Nuclear export factor 3 regulates the localization of small nucleolar RNAs

Metabolic diseases, such as obesity and diabetes, are associated with excess levels of lipids, which can lead to organelle dysfunction, cell death and eventually organ dysfunction. This process, termed lipotoxicity, is still not completely understood. In a genetic screen used to identify genes critical for lipotoxicity, the Schaffer lab has identified small nucleolar RNAs (snoRNAs) within the ribosomal protein L13a (Rpl13a) locus that mediate the cellular response to lipotoxic and general metabolic stress. These snoRNAs are non-canonical in that they accumulate in the cytosol after metabolic stresses like lipotoxicity and oxidative stress, suggesting that cells have specific mechanisms for regulating snoRNA distribution within the cell. To begin elucidating the underlying mechanism of snoRNA transport from the nucleus to the cytoplasm during metabolic stress, we modeled oxidative stress by treating cells with the chemotherapeutic drug doxorubicin (DOX). DOX is a potent inducer of superoxide through the activation of NADPH oxidase splice isoform 4D (NOX4D) and results in the cytosolic accumulation of Rpl13a snoRNAs. NOX inhibitors and genetic knockdown of NOX4D led to a decrease in the accumulation of Rpl13a snoRNAs in the cytosol after DOX treatment. Furthermore, RNA-sequencing studies demonstrated that snoRNAs as a class accumulated in the cytosol after DOX treatment, while simultaneous treatment with NOX inhibitors blunted the increase in cytosolic levels of snoRNAs. Together, these data indicate that snoRNAs as a class are present in the cytoplasm, where their levels are dynamically regulated by NOX4D during oxidative stress. The finding that loss-of-function of NXF3, a member of the nuclear export family of RNA transporters, protects cells from lipotoxic cell death suggested that this protein may function as a regulator of snoRNA distribution. In transient transfection assays, NXF3 knockdown increased abundance of cytosolic Rpl13a snoRNAs, whereas NXF3 overexpression led to decreased cytosolic levels. These observations suggested that snoRNAs traffic constitutively between the nucleus and cytoplasm, and NXF3 functions to efficiently concentrate snoRNAs in the nucleus. Consistent with a role for NXF3 as a snoRNA transporter, we found the Rpl13a snoRNAs co-immunoprecipitated with NXF3. Treatment of cells with forskolin caused a rapid decrease in cytosolic snoRNAs and increased both nuclear localization of NXF3 and association of NXF3 with Rpl13a snoRNAs. These effects of forskolin were abrogated by NXF3 knockdown. Our findings identify a novel trafficking pathway for snoRNAs that cycle between the nucleus and the cytosol. This pathway is regulated by oxidative stress and levels of the RNA transporter NXF3

Cerebroprotective Effects of Dimeric Copper(II) Bis(o-acetoxybenzoate) on Ischemia-reperfusion Injury in Gerbils

The cerebroprotective effects of copper aspirinate [dimeric copper(II) bis(o-acetoxybenzoate)] were investigated in gerbils subjected to 10-min global cerebral ischemia followed b 60-min reperfusion. The results showed that intragastric copper aspirinate (7.5, 15.0 and 30.0 mg Kg−1) markedly promoted the recovery of the electroencephalogram amplitude, attenuated the increase of lipid peroxide content and the decrease of superoxide dismutase activity in the cortex during ischemia-reperfusion injury. It suggested that copper aspirinate possesses potential neuroprotective properties, the mechanism of which might be related to an increase of the activity of endogenous superoxide dismutase

How do keystones govern their business ecosystems through resource orchestration?

Purpose: Sharing resources with stakeholders is the key for keystones to govern business ecosystems successfully. However, existing research has not paid further attention to how keystones share resources under the condition of resource sufficiency and how keystones balance resource sharing with complementors when they lack resources. Therefore, this paper aims to explore how keystones govern their business ecosystems under the conditions of resource sufficiency and resource insufficiency. Design/methodology/approach: This paper adopts the single case study method. First, by adopting Gioia coding to analyze the relevant data of the case sample, this paper obtains the key concepts of the business ecosystem governance process. Then, it establishes the relationship between the concepts by analyzing the governance process of the case sample. Findings: Under the condition of resource sufficiency, keystones under the condition of resource sufficiency, should make full use of resources to incubate more complementors, and further integrate the resources of the business ecosystem, to create more value for their business ecosystems. Under the condition of resource insufficiency, keystones should break the boundaries of business ecosystems and acquire external resources, to meet the resource needs of complementors. Subsequently, keystones should redeploy idle resources according to the actual needs of complementors, to meet the changing resource needs of complementors. Originality/value: This study subdivides business ecosystem governance conditions and further constructs the business ecosystem governance process model, which provides a theoretical and practical reference for business ecosystem governance

