T cell regulation of the immune response to infection in periodontal diseases

Although T cells have been implicated in the pathogenesis and are considered to be central both in progression and control of the chronic inflammatory periodontal diseases, the precise contribution of T cells to the regulation of tissue destruction has not been fully elucidated. Current dogma suggests that immunity to infection is controlled by distinct T helper 1 (Th1) and T helper 2 (Th2) subsets of T cells classified on the basis of their cytokine profile. Further, a subset of T cells with immunosuppressive function and cytokine profile distinct from Th1 or Th2 has been described and designated as regulatory T cells. Although these regulatory T cells have been considered to maintain self-tolerance resulting in the suppression of auto-immune responses, recent data suggest that these cells may also play a role in preventing infection-induced immunopathology. In this review, the role of functional and regulatory T cells in chronic inflammatory periodontal diseases will be summarized. This should not only provide an insight into the relationship between the immune response to periodontopathic bacteria and disease but should also highlight areas of development for potentially new therapeutic modalities.

An augmented Lanczos algorithm for the efficient computation of a dot-product of a function of a large sparse symmetric matrix

The Lanczos algorithm is appreciated in many situations due to its speed. and economy of storage. However, the advantage that the Lanczos basis vectors need not be kept is lost when the algorithm is used to compute the action of a matrix function on a vector. Either the basis vectors need to be kept, or the Lanczos process needs to be applied twice. In this study we describe an augmented Lanczos algorithm to compute a dot product relative to a function of a large sparse symmetric matrix, without keeping the basis vectors.

The tree cut and merge algorithm for estimation of network reliability

This article presents Monte Carlo techniques for estimating network reliability. For highly reliable networks, techniques based on graph evolution models provide very good performance. However, they are known to have significant simulation cost. An existing hybrid scheme (based on partitioning the time space) is available to speed up the simulations; however, there are difficulties with optimizing the important parameter associated with this scheme. To overcome these difficulties, a new hybrid scheme (based on partitioning the edge set) is proposed in this article. The proposed scheme shows orders of magnitude improvement of performance over the existing techniques in certain classes of network. It also provides reliability bounds with little overhead.

Antigen-specific suppression of a primed immune response by dendritic cells mediated by regulatory T cells secreting interleukin-10

Antigen-specific suppression of a previously primed immune response is a major challenge for immunotherapy of autoimmune disease. ReIB activation is required for myeloid DC differentiation. Here, we show that antigen-exposed DCs in which ReIB function is inhibited lack cell surface CD40, prevent priming of immunity, and suppress previously primed immune responses. DCs generated from CD40-deficient mice similarly confer suppression. Regulatory CD4(+) T cells induced by the DCs transfer antigen-specific Infectious tolerance to primed recipients in an interleukin10-dependent fashion. Thus CD40, regulated by ReIB activity, determines the consequences of antigen presentation by myeloid DCs. These observations have significance for autoimmune immunotherapy and suggest a mechanism by which peripheral tolerance might be constitutively maintained by RelB(-) CD40(-) DCs.

A genetic algorithm/method of moments approach to the optimization of an RF coil for MRI applications - Theoretical considerations - Abstract

A Combined Genetic Algorithm and Method of Moments design methods is presented for the design of unusual near-field antennas for use in Magnetic Resonance Imaging systems. The method is successfully applied to the design of an asymmetric coil structure for use at 190MHz and demonstrates excellent radiofrequency field homogeneity.

