216 resultados para Critical coupling parameter


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Infectious mouse mammary tumor virus (MMTV) is a retrovirus that expresses a superantigen shortly after infection of B cells. The superantigen first drives the polyclonal activation and proliferation of superantigen-reactive CD4+ T cells, which then induce the infected B cells to proliferate and differentiate. Part of the MMTV-induced B cell response leads to the production of Abs that are specific for the viral envelope protein gp52. Here we show that this Ab response has virus-neutralizing activity and confers protection against superinfection by other MMTV strains in vivo as soon as 4 to 7 days after infection. A protective Ab titer is maintained lifelong. Viral infection as well as the superantigen-induced T-B collaboration are required to generate this rapid and long lasting neutralizing Ab response. Polyclonal or superantigen-independent B cell activation, on the contrary, does not lead to detectable virus neutralization. The early onset of this superantigen-dependent neutralizing response suggests that viral envelope-specific B cells are selectively recruited to form part of the extrafollicular B cell response and are subsequently amplified and maintained by superantigen-reactive Th cells.

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Scientific discoveries that provide strong evidence of antitumor effects in preclinical models often encounter significant delays before being tested in patients with cancer. While some of these delays have a scientific basis, others do not. We need to do better. Innovative strategies need to move into early stage clinical trials as quickly as it is safe, and if successful, these therapies should efficiently obtain regulatory approval and widespread clinical application. In late 2009 and 2010 the Society for Immunotherapy of Cancer (SITC), convened an "Immunotherapy Summit" with representatives from immunotherapy organizations representing Europe, Japan, China and North America to discuss collaborations to improve development and delivery of cancer immunotherapy. One of the concepts raised by SITC and defined as critical by all parties was the need to identify hurdles that impede effective translation of cancer immunotherapy. With consensus on these hurdles, international working groups could be developed to make recommendations vetted by the participating organizations. These recommendations could then be considered by regulatory bodies, governmental and private funding agencies, pharmaceutical companies and academic institutions to facilitate changes necessary to accelerate clinical translation of novel immune-based cancer therapies. The critical hurdles identified by representatives of the collaborating organizations, now organized as the World Immunotherapy Council, are presented and discussed in this report. Some of the identified hurdles impede all investigators; others hinder investigators only in certain regions or institutions or are more relevant to specific types of immunotherapy or first-in-humans studies. Each of these hurdles can significantly delay clinical translation of promising advances in immunotherapy yet if overcome, have the potential to improve outcomes of patients with cancer.

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In Quantitative Microbial Risk Assessment, it is vital to understand how lag times of individual cells are distributed over a bacterial population. Such identified distributions can be used to predict the time by which, in a growth-supporting environment, a few pathogenic cells can multiply to a poisoning concentration level. We model the lag time of a single cell, inoculated into a new environment, by the delay of the growth function characterizing the generated subpopulation. We introduce an easy-to-implement procedure, based on the method of moments, to estimate the parameters of the distribution of single cell lag times. The advantage of the method is especially apparent for cases where the initial number of cells is small and random, and the culture is detectable only in the exponential growth phase.

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BACKGROUND: Pneumocystis jirovecii dihydropteroate synthase (DHPS) mutations are associated with failure of prophylaxis with sulfa drugs. This retrospective study sought to better understand the geographical variation in the prevalence of these mutations. METHODS: DHPS polymorphisms in 394 clinical specimens from immunosuppressed patients who received a diagnosis of P. jirovecii pneumonia and who were hospitalized in 3 European cities were examined using polymerase chain reaction (PCR) single-strand conformation polymorphism. Demographic and clinical characteristics were obtained from patients' medical charts. RESULTS: Of the 394 patients, 79 (20%) were infected with a P. jirovecii strain harboring one or both of the previously reported DHPS mutations. The prevalence of DHPS mutations was significantly higher in Lyon than in Switzerland (33.0% vs 7.5%; P < .001). The proportion of patients with no evidence of sulfa exposure who harbored a mutant P. jirovecii DHPS genotype was significantly higher in Lyon than in Switzerland (29.7% vs 3.0%; P < .001). During the study period in Lyon, in contrast to the Swiss hospitals, measures to prevent dissemination of P. jirovecii from patients with P. jirovecii pneumonia were generally not implemented, and most patients received suboptimal prophylaxis, the failure of which was strictly associated with mutated P. jirovecii. Thus, nosocomial interhuman transmission of mutated strains directly or indirectly from other individuals in whom selection of mutants occurred may explain the high proportion of mutations without sulfa exposure in Lyon. CONCLUSIONS: Interhuman transmission of P. jirovecii, rather than selection pressure by sulfa prophylaxis, may play a predominant role in the geographical variation in the prevalence in the P. jirovecii DHPS mutations.

