Neural stem cells (NSCs) derived from human induced pluripotent stem cells were used to investigate effects of exposure to the food contaminant acrylamide (AA) and its main metabolite glycidamide (GA) on key neuro-developmental processes. Diet is an important source of human AA exposure for pregnant women, and AA is known to pass the placenta and the newborn may also be exposed through breast feeding after birth. The NSCs were exposed to AA and GA (1 x10(-8) - 3 x10(-3) M) under 7 days of proliferation and up to 28 days of differentiation towards a mixed culture of neurons and astrocytes. Effects on cell viability was measured using Alamar B1ueTM cell viability assay, alterations in gene expression were assessed using real time PCR and RNA sequencing, and protein levels were quantified using immunocytochemistry and high content imaging. Effects of AA and GA on neumdevelopmental processes were evaluated using endpoints linked to common key events identified in the existing developmental neumtoxicity adverse outcome pathways (AOPs). Our results suggest that AA and GA at low concentrations (1 x10(-7) - 1 x10(-8) M) increased cell viability and markers of proliferation both in proliferating NSCs (7 days) and in maturing neurons after 14-28 days of differentiation. IC50 for cell death of AA and GA was 5.2 x 10(-3) M and 5.8 x 10(-4) M, respectively, showing about ten times higher potency for GA. Increased expression of brain derived neurotrophic factor (BDNF) concomitant with decreased synaptogenesis were observed for GA exposure (10(-7) M) only at later differentiation stages, and an increased number of astrocytes (up to 3-fold) at 14 and 21 days of differentiation. Also, AA exposure gave tendency towards decreased differentiation (increased percent Nestin positive cells). After 28 days, neurite branch points and number of neurites per neuron measured by microtubule-associated protein 2 (Map2) staining decreased, while the same neurite features measured by beta III-Tubulin increased, indicating perturbation of neuronal differentiation and maturation.

Decades of research on distributed file systems and storage systems exists. New researchers and engineers have a lot of literature to study, but only a comparatively small number of high-level design choices are available when creating a distributed file system. And within each aspect of the system, typically several common approaches are used. So, rather than surveying distributed file systems, this article presents a survey of important design decisions and, within those decisions, the most commonly used options. It also presents a qualitative exploration of their tradeoffs. We include several relatively recent designs and their variations that illustrate other tradeoff choices in the design space, despite being underexplored. In doing so, we provide a primer on distributed file systems, and we also show areas that are overexplored and underexplored, in the hopes of inspiring new research.

The biological response of organisms exposed to nanoparticles is often studiedin vitrousing adherent monolayers of cultured cells. In order to derive accurate concentration–response relationships, it is important to determine the local concentration of nanoparticles to which the cells are actually exposed rather than the nominal concentration of nanoparticles in the cell culture medium. In this study, the sedimentation–diffusion process of different sized and charged gold nanoparticles has been investigatedin vitroby evaluating their settling dynamics and by developing a theoretical model to predict the concentration depth profile of nanoparticles in solution over time. Experiments were carried out in water and in cell culture media at a range of controlled temperatures. The optical phenomenon of caustics was exploited to track nanoparticles in real time in a conventional optical microscope without any requirement for fluorescent labelling that potentially affects the dynamics of the nanoparticles. The results obtained demonstrate that size, temperature and the stability of the nanoparticles play a pivotal role in regulating the settling dynamics of nanoparticles. For gold nanoparticles larger than 60 nm in diameter, the initial nominal concentration did not accurately represent the concentration of nanoparticles local to the cells. Finally, the theoretical model proposed accurately described the settling dynamics of the nanoparticles and thus represents a promising tool to support the design ofin vitroexperiments and the study of concentration–response relationships.

Chemical safety assessment requires information on both chronic and acute effects of toxicants. Traditionally, such information has been provided by a set of animal studies conducted over different durations, ranging from a single dose with observation of effects over a few days, to repeat daily dosing and observations made over many months. With the advent of modern mechanistic approaches to toxicology, the role of in vitro studies within alternative approaches has never been more prominent. Typical in vitro experiments are conducted over short durations with measurements of response at a single time point, with a focus on providing effect and concentration-response information as input to hazard and risk assessment. This limits the usefulness of such data since potential chronic effects that cumulate over time are not usually considered. To address this, an experimental design is presented to characterise the toxicodynamics of a response not only in terms of concentration, but also as a function of time. Generation of concentration-time-effect responses allows both the extrapolation of points of departure from an acute to chronic exposure, and the determination of a chronicity index that provides a quantitative measure of a chemical's potential to cause cumulative effects over time. In addition, the approach provides a means to characterise the dynamics of key event relationships for the development of quantitative adverse outcome pathways.

