84 resultados para immune defense


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Visceral leishmaniasis is a chronic parasitic disease associated with severe immune dysfunction. Treatment options are limited to relatively toxic drugs and there is no vaccine for humans available. Hence, there is an urgent need to better understand immune responses following infection with Leishmania species by studying animal models of disease and clinical samples from patients. Here, we review recent discoveries in these areas and highlight shortcomings in our knowledge that need to be addressed if better treatment options are to be developed and effective vaccines designed.

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Hand, Foot and Mouth Disease (HFMD) is a self-limiting viral disease that mainly affects infants and children. In contrast with other HFMD causing enteroviruses, Enterovirus71 (EV71) has commonly been associated with severe clinical manifestation leading to death. Currently, due to a lack in understanding of EV71 pathogenesis, there is no antiviral therapeutics for the treatment of HFMD patients. Therefore the need to better understand the mechanism of EV71 pathogenesis is warranted. We have previously reported a human colorectal adenocarcinoma cell line (HT29) based model to study the pathogenesis of EV71. Using this system, we showed that knockdown of DGCR8, an essential cofactor for microRNAs biogenesis resulted in a reduction of EV71 replication. We also demonstrated that there are miRNAs changes during EV71 pathogenesis and EV71 utilise host miRNAs to attenuate antiviral pathways during infection. Together, data from this study provide critical information on the role of miRNAs during EV71 infection.

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We consider secret sharing with binary shares. This model allows us to use the well developed theory of cryptographically strong boolean functions. We prove that for given secret sharing, the average cheating probability over all cheating and original vectors, i.e., ρ ¯= 1 n ⋅ 2 −n ∑ n c=1 ∑ α∈Vn ρ c,α , satisfies ρ ¯⩾ 1 2 , and the equality holds ⇔ ρc,α satisfies ρc,α = 1/2 for every cheating vector δc and every original vector α. In this case the secret sharing is said to be cheating immune. We further establish a relationship between cheating-immune secret sharing and cryptographic criteria of boolean functions. This enables us to construct cheating-immune secret sharing.

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The work addresses the problem of cheating prevention in secret sharing. Two cheating scenarios are considered. In the first one, the cheaters always submit invalid shares to the combiner. In the second one, the cheaters collectively decide which shares are to be modified so the combiner gets a mixture of valid and invalid shares from the cheaters. The secret scheme is said to be k-cheating immune if any group of k cheaters has no advantage over honest participants. The paper investigates cryptographic properties of the defining function of secret sharing so the scheme is k-cheating immune. Constructions of secret sharing immune against k cheaters are given.

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The paper investigates the design of secret sharing that is immune against cheating (as defined by the Tompa-Woll attack). We examine secret sharing with binary shares and secrets. Bounds on the probability of successful cheating are given for two cases. The first case relates to secret sharing based on bent functions and results in a non-perfect scheme. The second case considers perfect secret sharing built on highly nonlinear balanced Boolean functions.

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The paper addresses the cheating prevention in secret sharing. We consider secret sharing with binary shares. The secret also is binary. This model allows us to use results and constructions from the well developed theory of cryptographically strong boolean functions. In particular, we prove that for given secret sharing, the average cheating probability over all cheating vectors and all original vectors, i.e., 1/n 2n ∑c=1...n ∑α∈V n ρc,α , denoted by ρ, satisfies ρ ≥ ½, and the equality holds if and only if ρc,α satisfies ρc,α= ½ for every cheating vector δc and every original vector α. In this case the secret sharing is said to be cheating immune. We further establish a relationship between cheating-immune secret sharing and cryptographic criteria of boolean functions.This enables us to construct cheating-immune secret sharing.

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Urinary tract infections (UTI) are among the most common infectious diseases of humans and are the most common nosocomial infections in the developed world. It is estimated that 40–50% of women and 5% of men will develop a UTI in their lifetime, and UTI accounts for more than 1 million hospitalizations and $1.6 billion in medical expenses each year in the USA. Uropathogenic Escherichia coli (UPEC) is the primary cause of UTI. This review presents an overview of recent discoveries related to the primary virulence factors of UPEC and major innate immune responses to infection of the lower urinary tract. New and emerging themes in UPEC research are discussed in the context of the interface between host and pathogen.