BigDataBench: a Big Data Benchmark Suite from Internet Services

As architecture, systems, and data management communities pay greater attention to innovative big data systems and architectures, the pressure of benchmarking and evaluating these systems rises. Considering the broad use of big data systems, big data benchmarks must include diversity of data and workloads. Most of the state-of-the-art big data benchmarking efforts target evaluating specific types of applications or system software stacks, and hence they are not qualified for serving the purposes mentioned above. This paper presents our joint research efforts on this issue with several industrial partners. Our big data benchmark suite BigDataBench not only covers broad application scenarios, but also includes diverse and representative data sets. BigDataBench is publicly available from http://prof.ict.ac.cn/BigDataBench . Also, we comprehensively characterize 19 big data workloads included in BigDataBench with varying data inputs. On a typical state-of-practice processor, Intel Xeon E5645, we have the following observations: First, in comparison with the traditional benchmarks: including PARSEC, HPCC, and SPECCPU, big data applications have very low operation intensity; Second, the volume of data input has non-negligible impact on micro-architecture characteristics, which may impose challenges for simulation-based big data architecture research; Last but not least, corroborating the observations in CloudSuite and DCBench (which use smaller data inputs), we find that the numbers of L1 instruction cache misses per 1000 instructions of the big data applications are higher than in the traditional benchmarks; also, we find that L3 caches are effective for the big data applications, corroborating the observation in DCBench.Comment: 12 pages, 6 figures, The 20th IEEE International Symposium On High Performance Computer Architecture (HPCA-2014), February 15-19, 2014, Orlando, Florida, US

High-level expression and large-scale preparation of soluble HBx antigen from Escherichia coli

The HBx (hepatitis B virus X protein) is a multifunctional regulator of cellular signal transduction and transcription pathways in host-infected cells. Evidence suggests that HBx has a critical role in the pathogenesis of hepatocellular carcinoma. However, the lack of efficient large-scale preparation methods for soluble HBx has hindered studies on the structure and function of HBx. Here, a new pMAL-c2x protein fusion and purification system was used for high-level expression of soluble HBx fusion protein. The high-purity fusion protein was obtained via amylose resin chromatography and Q-Sepharose chromatography. The untagged HBx was efficiently and rapidly purified by Sephadex G-75 chromatography after cleavage by Factor Xa at 23 °C. The purity of active HBx protein was >99% with a very stable secondary structure dominated by α-helix, β-sheet and random structure. The purified HBx protein can be analysed to determine its crystal structure and function and its capabilities as an effective immunogen

Variations in growth traits and wood physicochemical properties among Pinus koraiensis families in Northeast China

This study aimed to explore and improve the different economic values of Pinus koraiensis (Siebold and Zucc.) by examining the variations in 6 growth traits and 9 physicochemical wood properties among 53 P. koraiensis half-sib families. Growth traits assessed included height, diameter at breast height, volume, degree of stem straightness, stem form, and branch number per node, while wood properties assessed included density, fiber length and width, fiber length to width ratio, and cellulose, hemicellulose, holocellulose, lignin, and ash contents. Except for degree of stem straightness and branch number per node, all other traits exhibited highly significant variations (P < 0.01) among families. The coefficients of variation ranged from 5.3 (stem form) to 66.7% (ash content), whereas, the heritability ranged from 0.136 (degree of stem straightness) to 0.962 (ash content). Significant correlations were observed among growth traits and wood physicochemical properties. Principal component analysis identified four distinct groups representing growth traits, wood chemical and physical properties, and stem form traits. Multi-trait comprehensive evaluation identified three groups of elite families based on breeding objectives, including rapid growth, improved timber production for building and furniture materials, and pulpwood production. These specific families should be used to establish new plantations

AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentation

Despite the considerable progress in automatic abdominal multi-organ segmentation from CT/MRI scans in recent years, a comprehensive evaluation of the models' capabilities is hampered by the lack of a large-scale benchmark from diverse clinical scenarios. Constraint by the high cost of collecting and labeling 3D medical data, most of the deep learning models to date are driven by datasets with a limited number of organs of interest or samples, which still limits the power of modern deep models and makes it difficult to provide a fully comprehensive and fair estimate of various methods. To mitigate the limitations, we present AMOS, a large-scale, diverse, clinical dataset for abdominal organ segmentation. AMOS provides 500 CT and 100 MRI scans collected from multi-center, multi-vendor, multi-modality, multi-phase, multi-disease patients, each with voxel-level annotations of 15 abdominal organs, providing challenging examples and test-bed for studying robust segmentation algorithms under diverse targets and scenarios. We further benchmark several state-of-the-art medical segmentation models to evaluate the status of the existing methods on this new challenging dataset. We have made our datasets, benchmark servers, and baselines publicly available, and hope to inspire future research. Information can be found at https://amos22.grand-challenge.org