Search

Parkinson's disease (PD) is an age-related neurodegenerative disease. Long non-coding RNA urothelial carcinoma-associated 1 (UCA1) is involved in the pathogenesis of PD. However, the pathogenesis of PD regulated by UCA1 has not been fully explained. We used 1-Methyl-4-phenylpyridinium (MPP+)-induced SK-N-SH cells for functional analysis. Expression levels of UCA1, microRNA (miR)-671-5p, and KPNA4 (karyopherin subunit alpha 4) mRNA were detected using quantitative real-time polymerase chain reaction (qRT-PCR). Cell viability and apoptosis were analyzed using MTT (3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide) or flow cytometry assays. Some protein levels were measured by western blotting. The levels of pro-inflammatory cytokines were tested by ELISA (enzyme-linked immunosorbent assay). The levels of LDH (lactate dehydrogenase), MDA (malondialdehyde), and SOD (superoxide dismutase) were measured using corresponding kits. The relationship between UCA1 or KPNA4 and miR-671-5p was verified by dual-luciferase reporter assay and/or RNA immunoprecipitation (RIP) assay. MPP+ induced UCA1 expression in SK-N-SH cells in a concentration-dependent manner or time-dependent manner. UCA1 knockdown reduced MPP+-induced apoptosis, inflammation, and oxidative stress in SK-N-SH cells. MiR-671-5p was downregulated while KPNA4 was upregulated in MPP+-treated SK-N-SH cells. UCA1 sponged miR-671-5p to regulate KPNA4 expression. MiR-671-5p inhibition counteracted UCA1 knockdown-mediated influence on apoptosis, inflammation, and oxidative stress of MPP+-induced SK-N-SH cells. KPNA4 overexpression offset the inhibitory influence of miR-671-5p mimic on apoptosis, inflammation, and oxidative stress of MPP+-treated SK-N-SH cells. UCA1 inhibition reduced MPP+-induced neuronal damage through the miR-671-5p/KPNA4 pathway in SK-N-SH cells, providing a novel mechanism to understand the pathogenesis of PD. [ABSTRACT FROM AUTHOR]

Machine Learning Computers (MLCs) with tensor functional units (e.g., NVIDIA’s Tensor Core, Google’s TPU and Habana’s Tensor Processor Core) have emerged significantly over recent years. The broad diversity of MLCs makes it hard to deploy machine learning workloads with optimized performance. Though deep learning compilers (e.g., TVM) are effective to produce optimized code for different hardware back-ends, when deploying to a new MLC, it is tedious to implement platform-specific compilation optimizations by thoroughly understanding system/architectural details. To address this problem, we propose a holistic approach to achieve one-size-fits-all compilation optimization for inference across different MLCs. The key observation is that diverse MLCs share multiple key architectural characteristics (e.g., tensor primitives and on-chip scratchpad memory) for tensor processing, which can be generalized for conducting cross-platform compilation optimizations. Concretely, we propose the Tensor Abstract Machine (TAM), which features such common architectural characteristics, as the abstraction of a broad range of MLCs. To leverage architectural characteristics of the TAM, we propose the Tensor Scheduling Language (TSL) consisting of tensor computation description and tensor scheduling primitives for implementing operations with portable optimization. By implementing tensor operations with TSL, the related optimized code for different MLCs can be automatically generated. To validate our proposal, we conduct experiments on 3 commodity MLCs including GPU with Tensor Cores, VTA (on FPGA), and Cloud TPU. Experimental results demonstrate that the code generated from the same optimization schedule achieves 1.05x to 2.05x better performance than hand-tuned libraries and deep learning compilers across different platforms. [ABSTRACT FROM AUTHOR]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.cell.2005.05.025 Byline: Fei Sun (1)(2), Xia Huo (2), Yujia Zhai (1), Aojin Wang (2), Jianxing Xu (2), Dan Su (1), Mark Bartlam (1)(2), Zihe Rao (1)(2) Abstract: The mitochondrial respiratory Complex II or succinate:ubiquinone oxidoreductase (SQR) is an integral membrane protein complex in both the tricarboxylic acid cycle and aerobic respiration. Here we report the first crystal structure of Complex II from porcine heart at 2.4 A resolution and its complex structure with inhibitors 3-nitropropionate and 2-thenoyltrifluoroacetone (TTFA) at 3.5 A resolution. Complex II is comprised of two hydrophilic proteins, flavoprotein (Fp) and iron-sulfur protein (Ip), and two transmembrane proteins (CybL and CybS), as well as prosthetic groups required for electron transfer from succinate to ubiquinone. The structure correlates the protein environments around prosthetic groups with their unique midpoint redox potentials. Two ubiquinone binding sites are discussed and elucidated by TTFA binding. The Complex II structure provides a bona fide model for study of the mitochondrial respiratory system and human mitochondrial diseases related to mutations in this complex. Author Affiliation: (1) Tsinghua-IBP Joint Research Group for Structural Biology, Tsinghua University, Beijing 100084, China (2) National Laboratory of Biomacromolecules, Institute of Biophysics (IBP), Chinese Academy of Sciences, Beijing 100101, China Article History: Received 5 April 2005; Revised 5 May 2005; Accepted 19 May 2005 Article Note: (miscellaneous) Published: June 30, 2005