Autonomous migration of vertual machines for maximizing resource utilization

Virtualization of computing resources enables multiple virtual machines to run on a physical machine. When many virtual machines are deployed on a cluster of PCs, some physical machines will inevitably experience overload while others are under-utilized over time due to varying computational demands. This computational imbalance across the cluster undermines the very purpose of maximizing resource utilization through virtualization. To solve this imbalance problem, virtual machine migration has been introduced, where a virtual machine on a heavily loaded physical machine is selected and moved to a lightly loaded physical machine. The selection of the source virtual machine and the destination physical machine is based on a single fixed threshold value. Key to such threshold-based VM migration is to determine when to move which VM to what physical machine, since wrong or inadequate decisions can cause unnecessary migrations that would adversely affect the overall performance. The fixed threshold may not necessarily work for different computing infrastructures. Finding the optimal threshold is critical. In this research, a virtual machine migration framework is presented that autonomously finds and adjusts variable thresholds at runtime for different computing requirements to improve and maximize the utilization of computing resources. Central to this approach is the previous history of migrations and their effects before and after each migration in terms of standard deviation of utilization. To broaden this research, a proactive learning methodology is introduced that not only accumulates the past history of computing patterns and resulting migration decisions but more importantly searches all possibilities for the most suitable decisions. This research demonstrates through experimental results that the learning approach autonomously finds thresholds close to the optimal ones for different computing scenarios and that such varying thresholds yield an optimal number of VM migrations for maximizing resource utilization. The proposed framework is set up on a cluster of 8 and 16 PCs, each of which has multiple User-Mode Linux (UML)-based virtual machines. An extensive set of benchmark programs is deployed to closely resemble a real-world computing environment. Experimental results indicate that the proposed framework indeed autonomously finds thresholds close to the optimal ones for different computing scenarios, balances the load across the cluster through autonomous VM migration, and improves the overall performance of the dynamically changing computing environment

Multi-frame-based Cross-domain Image Denoising for Low-dose Computed Tomography

Computed tomography (CT) has been used worldwide for decades as one of the most important non-invasive tests in assisting diagnosis. However, the ionizing nature of X-ray exposure raises concerns about potential health risks such as cancer. The desire for lower radiation dose has driven researchers to improve the reconstruction quality, especially by removing noise and artifacts. Although previous studies on low-dose computed tomography (LDCT) denoising have demonstrated the effectiveness of learning-based methods, most of them were developed on the simulated data collected using Radon transform. However, the real-world scenario significantly differs from the simulation domain, and the joint optimization of denoising with modern CT image reconstruction pipeline is still missing. In this paper, for the commercially available third-generation multi-slice spiral CT scanners, we propose a two-stage method that better exploits the complete reconstruction pipeline for LDCT denoising across different domains. Our method makes good use of the high redundancy of both the multi-slice projections and the volumetric reconstructions while avoiding the collapse of information in conventional cascaded frameworks. The dedicated design also provides a clearer interpretation of the workflow. Through extensive evaluations, we demonstrate its superior performance against state-of-the-art methods

Broussonetia papyrifera Root Bark Extract Exhibits Anti-inflammatory Effects on Adipose Tissue and Improves Insulin Sensitivity Potentially Via AMPK Activation

The chronic low-grade inflammation in adipose tissue plays a causal role in obesity-induced insulin resistance and its associated pathophysiological consequences. In this study, we investigated the effects of extracts of Broussonetia papyrifera root bark (PRE) and its bioactive components on inflammation and insulin sensitivity. PRE inhibited TNF-alpha-induced NF-kappa B transcriptional activity in the NF-kappa B luciferase assay and pro-inflammatory genes' expression by blocking phosphorylation of I kappa B and NF-kappa B in 3T3-L1 adipocytes, which were mediated by activating AMPK. Ten-week-high fat diet (HFD)-fed C57BL6 male mice treated with PRE had improved glucose intolerance and decreased inflammation in adipose tissue, as indicated by reductions in NF-kappa B phosphorylation and pro-inflammatory genes' expression. Furthermore, PRE activated AMP-activated protein kinase (AMPK) and reduced lipogenic genes' expression in both adipose tissue and liver. Finally, we identified broussoflavonol B (BF) and kazinol J (KJ) as bioactive constituents to suppress pro-inflammatory responses via activating AMPK in 3T3-L1 adipocytes. Taken together, these results indicate the therapeutic potential of PRE, especially BF or KJ, in metabolic diseases such as obesity and type 2 diabetes

Anti-diabetic effect of Cyclo-His-Pro (CHP)-enriched yeast hydrolysate in streptozotocin-induced diabetic mice

The present study was designed to investigate the hypoglycemic effects of the daily oral dose of 0.50 to 0.75 g/kg of yeast hydrolysate (YH) containing high Cyclo-His-Pro (51.0 mg CHP/g YH) on normal and streptozotocin (STZ)-induced diabetic rats for 14 days. In STZ-induced diabetic rats, after administrations of the YH for 14 days, the body weight gain was significantly increased in dose dependent manner, and the plasma glucose levels were decreased approximately (60%) as compared to the STZ induced diabetic control group. Glucose level showed significant differences between the diabetic control (DC) and the YH administered groups in oral glucose tolerance test (OGTT) (P<0.05). Results of the OGTT showed a significant decrease in the area under curve (AUC) value of YH supplemented groups as compared to the DC group. The present data suggests that the CHP-enriched YH has potential anti-diabetic effect, which can help in the cure and management of diabetes.Keywords: Yeast hydrolysate, Cyclo-His-Pro (CHP), diabetes, streptozotocin.African Journal of Biotechnology Vol. 12(35), pp. 5473-547

