920 resultados para Acceleration pattern recognition
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This research aims to advance blinking detection in the context of work activity. Rather than patients having to attend a clinic, blinking videos can be acquired in a work environment, and further automatically analyzed. Therefore, this paper presents a methodology to perform the automatic detection of eye blink using consumer videos acquired with low-cost web cameras. This methodology includes the detection of the face and eyes of the recorded person, and then it analyzes the low-level features of the eye region to create a quantitative vector. Finally, this vector is classified into one of the two categories considered —open and closed eyes— by using machine learning algorithms. The effectiveness of the proposed methodology was demonstrated since it provides unbiased results with classification errors under 5%
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Color image processing, pattern recognition, machine vision, application
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Among the largest resources for biological sequence data is the large amount of expressed sequence tags (ESTs) available in public and proprietary databases. ESTs provide information on transcripts but for technical reasons they often contain sequencing errors. Therefore, when analyzing EST sequences computationally, such errors must be taken into account. Earlier attempts to model error prone coding regions have shown good performance in detecting and predicting these while correcting sequencing errors using codon usage frequencies. In the research presented here, we improve the detection of translation start and stop sites by integrating a more complex mRNA model with codon usage bias based error correction into one hidden Markov model (HMM), thus generalizing this error correction approach to more complex HMMs. We show that our method maintains the performance in detecting coding sequences.
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AbstractThe vertebrate immune system is composed of the innate and the adaptive branches. Innate immune cells represent the first line of defense and detect pathogens through pattern recognition receptors (PRRs), detecting evolutionary conserved pathogen- and danger- associated molecular patterns. Engagement of these receptors initiates the inflammatory response, but also instructs antigen-specific adaptive immune cells. NOD-like receptors (NLRs) are an important group of PRRs, leading to the production of inflammatory mediators and favoring antigen presentation to Τ lymphocytes through the regulation of major histocompatibility complex (MHC) molecules.In this work we focused our attention on selected NOD-like receptors (NLRs) and their role at the interface between innate and adaptive immunity. First, we describe a new regulatory mechanism controlling IL-1 production. Our results indicate that type I interferons (IFNs) block NLRP1 and NLRP3 inflammasome activity and interfere with LPS-driven proIL-Ια and -β induction. As type I IFNs are produced upon viral infections, these anti-inflammatory effects of type I IFN could be relevant in the context of superinfections, but could also help explaining the efficacy of IFN-β in multiple sclerosis treatment.The second project addresses the role of a novel NLR family member, called NLRC5. The function of this NLR is still matter of debate, as it has been proposed as both an inhibitor and an activator of different inflammatory pathways. We found that the expression of this protein is restricted to immune cells and is positively regulated by IFNs. We generated Nlrc5-deficient mice and found that this NLR plays an essential role in Τ, NKT and, NK lymphocytes, in which it drives the expression of MHC class I molecules. Accordingly, we could show that CD8+ Τ cell-mediated killing of target lymphocytes lacking NLRC5 is strongly impaired. Moreover, NLRC5 expression was found to be low in many lymphoid- derived tumor cell lines, a mechanism that could be exploited by tumors to escape immunosurveillance.Finally, we found NLRC5 to be involved in the production of IL-10 by CD4+ Τ cells, as Nlrc5- deficient Τ lymphocytes produced less of this cytokine upon TCR triggering. In line with these observations, Mrc5-deficient CD4+ Τ cells expanded more than control cells when transferred into lymphopenic hosts and led to a more rapid appearance of colitis symptoms. Therefore, our work gives novel insights on the function of NLRC5 by using knockout mice, and strongly supports the idea that NLRs direct not only innate, but also adaptive immune responses.
