Evaluator services for optimised service placement in distributed heterogeneous cloud infrastructures

Optimal placement of demanding real-time interactive applications in a distributed heterogeneous cloud very quickly results in a complex tradeoff between the application constraints and resource capabilities. This requires very detailed information of the various requirements and capabilities of the applications and available resources. In this paper, we present a mathematical model for the service optimization problem and study the concept of evaluator services as a flexible and efficient solution for this complex problem. An evaluator service is a service probe that is deployed in particular runtime environments to assess the feasibility and cost-effectiveness of deploying a specific application in such environment. We discuss how this concept can be incorporated in a general framework such as the FUSION architecture and discuss the key benefits and tradeoffs for doing evaluator-based optimal service placement in widely distributed heterogeneous cloud environments

Service oriented networking

This paper introduces a new paradigm for service oriented networking being developed in the FUSION project(1). Despite recent proposals in the area of information centric networking, a similar treatment of services - where networked software functions, rather than content, are dynamically deployed, replicated and invoked - has received little attention by the network research community to date. Our approach provides the mechanisms required to deploy a replicated service instance in the network and to route client requests to the closest instance in an efficient manner. We address the main issues that such a paradigm raises including load balancing, resource registration, domain monitoring and inter-domain orchestration. We also present preliminary evaluation results of current work

Molecular cloning and biochemical characterization of a Cu,Zn-superoxide dismutase from Scedosporium apiospermum.

A Cu,Zn-superoxide dismutase has been characterized from Scedosporium apiospermum, a fungus which often colonizes the respiratory tract of patients with cystic fibrosis. Enzyme production was stimulated by iron starvation. Purification was achieved from mycelial extract from 7-day-old cultures on Amberlite XAD-16. The purified enzyme presented a relative molecular mass of 16.4 kDa under reducing conditions and was inhibited by potassium cyanide and diethyldithiocarbamate, which are two known inhibitors of Cu,Zn-SODs. Its optimum pH was 7.0 and the enzyme retained full activity after pretreatment at temperatures up to 50 degrees C. Moreover, a 450-bp fragment of the gene encoding the enzyme was amplified by PCR using degenerate primers designed from sequence alignment of four fungal Cu,Zn-SODs. Sequence data from this fragment allowed us to design primers which were used to amplify by walking-PCR the flanking regions of the known fragment. SaSODC gene (890 bp) corresponded to a 154 amino acid polypeptide with a predicted molecular mass of 15.9 kDa. A database search for sequence homology revealed for the deduced amino acid sequence 72 and 83% identity rate with Cu,Zn-SODs from Aspergillus fumigatus and Neurospora crassa, respectively. To our knowledge, this enzyme is the first putative virulence factor of S. apiospermum to be characterized

HOXA1 binds RBCK1/HOIL-1 and TRAF2 and modulates the TNF/NF-κB pathway in a transcription-independent manner

HOX proteins define a family of key transcription factors regulating animal embryogenesis. HOX genes have also been linked to oncogenesis and HOXA1 has been described to be active in several cancers, including breast cancer. Through a proteome-wide interaction screening, we previously identified the TNFR-associated proteins RBCK1/HOIL-1 and TRAF2 as HOXA1 interactors suggesting that HOXA1 is functionally linked to the TNF/NF-κB signaling pathway. Here, we reveal a strong positive correlation between expression of HOXA1 and of members of the TNF/NF-κB pathway in breast tumor datasets. Functionally, we demonstrate that HOXA1 can activate NF-κB and operates upstream of the NF-κB inhibitor IκB. Consistently, we next demonstrate that the HOXA1-mediated activation of NF-κB is non-transcriptional and that RBCK1 and TRAF2 influences on NF-κB are epistatic to HOXA1. We also identify an 11 Histidine repeat and the homeodomain of HOXA1 to be required both for RBCK1 and TRAF2 interaction and NF-κB stimulation. Finally, we highlight that activation of NF-κB is crucial for HOXA1 oncogenic activity

Microbiota - obesity : associations from mouth to gut across all ages

In this paper, we give an integrated overview of the most recent insights regarding the role of the microbiota in obesity across body-sites for different age groups based on observational and interventional data published between April 2019 and March 2020

Mitigating Scoring Errors in Microsatellite Data from Wild Populations

Microsatellite data are widely used to test ecological and evolutionary hypotheses in wild populations. In this paper, we consider three typical sources of scoring errors capable of biasing biological conclusions: stuttering, large-allele dropout and null alleles. We describe methods to detect errors and propose conventions to mitigate scoring errors and report error rates in studies of wild populations. Finally, we discuss potential bias in ecological or evolutionary conclusions based on data sets containing these scoring errors

Current understanding of the human microbiome

Author Posting. © The Author(s), 2018. This is the author's version of the work. It is posted here by permission of Nature Publishing Group for personal use, not for redistribution. The definitive version was published in Nature Medicine 24 (2018): 392–400, doi:10.1038/nm.4517.Our understanding of the link between the human microbiome and disease, including obesity, inflammatory bowel disease, arthritis and autism, is rapidly expanding. Improvements in the throughput and accuracy of DNA sequencing of the genomes of microbial communities associated with human samples, complemented by analysis of transcriptomes, proteomes, metabolomes and immunomes, and mechanistic experiments in model systems, have vastly improved our ability to understand the structure and function of the microbiome in both diseased and healthy states. However, many challenges remain. In this Review, we focus on studies in humans to describe these challenges, and propose strategies that leverage existing knowledge to move rapidly from correlation to causation, and ultimately to translation.Many of the studies described here in our laboratories were supported by the NIH, NSF, DOE, and the Alfred P. Sloan Foundation.2018-10-1