950 resultados para Meaning transfer model
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Plasmids carry a wide range of genes that are often involved in bacterial social behaviour. The question of why such genes are frequently mobile has received increasing attention. Here, we use an explicit population genetic approach to model the evolution of plasmid-borne bacterial public goods production. Our findings highlight the importance of both transmission and relatedness as factors driving the evolution of plasmid-borne public goods production. We partition the effects of plasmid transfer of social traits into those of infectivity and the effect of increased relatedness. Our results demonstrate that, owing to its effect on relatedness, plasmid mobility increases the invasion and stability of public goods, in a way not seen in individually beneficial traits. In addition, we show that plasmid transfer increases relatedness when public goods production is rare but this effect declines when production is common, with both scenarios leading to an increase in the frequency of plasmid-borne public goods. Plasmids remain important vectors for the spread of social genes involved in bacterial virulence thus an understanding of their dynamics is highly relevant from a public health perspective.
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We report a spectroscopic study about the energy transfer mechanism among silicon nanoparticles (Si-np), both amorphous and crystalline, and Er ions in a silicon dioxide matrix. From infrared spectroscopic analysis, we have determined that the physics of the transfer mechanism does not depend on the Si-np nature, finding a fast (< 200 ns) energy transfer in both cases, while the amorphous nanoclusters reveal a larger transfer efficiency than the nanocrystals. Moreover, the detailed spectroscopic results in the visible range here reported are essential to understand the physics behind the sensitization effect, whose knowledge assumes a crucial role to enhance the transfer rate and possibly employing the material in optical amplifier devices. Joining the experimental data, performed with pulsed and continuous-wave excitation, we develop a model in which the internal intraband recombination within Si-np is competitive with the transfer process via an Auger electron"recycling" effect. Posing a different light on some detrimental mechanism such as Auger processes, our findings clearly recast the role of Si-np in the sensitization scheme, where they are able to excite very efficiently ions in close proximity to their surface. (C) 2010 American Institute of Physics.
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Microcirculation (2010) 17, 69-78. doi: 10.1111/j.1549-8719.2010.00002.x Abstract Background: This study was designed to explore the effect of transient inducible nitric oxide synthase (iNOS) overexpression via cationic liposome-mediated gene transfer on cardiac function, fibrosis, and microvascular perfusion in a porcine model of chronic ischemia. Methods and Results: Chronic myocardial ischemia was induced using a minimally invasive model in 23 landrace pigs. Upon demonstration of heart failure, 10 animals were treated with liposome-mediated iNOS-gene-transfer by local intramyocardial injection and 13 animals received a sham procedure to serve as control. The efficacy of this iNOS-gene-transfer was demonstrated for up to 7 days by reverse transcriptase-polymerase chain reaction in preliminary studies. Four weeks after iNOS transfer, magnetic resonance imaging showed no effect of iNOS overexpression on cardiac contractility at rest and during dobutamine stress (resting ejection fraction: control 27%, iNOS 26%; P = ns). Late enhancement, infarct size, and the amount of fibrosis were similar between groups. Although perfusion and perfusion reserve in response to adenosine and dobutamine were not significantly modified by iNOS-transfer, both vessel number and diameter were significantly increased in the ischemic area in the iNOS-treated group versus control (point score: control 15.3, iNOS 34.7; P < 0.05). Conclusions: Our findings demonstrate that transient iNOS overexpression does not aggravate cardiac dysfunction or postischemic fibrosis, while potentially contributing to neovascularization in the chronically ischemic heart.
