression: Convergent findings.

Cognitive reactivity (CR) is a psychological vulnerability marker of depression, whereas response to acute tryptophan depletion (ATD; a serotonergic challenge procedure) is a biological vulnerability marker. The aim of this study was to investigate the relationship between these markers. Thirty-nine remitted depressed patients participated in 2 ATD sessions in a double-blind crossover design. CR, assessed prior to the ATD sessions, predicted depressive response to high-dose ATD. CR also diminished the effects of 2 known predictors of ATD response: gender and residual symptoms. Neuroticism and behavioral inhibition were unrelated to ATD response. CR is associated with an increased sensitivity to reductions of serotonin concentrations. These findings present a small step toward unifying cognitive and neurobiological theories of depression. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A simple and powerful analytical model for MEMS piezoelectric multimorphs

We have developed an analytical model for use in design and modelling of piezoelectric MEMS devices. The model allows for incorporation of any number of device material layers in a multimorph structure including piezoelectric materials. The resulting lumped circuit model fully incorporates the electro-mechanical coupling effects in the piezoelectric layers as well as electrical or mechanical loading of the device structure. Since the model is analytic, and only requires the specification of well-defined material properties, it allows for fast and interactive modelling of a multitude of MEMS device structures incorporating piezoelectric materials. We will demonstrate the capability of the model by presenting results from fitting the model to impedance measurements performed on cantilever structures. This allows for extraction of device and material parameters that are difficult to obtain by other means, such as the piezoelectric coefficient and the mechanical quality factor.     

Imaging of the dopaminergic neurotransmission system using single-photon emission tomography and positron emission tomography in patients with parkinsonism

Parkinsonism is a feature of a number of neurodegenerative diseases, including Parkinson's disease, multiple system atrophy and progressive supranuclear palsy. The results of post-mortem studies point to dysfunction of the dopaminergic neurotransmitter system in patients with parkinsonism. Nowadays, by using single-photon emission tomography (SPET) and positron emission tomography (PET) it is possible to visualise both the nigrostriatal dopaminergic neurons and the striatal dopamine D2 receptors in vivo. Consequently, SPET and PET imaging of elements of the dopaminergic system can play an important role in the diagnosis of several parkinsonian syndromes. This review concentrates on findings of SPET and PET studies of the dopaminergic neurotransmitter system in various parkinsonian syndromes.     

Time-temperature superposition and linear viscoelastic behaviour of EPDM networks with various degrees of crosslinking

Summary Conventional time-temperature (t-T) superposition appears to be inappropriate to the viscoelastic behaviour of amorphous, peroxide cured EPDM networks. A phenomenological approach is presented that reduces these permanent elastomers to thermorheologically simple materials. Although the origin of the anomalous behaviour observed is not yet completely understood, it is attributed to an unusual variation of the equilibrium modulus with temperature.Presented at the 7th IUPAC Discussion Conference Polymer Networks, Karlovy Vary, CSSR, September 15–19, 1980     

Neuromuscular transmission and its pharmacological blockade. Part 3: Continuous infusion of relaxants and reversal and monitoring of relaxation

The use of seclusion or seclusion and restraints (S/SR) may affect patients negatively, even if controlling their behavior in the short run, by placing them in the "victim" role and fostering a corrosive atmosphere of patient-caregiver mistrust and alienation. This project's goal was to reduce the use of the most restrictive measures by increasing the use of the less restrictive removal from stimuli (RFS). Verbally and even physically threatening patients in a psychiatric intensive care unit were removed from stimuli if their behaviors were not sustained and they ultimately cooperated with staff. RFS was deemed successful when a patient did not need more restrictive measures following its use. The data for this study were obtained by tabulating RFS and S/SR utilization rates for a year. Frequencies, measures of variance, ratios, and t ratios were used to analyze the data. The use of RFS and other nonrestrictive measures to reduce patient stress and frustration resulted in decreased utilization of seclusion and restraints. The frequency and severity of negativistic, aggressive behaviors of patients were also observed to have diminished.     

A Comparison of Nonlinear Stochastic Self-Exciting Threshold Autoregressive and Chaotic <Emphasis Type="Italic">k</Emphasis>-Nearest Neighbour Models in Daily Streamflow Forecasting

A nonlinear stochastic self-exciting threshold autoregressive (SETAR) model and a chaotic k-nearest neighbour (k-nn) model, for the first time, were compared in one and multi-step ahead daily flow forecasting for nine rivers with low, medium, and high flows in the western United States. The embedding dimension and the number of nearest neighbours of the k-nn model and the parameters of the SETAR model were identified by a trial-and-error process and a least mean square error estimation method, respectively. Employing the recursive forecasting strategy for the first time in multi-step forecasting of SETAR and k-nn, the results indicated that SETAR is superior to k-nn by means of performance indices. SETAR models were found to be more efficient in forecasting flows in one and multi-step forecasting. SETAR is less sensitive to the propagated error variances than the k-nn model, particularly for larger lead times (i.e., 5 days). The k-nn model should carefully be used in multi-step ahead forecasting where peak flow forecasting is important by considering the risk of error propagation.     

Modelling mycotoxin formation by Fusarium graminearum in maize in The Netherlands

The predominant species in maize in temperate climates is Fusarium graminearum, which produces the mycotoxins deoxynivalenol and zearalenone. Projected climate change is expected to affect Fusarium incidence and thus the occurrence of these mycotoxins. Predictive models may be helpful in determining trends in the levels of these mycotoxins with expected changing climatic conditions. The aim of this study was to develop a model describing fungal infection and subsequent growth as well as the formation of deoxynivalenol and zearalenone in maize in The Netherlands. For this purpose, a published Italian model was used as a starting point. This model is a mixed empiric-mechanistic model that describes fungal infection during silking (based on wind speed and rainfall) and subsequent germination, growth and toxin formation (depending on temperature and water availability). Model input uses weather parameters and crop management factors, such as maize hybrid, sowing date, flowering period and harvest date. Model parameter values were obtained by fitting these parameters to deoxynivalenol and zearalenone measurements in Dutch maize, using national mycotoxin data from the years 2002-2007. The results showed that the adapted model is capable of describing the trend in average deoxynivalenol and zearalenone levels over these years. Validation with external data is needed to verify model outcomes. It is expected that the current model can be used to estimate the effect of projected climate change on trends in deoxynivalenol and zearalenone levels in the coming years.