Anti-Inflammatory and antiosteoclastogenic activities of parthenolide on human periodontal ligament cellsIn vitro

Periodontitis is an inflammatory disease that causes osteolysis and tooth loss. It is known that the nuclear factor kappa B (NF-κB) signalling pathway plays a key role in the progression of inflammation and osteoclastogenesis in periodontitis. Parthenolide (PTL), a sesquiterpene lactone extracted from the shoots of Tanacetum parthenium, has been shown to possess anti-inflammatory properties in various diseases. In the study reported herein, we investigated the effects of PTL on the inflammatory and osteoclastogenic response of human periodontal ligament-derived cells (hPDLCs) and revealed the signalling pathways in this process. Our results showed that PTL decreased NF-κB activation, I-κB degradation, and ERK activation in hPDLCs. PTL significantly reduced the expression of inflammatory (IL-1β, IL-6, and TNF-α) and osteoclastogenic (RANKL, OPG, and M-CSF) genes in LPS-stimulated hPDLCs. In addition, PTL attenuated hPDLC-induced osteoclastogenic differentiation of macrophages (RAW264.7 cells), as well as reducing gene expression of osteoclast-related markers in RAW264.7 cells in an hPDLC-macrophage coculture model. Taken together, these results demonstrate the anti-inflammatory and antiosteoclastogenic activities of PTL in hPDLCs in vitro. These data offer fundamental evidence supporting the potential use of PTL in periodontitis treatment.

Competitive interactions of anti-carcinogens with serum albumin: A spectroscopic study of bendamustine and dexamethasone with the aid of chemometrics

Interactions between the anti-carcinogens, bendamustine (BDM) and dexamethasone (DXM), with bovine serum albumin (BSA) were investigated with the use of fluorescence and UV–vis spectroscopies under pseudo-physiological conditions (Tris–HCl buffer, pH 7.4). The static mechanism was responsible for the fluorescence quenching during the interactions; the binding formation constant of the BSA–BDM complex and the binding number were 5.14 × 105 L mol−1 and 1.0, respectively. Spectroscopic studies for the formation of BDM–BSA complex were interpreted with the use of multivariate curve resolution – alternating least squares (MCR–ALS), which supported the complex formation. The BSA samples treated with site markers (warfarin – site I and ibuprofen – site II) were reacted separately with BDM and DXM; while both anti-carcinogens bound to site I, the binding constants suggested that DXM formed a more stable complex. Relative concentration profiles and the fluorescence spectra associated with BDM, DXM and BSA, were recovered simultaneously from the full fluorescence excitation–emission data with the use of the parallel factor analysis (PARAFAC) method. The results confirmed that on addition of DXM to the BDM–BSA complex, the BDM was replaced and the DXM–BSA complex formed; free BDM was released. This finding may have consequences for the transport of these drugs during any anti-cancer treatment.

Analysis of passenger group behaviour and its impact on passenger flow using an agent-based model

Group interaction within crowds is a common phenomenon and has great influence on pedestrian behaviour. This paper investigates the impact of passenger group dynamics using an agent-based simulation method for the outbound passenger process at airports. Unlike most passenger-flow models that treat passengers as individual agents, the proposed model additionally incorporates their group dynamics as well. The simulation compares passenger behaviour at airport processes and discretionary services under different group formations. Results from experiments (both qualitative and quantitative) show that incorporating group attributes, in particular, the interactions with fellow travellers and wavers can have significant influence on passengers activity preference as well as the performance and utilisation of services in airport terminals. The model also provides a convenient way to investigate the effectiveness of airport space design and service allocations, which can contribute to positive passenger experiences. The model was created using AnyLogic software and its parameters were initialised using recent research data published in the literature.

Dynamic agent composition for large-scale agent-based models

PURPOSE: This paper describes dynamic agent composition, used to support the development of flexible and extensible large-scale agent-based models (ABMs). This approach was motivated by a need to extend and modify, with ease, an ABM with an underlying networked structure as more information becomes available. Flexibility was also sought after so that simulations are set up with ease, without the need to program. METHODS: The dynamic agent composition approach consists in having agents, whose implementation has been broken into atomic units, come together at runtime to form the complex system representation on which simulations are run. These components capture information at a fine level of detail and provide a vast range of combinations and options for a modeller to create ABMs. RESULTS: A description of the dynamic agent composition is given in this paper, as well as details about its implementation within MODAM (MODular Agent-based Model), a software framework which is applied to the planning of the electricity distribution network. Illustrations of the implementation of the dynamic agent composition are consequently given for that domain throughout the paper. It is however expected that this approach will be beneficial to other problem domains, especially those with a networked structure, such as water or gas networks. CONCLUSIONS: Dynamic agent composition has many advantages over the way agent-based models are traditionally built for the users, the developers, as well as for agent-based modelling as a scientific approach. Developers can extend the model without the need to access or modify previously written code; they can develop groups of entities independently and add them to those already defined to extend the model. Users can mix-and-match already implemented components to form large-scales ABMs, allowing them to quickly setup simulations and easily compare scenarios without the need to program. The dynamic agent composition provides a natural simulation space over which ABMs of networked structures are represented, facilitating their implementation; and verification and validation of models is facilitated by quickly setting up alternative simulations.