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A systematic assessment of global neural network connectivity through direct electrophysiological assays has remained technically infeasible, even in simpler systems like dissociated neuronal cultures. We introduce an improved algorithmic approach based on Transfer Entropy to reconstruct structural connectivity from network activity monitored through calcium imaging. We focus in this study on the inference of excitatory synaptic links. Based on information theory, our method requires no prior assumptions on the statistics of neuronal firing and neuronal connections. The performance of our algorithm is benchmarked on surrogate time series of calcium fluorescence generated by the simulated dynamics of a network with known ground-truth topology. We find that the functional network topology revealed by Transfer Entropy depends qualitatively on the time-dependent dynamic state of the network (bursting or non-bursting). Thus by conditioning with respect to the global mean activity, we improve the performance of our method. This allows us to focus the analysis to specific dynamical regimes of the network in which the inferred functional connectivity is shaped by monosynaptic excitatory connections, rather than by collective synchrony. Our method can discriminate between actual causal influences between neurons and spurious non-causal correlations due to light scattering artifacts, which inherently affect the quality of fluorescence imaging. Compared to other reconstruction strategies such as cross-correlation or Granger Causality methods, our method based on improved Transfer Entropy is remarkably more accurate. In particular, it provides a good estimation of the excitatory network clustering coefficient, allowing for discrimination between weakly and strongly clustered topologies. Finally, we demonstrate the applicability of our method to analyses of real recordings of in vitro disinhibited cortical cultures where we suggest that excitatory connections are characterized by an elevated level of clustering compared to a random graph (although not extreme) and can be markedly non-local.
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Under field conditions in the Amazon forest, soil bulk density is difficult to measure. Rigorous methodological criteria must be applied to obtain reliable inventories of C stocks and soil nutrients, making this process expensive and sometimes unfeasible. This study aimed to generate models to estimate soil bulk density based on parameters that can be easily and reliably measured in the field and that are available in many soil-related inventories. Stepwise regression models to predict bulk density were developed using data on soil C content, clay content and pH in water from 140 permanent plots in terra firme (upland) forests near Manaus, Amazonas State, Brazil. The model results were interpreted according to the coefficient of determination (R2) and Akaike information criterion (AIC) and were validated with a dataset consisting of 125 plots different from those used to generate the models. The model with best performance in estimating soil bulk density under the conditions of this study included clay content and pH in water as independent variables and had R2 = 0.73 and AIC = -250.29. The performance of this model for predicting soil density was compared with that of models from the literature. The results showed that the locally calibrated equation was the most accurate for estimating soil bulk density for upland forests in the Manaus region.
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The observation that real complex networks have internal structure has important implication for dynamic processes occurring on such topologies. Here we investigate the impact of community structure on a model of information transfer able to deal with both search and congestion simultaneously. We show that networks with fuzzy community structure are more efficient in terms of packet delivery than those with pronounced community structure. We also propose an alternative packet routing algorithm which takes advantage of the knowledge of communities to improve information transfer and show that in the context of the model an intermediate level of community structure is optimal. Finally, we show that in a hierarchical network setting, providing knowledge of communities at the level of highest modularity will improve network capacity by the largest amount.
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The State of Santa Catarina, Brazil, has agricultural and livestock activities, such as pig farming, that are responsible for adding large amounts of phosphorus (P) to soils. However, a method is required to evaluate the environmental risk of these high soil P levels. One possible method for evaluating the environmental risk of P fertilization, whether organic or mineral, is to establish threshold levels of soil available P, measured by Mehlich-1 extractions, below which there is not a high risk of P transfer from the soil to surface waters. However, the Mehlich-1 extractant is sensitive to soil clay content, and that factor should be considered when establishing such P-thresholds. The objective of this study was to determine P-thresholds using the Mehlich-1 extractant for soils with different clay contents in the State of Santa Catarina, Brazil. Soil from the B-horizon of an Oxisol with 800 g kg-1 clay was mixed with different amounts of sand to prepare artificial soils with 200, 400, 600, and 800 g kg-1 clay. The artificial soils were incubated for 30 days with moisture content at 80 % of field capacity to stabilize their physicochemical properties, followed by additional incubation for 30 days after liming to raise the pH(H2O) to 6.0. Soil P sorption curves were produced, and the maximum sorption (Pmax) was determined using the Langmuir model for each soil texture evaluated. Based on the Pmax values, seven rates of P were added to four replicates of each soil, and incubated for 20 days more. Following incubation, available P contents (P-Mehlich-1) and P dissolved in the soil solution (P-water) were determined. A change-point value (the P-Mehlich-1 value above which P-water starts increasing sharply) was calculated through the use of segmented equations. The maximum level of P that a soil might safely adsorb (P-threshold) was defined as 80 % of the change-point value to maintain a margin for environmental safety. The P-threshold value, in mg dm-3, was dependent on the soil clay content according to the model P-threshold = 40 + Clay, where the soil clay content is expressed as a percentage. The model was tested in 82 diverse soil samples from the State of Santa Catarina and was able to distinguish samples with high and low environmental risk.
