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The investigation of an immune system has long been and will continue to be one of dominant themes in both ecology and biology due to its importance. In this paper, we consider Marchuk's model of an immune system where this model is governed by a system of three differential equations with time. This model has two equilibrium states which are healthy state and chronic state. It is healthy state when the antigen reproduction is small while chronic state is when antigen reproduction rate is large. The objectives of this paper are to analyse the stability of this model, to summarize this stability using bifurcation diagram and to discuss interaction between the healthy and chronic states at stationary solution. The methods involved are stability theory and bifurcation theory. Our results show that healthy states are saddle and only one chronic state is asymptotically stable for a region of parameter considered. For the bifurcation's case, as we increase the value of a parameter in this model, the chronic state shows that there are increment in the number of antigen, plasma cell and the antibody production. [ABSTRACT FROM AUTHOR]

Biosensors research combines molecular-level with system-level challenges. The molecular challenge is to rapidly and reliably detect very low concentrations of molecules in a complex biological sample. The system challenge is to find principles that enable the integration of a series of process steps in a disposable cartridge. This paper describes how both aspects can be served by the actuation and detection of magnetic particles, illustrated by the example of immunoassay biosensing. [ABSTRACT FROM AUTHOR]

Prostate cancer is one of the most common cancers in men; it grows slowly and it could be diagnosed in an early stage by dosing the Prostate Specific Antigen (PSA). However, a relapse after the primary therapy could arise in 25-30% of cases and different growth characteristics of the new tumor are observed. In order to get a better understanding of the phenomenon, a two parameters growth model is considered. To estimate the parameters values identifying the disease risk level a novel approach, based on combining Particle Swarm Optimization (PSO) with meshfree interpolation methods, is proposed. [ABSTRACT FROM AUTHOR]

Early recognition of Bacillus cereus group species is important since they can cause food-borne illnesses and deadly diseases in humans. Glycoconjugates (GCs) are carbohydrates covalently linked to non-sugar moieties including lipids, proteins or other entities. GCs are involved in recognition and signaling processes intrinsic to biochemical functions in cells. They also stimulate cell-cell adhesion and subsequent recognition and activation of receptors. We have demonstrated that GCs are involved in Bacillus cereus spore recognition. In the present study, we have investigated whether GCs possess the ability to bind and recognize B. cereus spores and Bacillus anthracis recombinant single toxins (sTX) and complex toxins (cTX). The affinity of GCs to spores + sTX and spores + cTX toxins was studied in the binding essay. Our results demonstrated that GC9 and GC10 were able to selectively bind to B. cereus spores and B. anthracis toxins. Different binding affinities for GCs were found toward Bacillus cereus spores + sTX and spores + cTX. Dilution of GCs does not impede the recognition and binding. Developed method provides a tool for simultaneous recognition and targeting of spores, bacteria toxins, and/or other entities. [ABSTRACT FROM AUTHOR]

In dendritic cells (DCs)-based cancer immunotherapy, it is important to present the epitope peptide derived from tumor associated antigens (TAAs) on MHC class I in order to induce tumor specific cytotoxic T lymphocytes (CTLs). However, MHC class I molecules generally present the epitope peptides derived from endogenous antigens for DCs but not exogenous ones such as TAAs. Recently, we developed the novel liposomal bubbles (Bubble liposomes) encapsulating perfluoropropane nanobubbles. In this study, we attempted to establish the novel antigen delivery system to induce MHC class I presentation using the combination of ultrasound and Bubble liposomes. Using ovalbumin (OVA) as model antigen, the combination of Bubble liposomes and ultrasound exposure for the DC could induce MHC class I presentation. In addition, the viability of DCs was more than 80%. These results suggest that Bubble liposomes might be a novel ultrasound enhanced antigen delivery tool in DC-based cancer immunotherapy. [ABSTRACT FROM AUTHOR]

Liposomes have some advantages as drug, antigen and gene delivery carriers. Their size can be easily controlled and they can be modified to add a targeting function. Based on liposome technology, we developed novel liposomal bubbles (Bubble liposomes) containing the ultrasound imaging gas, perfluoropropane. We assessed the feasibility of Bubble liposomes as carriers for gene delivery after cavitation induced by ultrasound. At first, we investigated their ability to deliver genes with Bubble liposomes and ultrasound to various types of cells such as mouse sarcoma cells, mouse melanoma cells, human T cell line and human umbilical vein endothelial cells. The results showed that the Bubble liposomes could deliver plasmid DNA to many cell types without cytotoxicity. In addition, we found that Bubble liposomes could effectively deliver plasmid DNA into mouse femoral artery in vivo. The gene transduction with Bubble liposomes was more effectively than conventional lipofection. We conclude that Bubble liposomes are unique and efficient gene delivery carriers in vitro and in vivo. © 2007 American Institute of Physics [ABSTRACT FROM AUTHOR]

Recently it has been shown that a simple model was able to reproduce the main “types” of infectious diseases encountered in human populations. This model takes into account key features of the immune system at the within-host level and an implicit description of the contact network of the host population at the between-hosts level. The implicit description of contact network neglects population-level selective pressures such as fluctuations in the number of infected individuals potentially leading to risk of extinction. We present a nested model that allows to keep a within-host level description of immune processes while allowing an explicit description of the ongoing epidemiological dynamics. This model allows us to understand the impact of human population size and contact networks structure in shaping the fitness optima for pathogens life history traits. We mostly focus on variation in duration of infection and antigenic evolution leading to immune escape. [ABSTRACT FROM AUTHOR]