Effect of HDAC-6 on PD cell induced by lactacystin

AbstractObjectiveTo explore the effects of histone deacetylase 6(HDAC-6) on the PD cell model induced by proteasome inhibitor lactacystin.MethodsHuman neuroblastoma SK-N-SH cells were cultured. The wild type pcDNA3.1-alpha-synuclein eukaryotic expression plasmid was transferred into the cells which then were divided into control group, group L, group T and group T+L. The cells of group L were added with 5 μmol/L lactacystin dissolved indimethylsulfoxide (DMSO) to induce PD cell model with abnormal protein aggregation, the cells of control group were treated with 5 μmol/L DMSO, the cells of group T were treated with 5 μmol/L selective HDAC-6 inhibitor tubacin dissolved in DMSO, and the cells of group T+L were treated with 5 μmol/L lactacystin and 10 μmol/L tubacin dissolved in DMSO. The expression levels of alpha-synuclein oligomers, HSP-27 and HSP-70 were detected by Western blot and the cell survival rate of all the groups was detected by MTT colorimetric assay, and compared 24 h after the cells were treated.ResultsThe expression levels of alpha-synuclein oligomers, HSP-27 and HSP-70 of the cells of group L were significantly higher than the control group, and the cell survival rate was significantly lower (P < 0.05); the expression level of alpha-synuclein oligomers of the cells of group T+L was significantly higher than group L, but the expression level of HSP-27 and HSP-70 were significantly lower, and so as the cell survival rate (P < 0.05); the differences of the expression level of alpha-synuclein oligomers, HSP-27 and HSP-70 and the cell survival rate of the cells of group T and the control group were not statistically significant (P > 0.05).ConclusionsThe expression level of alpha-synuclein oligomers can be improved and the cell survival rate can be reduced by the PD cell model induced by lactacystin and treated with selective HDAC-6 inhibitor tubacin, which means that alpha-synuclein oligomers of the PD cell model induced by lactacystin can be inhibited and the cell survival rate can be improved by HDAC-6, and the mechanism may be related to the increased of HSP-27 and HSP-70

A Kohn-Sham Scheme Based Neural Network for Nuclear Systems

A Kohn-Sham scheme based multi-task neural network is elaborated for the supervised learning of nuclear shell evolution. The training set is composed of the single-particle wave functions and occupation probabilities of 320 nuclei, calculated by the Skyrme density functional theory. It is found that the deduced density distributions, momentum distributions, and charge radii are in good agreements with the benchmarking results for the untrained nuclei. In particular, accomplishing shell evolution leads to a remarkable improvement in the extrapolation of nuclear density. After a further charge-radius-based calibration, the network evolves a stronger predictive capability. This opens the possibility to infer correlations among observables by combining experimental data for nuclear complex systems

A hybrid EDA for load balancing in multicast with network coding

Load balancing is one of the most important issues in the practical deployment of multicast with network coding. However, this issue has received little research attention. This paper studies how traffic load of network coding based multicast (NCM) is disseminated in a communications network, with load balancing considered as an important factor. To this end, a hybridized estimation of distribution algorithm (EDA) is proposed, where two novel schemes are integrated into the population based incremental learning (PBIL) framework to strike a balance between exploration and exploitation, thus enhance the efficiency of the stochastic search. The first scheme is a bi-probability-vector coevolution scheme, where two probability vectors (PVs) evolve independently with periodical individual migration. This scheme can diversify the population and improve the global exploration in the search. The second scheme is a local search heuristic. It is based on the problem-specific domain knowledge and improves the NCM transmission plan at the expense of additional computational time. The heuristic can be utilized either as a local search operator to enhance the local exploitation during the evolutionary process, or as a follow-up operator to improve the best-so-far solutions found after the evolution. Experimental results show the effectiveness of the proposed algorithms against a number of existing evolutionary algorithms

A modified ant colony optimization algorithm for network coding resource minimization

The paper presents a modified ant colony optimization approach for the network coding resource minimization problem. It is featured with several attractive mechanisms specially devised for solving the network coding resource minimization problem: 1) a multi-dimensional pheromone maintenance mechanism is put forward to address the issue of pheromone overlapping; 2) problem-specific heuristic information is employed to enhance the heuristic search (neighboring area search) capability; 3) a tabu-table based path construction method is devised to facilitate the construction of feasible (link-disjoint) paths from the source to each receiver; 4) a local pheromone updating rule is developed to guide ants to construct appropriate promising paths; 5) a solution reconstruction method is presented, with the aim of avoiding prematurity and improving the global search efficiency of proposed algorithm. Due to the way it works, the ant colony optimization can well exploit the global and local information of routing related problems during the solution construction phase. The simulation results on benchmark instances demonstrate that with the five extended mechanisms integrated, our algorithm outperforms a number of existing algorithms with respect to the best solutions obtained and the computational time

Parameter identification of BIPT system using chaotic-enhanced fruit fly optimization algorithm

Bidirectional inductive power transfer (BIPT) system facilitates contactless power transfer between two sides and across an air-gap, through weak magnetic coupling. Typically, this system is nonlinear high order system which includes nonlinear switch components and resonant networks, developing of accurate model is a challenging task. In this paper, a novel technique for parameter identification of a BIPT system is presented by using chaotic-enhanced fruit fly optimization algorithm (CFOA). The fruit fly optimization algorithm (FOA) is a new meta-heuristic technique based on the swarm behavior of the fruit fly. This paper proposes a novel CFOA, which employs chaotic sequence to enhance the global optimization capacity of original FOA. The parameter identification of the BIPT system is formalized as a multi-dimensional optimization problem, and an objective function is established minimizing the errors between the estimated and measured values. All the 11 parameters of this system (Lpi, LT, Lsi, Lso, CT, Cs, M, Rpi, RT, Rsi and Rso) can be identified simultaneously using measured input–output data. Simulations show that the proposed parameter identification technique is robust to measurements noise and variation of operation condition and thus it is suitable for practical application

Observation of quantum fingerprinting beating the classical limit

Quantum communication has historically been at the forefront of advancements, from fundamental tests of quantum physics to utilizing the quantum-mechanical properties of physical systems for practical applications. In the field of communication complexity, quantum communication allows the advantage of an exponential reduction in the information transmitted over classical communication to accomplish distributed computational tasks. However, to date, demonstrating this advantage in a practical setting continues to be a central challenge. Here, we report an experimental demonstration of a quantum fingerprinting protocol that for the first time surpasses the ultimate classical limit to transmitted information. Ultra-low noise superconducting single-photon detectors and a stable fibre-based Sagnac interferometer are used to implement a quantum fingerprinting system that is capable of transmitting less information than the classical proven lower bound over 20 km standard telecom fibre for input sizes of up to two Gbits. The results pave the way for experimentally exploring the advanced features of quantum communication and open a new window of opportunity for research in communication complexity and testing the foundations of physics.Comment: 19 pages, 4 figure