Small proline-rich protein 1A is a gp130 pathway- and stress-inducible cardioprotective protein.

The interleukin-6 cytokines, acting via gp130 receptor pathways, play a pivotal role in the reduction of cardiac injury induced by mechanical stress or ischemia and in promoting subsequent adaptive remodeling of the heart. We have now identified the small proline-rich repeat proteins (SPRR) 1A and 2A as downstream targets of gp130 signaling that are strongly induced in cardiomyocytes responding to biomechanical/ischemic stress. Upregulation of SPRR1A and 2A was markedly reduced in the gp130 cardiomyocyte-restricted knockout mice. In cardiomyocytes, MEK1/2 inhibitors prevented SPRR1A upregulation by gp130 cytokines. Furthermore, binding of NF-IL6 (C/EBPbeta) and c-Jun to the SPRR1A promoter was observed after CT-1 stimulation. Histological analysis revealed that SPRR1A induction after mechanical stress of pressure overload was restricted to myocytes surrounding piecemeal necrotic lesions. A similar expression pattern was found in postinfarcted rat hearts. Both in vitro and in vivo ectopic overexpression of SPRR1A protected cardiomyocytes against ischemic injury. Thus, this study identifies SPRR1A as a novel stress-inducible downstream mediator of gp130 cytokines in cardiomyocytes and documents its cardioprotective effect against ischemic stress.

Agents de migration : les intermédiaires sur le marché suisse des footballeurs et danseuses de cabaret

En se focalisant sur le cas des joueurs de football professionnels et des danseuses de cabaret, cet article met en lumière le rôle joué par différents types d'intermédiaire dans la mise en place, le développement et la gestion de canaux migratoires. Une attention particulière est accordée aux procédures recrutement et à la gestion de la circulation de ces deux catégories de travailleurs.

Amoebal pathogens as emerging causal agents of pneumonia.

Despite using modern microbiological diagnostic approaches, the aetiological agents of pneumonia remain unidentified in about 50% of cases. Some bacteria that grow poorly or not at all in axenic media used in routine clinical bacteriology laboratory but which can develop inside amoebae may be the agents of these lower respiratory tract infections (RTIs) of unexplained aetiology. Such amoebae-resisting bacteria, which coevolved with amoebae to resist their microbicidal machinery, may have developed virulence traits that help them survive within human macrophages, i.e. the first line of innate immune defence in the lung. We review here the current evidence for the emerging pathogenic role of various amoebae-resisting microorganisms as agents of RTIs in humans. Specifically, we discuss the emerging pathogenic roles of Legionella-like amoebal pathogens, novel Chlamydiae (Parachlamydia acanthamoebae, Simkania negevensis), waterborne mycobacteria and Bradyrhizobiaceae (Bosea and Afipia spp.).

Synthesis and multi-target biological profiling of a novel family of rhein derivatives as disease-modifying anti-Alzheimer agents

We have synthesized a family of rheinhuprine hybrids to hit several key targets for Alzheimer"s disease. Biological screening performed in vitro and in Escherichia coli cells has shown that these hybrids exhibit potent inhibitory activities against human acetylcholinesterase butyrylcholinesterase, and BACE-1, dual Aβ42 and tau anti-aggregating activity, and brain permeability. Ex vivo studies with the leads (+)- and ()-7e in brain slices of C57bl6 mice have revealed that they efficiently protect against the Aβ-induced synaptic dysfunction , preventing the loss of synaptic proteins and/or have a positive effect on the induction of long term potentiation. In vivo studies in APP-PS1 transgenic mice treated i.p. for 4 weeks with (+)- and ()-7e have shown a central soluble Aβ lowering effect, accompanied by an increase in the levels of mature amyloid precursor protein (APP). Thus, (+)- and ()-7e emerge as very promising disease-modifying anti-Alzheimer drug candidates.