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Difficult tracheal intubation assessment is an important research topic in anesthesia as failed intubations are important causes of mortality in anesthetic practice. The modified Mallampati score is widely used, alone or in conjunction with other criteria, to predict the difficulty of intubation. This work presents an automatic method to assess the modified Mallampati score from an image of a patient with the mouth wide open. For this purpose we propose an active appearance models (AAM) based method and use linear support vector machines (SVM) to select a subset of relevant features obtained using the AAM. This feature selection step proves to be essential as it improves drastically the performance of classification, which is obtained using SVM with RBF kernel and majority voting. We test our method on images of 100 patients undergoing elective surgery and achieve 97.9% accuracy in the leave-one-out crossvalidation test and provide a key element to an automatic difficult intubation assessment system.
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Throughout the animal kingdom, steroid hormones have been implicated in the defense against microbial infection, but how these systemic signals control immunity is unclear. Here, we show that the steroid hormone ecdysone controls the expression of the pattern recognition receptor PGRP-LC in Drosophila, thereby tightly regulating innate immune recognition and defense against bacterial infection. We identify a group of steroid-regulated transcription factors as well as two GATA transcription factors that act as repressors and activators of the immune response and are required for the proper hormonal control of PGRP-LC expression. Together, our results demonstrate that Drosophila use complex mechanisms to modulate innate immune responses, and identify a transcriptional hierarchy that integrates steroid signalling and immunity in animals.
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The investigation of perceptual and cognitive functions with non-invasive brain imaging methods critically depends on the careful selection of stimuli for use in experiments. For example, it must be verified that any observed effects follow from the parameter of interest (e.g. semantic category) rather than other low-level physical features (e.g. luminance, or spectral properties). Otherwise, interpretation of results is confounded. Often, researchers circumvent this issue by including additional control conditions or tasks, both of which are flawed and also prolong experiments. Here, we present some new approaches for controlling classes of stimuli intended for use in cognitive neuroscience, however these methods can be readily extrapolated to other applications and stimulus modalities. Our approach is comprised of two levels. The first level aims at equalizing individual stimuli in terms of their mean luminance. Each data point in the stimulus is adjusted to a standardized value based on a standard value across the stimulus battery. The second level analyzes two populations of stimuli along their spectral properties (i.e. spatial frequency) using a dissimilarity metric that equals the root mean square of the distance between two populations of objects as a function of spatial frequency along x- and y-dimensions of the image. Randomized permutations are used to obtain a minimal value between the populations to minimize, in a completely data-driven manner, the spectral differences between image sets. While another paper in this issue applies these methods in the case of acoustic stimuli (Aeschlimann et al., Brain Topogr 2008), we illustrate this approach here in detail for complex visual stimuli.
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The recognition of microbial pathogens based on their molecular patterns is essential for host defense. Recently, Toll-like receptors have been shown not only to recognize viruses as well as bacteria and fungi, but also to trigger an efficient immune response. A recent publication proposed that the retrovirus mouse mammary tumor virus exploits the pattern-recognition receptor Toll-like receptor 4 to achieve more efficient infection.
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Inflammasomes are molecular platforms activated upon cellular infection or stress that trigger the maturation of proinflammatory cytokines such as interleukin-1beta to engage innate immune defenses. Strong associations between dysregulated inflammasome activity and human heritable and acquired inflammatory diseases highlight the importance this pathway in tailoring immune responses. Here, we comprehensively review mechanisms directing normal inflammasome function and its dysregulation in disease. Agonists and activation mechanisms of the NLRP1, NLRP3, IPAF, and AIM2 inflammasomes are discussed. Regulatory mechanisms that potentiate or limit inflammasome activation are examined, as well as emerging links between the inflammasome and pyroptosis and autophagy.
