Adaptives Caching in verteilten Informationssysteme

In dieser Arbeit stellen wir eine neuartige Methode für verteiltes Caching vor, die das Ausnutzen des aggregierten Hauptspeichers eines lokalen Rechnernetzwerkes für datenintensive Anwendungen erlaubt. Ein detailliertes Kostenmodell dient als Basis für die Bestimmung einer guten Cache-Allokation. Da im allgemeinen die Eingabegrößen für dieses Kostenmodell im Online- Fall nicht a priori bekannt sind und darüber hinaus dynamisch schwanken können, werden speziell angepaßte Protokolle zur Bestimmung und Verteilung dieser Informationen benutzt. Durch eine approximative Online-Auswertung des Kostenmodells paßt sich unsere Caching-Strategie adaptiv an die aktuelle Last an und kann dadurch Engpäße auf den Systemressourcen verhindern. Zur Vermeidung von Lastungleichgewichten wird aus dem Kostenmodell zusätzlich eine Lastverteilungsheuristik abgeleitet, die im Hintergrund zielgerichtete Migrationen von Objekten zur Balancierung des Systems durchführen kann. Sowohl die Anpassung an die aktuelle Last als auch die Vermeidung von Ungleichgewichten führt zu einer — verglichen mit bisherigen Methoden — deutlich besseren Leistungsfähigkeit unserer Heuristik. Eine Erweiterung des entwickelten Caching- Verfahrens berechnet eine Partitionierung des aggregierten Hauptspeichers, so daß Antwortzeitziele für unterschiedliche Klassen von Operationen sichergestellt werden.This dissertation presents a new method for distributed caching to exploit the aggregate memory of networks of workstations in data-intensive applications. The approach is based on a detailed cost model to compute a good cache allocation. As the input parameters for the cost model are in general a-priori unkown and possibly evolve, we use specifically designed protocols to estimate and disseminate this information. Using an approximative online evaluation of the cost model,our caching heuristics adapts automatically to evolving workloads and thus avoids bottlenecks on system resources. To prevent load imbalances we further derive a load distribution method from the cost model. This load distribution method asynchronously migrates objects from highly loaded nodes onto lightly loaded nodes. The adaptation to the current workload and the prevention of imbalances result in significant performance improvements compared to prior methods. We further present a goal-oriented extension of the developed caching method, which determines a partitioning of the aggregate cache to satisfy given response-time goals for different classes of operations

Adaptives Caching in verteilten Informationssysteme

In dieser Arbeit stellen wir eine neuartige Methode für verteiltes Caching vor, die das Ausnutzen des aggregierten Hauptspeichers eines lokalen Rechnernetzwerkes für datenintensive Anwendungen erlaubt. Ein detailliertes Kostenmodell dient als Basis für die Bestimmung einer guten Cache-Allokation. Da im allgemeinen die Eingabegrößen für dieses Kostenmodell im Online- Fall nicht a priori bekannt sind und darüber hinaus dynamisch schwanken können, werden speziell angepaßte Protokolle zur Bestimmung und Verteilung dieser Informationen benutzt. Durch eine approximative Online-Auswertung des Kostenmodells paßt sich unsere Caching-Strategie adaptiv an die aktuelle Last an und kann dadurch Engpäße auf den Systemressourcen verhindern. Zur Vermeidung von Lastungleichgewichten wird aus dem Kostenmodell zusätzlich eine Lastverteilungsheuristik abgeleitet, die im Hintergrund zielgerichtete Migrationen von Objekten zur Balancierung des Systems durchführen kann. Sowohl die Anpassung an die aktuelle Last als auch die Vermeidung von Ungleichgewichten führt zu einer — verglichen mit bisherigen Methoden — deutlich besseren Leistungsfähigkeit unserer Heuristik. Eine Erweiterung des entwickelten Caching- Verfahrens berechnet eine Partitionierung des aggregierten Hauptspeichers, so daß Antwortzeitziele für unterschiedliche Klassen von Operationen sichergestellt werden.This dissertation presents a new method for distributed caching to exploit the aggregate memory of networks of workstations in data-intensive applications. The approach is based on a detailed cost model to compute a good cache allocation. As the input parameters for the cost model are in general a-priori unkown and possibly evolve, we use specifically designed protocols to estimate and disseminate this information. Using an approximative online evaluation of the cost model,our caching heuristics adapts automatically to evolving workloads and thus avoids bottlenecks on system resources. To prevent load imbalances we further derive a load distribution method from the cost model. This load distribution method asynchronously migrates objects from highly loaded nodes onto lightly loaded nodes. The adaptation to the current workload and the prevention of imbalances result in significant performance improvements compared to prior methods. We further present a goal-oriented extension of the developed caching method, which determines a partitioning of the aggregate cache to satisfy given response-time goals for different classes of operations

