The Magnaporthe oryzae effector Avr-PikD suppresses rice immunity by inhibiting an LSD1-like transcriptional activator

Avirulence effectors(Avrs),encoded by plant pathogens,can be recognized by plants harboring the corresponding resistance proteins,thereby initiating effector-triggered immunity(ETI).In susceptible plants,however,Avrs can function as effectors,facilitating infection via effector-triggered susceptibility(ETS).Mechanisms of Avr-mediated ETS remain largely unexplored.Here we report that the Magnaporthe oryzae effector Avr-PikD enters rice cells via the canonical cytoplasmic secretion pathway and suppresses rice basal defense.Avr-PikD interacts with an LSD1-like transcriptional activator AKIP30 of rice,and AKIP30 is also a positive regulator of rice immunity,whereas Avr-PikD impedes its nuclear localization and suppresses its transcriptional activity.In summary,M.oryzae delivers Avr-PikD into rice cells to facilitate ETS by inhibiting AKIP30-mediated transcriptional regulation of immune response against M.oryzae.

Ventilation function changes in patients with Duchenne muscular dystrophy under and over 12 years of age Analysis of 65 cases

BACKGROUND:Previous studies indicate that vital capacity in patients with Duchenne muscular dystrophy increases with age when they are under 12 years old, and decreases from 13 or 14 years of age; however, recent studies indicate that the vital capacity in patients with Duchenne muscular dystrophy begins to decrease even before 12 years of age. OBJECTIVE: To verify if the vital capacity in patients with Duchenne muscular dystrophy decreases before the age of 12 years and to observe the effect of rehabilitation exercise on vital capacity. DESIGN, TIME AND SETTING: The case analysis was performed at the Department of Neurology, The First Affiliated Hospital of Sun Yat-Sen University (Guangzhou, Guangdong Province, China) from December 2004 to January 2006. PARTICIPANTS: Sixty-five male patients diagnosed as having Duchenne muscular dystrophy and who underwent pulmonary ventilation function examination at the Department of Neurology, The First Affiliated Hospital of Sun Yat-Sen University (Guangzhou, Guangdong Province, China) from December 2004 to January 2006; ages ranged from 6 to 22 years old. METHODS: The ventilation function of 65 patients was determined using a Sensor Medics 2100 pulmonary function test apparatus (USA), and the data obtained were subjected to statistical analysis comparing patients under 12 years of age and those above 13 years of age, and comparing those who performed rehabilitation exercise with those who did not. MAIN OUTCOME MEASURES: Forced vital capacity (FVC); forced expiratory volume in one second (FEV1); maximal voluntary ventilation (MMV); the ratio of forced expiratory volume in one second and forced vital capacity (FEV1/FVC); each measured value as a percentage of the corresponding predicted value. RESULTS: There were no significant differences in FVC, FEV1 and MMV between patients under 12 years of age and those above 13 years of age (P > 0.05). The FVC, FEV1 and MMV values, as percentages of the predicted values, were, in patients under 12 years old, significantly higher than those in patients older than 13 (P < 0.05). All ventilation function parameters except FEV1/FVC in patients undergoing rehabilitation exercise were higher than those in patients without rehabilitation exercise. This difference was not significant in patients under 12 years of age, but was statistically significant in those older than 13 years (P < 0.05). CONCLUSION: Although the values of ventilation function measured increase with age in Duchenne muscular dystrophy patients less than 12 years of age, real ventilation function is already damaged. Thirteen years of age is an important time point for pulmonary function change. Rehabilitation exercise can slow down the process of pulmonary function exacerbation in Duchenne muscular dystrophy patients, especially when therapy starts before 12 years of age.

Analysis of Employment Trend in Flue-Cured Tobacco Planting

Based on the investigation of the amount of labor used in each production link of flue-cured tobacco planting in Liuyang since 1989,and through the analysis of the changes of labor-related factors,it is concluded that the amount of labor used in tobacco planting in Liuyang experienced a significant increase and relatively stable stage in the early 1990s,and it has been declining continuously since the beginning of the 21st century;the change of flue-cured tobacco planting technology mode,as well as mechanized,large-scale and specialized production are the main factors that affect the change of the amount of labor used in flue-cured tobacco planting in Liuyang.Based on the method of changing the technical model to reduce amount of labor used,the types of labor used for planting of flue-cured tobacco can be divided into the following types:reducing the amount of labor by technical methods;reducing the amount of labor by making use of weather;reducing the amount of labor by using drugs;reducing the amount of labor used at the cost of reducing the technical implementation standards of a certain production link.The change of labor used in flue-cured tobacco planting is not only related to the cost and price factors,but also related to the profound social and economic background.In the future,reducing labor and cost is the trend of flue-cured tobacco production,and mechanization,large-scale and specialized production are the main development direction of flue-cured tobacco production,but under the condition that flue-cured tobacco production is still dominated by manual operation,maintaining a certain amount of labor is still the basis for maintaining high quality of flue-cured tobacco planting at present.