Synthesis and multi-target biological profiling of a novel family of rhein derivatives as disease-modifying anti-Alzheimer agents

We have synthesized a family of rheinhuprine hybrids to hit several key targets for Alzheimer"s disease. Biological screening performed in vitro and in Escherichia coli cells has shown that these hybrids exhibit potent inhibitory activities against human acetylcholinesterase butyrylcholinesterase, and BACE-1, dual Aβ42 and tau anti-aggregating activity, and brain permeability. Ex vivo studies with the leads (+)- and ()-7e in brain slices of C57bl6 mice have revealed that they efficiently protect against the Aβ-induced synaptic dysfunction , preventing the loss of synaptic proteins and/or have a positive effect on the induction of long term potentiation. In vivo studies in APP-PS1 transgenic mice treated i.p. for 4 weeks with (+)- and ()-7e have shown a central soluble Aβ lowering effect, accompanied by an increase in the levels of mature amyloid precursor protein (APP). Thus, (+)- and ()-7e emerge as very promising disease-modifying anti-Alzheimer drug candidates.

Adaptive changes in a radial maze task: Efficient selection of baited arms with reduced foraging in senescent hooded rats

Qualitative differences in strategy selection during foraging in a partially baited maze were assessed in young and old rats. The baited and non-baited arms were at a fixed position in space and marked by a specific olfactory cue. The senescent rats did more re-entries during the first four-trial block but were more rapid than the young rats in selecting the reinforced arms during the first visits. Dissociation between the olfactory spatial cue reference by rotating the maze revealed that only few old subjects relied on olfactory cues to select the baited arms and the remainder relied mainly on the visuo-spatial cues.

Development of a hepatocyte hollow fiber bioreactor for the study of contrast agents by magnetic resonance imaging

Thanks to the continuous progress made in recent years, medical imaging has become an important tool in the diagnosis of various pathologies. In particular, magnetic resonance imaging (MRI) permits to obtain images with a remarkably high resolution without the use of ionizing radiation and is consequently widely applied for a broad range of conditions in all parts of the body. Contrast agents are used in MRI to improve tissue discrimination. Different categories of contrast agents are clinically available, the most widely used being gadolinium chelates. One can distinguish between extracellular gadolinium chelates such as Gd-DTPA, and hepatobiliary gadolinium chelates such as Gd-BOPTA. The latter are able to enter hepatocytes from where they are partially excreted into the bile to an extent dependent on the contrast agent and animal species. Due to this property, hepatobiliary contrast agents are particularly interesting for the MRI of the liver. Actually, a change in signal intensity can result from a change in transport functions signaling the presence of impaired hepatocytes, e.g. in the case of focal (like cancer) or diffuse (like cirrhosis) liver diseases. Although the excretion mechanism into the bile is well known, the uptake mechanisms of hepatobiliary contrast agents into hepatocytes are still not completely understood and several hypotheses have been proposed. As a good knowledge of these transport mechanisms is required to allow an efficient diagnosis by MRI of the functional state of the liver, more fundamental research is needed and an efficient MRI compatible in vitro model would be an asset. So far, most data concerning these transport mechanisms have been obtained by MRI with in vivo models or by a method of detection other than MRI with cellular or sub-cellular models. Actually, no in vitro model is currently available for the study and quantification of contrast agents by MRI notably because high cellular densities are needed to allow detection, and no metallic devices can be used inside the magnet room, which is incompatible with most tissue or cell cultures that require controlled temperature and oxygenation. The aim of this thesis is thus to develop an MRI compatible in vitro cellular model to study the transport of hepatobiliary contrast agents, in particular Gd-BOPTA, into hepatocytes directly by MRI. A better understanding of this transport and especially of its modification in case of hepatic disorder could permit in a second step to extrapolate this knowledge to humans and to use the kinetics of hepatobiliary contrast agents as a tool for the diagnosis of hepatic diseases.

Artificially Intelligent and Adaptive Methods for Prediction and Analysis of Superheater Fireside Corrosion in Fluidized Bed Boilers