Diversifying molecular and topological space via a supramolecular solid-state synthesis: a purely organic mok net sustained by hydrogen bonds

A three-dimensional hydrogen-bonded network based on a rare mok topology has been constructed using an organic molecule synthesized in the solid state. The molecule is obtained using a supramolecular protecting-group strategy that is applied to a solid-state [2+2] photodimerization. The photodimerization affords a novel head-to-head cyclobutane product. The cyclobutane possesses tetrahedrally disposed cis-hydrogen-bond donor (phenolic) and cis-hydrogen- bond acceptor (pyridyl) groups. The product self-assembles in the solid state to form a mok network that exhibits twofold interpenetration. The cyclobutane adopts different conformations to provide combinations of hydrogen-bond donor and acceptor sites to conform to the structural requirements of the mok net

Multifactorial disease risk calculator: risk prediction for multifactorial disease pedigrees

Construction of multifactorial disease models from epidemiological findings and their application to disease pedigrees for risk prediction is nontrivial for all but the simplest of cases. Multifactorial Disease Risk Calculator is a web tool facilitating this. It provides a user-friendly interface, extending a reported methodology based on a liability-threshold model. Multifactorial disease models incorporating all the following features in combination are handled: quantitative risk factors (including polygenic scores), categorical risk factors (including major genetic risk loci), stratified age of onset curves, and the partition of the population variance in disease liability into genetic, shared, and unique environment effects. It allows the application of such models to disease pedigrees. Pedigree-related outputs are (i) individual disease risk for pedigree members, (ii) n year risk for unaffected pedigree members, and (iii) the disease pedigree's joint liability distribution. Risk prediction for each pedigree member is based on using the constructed disease model to appropriately weigh evidence on disease risk available from personal attributes and family history. Evidence is used to construct the disease pedigree's joint liability distribution. From this, lifetime and n year risk can be predicted. Example disease models and pedigrees are provided at the website and are used in accompanying tutorials to illustrate the features available. The website is built on an R package which provides the functionality for pedigree validation, disease model construction, and risk prediction. Website: http://grass.cgs.hku.hk:3838/mdrc/current

Regression-based approach for testing the association between multi-region haplotype configuration and complex trait

<p>Abstract</p> <p>Background</p> <p>It is quite common that the genetic architecture of complex traits involves many genes and their interactions. Therefore, dealing with multiple unlinked genomic regions simultaneously is desirable.</p> <p>Results</p> <p>In this paper we develop a regression-based approach to assess the interactions of haplotypes that belong to different unlinked regions, and we use score statistics to test the null hypothesis of non-genetic association. Additionally, multiple marker combinations at each unlinked region are considered. The multiple tests are settled via the <it>minP </it>approach. The <it>P </it>value of the "best" multi-region multi-marker configuration is corrected via Monte-Carlo simulations. Through simulation studies, we assess the performance of the proposed approach and demonstrate its validity and power in testing for haplotype interaction association.</p> <p>Conclusion</p> <p>Our simulations showed that, for binary trait without covariates, our proposed methods prove to be equal and even more powerful than htr and hapcc which are part of the FAMHAP program. Additionally, our model can be applied to a wider variety of traits and allow adjustment for other covariates. To test the validity, our methods are applied to analyze the association between four unlinked candidate genes and pig meat quality.</p

Assessment of genotype imputation methods

Several methods have been proposed to impute genotypes at untyped markers using observed genotypes and genetic data from a reference panel. We used the Genetic Analysis Workshop 16 rheumatoid arthritis case-control dataset to compare the performance of four of these imputation methods: IMPUTE, MACH, PLINK, and fastPHASE. We compared the methods' imputation error rates and performance of association tests using the imputed data, in the context of imputing completely untyped markers as well as imputing missing genotypes to combine two datasets genotyped at different sets of markers. As expected, all methods performed better for single-nucleotide polymorphisms (SNPs) in high linkage disequilibrium with genotyped SNPs. However, MACH and IMPUTE generated lower imputation error rates than fastPHASE and PLINK. Association tests based on allele "dosage" from MACH and tests based on the posterior probabilities from IMPUTE provided results closest to those based on complete data. However, in both situations, none of the imputation-based tests provide the same level of evidence of association as the complete data at SNPs strongly associated with disease

Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology

BACKGROUND: The arrival of RNA-seq as a high-throughput method competitive to the established microarray technologies has necessarily driven a need for comparative evaluation. To date, cross-platform comparisons of these technologies have been relatively few in number of platforms analyzed and were typically gene name annotation oriented. Here, we present a more extensive and yet precise assessment to elucidate differences and similarities in performance of numerous aspects including dynamic range, fidelity of raw signal and fold-change with sample titration, and concordance with qRT-PCR (TaqMan). To ensure that these results were not confounded by incompatible comparisons, we introduce the concept of probe mapping directed “transcript pattern”. A transcript pattern identifies probe(set)s across platforms that target a common set of transcripts for a specific gene. Thus, three levels of data were examined: entire data sets, data derived from a subset of 15,442 RefSeq genes common across platforms, and data derived from the transcript pattern defined subset of 7,034 RefSeq genes. RESULTS: In general, there were substantial core similarities between all 6 platforms evaluated; but, to varying degrees, the two RNA-seq protocols outperformed three of the four microarray platforms in most categories. Notably, a fourth microarray platform, Agilent with a modified protocol, was comparable, or marginally superior, to the RNA-seq protocols within these same assessments, especially in regards to fold-change evaluation. Furthermore, these 3 platforms (Agilent and two RNA-seq methods) demonstrated over 80 % fold-change concordance with the gold standard qRT-PCR (TaqMan). CONCLUSIONS: This study suggests that microarrays can perform on nearly equal footing with RNA-seq, in certain key features, specifically when the dynamic range is comparable. Furthermore, the concept of a transcript pattern has been introduced that may minimize potential confounding factors of multi-platform comparison and may be useful for similar evaluations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-1913-6) contains supplementary material, which is available to authorized users

Pooled analysis of iron-related genes in Parkinson's disease: Association with transferrin

Pathologic features of Parkinson's disease (PD) include death of dopaminergic neurons in the substantia nigra, presence of α-synuclein containing Lewy bodies, and iron accumulation in PD-related brain regions. The observed iron accumulation may be contributing to PD etiology but it also may be a byproduct of cell death or cellular dysfunction. To elucidate the possible role of iron accumulation in PD, we investigated genetic variation in 16 genes related to iron homeostasis in three case-control studies from the United States, Australia, and France. After screening 90 haplotype tagging single nucleotide polymorphisms (SNPs) within the genes of interest in the US study population, we investigated the five most promising gene regions in two additional independent case-control studies. For the pooled data set (1289 cases, 1391 controls) we observed a protective association (OR. = 0.83, 95% CI: 0.71-0.96) between PD and a haplotype composed of the A allele at rs1880669 and the T allele at rs1049296 in transferrin (TF; GeneID: 7018). Additionally, we observed a suggestive protective association (OR. = 0.87, 95% CI: 0.74-1.02) between PD and a haplotype composed of the G allele at rs10247962 and the A allele at rs4434553 in transferrin receptor 2 (TFR2; GeneID: 7036). We observed no associations in our pooled sample for haplotypes in SLC40A1, CYB561, or HFE. Taken together with previous findings in model systems, our results suggest that TF or a TF- TFR2 complex may have a role in the etiology of PD, possibly through iron misregulation or mitochondrial dysfunction within dopaminergic neurons

Curcumin-Loaded Apotransferrin Nanoparticles Provide Efficient Cellular Uptake and Effectively Inhibit HIV-1 Replication In Vitro

Curcumin (diferuloylmethane) shows significant activity across a wide spectrum of conditions, but its usefulness is rather limited because of its low bioavailability. Use of nanoparticle formulations to enhance curcumin bioavailability is an emerging area of research.In the present study, curcumin-loaded apotransferrin nanoparticles (nano-curcumin) prepared by sol-oil chemistry and were characterized by electron and atomic force microscopy. Confocal studies and fluorimetric analysis revealed that these particles enter T cells through transferrin-mediated endocytosis. Nano-curcumin releases significant quantities of drug gradually over a fairly long period, ∼50% of curcumin still remaining at 6 h of time. In contrast, intracellular soluble curcumin (sol-curcumin) reaches a maximum at 2 h followed by its complete elimination by 4 h. While sol-curcumin (GI(50) = 15.6 µM) is twice more toxic than nano-curcumin (GI(50) = 32.5 µM), nano-curcumin (IC(50)<1.75 µM) shows a higher anti-HIV activity compared to sol-curcumin (IC(50) = 5.1 µM). Studies in vitro showed that nano-curcumin prominently inhibited the HIV-1 induced expression of Topo II α, IL-1β and COX-2, an effect not seen with sol-curcumin. Nano-curcumin did not affect the expression of Topoisomerase II β and TNF α. This point out that nano-curcumin affects the HIV-1 induced inflammatory responses through pathways downstream or independent of TNF α. Furthermore, nano-curcumin completely blocks the synthesis of viral cDNA in the gag region suggesting that the nano-curcumin mediated inhibition of HIV-1 replication is targeted to viral cDNA synthesis.Curcumin-loaded apotransferrin nanoparticles are highly efficacious inhibitors of HIV-1 replication in vitro and promise a high potential for clinical usefulness