Characteristics of electroosmotic flow and migration of neutral solutes under stepwise gradient elution of capillary electrochromatography

A theoretical study on the velocity of electroosmotic flow (EOF) and the retention times of neutral solutes under multiple-step gradient of capillary electrochromatography (CEC) was carried out, focusing on that with three kinds of mobile phases. Through the model computations, the detaining time of the second kind of mobile phase in the column was proved to play an important role in affecting EOF. The variation speed of EOF was shown to be determined by the differences among dead times in different steps. In addition, the prediction of the retention times of 13 aromatic compounds under gradient mode was performed with the deduced equations. A relative error below 3.3% between the calculated and experimental values was obtained, which demonstrated the rationality of the theoretical deduction. Our study could not only improve the comprehension of stepwise gradient elution, but also be of significance for the further optimization of separation conditions in the analysis of complex samples.

Migration of neutral solutes by double stepwise gradient elution in capillary electrochromatography

Characteristics of electroosmotic flow (EOF) and the migration of neutral solutes under double stepwise gradient elution in capillary electrochromatography were studied systematically. EOF velocity proved to be the function of operation time changing with the introduction of the second mobile phase. Accordingly, the retention of components also changed. The migration of neutral solutes was studied under the following three situations; A, components eluted when the column was filled only with the first kind of mobile phase; B, solutes eluted still in the first kind of mobile phase while at that time two kinds of mobile phase coexisted in the column and C, samples eluted in the second kind of mobile phase. Equations to describe the retention times of components under these three kinds of conditions were deduced and applied to predict the retention times of 12 aromatic compounds. Relative errors between experimental and calculated values were below 5.0%, which proved the reliability of the equations. In addition, parameters that might affect the retention time of solutes, such as the transferring time of mobile phase vials, the capacity factors of components and EOF velocities two steps were studied systematically (C) 2001 Elsevier Science B.V. All rights reserved.

Migration of breast cancer cells : understanding the roles of volume exclusion and cell-to-cell adhesion

We study MCF-7 breast cancer cell movement in a transwell apparatus. Various experimental conditions lead to a variety of monotone and nonmonotone responses which are difficult to interpret. We anticipate that the experimental results could be caused by cell-to-cell adhesion or volume exclusion. Without any modeling, it is impossible to understand the relative roles played by these two mechanisms. A lattice-based exclusion process random-walk model incorporating agent-to-agent adhesion is applied to the experimental system. Our combined experimental and modeling approach shows that a low value of cell-to-cell adhesion strength provides the best explanation of the experimental data suggesting that volume exclusion plays a more important role than cell-to-cell adhesion. This combined experimental and modeling study gives insight into the cell-level details and design of transwell assays.

Fractional models for the migration of biological cells in complex spatial domains

Travelling wave phenomena are observed in many biological applications. Mathematical theory of standard reaction-diffusion problems shows that simple partial differential equations exhibit travelling wave solutions with constant wavespeed and such models are used to describe, for example, waves of chemical concentrations, electrical signals, cell migration, waves of epidemics and population dynamics. However, as in the study of cell motion in complex spatial geometries, experimental data are often not consistent with constant wavespeed. Non-local spatial models have successfully been used to model anomalous diffusion and spatial heterogeneity in different physical contexts. In this paper, we develop a fractional model based on the Fisher-Kolmogoroff equation and analyse it for its wavespeed properties, attempting to relate the numerical results obtained from our simulations to experimental data describing enteric neural crest-derived cells migrating along the intact gut of mouse embryos. The model proposed essentially combines fractional and standard diffusion in different regions of the spatial domain and qualitatively reproduces the behaviour of neural crest-derived cells observed in the caecum and the hindgut of mouse embryos during in vivo experiments.

Performance-driven live migration of multiple virtual machines in datacenters

Live migration of multiple Virtual Machines (VMs) has become an indispensible management activity in datacenters for application performance, load balancing, server consolidation. While state-of-the-art live VM migration strategies focus on the improvement of the migration performance of a single VM, little attention has been given to the case of multiple VMs migration. Moreover, existing works on live VM migration ignore the inter-VM dependencies, and underlying network topology and its bandwidth. Different sequences of migration and different allocations of bandwidth result in different total migration times and total migration downtimes. This paper concentrates on developing a multiple VMs migration scheduling algorithm such that the performance of migration is maximized. We evaluate our proposed algorithm through simulation. The simulation results show that our proposed algorithm can migrate multiple VMs on any datacenter with minimum total migration time and total migration downtime.

