Technical Report: TeraGrid eXtreme Digital Campus Cyberinfrastructure and Campus Bridging Requirements Elicitation Meeting

In an effort to systematically investigate requirements for TeraGrid XD, the XROADS collaboration held during 2009 a series of requirements elicitation meetings (REM) with small groups of stakeholders. This report summarizes the conduct of and results from a requirements elicitation meeting on the topics of campus bridging and campus cyberinfrastructure. The meeting’s goal was to develop a clearer and more functional definition of what the next phase of the TeraGrid should do to be a resource broadly useful to and used by university and college campuses throughout the US.This report depends very much on the prior involvement of several XROADS partners in the TeraGrid, which has been funded in part by the NSF via the following grant awards: 0504086, 0503697, and 0742145 to the University of Chicago; 0451237 and 0504075 to Indiana University; and 0122272, 0332113, 0451566, 0503944, 0910847 to the University of California San Diego

TNFα-mediated Hsd11b1 binding of NF-κB p65 is associated with suppression of 11β-HSD1 in muscle

The activity of the enzyme 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1), which converts inactive cortisone (11-dehydrocorticosterone (11-DHC)) (in mice) into the active glucocorticoid (GC) cortisol (corticosterone in mice), can amplify tissue GC exposure. Elevated TNFα is a common feature in a range of inflammatory disorders and is detrimental to muscle function in diseases such as rheumatoid arthritis and chronic obstructive pulmonary disease.We have previously demonstrated that 11β-HSD1 activity is increased in the mesenchymal stromal cells (MSCs) by TNFα treatment and suggested that this is an autoregulatory anti-inflammatory mechanism. This upregulation was mediated by the P2 promoter of the Hsd11β1 gene and was dependent on the NF-kB signalling pathway. In this study, we show that in contrast to MSCs, in differentiated C2C12 and primary murine myotubes, TNFα suppresses Hsd11β1 mRNA expression and activity through the utilization of the alternative P1 promoter. As with MSCs, in response to TNFα treatment, NF-κB p65 was translocated to the nucleus. However, ChIP analysis demonstrated that the direct binding was seen at positionK218 toK245 bp of the Hsd11β1 gene's P1 promoter but not at the P2 promoter. These studies demonstrate the existence of differential regulation of 11β-HSD1 expression in muscle cells through TNFα/p65 signalling and the P1 promoter, further enhancing our understanding of the role of 11β-HSD1 in the context of inflammatory disease

Basal melt of the southern Filchner Ice Shelf, Antarctica

Basal melt of ice shelves is a key factor governing discharge of ice from the Antarctic Ice Sheet as a result of its effects on buttressing. Here, we use radio echo sounding to determine the spatial variability of the basal melt rate of the southern Filchner Ice Shelf, Antarctica, along the inflow of Support Force Glacier. We find moderate melt rates with a maximum of 1.13 m/a about 50 km downstream of the grounding line. The variability of the melt rates over distances of a few kilometres is low (all but one <0.15 m/a at 2 km distance), indicating that measurements on coarse observational grids are able to yield a representative melt rate distribution. A comparison with remote-sensing-based melt rates revealed that, for the study area, large differences were due to inaccuracies in the estimation of vertical strain rates from remote sensing velocity fields. These inaccuracies can be overcome by using modern velocity fields

Rockhopper: a True HPC System with Cloud Concepts

Presented at IEEE Cluster 2013 in Indianapolis, INA number of services for scientific computing based on cloud resources have recently drawn significant attention in both research and infrastructure provider communities. Most cloud resources currently available lack true high performance characteristics, such as high-speed interconnects or storage. Researchers studying cloud systems have pointed out that many cloud services do not provide service level agreements that may meet the needs of the research community. Furthermore, the lack of location information provided to the user and the shared nature of the systems use may create risk for users of the system, in the instance that their data is moved to an unknown location with an unknown level of security. Indiana University and Penguin Computing have partnered to create a system, Rockhopper, which addresses many of these issues. This system is a true high performance resource, with on-demand allocations and control and tracking of jobs, situated at Indiana University's high-security datacenter facility. Rockhopper allows researchers to flexibly conduct their work under a number of use cases while also serving as an extension of cyberinfrastructure that scales from the researcher's local environment all the way up through large national resources. We describe the architecture and ideas behind the creation of the system, present a use case for campus bridging, and provide a typical example of system usage. In a comparison of Rockhopper to a cloud-based system, we run the Trinity RNA-seq software against a number of datasets on both the Rockhopper system and on Amazon's EC2 service