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This report describes the diagnostic features, clinical management and the issues associated with management of a young immunocompetent male who presented with a presumed left Herpes simplex immune stromal keratitis, and ten months later, a right immune stromal keratitis associated with Herpes zoster ophthalmicus.

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Amoebic gill disease (AGD) is a parasite-mediated proliferative gill disease capable of affecting a range of teleost hosts. While a moderate heritability for AGD resistance in Atlantic salmon has been reported previously, the mechanisms by which individuals resist the proliferative effects remain poorly understood. To gain more knowledge of this commercially important trait, we compared gill transcriptomes of two groups of Atlantic salmon, one designated putatively resistant, and one designated putatively susceptible to AGD. Utilising a 17k Atlantic salmon cDNA microarray we identified 196 transcripts that were differentially expressed between the two groups. Expression of 11 transcripts were further examined with real-time quantitative RT-PCR (qPCR) in the AGD-resistant and AGD-susceptible animals, as well as non-infected naïve fish. Gene expression determined by qPCR was in strong agreement with the microarray analysis. A large number of differentially expressed genes were involved in immune and cell cycle responses. Resistant individuals displayed significantly higher expression of genes involved in adaptive immunity and negative regulation of the cell cycle. In contrast, AGD-susceptible individuals showed higher expression of acute phase proteins and positive regulators of the cell cycle. Combined with the gill histopathology, our results suggest AGD resistance is acquired rather than innately present, and that this resistance is for the most part associated with the dysregulation of immune and cell cycle pathways. © 2008 Elsevier Ltd. All rights reserved.

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Lewis’s Medical-Surgical Nursing: Assessment and Management of Clinical Problems, 4th Edition is the most comprehensive go-to reference for essential information about all aspects of professional nursing care of patients. Using the nursing process as a framework for practice, the fourth edition has been extensively revised to reflect the rapid changing nature of nursing practice and the increasing focus on key nursing care priorities. Building on the strengths of the third Australian and New Zealand edition and incorporating relevant global nursing research and practice from the prominent US title Medical-Surgical Nursing, 9Th Edition, Lewis’s Medical-Surgical Nursing, 4th Edition is an essential resource for students seeking to understand the role of the professional nurse in the contemporary health environment.

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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.

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In this paper we present an update on our novel visualization technologies based on cellular immune interaction from both large-scale spatial and temporal perspectives. We do so with a primary motive: to present a visually and behaviourally realistic environment to the community of experimental biologists and physicians such that their knowledge and expertise may be more readily integrated into the model creation and calibration process. Visualization aids understanding as we rely on visual perception to make crucial decisions. For example, with our initial model, we can visualize the dynamics of an idealized lymphatic compartment, with antigen presenting cells (APC) and cytotoxic T lymphocyte (CTL) cells. The visualization technology presented here offers the researcher the ability to start, pause, zoom-in, zoom-out and navigate in 3-dimensions through an idealised lymphatic compartment.

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We develop a hybrid cellular automata model to describe the effect of the immune system and chemokines on a growing tumor. The hybrid cellular automata model consists of partial differential equations to model chemokine concentrations, and discrete cellular automata to model cell–cell interactions and changes. The computational implementation overlays these two components on the same spatial region. We present representative simulations of the model and show that increasing the number of immature dendritic cells (DCs) in the domain causes a decrease in the number of tumor cells. This result strongly supports the hypothesis that DCs can be used as a cancer treatment. Furthermore, we also use the hybrid cellular automata model to investigate the growth of a tumor in a number of computational “cancer patients.” Using these virtual patients, the model can explain that increasing the number of DCs in the domain causes longer “survival.” Not surprisingly, the model also reflects the fact that the parameter related to tumor division rate plays an important role in tumor metastasis.