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Stimulation of resident cells by NF-κB activating cytokines is a central element of inflammatory and degenerative disorders of the central nervous system (CNS). This disease-mediated NF-κB activation could be used to drive transgene expression selectively in affected cells, using adeno-associated virus (AAV)-mediated gene transfer. We have constructed a series of AAV vectors expressing GFP under the control of different promoters including NF-κB -responsive elements. As an initial screen, the vectors were tested in vitro in HEK-293T cells treated with TNF-α. The best profile of GFP induction was obtained with a promoter containing two blocks of four NF-κB -responsive sequences from the human JCV neurotropic polyoma virus promoter, fused to a new tight minimal CMV promoter, optimally distant from each other. A therapeutical gene, glial cell line-derived neurotrophic factor (GDNF) cDNA under the control of serotype 1-encapsidated NF-κB -responsive AAV vector (AAV-NF) was protective in senescent cultures of mouse cortical neurons. AAV-NF was then evaluated in vivo in the kainic acid (KA)-induced status epilepticus rat model for temporal lobe epilepsy, a major neurological disorder with a central pathophysiological role for NF-κB activation. We demonstrate that AAV-NF, injected in the hippocampus, responded to disease induction by mediating GFP expression, preferentially in CA1 and CA3 neurons and astrocytes, specifically in regions where inflammatory markers were also induced. Altogether, these data demonstrate the feasibility to use disease-activated transcription factor-responsive elements in order to drive transgene expression specifically in affected cells in inflammatory CNS disorders using AAV-mediated gene transfer.
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Finite cluster models and a variety of ab initio wave functions have been used to study the electronic structure of bulk KNiF3. Several electronic states, including the ground state and some charge-transfer excited states, have been considered. The study of the cluster-model wave functions has permitted an understanding of the nature of the chemical bond in the electronic ground state. This is found to be highly ionic and the different ionic and covalent contributions to the bonding have been identified and quantified. Finally, we have studied the charge-transfer excited states leading to the optical gap and have found that calculated and experimental values are in good agreement. The wave functions corresponding to these excited states have also been analyzed and show that although KNiF3 may be described as a ligand-to-metal charge-transfer insulator there is a strong configuration mixing with the metal-to-metal charge-transfer states.
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This study aims to improve the accuracy of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 130 representative pavement sites across Iowa were selected. The selected pavement sites represent flexible, rigid, and composite pavement systems throughout Iowa. The required MEPDG inputs and the historical performance data for the selected sites were extracted from a variety of sources. The accuracy of the nationally-calibrated MEPDG prediction models for Iowa conditions was evaluated. The local calibration factors of MEPDG performance prediction models were identified to improve the accuracy of model predictions. The identified local calibration coefficients are presented with other significant findings and recommendations for use in MEPDG/DARWin-ME for Iowa pavement systems.
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Genomic islands (GEIs) are large DNA segments, present in most bacterial genomes, that are most likely acquired via horizontal gene transfer. Here, we study the self-transfer system of the integrative and conjugative element ICEclc of Pseudomonas knackmussii B13, which stands model for a larger group of ICE/GEI with syntenic core gene organization. Functional screening revealed that unlike conjugative plasmids and other ICEs ICEclc carries two separate origins of transfer, with different sequence context but containing a similar repeat motif. Conjugation experiments with GFP-labelled ICEclc variants showed that both oriTs are used for transfer and with indistinguishable efficiencies, but that having two oriTs results in an estimated fourfold increase of ICEclc transfer rates in a population compared with having a single oriT. A gene for a relaxase essential for ICEclc transfer was also identified, but in vivo strand exchange assays suggested that the relaxase processes both oriTs in a different manner. This unique dual origin of transfer system might have provided an evolutionary advantage for distribution of ICE, a hypothesis that is supported by the fact that both oriT regions are conserved in several GEIs related to ICEclc.