An agent-based approach to immune modelling

This study focuses on trying to understand why the range of experience with respect to HIV infection is so diverse, especially as regards to the latency period. The challenge is to determine what assumptions can be made about the nature of the experience of antigenic invasion and diversity that can be modelled, tested and argued plausibly. To investigate this, an agent-based approach is used to extract high-level behaviour which cannot be described analytically from the set of interaction rules at the cellular level. A prototype model encompasses local variation in baseline properties contributing to the individual disease experience and is included in a network which mimics the chain of lymphatic nodes. Dealing with massively multi-agent systems requires major computational efforts. However, parallelisation methods are a natural consequence and advantage of the multi-agent approach. These are implemented using the MPI library.

Considerations for a social and geographical framework for agent-based epidemics

Understanding the dynamics of disease spread is of crucial importance, in contexts such as estimating load on medical services to risk assessment and intervention policies against large-scale epidemic outbreaks. However, most of the information is available after the spread itself, and preemptive assessment is far from trivial. Here, we investigate the use of agent-based simulations to model such outbreaks in a stylised urban environment. For most diseases, infection of a new individual may occur from casual contact in crowds as well as from repeated interactions with social partners such as work colleagues or family members. Our model therefore accounts for these two phenomena.Presented in this paper is the initial framework for such a model, detailing implementation of geographical features and generation of social structures. Preliminary results are a promising step towards large-scale simulations and evaluation of potential intervention policies.

Model refinement through high-performance computing: an agent-based HIV example

Background Recent advances in Immunology highlighted the importance of local properties on the overall progression of HIV infection. In particular, the gastrointestinal tract is seen as a key area during early infection, and the massive cell depletion associated with it may influence subsequent disease progression. This motivated the development of a large-scale agent-based model. Results Lymph nodes are explicitly implemented, and considerations on parallel computing permit large simulations and the inclusion of local features. The results obtained show that GI tract inclusion in the model leads to an accelerated disease progression, during both the early stages and the long-term evolution, compared to a theoretical, uniform model. Conclusions These results confirm the potential of treatment policies currently under investigation, which focus on this region. They also highlight the potential of this modelling framework, incorporating both agent-based and network-based components, in the context of complex systems where scaling-up alone does not result in models providing additional insights.

Agent-based modelling of viral infection

The three phases of the macroscopic evolution of the HIV infection are well known, but it is still difficult to understand how the cellular-level interactions come together to create this characteristic pattern and, in particular, why there are such differences in individual responses. An 'agent-based' approach is chosen as a means of inferring high-level behaviour from a small set of interaction rules at the cellular level. Here the emphasis is on cell mobility and viral mutations.

A parallel approach to social network generation and agent-based epidemic simulation

Understanding the dynamics of disease spread is essential in contexts such as estimating load on medical services, as well as risk assessment and interven- tion policies against large-scale epidemic outbreaks. However, most of the information is available after the outbreak itself, and preemptive assessment is far from trivial. Here, we report on an agent-based model developed to investigate such epidemic events in a stylised urban environment. For most diseases, infection of a new individual may occur from casual contact in crowds as well as from repeated interactions with social partners such as work colleagues or family members. Our model therefore accounts for these two phenomena. Given the scale of the system, efficient parallel computing is required. In this presentation, we focus on aspects related to paralllelisation for large networks generation and massively multi-agent simulations.

Decentralised Communication in Autonomous Agent Swarms

Communication and information diffusion are typically difficult in situations where centralised structures may become unavailable. In this context, decentralised communication based on epidemic broadcast becomes essential. It can be seen as an opportunity-based flooding for message broadcasting within a swarm of autonomous agents, where each entity tries to share the information it possesses with its neighbours. As an example of applications for such a system, we present simulation results where agents have to coordinate to map an unknown area.