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The paper proposes an approach aimed at detecting optimal model parameter combinations to achieve the most representative description of uncertainty in the model performance. A classification problem is posed to find the regions of good fitting models according to the values of a cost function. Support Vector Machine (SVM) classification in the parameter space is applied to decide if a forward model simulation is to be computed for a particular generated model. SVM is particularly designed to tackle classification problems in high-dimensional space in a non-parametric and non-linear way. SVM decision boundaries determine the regions that are subject to the largest uncertainty in the cost function classification, and, therefore, provide guidelines for further iterative exploration of the model space. The proposed approach is illustrated by a synthetic example of fluid flow through porous media, which features highly variable response due to the parameter values' combination.

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The three-dimensional (3D) correction of glenoid erosion is critical to the long-term success of total shoulder replacement (TSR). In order to characterise the 3D morphology of eroded glenoid surfaces, we looked for a set of morphological parameters useful for TSR planning. We defined a scapular coordinates system based on non-eroded bony landmarks. The maximum glenoid version was measured and specified in 3D by its orientation angle. Medialisation was considered relative to the spino-glenoid notch. We analysed regular CT scans of 19 normal (N) and 86 osteoarthritic (OA) scapulae. When the maximum version of OA shoulders was higher than 10°, the orientation was not only posterior, but extended in postero-superior (35%), postero-inferior (6%) and anterior sectors (4%). The medialisation of the glenoid was higher in OA than normal shoulders. The orientation angle of maximum version appeared as a critical parameter to specify the glenoid shape in 3D. It will be very useful in planning the best position for the glenoid in TSR.

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Since its introduction 16 years ago, the astrocyte-neuron lactate shuttle (ANLS) model has profoundly modified our understanding of neuroenergetics by bringing a cellular and molecular resolution. Praised or disputed, the concept has never ceased to attract attention, leading to critical advances and unexpected insights. Here, we summarize recent experimental evidence further supporting the main tenets of the model. Thus, evidence for distinct metabolic phenotypes between neurons (mainly oxidative) and astrocytes (mainly glycolytic) have been provided by genomics and classical metabolic approaches. Moreover, it has become clear that astrocytes act as a syncytium to distribute energy substrates such as lactate to active neurones. Glycogen, the main energy reserve located in astrocytes, is used as a lactate source to sustain glutamatergic neurotransmission and synaptic plasticity. Lactate is also emerging as a neuroprotective agent as well as a key signal to regulate blood flow. Characterization of monocarboxylate transporter regulation indicates a possible involvement in synaptic plasticity and memory. Finally, several modeling studies captured the implications of such findings for many brain functions. The ANLS model now represents a useful, experimentally based framework to better understand the coupling between neuronal activity and energetics as it relates to neuronal plasticity, neurodegeneration, and functional brain imaging.

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We study wave-induced fluid flow effects in porous rocks partially saturated with gas and water, where the saturation patterns are governed by mesoscopic heterogeneities associated with the dry frame properties. The link between the dry frame properties and the gas saturation is defined by the assumption of capillary pressure equilibrium, which in the presence of heterogeneity implies that neighboring regions can exhibit different levels of saturation. In order to determine the equivalent attenuation and phase velocity of the synthetic rock samples considered in this study, we apply a numerical upscaling procedure, which permits to take into account mesoscopic heterogeneities associated with the dry frame properties as well as spatially continuous variations of the pore fluid properties. We consider numerical experiments to analyze such effects in heterogeneous partially saturated porous media, where the saturation field is determined by realistic variations in porosity. Our results indicate that the spatially continuous nature of gas saturation inherent to this study is a critical parameter controlling the seismic response of these environments, which in turn suggests that the physical mechanisms governing partial saturation should be accounted for when analyzing seismic data in a poro-elastic context.

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Signals detected with functional brain imaging techniques are based on the coupling of neuronal activity with energy metabolism. Techniques such as positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) allow the visualization of brain areas that are activated by a variety of sensory, motor or cognitive tasks. Despite the technological sophistication of these brain imaging techniques, the precise mechanisms and cell types involved in coupling and in generating metabolic signals are still debated. Recent experimental data on the cellular and molecular mechanisms that underlie the fluorodeoxyglucose (FDG) - based PET imaging point to a critical role of a particular brain cell type, the astrocytes, in coupling neuronal activity to glucose utilization. Indeed, astrocytes possess receptors and re-uptake sites for a variety of neurotransmitters, including glutamate, the predominant excitatory neurotransmitter in the brain, In addition, astrocytic end-feet, which surround capillaries, are enriched in the specific glucose transporter GLUT-1. These features allow astrocytes to "sense" synaptic activity and to couple it with energy metabolism. In vivo and in vitro data support the following functional model: in response to glutamate released by active neurons, glucose is predominantly taken up by astrocytic end-feet; glucose is then metabolized to lactate which provides a preferred energy substrate for neurons. These data support the notion that astrocytes markedly contribute to the FDG-PET signal.