Peripheral isolates as sources of adaptive diversity under climate change

As climate change progresses, there is increasing focus on the possibility of using targeted gene flow (TGF, the movement of pre-adapted individuals into declining populations) as a management tool. Targeted gene flow is a relatively cheap, low-risk management option, and will almost certainly come into increased use over the coming decades. Before such action can be taken, however, we need to know where to find pre-adapted individuals. We argue that, for many species, the obvious place to look for this diversity is in peripheral isolates: isolated populations at the current edges of a species' range. Both evolutionary and ecological considerations suggest that the bulk of a species' adaptive variation may be contained in the total set of these peripheral isolates. Moreover, by exploring both evolutionary and ecological perspectives it becomes clear that we should be able to assess the potential value of each isolate using remotely sensed data and three measurable axes of variation in patch traits: population size, connectivity, and climatic environment. Locating the “sweet spot” in this trait space, however, remains a challenge. Throughout, we illustrate these ideas using Australia's Wet Tropics rainforests as a model system.We thank the Australian Research Council for funding this work (DP1094646, FL110100104, DP130100318, FT160100198); the Tropical Landscapes Joint Venture (a collaboration between CSIRO and JCU) for support to SM and JL; and the Wet Tropics Management Authority for support to SM

Understanding social and clinical associations with unemployment for people with schizophrenia and bipolar disorders: large-scale health records study

Purpose People with severe mental illness (SMI) experience high levels of unemployment. We aimed to better understand the associations between clinical, social, and demographic inequality indicators and unemployment. Methods Data were extracted from de-identified health records of people with SMI in contact with secondary mental health services in south London, UK. A Natural Language Processing text-mining application was applied to extract information on unemployment in the health records. Multivariable logistic regression was used to assess associations with unemployment, in people with SMI. Results Records from 19,768 service users were used for analysis, 84.9% (n = 16,778) had experienced unemployment. In fully adjusted models, Black Caribbean and Black African service users were more likely to experience unemployment compared with White British service users (Black Caribbean: aOR 1.62, 95% CI 1.45–1.80; Black African: 1.32, 1.15–1.51). Although men were more likely to have experienced unemployment relative to women in unadjusted models (OR 1.36, 95% CI 1.26–1.47), differences were no longer apparent in the fully adjusted models (aOR 1.05, 95% CI 0.97–1.15). The presence of a non-affective (compared to affective) diagnosis (1.24, 1.13–1.35), comorbid substance use (2.02, 1.76–2.33), previous inpatient admissions (4.18, 3.71–4.70), longer inpatient stays (78 + days: 7.78, 6.34–9.54), and compulsory admissions (3.45, 3.04–3.92) were associated with unemployment, in fully adjusted models. Conclusion People with SMI experience high levels of unemployment, and we found that unemployment was associated with several clinical and social factors. Interventions to address low employment may need to also address these broader inequalities

Computational Biology and High Performance Computing 2000

Tutorial to be presented at Supercomputing 2000, Dallas TX, 6-10 November 2000.This work was supported by the Director, Office of Science, Office of Advanced Scientific computing Research, Mathematical, Information, and Computational Sciences Division of the U.S. Department of Energy under Contract No. DE-AC03-76SF0009

Computational Biology and High Performance Computing 2000

Tutorial to be presented at Supercomputing 2000, Dallas TX, 6-10 November 2000.This work was supported by the Director, Office of Science, Office of Advanced Scientific computing Research, Mathematical, Information, and Computational Sciences Division of the U.S. Department of Energy under Contract No. DE-AC03-76SF0009