Elevated YKL40 is associated with advanced prostate cancer (PCa) and positively regulates invasion and migration of PCa cells

Chitinase 3-like 1 (CHI3L1 or YKL40) is a secreted glycoprotein highly expressed in tumours from patients with advanced stage cancers, including prostate cancer (PCa). The exact function of YKL40 is poorly understood, but it has been shown to play an important role in promoting tumour angiogenesis and metastasis. The therapeutic value and biological function of YKL40 are unknown in PCa. The objective of this study was to examine the expression and function of YKL40 in PCa. Gene expression analysis demonstrated that YKL40 was highly expressed in metastatic PCa cells when compared with less invasive and normal prostate epithelial cell lines. In addition, the expression was primarily limited to androgen receptor-positive cell lines. Evaluation of YKL40 tissue expression in PCa patients showed a progressive increase in patients with aggressive disease when compared with those with less aggressive cancers and normal controls. Treatment of LNCaP and C4-2B cells with androgens increased YKL40 expression, whereas treatment with an anti-androgen agent decreased the gene expression of YKL40 in androgen-sensitive LNCaP cells. Furthermore, knockdown of YKL40 significantly decreased invasion and migration of PCa cells, whereas overexpression rendered them more invasive and migratory, which was commensurate with an enhancement in the anchorage-independent growth of cells. To our knowledge, this study characterises the role of YKL40 for the first time in PCa. Together, these results suggest that YKL40 plays an important role in PCa progression and thus inhibition of YKL40 may be a potential therapeutic strategy for the treatment of PCa.

A random key genetic algorithm for live migration of multiple virtual machines in data centers

Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.

Leaving family behind: Understanding the irregular migration of unaccompanied asylum-seeking minors - A qualitative study

This qualitative study investigated the drivers and determinants of irregular maritime migration among 17 protection visa holders who arrived in Australia as unaccompanied asylum-seeking minors. Semi-structured interviews were also conducted with eight non-government service providers working with unaccompanied minors in the Greater Brisbane area.

A Strength Pareto Evolutionary Algorithm for live migration of multiple interdependent virtual machines in data centers

Although live VM migration has been intensively studied, the problem of live migration of multiple interdependent VMs has hardly been investigated. The most important problem in the live migration of multiple interdependent VMs is how to schedule VM migrations as the schedule will directly affect the total migration time and the total downtime of those VMs. Aiming at minimizing both the total migration time and the total downtime simultaneously, this paper presents a Strength Pareto Evolutionary Algorithm 2 (SPEA2) for the multi-VM migration scheduling problem. The SPEA2 has been evaluated by experiments, and the experimental results show that the SPEA2 can generate a set of VM migration schedules with a shorter total migration time and a shorter total downtime than an existing genetic algorithm, namely Random Key Genetic Algorithm (RKGA). This paper also studies the scalability of the SPEA2.

Migration of feral pigs (Sus scrofa) in rainforests of north Queensland: fact or fiction?

The Wet Tropics bioregion of north Queensland has been identified as an area of global significance. The world-heritage-listed rainforests have been invaded by feral pigs (Sus scrofa) that are perceived to cause substantial environmental damage. A community perception exists of an annual altitudinal migration of the feral-pig population. The present study describes the movements of 29 feral pigs in relation to altitudinal migration (highland, transitional and lowland areas). Feral pigs were sedentary and stayed within their home range throughout a 4-year study period. No altitudinal migration was detected; pigs moved no more than a mean distance of 1.0 km from the centre of their calculated home ranges. There was no significant difference between the mean (+/- 95% confidence interval) aggregate home ranges for males (8.7 +/- 4.3 km², n = 15) and females (7.2 +/- 1.8 km², n = 14). No difference in home range was detected among the three altitudinal areas: 7.2 +/- 2.4 km² for highland, 6.2 +/- 3.9 km² for transitional and 9.9 +/- 5.3 km² for lowland areas. The aggregate mean home range for all pigs in the present study was 8.0 +/- 2.4 km². The study also assessed the influence seasons had on the home range of eight feral pigs on the rainforest boundary; home ranges did not significantly vary in size between the tropical wet and dry seasons, although the mean home range in the dry season (7.7 +/- 6.9 km²) was more than twice the home range in the wet season (2.9 +/- 0.8 km²). Heavier pigs tended to have larger home ranges. The results of the present study suggest that feral pigs are sedentary throughout the year so broad-scale control techniques need to be applied over sufficient areas to encompass individual home ranges. Control strategies need a coordinated approach if a long-term reduction in the pig population is to be achieved.

Migration of green turtles (Chelonia mydas) from Australasian feeding grounds inferred from genetic analyses

Coastal seagrass habitats in tropical and subtropical regions support aggregations of resident green turtles (Chelonia mydas) from several genetically distinct breeding populations. Migration of individuals to their respective dispersed breeding sites provides a complex pattern of migratory connectivity among nesting and feeding habitats of this species. An understanding of this pattern is important in regions where the persistence of populations is under threat from anthropogenic impacts. The present study uses mitochondrial DNA and mixed-stock analyses to assess the connectivity among seven feeding grounds across the north Australian coast and adjacent areas and 17 genetically distinct breeding populations from the Indo-Pacific region. It was hypothesised that large and geographically proximate breeding populations would dominate at nearby feeding grounds. As expected, each sampled feeding area appears to support multiple breeding populations, with two aggregations dominated by a local breeding population. Geographic distance between breeding and feeding habitat strongly influenced whether a breeding population contributed to a feeding ground (wi = 0.654); however, neither distance nor size of a breeding population was a good predictor of the extent of their contribution. The differential proportional contributions suggest the impact of anthropogenic mortality at feeding grounds should be assessed on a case-by-case basis.