Heterogeneous Parallel Algorithm Design and Performance Optimization for WENO on the Sunway TaihuLight Supercomputer

A Weighted Essentially Non-Oscillatory scheme(WENO) is a solution to hyperbolic conservation laws,suitable for solving high-density fluid interface instability with strong intermittency. These problems have a large and complex flow structure. To fully utilize the computing power of High Performance Computing(HPC) systems, it is necessary to develop specific methodologies to optimize the performance of applications based on the particular system’s architecture. The Sunway TaihuLight supercomputer is currently ranked as the fastest supercomputer in the world. This article presents a heterogeneous parallel algorithm design and performance optimization of a high-order WENO on Sunway TaihuLight. We analyzed characteristics of kernel functions, and proposed an appropriate heterogeneous parallel model. We also figured out the best division strategy for computing tasks,and implemented the parallel algorithm on Sunway TaihuLight. By using access optimization, data dependency elimination, and vectorization optimization, our parallel algorithm can achieve up to 172× speedup on one single node, and additional 58× speedup on 64 nodes, with nearly linear scalability.

Helmholtz Solving and Performance Optimization in Global/Regional Assimilation and Prediction System

Despite efficient parallelism in the solution of physical parameterization in the Global/Regional Assimilation and Prediction System(GRAPES),the Helmholtz equation in the dynamic core,with the increase of resolution,can hardly achieve sufficient parallelism in the solving process due to a large amount of communication and irregular access.In this paper,optimizing the Helmholtz equation solution for better performance and higher efficiency has been an urgent task.An optimization scheme for the parallel solution of the Helmholtz equation is proposed in this paper.Specifically,the geometrical multigrid optimization strategy is designed by taking advantage of the data anisotropy of grid points near the pole and the isotropy of those near memory equator in the Helmholtz equation,and the Incomplete LU(ILU)decomposition preconditioner is adopted to speed up the convergence of the improved Generalized Conjugate Residual(GCR),which effectively reduces the number of iterations and the computation time.The overall solving performance of the Helmholtz equation is improved by thread-level parallelism,vectorization,and reuse of data in the cache.The experimental results show that the proposed optimization scheme can effectively eliminate the bottleneck of the Helmholtz equation as regards the solving speed.Considering the test results on a 10-node two-way server,the solution of the Helmholtz equation,compared with the original serial version,is accelerated by 100,with one-third of iterations reduced.

An MPI+OpenACC-Based PRM Scalar Advection Scheme in the GRAPES Model over a Cluster with Multiple CPUs and GPUs

A moisture advection scheme is an essential module of a numerical weather/climate model representing the horizontal transport of water vapor.The Piecewise Rational Method(PRM) scalar advection scheme in the Global/Regional Assimilation and Prediction System(GRAPES) solves the moisture flux advection equation based on PRM.Computation of the scalar advection involves boundary exchange,and computation of higher bandwidth requirements is complicated and time-consuming in GRAPES.Recently,Graphics Processing Units(GPUs) have been widely used to solve scientific and engineering computing problems owing to advancements in GPU hardware and related programming models such as CUDA/OpenCL and Open Accelerator(OpenACC).Herein,we present an accelerated PRM scalar advection scheme with Message Passing Interface(MPI) and OpenACC to fully exploit GPUs’ power over a cluster with multiple Central Processing Units(CPUs) and GPUs,together with optimization of various parameters such as minimizing data transfer,memory coalescing,exposing more parallelism,and overlapping computation with data transfers.Results show that about 3.5 times speedup is obtained for the entire model running at medium resolution with double precision when comparing the scheme’s elapsed time on a node with two GPUs(NVIDIA P100) and two 16-core CPUs(Intel Gold 6142).Further,results obtained from experiments of a higher resolution model with multiple GPUs show excellent scalability.