Background The biological response of organisms exposed to nanoparticles is often studied in vitro using adherent monolayers of cultured cells. In order to derive accurate concentration-response relationships, it is important to determine the local concentration of nanoparticles to which the cells are actually exposed rather than the nominal concentration of nanoparticles in the cell-culture medium. In this study, we investigated the sedimentation–diffusion process of different sized and charged gold nanoparticles in vitro by evaluating their settling dynamics and by developing a theoretical model to predict the concentration depth-profile of nanoparticles in solution over time. Results Experiments were carried out in water and in cell-culture media at a range of controlled temperatures. The optical phenomenon of caustics was exploited to track nanoparticles in real-time in a conventional optical microscope without any requirement for fluorescent labelling that potentially affects the dynamics of the nanoparticles. The results obtained demonstrate that size, temperature, and the stability of the nanoparticles play a pivotal role in regulating settling dynamics of nanoparticles. For gold nanoparticles larger than 60 nm in diameter, the initial nominal concentration did not accurately represent the concentration of nanoparticles local to the cells. Conclusion Nanoparticles dynamics in solution regulate the amount of material at the cellular level and must be taken into account when evaluating the biological response of organisms. the theoretical model proposed in this study accurately described the settling dynamics of the nanoparticles and thus represents a promising tool to support the design of in vitro experiments and the study of concentration-response relationships.

Van der Waals and electrostatic interactions are the dominant forces acting at the nanoscale and they have been reported to directly influence a range of phenomena including surface adhesion, friction, and colloid stability but their contribution on nanoparticle diffusion dynamics is still not clear. In this study we evaluated experimentally the changes in the diffusion coefficient of nanoparticles as a result of varying the magnitude of Van der Waals and electrostatic forces. We controlled the magnitude of these forces by varying the ionic strength of a salt solution, which has been shown to be a parameter that directly controls the forces, and found by tracking single nanoparticles dispersed in solutions with different salt molarity that the diffusion of nanoparticles increases with the magnitude of the electrostatic forces and Van der Waals forces. Our results demonstrate that these two concurrently dynamic forces play a pivotal role in driving the diffusion process and must be taken into account when considering nanoparticle behaviour.

The large amount of existing nanomaterials demands rapid and reliable methods for testing their potential toxicological effect on human health, preferably by means of relevant in vitro techniques in order to reduce testing on animals. Combining high throughput workflows with automated high content imaging techniques allows deriving much more information from cell-based assays than the typical readouts (i.e. one measurement per well) with optical plate-readers. We present here a dataset including data based on a maximum of 14 different read outs (including viable cell count, cell membrane permeability, apoptotic cell death, mitochondrial membrane potential and steatosis) of the human hepatoma HepaRG cell line treated with a large set of nanomaterials, coatings and supernatants at different concentrations. The database, given its size, can be utilized in the development of in silico hazard assessment and prediction tools or can be combined with toxicity results from other in vitro test systems.

The rapid growth of customer applications and datasets has led to demand for storage that can scale with the needs of modern workloads. We have developed FlexGroup volumes to meet this need. FlexGroups combine local WAFL® file systems in a distributed storage cluster to provide a single namespace that seamlessly scales across the aggregate resources of the cluster (CPU, storage, etc.) while preserving the features and robustness of the WAFL file system. In this paper we present the FlexGroup design, which includes a new remote access layer that supports distributed transactions and the novel heuristics used to balance load and capacity across a storage cluster. We evaluate FlexGroup performance and efficacy through lab tests and field data from over 1,000 customer FlexGroups.

Manufactured nanomaterials (MNMs) selected from a library of over 120 different MNMs with varied compositions, sizes, and surface coatings were tested by four different laboratories for toxicity by high-throughput/-content (HT/C) techniques. The selected particles comprise 14 MNMs composed of CeO2, Ag, TiO2, ZnO and SiO2 with different coatings and surface characteristics at varying concentrations. The MNMs were tested in different mammalian cell lines at concentrations between 0.5 and 250 µg/mL to link physical–chemical properties to multiple adverse effects. The cell lines are derived from relevant organs such as liver, lung, colon and the immune system. Endpoints such as viable cell count, cell membrane permeability, apoptotic cell death, mitochondrial membrane potential, lysosomal acidification and steatosis have been studied. Soluble MNMs, Ag and ZnO, were toxic in all cell types. TiO2 and SiO2 MNMs also triggered toxicity in some, but not all, cell types and the cell type-specific effects were influenced by the specific coating and surface modification. CeO2 MNMs were nearly ineffective in our test systems. Differentiated liver cells appear to be most sensitive to MNMs, Whereas most of the investigated MNMs showed no acute toxicity, it became clear that some show adverse effects dependent on the assay and cell line. Hence, it is advised that future nanosafety studies utilise a multi-parametric approach such as HT/C screening to avoid missing signs of toxicity. Furthermore, some of the cell type-specific effects should be followed up in more detail and might also provide an incentive to address potential adverse effects in vivo in the relevant organ.

