Effects of neuromuscular blocking agents on excitatory transmission and gamma-aminobutyric acidA-mediated inhibition in the rat hippocampal slice

BACKGROUND: Although neuromuscular blocking agents do not cross the blood-brain barrier, they may penetrate the central nervous system under particular circumstances and eventually cause neurotoxic consequences. METHODS: The effects of neuromuscular blocking agents on excitatory and inhibitory transmission in area CA1 of rat hippocampal slices were investigated using extracellular and intracellular recording techniques. RESULTS: Application of atracurium in the perfusion medium resulted in a dose-dependent enhancement of excitatory synaptic responses averaging 48.7 +/- 4.3% at a concentration of 10 nM. This effect was correlated with an increase in the size of the presynaptic fiber volley. Laudanosine, but not pancuronium bromide or vecuronium bromide, produced similar changes. In addition, atracurium and laudanosine blocked inhibitory transmission and reduced intracellularly recorded gamma-aminobutyric acidA receptor-mediated potentials. These effects were observed only at concentrations >1 microM and were not reproduced by pancuronium bromide and vecuronium bromide. CONCLUSIONS: Atracurium and its metabolite, laudanosine, contrary to pancuronium bromide and vecuronium bromide, produce two distinct effects on hippocampal slices. They enhance excitatory transmission and neuronal excitability and they block inhibitory gamma-aminobutyric acidA-mediated synaptic responses.     

Reactions of saturated hydrocarbons I. Oxidation of isoparaffins by chromic acid

Measurements of the rate of reduction of chromium(VI) oxide in acetic acid–acetic anhydride solution by 2-methyl-pentane, 3-methylpentane, 2,3-dimethylbutane and 2,4-dimethylpentane show that the initial rate depends on the number and nature of carbon atoms in the hydrocarbon. When steric or other interaction effects prevail between adjacent atoms or groups in the molecule, these effects also influence the rate. The values obtained for the oxidation rates agree with those calculated from a proposed expression (Rn_p+R'n_s+R'n_t)/(n_p+n_s+n_t) based on the formula of Chambers & Ubbelohde.     

Concentration and distribution of platinum group elements (Pt, Pd, Rh) in airborne particulate matter in Frankfurt am Main, Germany

The concentrations and distribution of platinum group elements (Pt, Pd, Rh) in airborne particulate matter were studied in a period of one year from August 2001 to July 2002 in urban and in nonurban areas. Airborne dust samples were collected as a total amount (particles with an aerodynamic diameter <22 microm) and classified using an eight-stage Andersen impactor (<10 microm) at three locations with different traffic density roads in the Frankfurt am Main and nonurban areas. Sampling at the three locations was performed simultaneously for total airborne dust and fractionated airborne dust. Pd was determined by total reflection X-ray fluorescence after Hg coprecipitation. Pt and Rh were analyzed by adsorptive striping voltammetry after HPA digestion. The results show that the PGE concentrations in airborne samples depend on the traffic density. The highest PGE concentrations in air were found in the vicinity of major roads with heavy traffic, and the lowest ones were found in the nonurban area. The presence of PGE at the sampling station relatively free of traffic in a nonurban area hints to a transport of some of the emitted PGE from the city to this station by wind. At all three sampling locations, a heterogeneous distribution of the Pd, Pt, and Rh concentrations during the sampling year can be observed. The sum of PGE concentrations in total airborne dust is comparable with the sum of impactor samples. However, the concentration of Pt and Rh in total airborne dust (<22 microm) is on average higher than in impactor samples (<10 microm). On the contrary, Pd concentration is higher in impactor samples in most cases. The airborne PGE distribution is dominated by Pt, followed by Pd and Rh. The impactor samples are dominated by Pd, followed by Pt and Rh. This fact indicates that palladium occurs mainly in relatively fine airborne particles. The main fraction of PGE is found on average in particle sizes between 1.1 and 4.7 microm. Knowledge of the size distribution of particles containing PGE is important with respect to risk assessment of human inhalation.     

Extraction of delta-lognormal parameters from handwriting strokes

In the context of the Kinematic Theory of Rapid Human Movement, handwriting strokes are considered to be primitives that reflect the intrinsic properties of the neuromuscular system of a writer as well as the basic control strategies that the writer uses to produce such strokes. The study of these strokes relies on the extraction of the different parameters that characterize a stroke velocity profile. In this paper, we present a new method for stroke parameter extraction. The algorithm is described and evaluated under various testing conditions.     

Use of modelling for optimization and upgrade of a tropical wastewater treatment plant in a developing country.

This paper presents results of a novel application of coupling the Activated Sludge Model No. 3 (ASM3) and the Anaerobic Digestion Model No.1 (ADM1) to assess a tropical wastewater treatment plant in a developing country (Surat, India). In general, the coupled model was very capable of predicting current plant operation. The model proved to be a useful tool in investigating various scenarios for optimising treatment performance under present conditions and examination of upgrade options to meet stricter and upcoming effluent discharge criteria regarding N removal. It appears that use of plant-wide modelling of wastewater treatment plants is a promising approach towards addressing often complex interactions within the plant itself. It can also create an enabling environment for the implementations of the novel side processes for treatment of nutrient-rich, side-streams (reject water) from sludge treatment.     

An Efficient Medical Image Deep Fusion Model Based on Convolutional Neural Networks

Medical image fusion is considered the best method for obtaining one image with rich details for efficient medical diagnosis and therapy. Deep learning provides a high performance for several medical image analysis applications. This paper proposes a deep learning model for the medical image fusion process. This model depends on Convolutional Neural Network (CNN). The basic idea of the proposed model is to extract features from both CT and MR images. Then, an additional process is executed on the extracted features. After that, the fused feature map is reconstructed to obtain the resulting fused image. Finally, the quality of the resulting fused image is enhanced by various enhancement techniques such as Histogram Matching (HM), Histogram Equalization (HE), fuzzy technique, fuzzy type Π, and Contrast Limited Histogram Equalization (CLAHE). The performance of the proposed fusion-based CNN model is measured by various metrics of the fusion and enhancement quality. Different realistic datasets of different modalities and diseases are tested and implemented. Also, real datasets are tested in the simulation analysis.     

A smart multi-user massive MIMO system for next G Wireless communications using evolutionary optimized antenna selection

Recently multiserver queues with setup times have been extensively studied because they have applications in power-saving data centers. A challenging model is the M/M/c/Setup queue where a server is turned off when it is idle and is turned on if there are some waiting jobs. Recently, Gandhi et al. (in: Proceedings of the ACM SIGMETRICS, pp. 153–166, ACM, 2013; Queueing Syst. 77(2):177–209, 2014) obtain the generating function of the number of jobs in the system, as well as the Laplace transform of the response time using the recursive renewal reward approach and the distributional Little’s law (Keilson and Servi in Oper Res Lett 7(5):223– 227, 1988). In this paper, we derive exact solutions for the joint stationary queue length distribution of the same model using two alternative methodologies: generating function approach and matrix analytic method. The generating function approach yields exact closed form expressions for the joint stationary queue length distribution and the conditional decomposition formula. On the other hand, the matrix analytic approach leads to an exact recursive algorithm to calculate the joint stationary distribution and performance measures so as to provide some application insights.