High-performance data mining with intelligent SSD

An intuitive way to process the big data efficiently is to reduce the volume of data transferred over the storage interface to a host system. This is the reason that the notion of intelligent SSD (iSSD) was proposed to give processing power to SSD. There is rich literature on iSSD, however, its real implementation has not been provided to the public yet. Most prior work aims to quantify the benefits of iSSD with analytical modeling. In this paper, we first develop on iSSD simulator and present the potential of iSSD in data mining through the iSSD simulator. Our iSSD simulator performs on top of the gem 5 simulator and fully simulates all the processes of data mining algorithms running in iSSD with cycle-level accuracy. Then, we further addresse how to exploit all the computing resources for efficient processing of data mining algorithms. These days, CPU, GPU, and SSD are recently equipped together in most computing environment. If SSD is replaced with iSSD later on, we have a new computing environment where the three computing resources collaborate one another to process big data quite effectively. For this, scheduling is required to decide which computing resource is going to run for which function at which time. In our heterogeneous scheduling, types of computing resources, memory sizes in computing resources, and inter-processor communication times including IO time in SSD are considered. Our scheduling results show that processing in the collaborative environment outperforms that in the traditional one by up to about 10 times.     

Quantification of Metabolic Rearrangements During Neural Stem Cells Differentiation into Astrocytes by Metabolic Flux Analysis

Proliferation and differentiation of neural stem cells (NSCs) have a crucial role to ensure neurogenesis and gliogenesis in the mammalian brain throughout life. As there is growing evidence for the significance of metabolism in regulating cell fate, knowledge on the metabolic programs in NSCs and how they evolve during differentiation into somatic cells may provide novel therapeutic approaches to address brain diseases. In this work, we applied a quantitative analysis to assess how the central carbon metabolism evolves upon differentiation of NSCs into astrocytes. Murine embryonic stem cell (mESC)-derived NSCs and astrocytes were incubated with labelled [1-¹³C]glucose and the label incorporation into intracellular metabolites was followed by GC-MS. The obtained ¹³C labelling patterns, together with uptake/secretion rates determined from supernatant analysis, were integrated into an isotopic non-stationary metabolic flux analysis (¹³C-MFA) model to estimate intracellular flux maps. Significant metabolic differences between NSCs and astrocytes were identified, with a general downregulation of central carbon metabolism during astrocytic differentiation. While glucose uptake was 1.7-fold higher in NSCs (on a per cell basis), a high lactate-secreting phenotype was common to both cell types. Furthermore, NSCs consumed glutamine from the medium; the highly active reductive carboxylation of alpha-ketoglutarate indicates that this was converted to citrate and used for biosynthetic purposes. In astrocytes, pyruvate entered the TCA cycle mostly through pyruvate carboxylase (81%). This pathway supported glutamine and citrate secretion, recapitulating well described metabolic features of these cells in vivo. Overall, this fluxomics study allowed us to quantify the metabolic rewiring accompanying astrocytic lineage specification from NSCs.     

A high-sensitivity method for detection and measurement of HMGB1 protein concentration by high-affinity binding to DNA hemicatenanes

Background

Protein HMGB1, an abundant nuclear non-histone protein that interacts with DNA and has an architectural function in chromatin, was strikingly shown some years ago to also possess an extracellular function as an alarmin and a mediator of inflammation. This extracellular function has since been actively studied, both from a fundamental point of view and in relation to the involvement of HMGB1 in inflammatory diseases. A prerequisite for such studies is the ability to detect HMGB1 in blood or other biological fluids and to accurately measure its concentration.

Methodology/Principal Findings

In addition to classical techniques (western blot, ELISA) that make use of specific anti-HMGB1 antibodies, we present here a new, extremely sensitive technique that is based on the fact that hemicatenated DNA loops (hcDNA) bind HMGB1 with extremely high affinity, higher than the affinity of specific antibodies, similar in that respect to DNA aptamers. DNA-protein complexes formed between HMGB1 and radiolabeled hcDNA are analyzed by electrophoresis on nondenaturing polyacrylamide gels using the band-shift assay method. In addition, using a simple and fast protocol to purify HMGB1 on the basis of its solubility in perchloric acid allowed us to increase the sensitivity by suppressing any nonspecific background. The technique can reliably detect HMGB1 at a concentration of 1 pg per microliter in complex fluids such as serum, and at much lower concentrations in less complex samples. It compares favorably with ELISA in terms of sensitivity and background, and is less prone to interference from masking proteins in serum.

Conclusion

The new technique, which illustrates the potential of DNA nanoobjects and aptamers to form high-affinity complexes with selected proteins, should provide a valuable tool to further investigate the extracellular functions of HMGB1 and its involvement in inflammatory pathologies.     