Where to after Drink Rite: An evaluation of opportunities for police and community promotion of an anti-drink driving message in the licensed venue setting. Report to the National Drug Strategy Law Enforcement Funding Committee

Estimating the prevalence of drink driving is a difficult task. Self‐reported drink driving indicates that drink driving is far more common than official statistics suggest. In order to promote a responsible attitude towards alcohol consumption and drink driving within the Queensland community, the Queensland Police Service, Queensland Health and Queensland Transport developed the ‘Drink Rite’ program (Queensland Police Service information sheet, 2009). However, the feasibility of the program is now in doubt as the National Health and Medical Research Council’s guidelines for alcohol consumption changed in 2009 to state “For healthy men and women, drinking no more than four standard drinks on a single occasion reduces the risk of alcohol‐related injury arising from that occasion” (NHMRC Publication, 2009, p. 51). As such, adhering to the NHMRC guidelines places restrictions on how the existing Drink Rite program can be operated (i.e. by reducing the number of standard drinks provided to participants from eight to four). It is arguable that a reduction in the number of alcoholic drinks provided to participants in the program will result in a large reduction in observed BAC readings. This, in turn, will lead to a potential loss of message content when discussing the variation in the effects of alcohol.

Agent-based modelling and simulation of airplane boarding processes

Passenger flow simulations are an important tool for designing and managing airports. This thesis examines the different boarding strategies for the Boeing 777 and Airbus 380 aircraft in order to investigate their current performance and to determine minimum boarding times. The most optimal strategies have been discovered and new strategies that are more efficient are proposed. The methods presented offer reduced aircraft boarding times which plays an important role for reducing the overall aircraft Turn Time for an airline.

Paralog-specific kinase inhibition of FGFR4: Adding to the arsenal of anti-FGFR agents

In this issue of Cancer Discovery, Hagel and colleagues report the design and the in vitro and in vivo activity of a novel, irreversible, paralog-specific kinase inhibitor of FGFR4, BLU9931. This compound binds covalently to a cysteine residue in the hinge region of FGFR4 but not in FGFR1-3. BLU9931 induces tumor shrinkage in hepatocellular carcinoma models that express a functioning ligand/receptor complex consisting of FGF19/FGFR4/KLB and adds to a growing list of anti-FGFR4 agents.

Anti-tumour effects of antibodies targeting the extracellular cysteine-rich region of the receptor tyrosine kinase EphB4

EphB4 is a membrane-bound receptor tyrosine kinase (RTK) commonly over-produced by many epithelial cancers but with low to no expression in most normal adult tissues. EphB4 over-production promotes ligand-independent signaling pathways that increase cancer cell viability and stimulate migration and invasion. Several studies have shown that normal ligand-dependent signaling is tumour suppressive and therefore novel therapeutics which block the tumour promoting ligand-independent signaling and/or stimulate tumour suppressive ligand-dependent signaling will find application in the treatment of cancer. An EphB4-specific polyclonal antibody, targeting a region of 200 amino acids in the extracellular portion of EphB4, showed potent in vitro anti-cancer effects measured by an increase in apoptosis and a decrease in anchorage independent growth. Peptide exclusion was used to identify the epitope targeted by this antibody within the cysteine-rich region of the EphB4 protein, a sequence defined as a potential ligand interacting interface. Addition of antibody to cancer cells resulted in phosphorylation and subsequent degradation of the EphB4 protein, suggesting a mechanism that is ligand mimetic and tumour suppressive. A monoclonal antibody which specifically targets this identified extracellular epitope of EphB4 significantly reduced breast cancer xenograft growth in vivo confirming that EphB4 is a useful target for ligand-mimicking antibody-based anti-cancer therapies.

Magnetic nanoparticles boosting the osmotic efficiency of a polymeric FO draw agent: Effect of polymer conformation

Poly sodium acrylate (PSA)-coated Magnetic Nanoparticles (PSA-MNPs) were synthesized as smart osmotic draw agent (SMDA) for water desalination by forward osmosis (FO) process. The PSA-coated MNPs demonstrated significantly higher osmotic pressure (~ 30 fold) as well as high FO water flux (~ 2–3 fold) when compared to their polymer (polyelectrolyte) counterpart, even at a very low concentration of ~ 0.13 wt.% in the draw solution. The PSA polymer chain conformation – coiled to extended – demonstrates a significant impact on the availability of the polymer hydrophilic groups in solution which is the driving force to attain higher osmotic pressure and water flux. When an optimum concentration of the polymer was anchored to a NP surface, the polymer chains assume an extended open conformation making the functional hydrophilic groups available to attract water molecules. This in turn boosts the osmotic pressure and FO water flux of the PSA-MNP draw agents. The low concentration of the PSA-MNP osmotic agent and the associated high water flux enhances the cost-effectiveness of our proposed SMDA system. In addition, easier magnetic separation and regeneration of the SMDA also improves its usability making it efficient, cost-effective and environment-friendly.