An optical technique for tracking single particles has been used to evaluate the particle diameter at which diffusion transitions from molecular behaviour described by the fractional Stokes–Einstein relationship to particle behaviour described by the classical Stokes–Einstein relationship. The results confirm a prior prediction from molecular dynamic simulations that there is a particle size at which transition occurs and show it is inversely dependent on concentration and viscosity but independent of particle density. For concentrations in the range 5 × 10−3 to 5 × 10−6 mg ml−1 and viscosities from 0.8 to 150 mPa s, the transition was found to occur in the diameter range 150–300 nm.

In order to replace the use of animals in toxicity testing, there is a need to predict human in vivo toxic doses from concentrations that cause adverse effects in in vitro test systems. The virtual cell based assay (VCBA) has been developed to simulate intracellular concentrations as a function of time, and can be used to interpret in vitro concentration-response curves. In this study we refine and extend the VCBA model by including additional target-organ cell models and by simulating the fate and effects of chemicals at the organelle level. In particular, we describe the extension of the original VCBA to simulate chemical fate in liver (HepaRG) cells and cardiomyocytes (ICell cardiomyocytes), and we explore the effects of chemicals at the mitochondrial level. This includes a comparison of: a) in vitro results on cell viability and mitochondrial membrane potential (mmp) from two cell models (HepaRG cells and ICell cardiomyocytes); and b) VCBA simulations, including the cell and mitochondrial compartment, simulating the mmp for both cell types. This proof of concept study illustrates how the relationship between intra cellular, intra mitochondrial concentration, mmp and cell toxicity can be obtained by using the VCBA.

The present study assesses acute and chronic toxicity of doxorubicin in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), with the aim to obtain in vitro biomarkers that can be used as readouts to predict in vivo cardiotoxicity. Possible acute toxicity was investigated by assessing effects on the beating rate and the field potential duration (FPD) of doxorubicin-exposed cardiomyocytes by measuring electrical activity using multi-electrode array (MEA) analyses. No effects on the beating rate and FPD were found at concentrations up to 6μM, whereas at 12μM no electrical activity was recorded, indicating that the cardiomyocytes stopped beating. Acute and chronic effects of doxorubicin on mitochondria, which have been reported to be affected in doxorubicin-induced cardiotoxicity, were assessed using high content imaging techniques. To this end hiPSC-CMs were exposed to 150 or 300nM doxorubicin using both single dosing (3h and 2days) and repetitive dosing (3 times, of 2days each), including washout studies to assess delayed effects (assessment at day 14) and effects on cell number, mitochondrial density, mitochondrial membrane potential, mitochondrial superoxide levels and mitochondrial calcium levels were assessed. No effects of doxorubicin were found on mitochondrial density and mitochondrial superoxide levels, whereas doxorubicin reduced cell survival and slightly altered mitochondrial membrane potential and mitochondrial calcium levels, which was most profound in the washout studies. Altogether, the results of the present study show that concentrations of doxorubicin in the micromolar range were required to affect electrical activity of hiPSC-CMs, whereas nanomolar concentrations already affected cell viability and caused mitochondrial disturbances. Integration of these data with other in vitro data may enable the selection of a series of in vitro biomarkers that can be used as readouts to screen chemicals for possible cardiotoxicity.

Shingled magnetic recording (SMR) increases the capacity of magnetic hard drives, but it requires that each zone of a disk be written sequentially and erased in bulk. This makes SMR a good fit for workloads dominated by large data objects with limited churn. To explore this possibility, we have developed SMORE, an object storage system designed to reliably and efficiently store large, seldom-changing data objects on an array of host-managed or host-aware SMR disks. SMORE uses a log-structured approach to accommodate the constraint that all writes to an SMR drive must be sequential within large shingled zones. It stripes data across zones on separate disks, using erasure coding to protect against drive failure. A separate garbage collection thread reclaims space by migrating live data out of the emptiest zones so that they can be trimmed and reused. An index stored on flash and backed up to the SMR drives maps object identifiers to on-disk locations. SMORE interleaves log records with object data within SMR zones to enable index recovery after a system crash (or failure of the flash device) without any additional logging mechanism. SMORE achieves full disk bandwidth when ingesting data---with a variety of object sizes---and when reading large objects. Read performance declines for smaller object sizes where inter- object seek time dominates. With a worst-case pattern of random deletions, SMORE has a write amplification (not counting RAID parity) of less than 2.0 at 80% occupancy. By taking an index snapshot every two hours, SMORE recovers from crashes in less than a minute. More frequent snapshots allow faster recovery.

