Dopamine dysregulation in a mouse model of paroxysmal nonkinesigenic dyskinesia.

Paroxysmal nonkinesigenic dyskinesia (PNKD) is an autosomal dominant episodic movement disorder. Patients have episodes that last 1 to 4 hours and are precipitated by alcohol, coffee, and stress. Previous research has shown that mutations in an uncharacterized gene on chromosome 2q33-q35 (which is termed PNKD) are responsible for PNKD. Here, we report the generation of antibodies specific for the PNKD protein and show that it is widely expressed in the mouse brain, exclusively in neurons. One PNKD isoform is a membrane-associated protein. Transgenic mice carrying mutations in the mouse Pnkd locus equivalent to those found in patients with PNKD recapitulated the human PNKD phenotype. Staining for c-fos demonstrated that administration of alcohol or caffeine induced neuronal activity in the basal ganglia in these mice. They also showed nigrostriatal neurotransmission deficits that were manifested by reduced extracellular dopamine levels in the striatum and a proportional increase of dopamine release in response to caffeine and ethanol treatment. These findings support the hypothesis that the PNKD protein functions to modulate striatal neuro-transmitter release in response to stress and other precipitating factors

Analyzing Dynamic Changes of Laboratory Indexes in Patients with Acute Heart Failure Based on Retrospective Study

Background. Changes of N-terminal probrain natriuretic peptide (NT-proBNP) have been studied whether in the long term or the short term in patients of acute heart failure (AHF); however, changes of NT-proBNP in the first five days and their association with other factors have not been investigated. Aims. To describe the dynamic changes of relevant laboratory indexes in the first five days between different outcomes of AHF patients and their associations. Methods and Results. 284 AHF with dynamic values recorded were analyzed. Changes of NT-proBNP, troponin T, and C-reactive protein were different between patients with different outcomes, with higher values in adverse group than in control group at the same time points ( < 0.05). Then, prognostic use and risk stratification of NT-proBNP were assessed by receiver-operating characteristic curve and logistic regression. NT-proBNP levels at day 3 showed the best prognostic power (area under the curve = 0.730, 95% confidence interval (CI): 0.657 to 0.794) and was an independent risk factor for adverse outcome (odds ratio, OR: 2.185, 95% CI: 1.584-3.015). Classified changes of NT-proBNP may be predictive for adverse outcomes in AHF patients. Conclusions. Sequential monitoring of laboratory indexes within the first 5 days may be helpful for management of AHF patients

Roman domination in regular graphs

AbstractA Roman domination function on a graph G=(V(G),E(G)) is a function f:V(G)→{0,1,2} satisfying the condition that every vertex u for which f(u)=0 is adjacent to at least one vertex v for which f(v)=2. The weight of a Roman dominating function is the value f(V(G))=∑u∈V(G)f(u). The minimum weight of a Roman dominating function on a graph G is called the Roman domination number of G. Cockayne et al. [E. J. Cockayne et al. Roman domination in graphs, Discrete Mathematics 278 (2004) 11–22] showed that γ(G)≤γR(G)≤2γ(G) and defined a graph G to be Roman if γR(G)=2γ(G). In this article, the authors gave several classes of Roman graphs: P3k,P3k+2,C3k,C3k+2 for k≥1, Km,n for min{m,n}≠2, and any graph G with γ(G)=1; In this paper, we research on regular Roman graphs and prove that: (1) the circulant graphs C(n;{1,3})(n≥7,n⁄≡4(mod5)) and C(n;{1,2,…,k})(k≤⌊n2⌋), n⁄≡1 (mod (2k+1)), (n≠2k) are Roman graphs, (2) the generalized Petersen graphs P(n,2k+1)(n≠4k+2,n≡0 (mod 4) and 0≤k≤⌊n2⌋), P(n,1) (n⁄≡2 (mod 4)), P(n,3) (n≥7,n⁄≡3 (mod 4)) and P(11,3) are Roman graphs, and (3) the Cartesian product graphs C5m□C5n(m≥1,n≥1) are Roman graphs