Development of Pseudomembranous Colitis Four Months after Initiation of Rifampicin

Pseudomembranous colitis (PMC) may develop with long-term antibiotic administration, but is rarely reported to be caused by antitubercular agents. We present a case of PMC that occurred 120 days after starting rifampicin. A 74-year-old man was diagnosed with pulmonary tuberculosis and started on a standard HERZ regimen (isoniazid, ethambutol, rifampicin, pyrazinamide). After 4 months of HERZ, he presented with frequent bloody, mucoid, jelly-like diarrhea and lower abdominal pain. Sigmoidoscopy revealed multiple whitish plaques with edematous mucosa that were compatible with PMC. Biopsies from these lesions showed ulcer-related necrotic and granulation tissue. We stopped antitubercular treatment and started the patient on oral metronidazole. His symptoms completely resolved within 2 weeks. Antitubercular treatment was restarted by replacing rifampicin with levofloxacin. The patient did not present with diarrhea or bloody stool throughout the rest of treatment

Functional enhancement of neuronal cell behaviors and differentiation by elastin-mimetic recombinant protein presenting Arg-Gly-Asp peptides

Background: Integrin-mediated interaction of neuronal cells with extracellular matrix (ECM) is important for the control of cell adhesion, morphology, motility, and differentiation in both in vitro and in vivo systems. Arg-Gly-Asp (RGD) sequence is one of the most potent integrin-binding ligand found in many native ECM proteins. An elastin-mimetic recombinant protein, TGPG[VGRGD(VGVPG)6]20WPC, referred to as [RGD-V6]20, contains multiple RGD motifs to bind cell-surface integrins. This study aimed to investigate how surface-adsorbed recombinant protein can be used to modulate the behaviors and differentiation of neuronal cells in vitro. For this purpose, biomimetic ECM surfaces were prepared by isothermal adsorption of [RGD-V6]20 onto the tissue culture polystyrene (TCPS), and the effects of protein-coated surfaces on neuronal cell adhesion, spreading, migration, and differentiation were quantitatively measured using N2a neuroblastoma cells.Results: The [RGD-V6]20 was expressed in E. coli and purified by thermally-induced phase transition. N2a cell attachment to either [RGD-V6]20 or fibronectin followed hyperbolic binding kinetics saturating around 2 μM protein concentration. The apparent maximum cell binding to [RGD-V6]20 was approximately 96% of fibronectin, with half-maximal adhesion on [RGD-V6]20 and fibronectin occurring at a coating concentration of 2.4 × 10-7 and 1.4 × 10-7 M, respectively. The percentage of spreading cells was in the following order of proteins: fibronectin (84.3% ± 6.9%) > [RGD-V6]20 (42.9% ± 6.5%) > [V7]20 (15.5% ± 3.2%) > TCPS (less than 10%). The migration speed of N2a cells on [RGD-V6]20 was similar to that of cells on fibronectin. The expression of neuronal marker proteins Tuj1, MAP2, and GFAP was approximately 1.5-fold up-regulated by [RGD-V6]20 relative to TCPS. Moreover, by the presence of both [RGD-V6]20 and RA, the expression levels of NSE, TuJ1, NF68, MAP2, and GFAP were significantly elevated.Conclusion: We have shown that an elastin-mimetic protein consisting of alternating tropoelastin structural domains and cell-binding RGD motifs is able to stimulate neuronal cell behaviors and differentiation. In particular, adhesion-induced neural differentiation is highly desirable for neural development and nerve repair. In this context, our data emphasize that the combination of biomimetically engineered recombinant protein and isothermal adsorption approach allows for the facile preparation of bioactive matrix or coating for neural tissue regeneration. © 2012 Jeon et al.; licensee BioMed Central Ltd.1

Bioinspired Heparin Nanosponge Prepared by Photo-crosslinking for Controlled Release of Growth Factors

Indexación: Scopus.Growth factors have great therapeutic potential for various disease therapy and tissue engineering applications. However, their clinical efficacy is hampered by low bioavailability, rapid degradation in vivo and non-specific biodistribution. Nanoparticle based delivery systems are being evaluated to overcome these limitations. Herein, we have developed a thermosensitive heparin nanosponge (Hep-NS) by a one step photopolymerization reaction between diacrylated pluronic and thiolated heparin molecules. The amount of heparin in Hep-NS was precisely controlled by varying the heparin amount in the reaction feed. Hep-NS with varying amounts of heparin showed similar size and shape properties, though surface charge decreased with an increase in the amount of heparin conjugation. The anticoagulant activity of the Hep-NS decreased by 65% compared to free heparin, however the Hep-NS retained their growth factor binding ability. Four different growth factors, bFGF, VEGF, BMP-2, and HGF were successfully encapsulated into Hep-NS. In vitro studies showed sustained release of all the growth factors for almost 60 days and the rate of release was directly dependent on the amount of heparin in Hep-NS. The released growth factors retained their bioactivity as assessed by a cell proliferation assay. This heparin nanosponge is therefore a promising nanocarrier for the loading and controlled release of growth factors.https://www.nature.com/articles/s41598-017-14040-5.pd