We present LLAMA, a graph storage and analysis system that supports mutability and out-of-memory execution. LLAMA performs comparably to immutable main-memory analysis systems for graphs that fit in memory and significantly outperforms existing out-of-memory analysis systems for graphs that exceed main memory. LLAMA bases its implementation on the compressed sparse row (CSR) representation, which is a read-only representation commonly used for graph analytics. We augment this representation to support mutability and persistence using a novel implementation of multi-versioned array snapshots, making it ideal for applications that receive a steady stream of new data, but need to perform whole-graph analysis on consistent views of the data. We compare LLAMA to state-of-the-art systems on representative graph analysis workloads, showing that LLAMA scales well both out-of-memory and across parallel cores. Our evaluation shows that LLAMA's mutability introduces modest overheads of 3-18% relative to immutable CSR for in-memory execution and that it outperforms state-of-the-art out-of-memory systems in most cases, with a best case improvement of 5x on breadth-first-search.

Having effective visualizations of filesystem provenance data is valuable for understanding its complex hierarchical structure. The most common visual representation of provenance data is the node-link diagram. While effective for understanding local activity, the node-link diagram fails to offer a high-level summary of activity and inter-relationships within the data. We present a new tool, InProv, which displays filesystem provenance with an interactive radial-based tree layout. The tool also utilizes a new time-based hierarchical node grouping method for filesystem provenance data we developed to match the user's mental model and make data exploration more intuitive. We compared InProv to a conventional node-link based tool, Orbiter, in a quantitative evaluation with real users of filesystem provenance data including provenance data experts, IT professionals, and computational scientists. We also compared in the evaluation our new node grouping method to a conventional method. The results demonstrate that InProv results in higher accuracy in identifying system activity than Orbiter with large complex data sets. The results also show that our new time-based hierarchical node grouping method improves performance in both tools, and participants found both tools significantly easier to use with the new time-based node grouping method. Subjective measures show that participants found InProv to require less mental activity, less physical activity, less work, and is less stressful to use. Our study also reveals one of the first cases of gender differences in visualization; both genders had comparable performance with InProv, but women had a significantly lower average accuracy (56%) compared to men (70%) with Orbiter.

Systems that capture and store data provenance, the record of how an object has arrived at its current state, accumulate historical metadata over time, forming a large graph. Local clustering in these graphs, in which we start with a seed vertex and grow a cluster around it, is of paramount importance because it supports critical provenance applications such as identifying semantically meaningful tasks in an object's history. However, generic graph clustering algorithms are not effective at these tasks. We identify three key properties of provenance graphs and exploit them to justify two new centrality metrics we developed for use in performing local clustering on provenance graphs.

The explosion of graph data in social and biological networks, recommendation systems, provenance databases, etc. makes graph storage and processing of paramount importance. We present a performance introspection framework for graph databases, PIG, which provides both a toolset and methodology for understanding graph database performance. PIG consists of a hierarchical collection of benchmarks that compose to produce performance models; the models provide a way to illuminate the strengths and weaknesses of a particular implementation. The suite has three layers of benchmarks: primitive operations, composite access patterns, and graph algorithms. While the framework could be used to compare different graph database systems, its primary goal is to help explain the observed performance of a particular system. Such introspection allows one to evaluate the degree to which systems exploit their knowledge of graph access patterns. We present both the PIG methodology and infrastructure and then demonstrate its efficacy by analyzing the popular Neo4j and DEX graph databases.

Most provenance capture takes place inside particular tools - a workflow engine, a database, an operating system, or an application. However, most users have an existing toolset - a collection of different tools that work well for their needs and with which they are comfortable. Currently, such users have limited ability to collect provenance without disrupting their work and changing environments, which most users are hesitant to do. Even users who are willing to adopt new tools, may realize limited benefit from provenance in those tools if they do not integrate with their entire environment, which may include multiple languages and frameworks. We present the Core Provenance Library (CPL), a portable, multi-lingual library that application programmers can easily incorporate into a variety of tools to collect and integrate provenance. Although the manual instrumentation adds extra work for application programmers, we show that in most cases, the work is minimal, and the resulting system solves several problems that plague more constrained provenance collection systems.