A K-means Algorithm Based On Feature Weighting

Cluster analysis is a statistical analysis technique that divides the research objects into relatively homogeneous groups. The core of cluster analysis is to find useful clusters of objects. K-means clustering algorithm has been receiving much attention from scholars because of its excellent speed and good scalability. However, the traditional K-means algorithm does not consider the influence of each attribute on the final clustering result, which makes the accuracy of clustering have a certain impact. In response to the above problems, this paper proposes an improved feature weighting algorithm. The improved algorithm uses the information gain and ReliefF feature selection algorithm to weight the features and correct the distance function between clustering objects, so that the algorithm can achieve more accurate and efficient clustering effect. The simulation results show that compared with the traditional K-means algorithm, the improved algorithm clustering results are stable, and the accuracy of clustering is significantly improved

Decoupling Control Strategy of Magnetic Levitation Planar Motor

There is tight electromagnetic and mechanical coupling among 6-degree of freedom (DOF) motions of magnetic levitation planar motor for photolithography. For decoupling control of the 6-DOF motions, this paper presents the current-controlled model of linear motors as the electromagnetic actuators, the decoupled kinetics model based on the modal forces, and the decoupling control strategy of the planar motor. The 6-DOF kinetics models are successfully decoupled by the modal forces and become simple 2nd order linear systems. The X position servo controller of the prototype is designed. The simulation results show that the controller proposed makes the decoupled X position control with the disired performaces and the control system has good immunity and robust stability

A K-means Algorithm Based On Feature Weighting

Cluster analysis is a statistical analysis technique that divides the research objects into relatively homogeneous groups. The core of cluster analysis is to find useful clusters of objects. K-means clustering algorithm has been receiving much attention from scholars because of its excellent speed and good scalability. However, the traditional K-means algorithm does not consider the influence of each attribute on the final clustering result, which makes the accuracy of clustering have a certain impact. In response to the above problems, this paper proposes an improved feature weighting algorithm. The improved algorithm uses the information gain and ReliefF feature selection algorithm to weight the features and correct the distance function between clustering objects, so that the algorithm can achieve more accurate and efficient clustering effect. The simulation results show that compared with the traditional K-means algorithm, the improved algorithm clustering results are stable, and the accuracy of clustering is significantly improved

Monte Carlo Simulation and Experimental Validation for Radiation Protection with Multiple Complex Source Terms and Deep Penetration for a Radioactive Liquid Waste Cementation Facility

A new radioactive liquid waste cementation facility was under commissioning recently in the Institute of Nuclear and New Energy Technology of Tsinghua University, which is designed to simultaneously process multiple intermediate-level radioactive waste drums. Therefore, the multiple volume sources and the scattering effect becomes a key issue in its radiation protection. For this purpose, the Monte Carlo program FLUKA code and experimental measurement were both adopted. In the FLUKA simulation, five different scenarios were considered, i.e., one drum, two drums, four drums, six drums, and eight drums. For the multiple volume sources, the source subroutine code of FLUKA was rewritten to realize the sampling. The complex shielding also leads to a deep penetration problem; hence, the optimization algorithm and variance reduction techniques were adopted. During the measurement, two scenarios, outdoor and indoor, were carried out separately representing the dose field when only one drum is considered and when the scattering effect is considered. A comparison between the experiments and calculations shows very good agreement. From both of the Monte Carlo simulation and the experimental measurement, it can be drawn that, in the horizontal direction, with the increase of the drum number, the dose rate increases very little, while in the vertical direction, the increase of the dose rate is very obvious with the increase of the drum number. The complicated source term sampling methods, the optimization algorithm and variance reduction techniques, and the experimental verification can provide valuable references for the similar scattering problem in radiation protection and shielding design