Plasma zinc and immune markers in runners in response to a moderate increase in training volume

Changes in plasma zinc concentration and markers of immune function were examined in a group of 10 male runners (n = 10) following a moderate increase in training over four weeks. Seven sedentary males acted as controls. Fasting blood samples were taken at rest, before (T0) and after T4) four weeks of increased (+ 16 %) training and after two weeks of reduced (- 31 %) training (W. Blood was analysed for plasma zinc concentration, differential leucocyte counts, lymphocyte subpopulations and lymphocyte proliferation using incorporation of H-3-thymidine. The runners increased their training volume by 16 % over the four weeks. When compared with the nonathletes, the runners had lower concentrations of plasma zinc (p = 0.012), CD3(+) (p = 0.042) and CD19(+) lymphocytes (p = 0.010) over the four weeks. Lymphocyte proliferation in response to Concanavalin A stimulation was greater in the runners (p = 0.0090). Plasma zinc concentration and immune markers remained constant during the study. Plasma zinc concentration correlated with total leucocyte counts in the athletes at T6 (r = -0.72, p < 0.05) and with Pokeweed mitogen stimulation in the nonathletes at T6 (r = -0.92, p < 0.05). Therefore, athletes are unlikely to benefit from zinc supplementation during periods of moderately increased training volume.

Automated traffic route identification through the shared nearest neighbour algorithm

Many organisations need to extract useful information from huge amounts of movement data. One example is found in maritime transportation, where the automated identification of a diverse range of traffic routes is a key management issue for improving the maintenance of ports and ocean routes, and accelerating ship traffic. This paper addresses, in a first stage, the research challenge of developing an approach for the automated identification of traffic routes based on clustering motion vectors rather than reconstructed trajectories. The immediate benefit of the proposed approach is to avoid the reconstruction of trajectories in terms of their geometric shape of the path, their position in space, their life span, and changes of speed, direction and other attributes over time. For clustering the moving objects, an adapted version of the Shared Nearest Neighbour algorithm is used. The motion vectors, with a position and a direction, are analysed in order to identify clusters of vectors that are moving towards the same direction. These clusters represent traffic routes and the preliminary results have shown to be promising for the automated identification of traffic routes with different shapes and densities, as well as for handling noise data.

Multi-centre validation of an automatic algorithm for fast 4D myocardial segmentation in cine CMR datasets

Quantitative analysis of cine cardiac magnetic resonance (CMR) images for the assessment of global left ventricular morphology and function remains a routine task in clinical cardiology practice. To date, this process requires user interaction and therefore prolongs the examination (i.e. cost) and introduces observer variability. In this study, we sought to validate the feasibility, accuracy, and time efficiency of a novel framework for automatic quantification of left ventricular global function in a clinical setting.

Immune cell changes in response to a swimming training session during a 24-h recovery period

Understanding the impact of training sessions on the immune response is crucial for the adequate periodization of training, to prevent both a negative influence on health and a performance impairment of the athlete. This study evaluated acute systemic immune cell changes in response to an actual swimming session, during a 24-h recovery period, controlling for sex, menstrual cycle phases, maturity, and age group. Competitive swimmers (30 females, 15 ± 1.3 years old; and 35 males, 16.5 ± 2.1 years old) performed a high-intensity training session. Blood samples were collected before, immediately after, 2 h after, and 24 h after exercise. Standard procedures for the assessment of leukogram by automated counting (Coulter LH 750, Beckman) and lymphocytes subsets by flow cytometry (FACS Calibur BD, Biosciences) were used. Subjects were grouped according to competitive age groups and pubertal Tanner stages. Menstrual cycle phase was monitored. The training session induced neutrophilia, lymphopenia, and a low eosinophil count, lasting for at least 2 h, independent of sex and maturity. At 24 h postexercise, the acquired immunity of juniors (15-17 years old), expressed by total lymphocytes and total T lymphocytes (CD3+), was not fully recovered. This should be accounted for when planning a weekly training program. The observed lymphopenia suggests a lower immune surveillance at the end of the session that may depress the immunity of athletes, highlighting the need for extra care when athletes are exposed to aggressive environmental agents such as swimming pools

Lanczos algorithm on the grassmann manifold

5th. European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2008) 8th. World Congress on Computational Mechanics (WCCM8)

IOPT Petri Net State Space Generation Algorithm with Maximal-Step Execution Semantics

This paper presents an algorithm to efficiently generate the state-space of systems specified using the IOPT Petri-net modeling formalism. IOPT nets are a non-autonomous Petri-net class, based on Place-Transition nets with an extended set of features designed to allow the rapid prototyping and synthesis of system controllers through an existing hardware-software co-design framework. To obtain coherent and deterministic operation, IOPT nets use a maximal-step execution semantics where, in a single execution step, all enabled transitions will fire simultaneously. This fact increases the resulting state-space complexity and can cause an arc "explosion" effect. Real-world applications, with several million states, will reach a higher order of magnitude number of arcs, leading to the need for high performance state-space generator algorithms. The proposed algorithm applies a compilation approach to read a PNML file containing one IOPT model and automatically generate an optimized C program to calculate the corresponding state-space.