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Sepsis is among the leading causes of death worldwide and its incidence is increasing. Defined as the host response to infection, sepsis is a clinical syndrome considered to be the expression of a dysregulated immune reaction induced by danger signals that may lead to organ failure and death. Remarkable progresses have been made in our understanding of the molecular basis of host defenses in recent years. The host defense response is initiated by innate immune sensors of danger signals designated under the collective name of pattern-recognition receptors. Members of the family of microbial sensors include the complement system, the Toll-like receptors, the nucleotide-binding oligomerization domainlike receptors, the RIG-I-like helicases and the C-type lectin receptors. Ligand-activated pattern-recognition receptors kick off a cascade of intracellular events resulting in the expression of co-stimulatory molecules and release of effector molecules playing a fundamental role in the initiation of the innate and adaptive immune responses. Fine tuning of proinflammatory and anti-inflammatory reactions is critical for keeping the innate immune response in check. Overwhelming or dysregulated responses induced by infectious stimuli may have dramatic consequences for the host as shown by the profound derangements observed in sepsis. Unfortunately, translational research approaches aimed at the development of therapies targeting newly identified innate immune pathways have not held their promises. Indeed, all recent clinical investigations of adjunctive anti-sepsis treatments had little, if any, impact on morbidity and all-cause mortality of sepsis. Dissecting the mechanisms underlying the transition from infection to sepsis is essential for solving the sepsis enigma. Important components of the puzzle have already been identified, but the hunt must go on in the laboratory and at the bedside.
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The class B scavenger receptor CD36 is a component of the pattern recognition receptors on monocytes that recognizes a variety of molecules. CD36 expression in monocytes depends on exposure to soluble mediators. We demonstrate here that CD36 expression is induced in human monocytes following exposure to IL-13, a Th2 cytokine, via the peroxisome proliferator-activated receptor (PPAR)gamma pathway. Induction of CD36 protein was paralleled by an increase in CD36 mRNA. The PPARgamma pathway was demonstrated using transfection of a PPARgamma expression plasmid into the murine macrophage cell line RAW264.7, expressing very low levels of PPARgamma, and in peritoneal macrophages from PPARgamma-conditional null mice. We also show that CD36 induction by IL-13 via PPARgamma is dependent on phospholipase A2 activation and that IL-13 induces the production of endogenous 15-deoxy-Delta12,14-prostaglandin J2, an endogenous PPARgamma ligand, and its nuclear localization in human monocytes. Finally, we demonstrate that CD36 and PPARgamma are involved in IL-13-mediated phagocytosis of Plasmodium falciparum-parasitized erythrocytes. These results reveal a novel role for PPARgamma in the alternative activation of monocytes by IL-13, suggesting that endogenous PPARgamma ligands, produced by phospholipase A2 activation, could contribute to the biochemical and cellular functions of CD36.
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Pattern recognition receptors (PRRs) are commonly known as sensor proteins crucial for the early detection of microbial or host-derived stress signals by innate immune cells. Interestingly, some PRRs are also expressed and functional in cells of the adaptive immune system. These receptors provide lymphocytes with innate sensing abilities; for example, B cells express Toll-like receptors, which are important for the humoral response. Strikingly, certain other NOD-like receptors are not only highly expressed in adaptive immune cells, but also exert functions related specifically to adaptive immune system pathways, such as regulating antigen presentation. In this review, we will focus particularly on the current understanding of PRR functions intrinsic to B and T lymphocytes; a developing aspect of PRR biology.
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Specific properties emerge from the structure of large networks, such as that of worldwide air traffic, including a highly hierarchical node structure and multi-level small world sub-groups that strongly influence future dynamics. We have developed clustering methods to understand the form of these structures, to identify structural properties, and to evaluate the effects of these properties. Graph clustering methods are often constructed from different components: a metric, a clustering index, and a modularity measure to assess the quality of a clustering method. To understand the impact of each of these components on the clustering method, we explore and compare different combinations. These different combinations are used to compare multilevel clustering methods to delineate the effects of geographical distance, hubs, network densities, and bridges on worldwide air passenger traffic. The ultimate goal of this methodological research is to demonstrate evidence of combined effects in the development of an air traffic network. In fact, the network can be divided into different levels of âeurooecohesionâeuro, which can be qualified and measured by comparative studies (Newman, 2002; Guimera et al., 2005; Sales-Pardo et al., 2007).