Superheater corrosion causes vast annual losses for the power companies. With a reliable corrosion prediction method, the plants can be designed accordingly, and knowledge of fuel selection and determination of process conditions may be utilized to minimize superheater corrosion. Growing interest to use recycled fuels creates additional demands for the prediction of corrosion potential. Models depending on corrosion theories will fail, if relations between the inputs and the output are poorly known. A prediction model based on fuzzy logic and an artificial neural network is able to improve its performance as the amount of data increases. The corrosion rate of a superheater material can most reliably be detected with a test done in a test combustor or in a commercial boiler. The steel samples can be located in a special, temperature-controlled probe, and exposed to the corrosive environment for a desired time. These tests give information about the average corrosion potential in that environment. Samples may also be cut from superheaters during shutdowns. The analysis ofsamples taken from probes or superheaters after exposure to corrosive environment is a demanding task: if the corrosive contaminants can be reliably analyzed, the corrosion chemistry can be determined, and an estimate of the material lifetime can be given. In cases where the reason for corrosion is not clear, the determination of the corrosion chemistry and the lifetime estimation is more demanding. In order to provide a laboratory tool for the analysis and prediction, a newapproach was chosen. During this study, the following tools were generated: · Amodel for the prediction of superheater fireside corrosion, based on fuzzy logic and an artificial neural network, build upon a corrosion database developed offuel and bed material analyses, and measured corrosion data. The developed model predicts superheater corrosion with high accuracy at the early stages of a project. · An adaptive corrosion analysis tool based on image analysis, constructedas an expert system. This system utilizes implementation of user-defined algorithms, which allows the development of an artificially intelligent system for thetask. According to the results of the analyses, several new rules were developed for the determination of the degree and type of corrosion. By combining these two tools, a user-friendly expert system for the prediction and analyses of superheater fireside corrosion was developed. This tool may also be used for the minimization of corrosion risks by the design of fluidized bed boilers.

Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses

Background: Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements. Results: We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer- approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shock Conclusion: Our results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.

Minimization of biosynthetic costs in adaptive gene expression responses of yeast to environmental changes

Yeast successfully adapts to an environmental stress by altering physiology and fine-tuning metabolism. This fine-tuning is achieved through regulation of both gene expression and protein activity, and it is shaped by various physiological requirements. Such requirements impose a sustained evolutionary pressure that ultimately selects a specific gene expression profile, generating a suitable adaptive response to each environmental change. Although some of the requirements are stress specific, it is likely that others are common to various situations. We hypothesize that an evolutionary pressure for minimizing biosynthetic costs might have left signatures in the physicochemical properties of proteins whose gene expression is fine-tuned during adaptive responses. To test this hypothesis we analyze existing yeast transcriptomic data for such responses and investigate how several properties of proteins correlate to changes in gene expression. Our results reveal signatures that are consistent with a selective pressure for economy in protein synthesis during adaptive response of yeast to various types of stress. These signatures differentiate two groups of adaptive responses with respect to how cells manage expenditure in protein biosynthesis. In one group, significant trends towards downregulation of large proteins and upregulation of small ones are observed. In the other group we find no such trends. These results are consistent with resource limitation being important in the evolution of the first group of stress responses.

Can we translate vitamin D immunomodulating effect on innate and adaptive immunity to vaccine response?

Vitamin D (VitD), which is well known for its classic role in the maintenance of bone mineral density, has now become increasingly studied for its extra-skeletal roles. It has an important influence on the body's immune system and modulates both innate and adaptive immunity and regulates the inflammatory cascade. In this review our aim was to describe how VitD might influence immune responsiveness and its potential modulating role in vaccine immunogenicity. In the first instance, we consider the literature that may provide molecular and genetic support to the idea that VitD status may be related to innate and/or adaptive immune response with a particular focus on vaccine immunogenicity and then discuss observational studies and controlled trials of VitD supplementation conducted in humans. Finally, we conclude with some knowledge gaps surrounding VitD and vaccine response, and that it is still premature to recommend "booster" of VitD at vaccination time to enhance vaccine response.

Automated monitoring of medical protocols: a secure and distributed architecture

The control of the right application of medical protocols is a key issue in hospital environments. For the automated monitoring of medical protocols, we need a domain-independent language for their representation and a fully, or semi, autonomous system that understands the protocols and supervises their application. In this paper we describe a specification language and a multi-agent system architecture for monitoring medical protocols. We model medical services in hospital environments as specialized domain agents and interpret a medical protocol as a negotiation process between agents. A medical service can be involved in multiple medical protocols, and so specialized domain agents are independent of negotiation processes and autonomous system agents perform monitoring tasks. We present the detailed architecture of the system agents and of an important domain agent, the database broker agent, that is responsible of obtaining relevant information about the clinical history of patients. We also describe how we tackle the problems of privacy, integrity and authentication during the process of exchanging information between agents.