Genetic algorithm methodology applied to intelligent house control

In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.

Structural characterization and immunogenicity in wildtype and immune tolerant mice of degraded recombinant human interferon alpha2b

Purpose - To study the influence of protein structure on the immunogenicity in wildtype and immune tolerant mice of well-characterized degradation products of recombinant human interferon alpha2b (rhIFNα2b). Methods - RhIFNα2b was degraded by metal catalyzed oxidation (M), crosslinking with glutaraldehyde (G), oxidation with hydrogen peroxide (H) and incubation in a boiling water bath (B). The products were characterized with UV absorption, circular dichroism and fluorescence spectroscopy, gel permeation chromatography, reversed-phase HPLC, SDS-PAGE, Western blotting and mass spectrometry. The immunogenicity of the products was evaluated in wildtype mice and in transgenic mice immune tolerant for hIFNα2. Serum antibodies were detected by ELISA or surface plasmon resonance. Results - M-rhIFNα2b contained covalently aggregated rhIFNα2b with three methionines partly oxidized to methionine sulfoxides. G-rhIFNα2b contained covalent aggregates and did not show changes in secondary structure. H-rhIFNα2b was only chemically changed with four partly oxidized methionines. B-rhIFNα2b was largely unfolded and heavily aggregated. Native (N) rhIFNα2b was immunogenic in the wildtype mice but not in the transgenic mice, showing that the latter were immune tolerant for rhIFNα2b. The antirhIFNα2b antibody levels in the wildtype mice depended on the degradation product: M-rhIFNα2b > H-rhIFNα2b ~ N-rhIFNα2b >> B-rhIFNα2b; G-rhIFNα2b did not induce anti-rhIFNα2b antibodies. In the transgenic mice, only M-rhIFNα2b could break the immune tolerance. Conclusions - RhIFNα2b immunogenicity is related to its structural integrity. Moreover, the immunogenicity of aggregated rhIFNα2b depends on the structure and orientation of the constituent protein molecules and/or on the aggregate size.

Ant colony search algorithm for the optimal power flow problem

To maintain a power system within operation limits, a level ahead planning it is necessary to apply competitive techniques to solve the optimal power flow (OPF). OPF is a non-linear and a large combinatorial problem. The Ant Colony Search (ACS) optimization algorithm is inspired by the organized natural movement of real ants and has been successfully applied to different large combinatorial optimization problems. This paper presents an implementation of Ant Colony optimization to solve the OPF in an economic dispatch context. The proposed methodology has been developed to be used for maintenance and repairing planning with 48 to 24 hours antecipation. The main advantage of this method is its low execution time that allows the use of OPF when a large set of scenarios has to be analyzed. The paper includes a case study using the IEEE 30 bus network. The results are compared with other well-known methodologies presented in the literature.

Optimal dispatch with reactive power compensation by Genetic Algorithm

This paper presents a Unit Commitment model with reactive power compensation that has been solved by Genetic Algorithm (GA) optimization techniques. The GA has been developed a computational tools programmed/coded in MATLAB. The main objective is to find the best generations scheduling whose active power losses are minimal and the reactive power to be compensated, subjected to the power system technical constraints. Those are: full AC power flow equations, active and reactive power generation constraints. All constraints that have been represented in the objective function are weighted with a penalty factors. The IEEE 14-bus system has been used as test case to demonstrate the effectiveness of the proposed algorithm. Results and conclusions are dully drawn.