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Integrative and conjugative elements (ICEs) are particularly interesting model systems for horizontal gene transfer, because they normally reside in an integrated state in the host chromosome but can excise and self-transfer under particular conditions, typically requiring exquisite regulatory cascades. Despite important advances in our understanding of the transfer mechanisms of a number of ICE, many essential details are lacking. Recently we reported that ICEclc, a 103 kb ICE of Pseudomonas knackmussii B13, has two active origins of transfer (oriTs), which is very much unlike conjugative plasmids that usually employ a single oriT. We discuss here how this dual oriT system could function and how it actually could have presented an evolutionary advantage for ICEclc distribution.
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PURPOSE: Local breast cancer relapse after breast-saving surgery and radiotherapy is associated with increased risk of distant metastasis formation. The mechanisms involved remain largely elusive. We used the well-characterized 4T1 syngeneic, orthotopic breast cancer model to identify novel mechanisms of postradiation metastasis. EXPERIMENTAL DESIGN: 4T1 cells were injected in 20 Gy preirradiated mammary tissue to mimic postradiation relapses, or in nonirradiated mammary tissue, as control, of immunocompetent BALB/c mice. Molecular, biochemical, cellular, histologic analyses, adoptive cell transfer, genetic, and pharmacologic interventions were carried out. RESULTS: Tumors growing in preirradiated mammary tissue had reduced angiogenesis and were more hypoxic, invasive, and metastatic to lung and lymph nodes compared with control tumors. Increased metastasis involved the mobilization of CD11b(+)c-Kit(+)Ly6G(high)Ly6C(low)(Gr1(+)) myeloid cells through the HIF1-dependent expression of Kit ligand (KitL) by hypoxic tumor cells. KitL-mobilized myeloid cells homed to primary tumors and premetastatic lungs, to give rise to CD11b(+)c-Kit(-) cells. Pharmacologic inhibition of HIF1, silencing of KitL expression in tumor cells, and inhibition of c-Kit with an anti-c-Kit-blocking antibody or with a tyrosine kinase inhibitor prevented the mobilization of CD11b(+)c-Kit(+) cells and attenuated metastasis. C-Kit inhibition was also effective in reducing mobilization of CD11b(+)c-Kit(+) cells and inhibiting lung metastasis after irradiation of established tumors. CONCLUSIONS: Our work defines KitL/c-Kit as a previously unidentified axis critically involved in promoting metastasis of 4T1 tumors growing in preirradiated mammary tissue. Pharmacologic inhibition of this axis represents a potential therapeutic strategy to prevent metastasis in breast cancer patients with local relapses after radiotherapy. Clin Cancer Res; 18(16); 4365-74. ©2012 AACR.
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PURPOSE: The longitudinal relaxation rate (R1 ) measured in vivo depends on the local microstructural properties of the tissue, such as macromolecular, iron, and water content. Here, we use whole brain multiparametric in vivo data and a general linear relaxometry model to describe the dependence of R1 on these components. We explore a) the validity of having a single fixed set of model coefficients for the whole brain and b) the stability of the model coefficients in a large cohort. METHODS: Maps of magnetization transfer (MT) and effective transverse relaxation rate (R2 *) were used as surrogates for macromolecular and iron content, respectively. Spatial variations in these parameters reflected variations in underlying tissue microstructure. A linear model was applied to the whole brain, including gray/white matter and deep brain structures, to determine the global model coefficients. Synthetic R1 values were then calculated using these coefficients and compared with the measured R1 maps. RESULTS: The model's validity was demonstrated by correspondence between the synthetic and measured R1 values and by high stability of the model coefficients across a large cohort. CONCLUSION: A single set of global coefficients can be used to relate R1 , MT, and R2 * across the whole brain. Our population study demonstrates the robustness and stability of the model. Magn Reson Med, 2014. © 2014 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. Magn Reson Med 73:1309-1314, 2015. © 2014 Wiley Periodicals, Inc.