Design of an ex vivo culture system to investigate the effects of shear stress on cardiovascular tissue

Mechanical forces are known to affect the biomechanical properties of native and engineered cardiovascular tissue. In particular, shear stress that results from the relative motion of heart valve leaflets with respect to the blood flow is one important component of their mechanical environment in vivo. Although different types of bioreactors have been designed to subject cells to shear stress, devices to expose biological tissue are few. In an effort to address this issue, the aim of this study was to design an ex vivo tissue culture system to characterize the biological response of heart valve leaflets subjected to a well-defined steady or time-varying shear stress environment. The novel apparatus was designed based on a cone-and-plate viscometer. The device characteristics were defined to limit the secondary flow effects inherent to this particular geometry. The determination of the operating conditions producing the desired shear stress profile was streamlined using a computational fluid dynamic (CFD) model validated with laser Doppler velocimetry. The novel ex vivo tissue culture system was validated in terms of its capability to reproduce a desired cone rotation and to maintain sterile conditions. The CFD results demonstrated that a cone angle of 0.5 deg, a cone radius of 40 mm, and a gap of 0.2 mm between the cone apex and the plate could limit radial secondary flow effects. The novel cone-and-plate permits to expose nine tissue specimens to an identical shear stress waveform. The whole setup is capable of accommodating four cone-and-plate systems, thus concomitantly subjecting 36 tissue samples to desired shear stress condition. The innovative design enables the tissue specimens to be flush mounted in the plate in order to limit flow perturbations caused by the tissue thickness. The device is capable of producing shear stress rates of up to 650 dyn cm(-2) s(-1) (i.e., maximum shear stress rate experienced by the ventricular surface of an aortic valve leaflet) and was shown to maintain tissue under sterile conditions for 120 h. The novel ex vivo tissue culture system constitutes a valuable tool toward elucidating heart valve mechanobiology. Ultimately, this knowledge will permit the production of functional tissue engineered heart valves, and a better understanding of heart valve biology and disease progression.     

Longer lifespan in male mice treated with a weakly estrogenic agonist,an antioxidant,an α‐glucosidase inhibitor or a Nrf2‐inducer

The National Institute on Aging Interventions Testing Program (ITP) evaluates agents hypothesized to increase healthy lifespan in genetically heterogeneous mice. Each compound is tested in parallel at three sites, and all results are published. We report the effects of lifelong treatment of mice with four agents not previously tested: Protandim, fish oil, ursodeoxycholic acid (UDCA) and metformin – the latter with and without rapamycin, and two drugs previously examined: 17‐α‐estradiol and nordihydroguaiaretic acid (NDGA), at doses greater and less than used previously. 17‐α‐estradiol at a threefold higher dose robustly extended both median and maximal lifespan, but still only in males. The male‐specific extension of median lifespan by NDGA was replicated at the original dose, and using doses threefold lower and higher. The effects of NDGA were dose dependent and male specific but without an effect on maximal lifespan. Protandim, a mixture of botanical extracts that activate Nrf2, extended median lifespan in males only. Metformin alone, at a dose of 0.1% in the diet, did not significantly extend lifespan. Metformin (0.1%) combined with rapamycin (14 ppm) robustly extended lifespan, suggestive of an added benefit, based on historical comparison with earlier studies of rapamycin given alone. The α‐glucosidase inhibitor, acarbose, at a concentration previously tested (1000 ppm), significantly increased median longevity in males and 90th percentile lifespan in both sexes, even when treatment was started at 16 months. Neither fish oil nor UDCA extended lifespan. These results underscore the reproducibility of ITP longevity studies and illustrate the importance of identifying optimal doses in lifespan studies.     

Host plant distributions and climate interact to affect the predicted geographic distribution of a Neotropical termite

Species distribution models (SDMs) have been widely used in the scientific literature. The majority of SDMs use climate data or other abiotic variables to forecast the potential distribution of a species in geographic space. Biotic interactions can affect the predicted spatial distribution of a species in many ways across multiple spatial scales, and incorporating these predictors in an SDM is a current topic in the scientific literature. Constrictotermes cyphergaster is a widely distributed termite in the Neotropics. This termite species nests in plants and more frequently nests in some arboreal species. Thus, this species is an excellent model to evaluate the influence of biotic interactions in SDMs. We evaluate the influences of climate and the geographic distribution of host plants on the potential distribution of C. cyphergaster. Three correlative models (MaxEnt) were built to predict the geographic distribution of the termite: (1) climate data, (2) biotic data (i.e., the geographic distribution of host plants), and (3) climate and biotic data. The models that were generated indicate that the potential geographic distribution of C. cyphergaster is concentrated in the Cerrado and Caatinga regions. In addition, path analysis and multiple regression revealed the importance of the direct effects of biological interactions in the geographic distribution of the termite, while climate affected the distribution of the termite mainly through indirect effects by influencing the geographic distributions of host plants. The current study endorses the importance of including biological interactions in SDMs. We recommend using biotic predictors in SDM studies of insect species, mainly because insects have important environmental services and biotic interaction data can improve the macroecological studies of this group.     