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Network analysis naturally relies on graph theory and, more particularly, on the use of node and edge metrics to identify the salient properties in graphs. When building visual maps of networks, these metrics are turned into useful visual cues or are used interactively to filter out parts of a graph while querying it, for instance. Over the years, analysts from different application domains have designed metrics to serve specific needs. Network science is an inherently cross-disciplinary field, which leads to the publication of metrics with similar goals; different names and descriptions of their analytics often mask the similarity between two metrics that originated in different fields. Here, we study a set of graph metrics and compare their relative values and behaviors in an effort to survey their potential contributions to the spatial analysis of networks.
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SUMMARYThe innate immune system plays a central role in host defenses against invading pathogens. Innate immune cells sense the presence of pathogens through pattern recognition receptors that trigger intracellular signaling, leading to the production of pro-inflammatory mediators like cytokines, which shape innate and adaptive immune responses. Both by excess and by default inflammation may be detrimental to the host. Indeed, severe sepsis and septic shock are lethal complications of infections characterized by a dysregulated inflammatory response.In recent years, members of the superfamily of histone deacetylases have been the focus of great interest. In mammals, histone deacetylases are broadly classified into two main subfamilies comprising histone deacetylases 1-11 (HDAC1-11) and sirtuins 1-7 (SIRT1-7). These enzymes influence gene expression by deacetylating histones and numerous non-histone proteins. Histone deacetylases have been involved in the development of oncologic, metabolic, cardiovascular, neurodegenerative and autoimmune diseases. Pharmacological modulators of histone deacetylase activity, principally inhibitors, have been developed for the treatment of cancer and metabolic diseases. When we initiated this project, several studies suggested that inhibitors of HDAC 1-11 have anti-inflammatory activity. Yet, their influence on innate immune responses was largely uncharacterized. The present study was initiated to fill in this gap.In the first part of this work, we report the first comprehensive study of the effects of HDAC 1- 11 inhibitors on innate immune responses in vitro and in vivo. Strikingly, expression studies revealed that HDAC1-11 inhibitors act essentially as negative regulators of basal and microbial product- induced expression of critical immune receptors and antimicrobial products by mouse and human innate immune cells like macrophages and dendritic cells. Furthermore, we describe a new molecular mechanism whereby HDAC1-11 inhibitors repress pro-inflammatory cytokine expression through the induction of the expression and the activity of the transcriptional repressor Μί-2β. HDAC1-11 inhibitors also impair the potential of macrophages to engulf and kill bacteria. Finally, mice treated with an HDAC inhibitor are more susceptible to non-severe bacterial and fungal infection, but are protected against toxic and septic shock. Altogether these data support the concept that HDAC 1-11 inhibitors have potent anti-inflammatory and immunomodulatory activities in vitro and in vivo.Macrophage migration inhibitory factor (MIF) is a pro-inflammatory cytokine that plays a central role in innate immune responses, cell proliferation and oncogenesis. In the second part of this manuscript, we demonstrate that HDAC1-11 inhibitors inhibit MIF expression in vitro and in vivo and describe a novel molecular mechanism accounting for these effects. We propose that inhibition of MIF expression by HDAC 1-11 inhibitors may contribute to the antitumorigenic and anti-inflammatory effects of these drugs.NAD+ is an essential cofactor of sirtuins activity and one of the major sources of energy within the cells. Therefore, sirtuins link deacetylation to NAD+ metabolism and energy status. In the last part of this thesis, we report preliminary results indicating that a pharmacological inhibitor of SIRT1-2 drastically decreases pro-inflammatory cytokine production (RNA and protein) and interferes with MAP kinase intracellular signal transduction pathway in macrophages. Moreover, administration of the SIRT1-2 inhibitor protects mice from lethal endotoxic shock and septic shock.Overall, our studies demonstrate that inhibitors of HDAC1-11 and sirtuins are powerful anti-inflammatory molecules. Given their profound negative impact on the host antimicrobial defence response, these inhibitors might increase the susceptibility to opportunistic infections, especially in immunocompromised cancer patients. Yet, these inhibitors might be useful to control the inflammatory response in severely ill septic patients or in patients suffering from chronic inflammatory diseases.