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Membrane proteins are notoriously difficult to express in a soluble form. Here, we use wheat germ cell-free expression in the presence of various detergents to produce the non-structural membrane proteins 2, 4B and 5A of the hepatitis C virus (HCV). We show that lauryl maltose neopentyl glycol (MNG-3) and dodecyl octaethylene glycol ether (C12E8) detergents can yield essentially soluble membrane proteins at detergent concentrations that do not inhibit the cell-free reaction. This finding can be explained by the low critical micelle concentration (CMC) of these detergents, which keeps the monomer concentrations low while at the same time providing the necessary excess of detergent concentration above CMC required for full target protein solubilization. We estimate that a tenfold excess of detergent micelles with respect to the protein concentration is sufficient for solubilization, a number that we propose as a guideline for detergent screening assays.

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Abstract Accurate characterization of the spatial distribution of hydrological properties in heterogeneous aquifers at a range of scales is a key prerequisite for reliable modeling of subsurface contaminant transport, and is essential for designing effective and cost-efficient groundwater management and remediation strategies. To this end, high-resolution geophysical methods have shown significant potential to bridge a critical gap in subsurface resolution and coverage between traditional hydrological measurement techniques such as borehole log/core analyses and tracer or pumping tests. An important and still largely unresolved issue, however, is how to best quantitatively integrate geophysical data into a characterization study in order to estimate the spatial distribution of one or more pertinent hydrological parameters, thus improving hydrological predictions. Recognizing the importance of this issue, the aim of the research presented in this thesis was to first develop a strategy for the assimilation of several types of hydrogeophysical data having varying degrees of resolution, subsurface coverage, and sensitivity to the hydrologic parameter of interest. In this regard a novel simulated annealing (SA)-based conditional simulation approach was developed and then tested in its ability to generate realizations of porosity given crosshole ground-penetrating radar (GPR) and neutron porosity log data. This was done successfully for both synthetic and field data sets. A subsequent issue that needed to be addressed involved assessing the potential benefits and implications of the resulting porosity realizations in terms of groundwater flow and contaminant transport. This was investigated synthetically assuming first that the relationship between porosity and hydraulic conductivity was well-defined. Then, the relationship was itself investigated in the context of a calibration procedure using hypothetical tracer test data. Essentially, the relationship best predicting the observed tracer test measurements was determined given the geophysically derived porosity structure. Both of these investigations showed that the SA-based approach, in general, allows much more reliable hydrological predictions than other more elementary techniques considered. Further, the developed calibration procedure was seen to be very effective, even at the scale of tomographic resolution, for predictions of transport. This also held true at locations within the aquifer where only geophysical data were available. This is significant because the acquisition of hydrological tracer test measurements is clearly more complicated and expensive than the acquisition of geophysical measurements. Although the above methodologies were tested using porosity logs and GPR data, the findings are expected to remain valid for a large number of pertinent combinations of geophysical and borehole log data of comparable resolution and sensitivity to the hydrological target parameter. Moreover, the obtained results allow us to have confidence for future developments in integration methodologies for geophysical and hydrological data to improve the 3-D estimation of hydrological properties.

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OBJECTIVE: Macrophages play a critical role in intestinal wound repair. However, the molecular pathways that regulate macrophage wound repair activities remain poorly understood. The aim of this study was to evaluate the role of GM-CSF receptor signaling in the wound repair activities of macrophages. METHODS: Murine macrophages were differentiated from bone marrow cells and human macrophages from monocytes isolated from peripheral blood mononuclear cells of Crohn's disease (CD) patients. In vitro models were used to study the repair activities of macrophages. RESULTS: We provide evidence that GM-CSF receptor signaling is required for murine macrophages to promote epithelial repair. In addition, we demonstrate that the deficient repair properties of macrophages from CD patients with active disease can be recovered via GM-CSF therapy. CONCLUSION: Our data support a critical role of the GM-CSF signaling pathway in the pro-repair activities of mouse and human macrophages. © 2014 S. Karger AG, Basel.