Stability of the Transthyretin Molecule as a Key Factor in the Interaction with A-Beta Peptide - Relevance in Alzheimer's Disease

Transthyretin (TTR) protects against A-Beta toxicity by binding the peptide thus inhibiting its aggregation. Previous work showed different TTR mutations interact differently with A-Beta, with increasing affinities correlating with decreasing amyloidogenecity of the TTR mutant; this did not impact on the levels of inhibition of A-Beta aggregation, as assessed by transmission electron microscopy. Our work aimed at probing differences in binding to A-Beta by WT, T119M and L55P TTR using quantitative assays, and at identifying factors affecting this interaction. We addressed the impact of such factors in TTR ability to degrade A-Beta. Using a dot blot approach with the anti-oligomeric antibody A11, we showed that A-Beta formed oligomers transiently, indicating aggregation and fibril formation, whereas in the presence of WT and T119M TTR the oligomers persisted longer, indicative that these variants avoided further aggregation into fibrils. In contrast, L55PTTR was not able to inhibit oligomerization or to prevent evolution to aggregates and fibrils. Furthermore, apoptosis assessment showed WT and T119M TTR were able to protect against A-Beta toxicity. Because the amyloidogenic potential of TTR is inversely correlated with its stability, the use of drugs able to stabilize TTR tetrameric fold could result in increased TTR/A-Beta binding. Here we showed that iododiflunisal, 3-dinitrophenol, resveratrol, [2-(3,5-dichlorophenyl)amino] (DCPA) and [4-(3,5-difluorophenyl)] (DFPB) were able to increase TTR binding to A-Beta; however only DCPA and DFPB improved TTR proteolytic activity. Thyroxine, a TTR ligand, did not influence TTR/A-Beta interaction and A-Beta degradation by TTR, whereas RBP, another TTR ligand, not only obstructed the interaction but also inhibited TTR proteolytic activity. Our results showed differences between WT and T119M TTR, and L55PTTR mutant regarding their interaction with A-Beta and prompt the stability of TTR as a key factor in this interaction, which may be relevant in AD pathogenesis and for the design of therapeutic TTR-based therapies.     

Silencing of MicroRNA-21 Confers Radio-Sensitivity through Inhibition of the PI3K/AKT Pathway and Enhancing Autophagy in Malignant Glioma Cell Lines

Radiation is a core part of therapy for malignant glioma and is often provided following debulking surgery. However, resistance to radiation occurs in most patients, and the underlying molecular mechanisms of radio-resistance are not fully understood. Here, we demonstrated that microRNA 21 (miR-21), a well-known onco-microRNA in malignant glioma, is one of the major players in radio-resistance. Radio-resistance in different malignant glioma cell lines measured by cytotoxic cell survival assay was closely associated with miR-21 expression level. Blocking miR-21 with anti-miR-21 resulted in radio-sensitization of U373 and U87 cells, whereas overexpression of miR-21 lead to a decrease in radio-sensitivity of LN18 and LN428 cells. Anti-miR-21 sustained γ-H2AX DNA foci formation, which is an indicator of double-strand DNA damage, up to 24 hours and suppressed phospho-Akt (ser473) expression after exposure to γ-irradiation. In a cell cycle analysis, a significant increase in the G₂/M phase transition by anti-miR-21 was observed at 48 hours after irradiation. Interestingly, our results showed that anti-miR-21 increased factors associated with autophagosome formation and autophagy activity, which was measured by acid vesicular organelles, LC3 protein expression, and the percentage of GFP-LC3 positive cells. Furthermore, augmented autophagy by anti-miR-21 resulted in an increase in the apoptotic population after irradiation. Our results show that miR-21 is a pivotal molecule for circumventing radiation-induced cell death in malignant glioma cells through the regulation of autophagy and provide a novel phenomenon for the acquisition of radio-resistance.     

QTL-seq identifies an early flowering QTL located near Flowering Locus T in cucumber

Key message

Next-generation sequencing enabled a fast discovery of a major QTL controlling early flowering in cucumber, corresponding to the FT gene conditioning flowering time in Arabidopsis.

Abstract

Next-generation sequencing technologies are making it faster and more efficient to establish the association of agronomic traits with molecular markers or candidate genes, which is the requirement for marker-assisted selection in molecular breeding. Early flowering is an important agronomic trait in cucumber (Cucumis sativus L.), but the underlying genetic mechanism is unknown. In this study, we identified a candidate gene for early flowering QTL, Ef1.1 through QTL-seq. Segregation analysis in F₂ and BC₁ populations derived from a cross between two inbred lines “Muromskij” (early flowering) and “9930” (late flowering) suggested quantitative nature of flowering time in cucumber. Genome-wide comparison of SNP profiles between the early and late-flowering bulks constructed from F₂ plants identified a major QTL, designated Ef1.1 on cucumber chromosome 1 for early flowering in Muromskij, which was confirmed by microsatellite marker-based classical QTL mapping in the F₂ population. Joint QTL-seq and traditional QTL analysis delimited Ef1.1 to an 890 kb genomic region. A cucumber gene, Csa1G651710, was identified in this region, which is a homolog of the FLOWERING LOCUS T (FT), the main flowering switch gene in Arabidopsis. Quantitative RT-PCR study of the expression level of Csa1G651710 revealed significantly higher expression in early flowering genotypes. Data presented here provide support for Csa1G651710 as a possible candidate gene for early flowering in the cucumber line Muromskij.