Regulation of Spo12 Phosphorylation and Its Essential Role in the FEAR Network

Background: In budding yeast, the protein phosphatase Cdc14 coordinates late mitotic events and triggers exit from mitosis. During early anaphase, Cdc14 is activated by the FEAR network, but how signaling through the FEAR network occurs is poorly understood. Results: We find that the FEAR network component Spo12 is phosphorylated on S118. This phosphorylation is essential for Spo12 function and is restricted to early anaphase, when the FEAR network is active. The anaphase-specific phosphorylation of Spo12 requires mitotic CDKs and depends on the FEAR network components Separase and Slk19. Furthermore, we find that CDC14 is required to maintain Spo12 in the dephosphorylated state prior to anaphase. Conclusions: Our results show that anaphase-specific phosphorylation of Spo12 is essential for FEAR network function and raise the interesting possibility that Cdc14 itself helps to prevent the FEAR network from being prematurely activated.National Institutes of Health (U.S.) (grant GM 056800)Howard Hughes Medical Institute (Investigator

AstroGrid-D: Grid Technology for Astronomical Science

We present status and results of AstroGrid-D, a joint effort of astrophysicists and computer scientists to employ grid technology for scientific applications. AstroGrid-D provides access to a network of distributed machines with a set of commands as well as software interfaces. It allows simple use of computer and storage facilities and to schedule or monitor compute tasks and data management. It is based on the Globus Toolkit middleware (GT4). Chapter 1 describes the context which led to the demand for advanced software solutions in Astrophysics, and we state the goals of the project. We then present characteristic astrophysical applications that have been implemented on AstroGrid-D in chapter 2. We describe simulations of different complexity, compute-intensive calculations running on multiple sites, and advanced applications for specific scientific purposes, such as a connection to robotic telescopes. We can show from these examples how grid execution improves e.g. the scientific workflow. Chapter 3 explains the software tools and services that we adapted or newly developed. Section 3.1 is focused on the administrative aspects of the infrastructure, to manage users and monitor activity. Section 3.2 characterises the central components of our architecture: The AstroGrid-D information service to collect and store metadata, a file management system, the data management system, and a job manager for automatic submission of compute tasks. We summarise the successfully established infrastructure in chapter 4, concluding with our future plans to establish AstroGrid-D as a platform of modern e-Astronomy.Comment: 14 pages, 12 figures Subjects: data analysis, image processing, robotic telescopes, simulations, grid. Accepted for publication in New Astronom

Liver resection or combined chemoembolization and radiofrequency ablation improve survival in patients with hepatocellular carcinoma

Background/ Aims: To evaluate the long-term outcome of surgical and non-surgical local treatments of patients with hepatocellular carcinoma (HCC). Methods: We stratified a cohort of 278 HCC patients using six independent predictors of survival according to the Vienna survival model for HCC (VISUM- HCC). Results: Prior to therapy, 224 HCC patients presented with VISUM stage 1 (median survival 18 months) while 29 patients were classified as VISUM stage 2 (median survival 4 months) and 25 patients as VISUM stage 3 (median survival 3 months). A highly significant (p < 0.001) improved survival time was observed in VISUM stage 1 patients treated with liver resection ( n = 52; median survival 37 months) or chemoembolization (TACE) and subsequent radiofrequency ablation ( RFA) ( n = 44; median survival 45 months) as compared to patients receiving chemoembolization alone (n = 107; median survival 13 months) or patients treated by tamoxifen only (n = 21; median survival 6 months). Chemoembolization alone significantly (p <= 0.004) improved survival time in VISUM stage 1 - 2 patients but not (p = 0.341) in VISUM stage 3 patients in comparison to those treated by tamoxifen. Conclusion: Both liver resection or combined chemoembolization and RFA improve markedly the survival of patients with HCC

Load Balancing in MapReduce Based on Scalable Cardinality Estimates

Abstract—MapReduce has emerged as a popular tool for distributed and scalable processing of massive data sets and is increasingly being used in e-science applications. Unfortunately, the performance of MapReduce systems strongly depends on an even data distribution, while scientific data sets are often highly skewed. The resulting load imbalance, which raises the processing time, is even amplified by the high runtime complexities of the reducer tasks. An adaptive load balancing strategy is required for appropriate skew handling. In this paper, we address the problem of estimating the cost of the tasks that are distributed to the reducers based on a given cost model. A realistic cost estimation is the basis for adaptive load balancing algorithms and requires to gather statistics from the mappers. This is challenging: (a) Since the statistics from all mappers must be integrated, the mapper statistics must be small. (b) Although each mapper sees only a small fraction of the data, the integrated statistics must capture the global data distribution. (c) The mappers terminate after sending the statistics to the controller, and no second round is possible. Our solution to these challenges consists of two components. First, a monitoring component executed on every mapper captures the local data distribution and identifies its most relevant subset for cost estimation. Second, an integration component aggregates these subsets and approximates the global data distribution. I