79 resultados para synergistic
Resumo:
Dendritic cells (DCs) as sentinels of the immune system are important for eliciting both primary and secondary immune responses to a plethora of microbial pathogens. Cooperative stimulation of a complex set of pattern-recognition receptors, including TLR2 and nucleotide-binding oligomerization domain (NOD)-like receptors on DCs, acts as a rate-limiting factor in determining the initiation and mounting of the robust immune response. It underscores the need for ``decoding'' these multiple receptor interactions. In this study, we demonstrate that TLR2 and NOD receptors cooperatively regulate functional maturation of human DCs. Intriguingly, synergistic stimulation of TLR2 and NOD receptors renders enhanced refractoriness to TGF-beta- or CTLA-4-mediated impairment of human DC maturation. Signaling perturbation data suggest that NOTCH1-PI3K signaling dynamics assume critical importance in TLR2- and NOD receptor-mediated surmounting of CTLA-4- and TGF-beta -suppressed maturation of human DCs. Interestingly, the NOTCH1-PI3K signaling axis holds the capacity to regulate DC functions by virtue of PKC delta-MAPK-dependent activation of NF-kappa B. This study provides mechanistic and functional insights into TLR2-and NOD receptor-mediated regulation of DC functions and unravels NOTCH1-PI3K as a signaling cohort for TLR2 and NOD receptors. These findings serve in building a conceptual foundation for the design of improved strategies for adjuvants and immunotherapies against infectious diseases.
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Freshwater ecosystems vary in size and composition and contain a wide range of organisms which interact with each other and with the environment. These interactions are between organisms and the environment as nutrient cycling, biomass formation and transfer, maintenance of internal environment and interactions with the external environment. The range of organisms present in aquatic communities decides the generation and transfer function of biomass, which defines and characterises the system. These organisms have distinct roles as they occupy particular trophic levels, forming an interconnected system in a food chain. Availability of resources and competition would primarily determine the balance of individual species within the food web, which in turn influences the variety and proportions of the different organisms, with important implications for the overall functioning of the system. This dynamic and diverse relationship decides the physical, chemical and biological elements across spatial and temporal scales in the aquatic ecosystem, which can be recorded by regular inventorying and monitoring to maintain the integrity and conserve the ecosystem. Regular environmental monitoring, particularly water quality monitoring allows us to detect, assess and manage the overall impacts on the rivers. The appreciation of water quality is in constant flux. Water quality assessments derived through the biotic indices, i.e. assessments based on observations of the resident floral and faunal communities has gained importance in recent years. Biological evaluations provide a description of the water quality that is often not achievable from elemental analyses alone. A biological indicator (or bioindicator) is a taxon or taxa selected based on its sensitivity to a particular attribute, and then assessed to make inferences about that attribute. In other words, they are a substitute for directly measuring abiotic features or other biota. Bioindicators are evaluated through presence or absence, condition, relative abundance, reproductive success, community structure (i.e. composition and diversity), community function (i.e. trophic structure), or any combination thereof.Biological communities reflect the overall ecological integrity by integrating various stresses, thus providing a broad measure of their synergistic impacts. Aquatic communities, both plants and animals, integrate and reflect the effects of chemical and physical disturbances that occur over extended periods of time. Monitoring procedures based on the biota measure the health of a river and the ability of aquatic ecosystems to support life as opposed to simply characterising the chemical and physical components of a particular system. This is the central purpose of assessing the biological condition of aquatic communities of a river.Diatoms (Bacillariophyceae), blue green algae (Cyanophyceae), green algae (Chlorophyceae), and red algae (Rhodphyceae) are the main groups of algae in flowing water. These organisms are widely used as biological indicators of environmental health in the aquatic ecosystem because algae occupy the most basic level in the transfer of energy through natural aquatic systems. The distribution of algae in an aquatic ecosystem is directly related to the fundamental factors such as physical, chemical and biological constituents. Soft algae (all the algal groups except diatoms) have also been used as indicators of biological integrity, but they may have less efficiency than diatoms in this respect due to their highly variable morphology. The diatoms (Bacillariophyceae) comprise a ubiquitous, highly successful and distinctive group of unicellular algae with the most obvious distinguishing characteristic feature being siliceous cell walls (frustules). The photosynthetic organisms living within its photic zone are responsible for about one-half of global primary productivity. The most successful organisms are thought to be photosynthetic prokaryotes (cyanobacteria and prochlorophytes) and a class of eukaryotic unicellular algae known as diatoms. Diatoms are likely to have arisen around 240 million years ago following an endosymbiotic event between a red eukaryotic alga and a heterotrophic flagellate related to the Oomycetes.The importance of algae to riverine ecology is easily appreciated when one considers that they are primary producers that convert inorganic nutrients into biologically active organic compounds while providing physical habitat for other organisms. As primary producers, algae transform solar energy into food from which many invertebrates obtain their energy. Algae also transform inorganic nutrients, such as atmospheric nitrogen into organic forms such as ammonia and amino acids that can be used by other organisms. Algae stabilises the substrate and creates mats that form structural habitats for fish and invertebrates. Algae are a source of organic matter and provide habitat for other organisms such as non-photosynthetic bacteria, protists, invertebrates, and fish. Algae's crucial role in stream ecosystems and their excellent indicator properties make them an important component of environmental studies to assess the effects of human activities on stream health. Diatoms are used as biological indicators for a number of reasons: 1. They occur in all types of aquatic ecosystems. 2. They collectively show a broad range of tolerance along a gradient of aquatic productivity, individual species have specific water chemistry requirements. 3. They have one of the shortest generation times of all biological indicators (~2 weeks). They reproduce and respond rapidly to environmental change and provide early measures of both pollution impacts and habitat restoration. 4. It takes two to three weeks before changes are reflected to a measurable extent in the assemblage composition.
Resumo:
Ce(0.65)Fe(0.33)Pt(0.02)O(2-delta) and Ce(0.67)Fe(0.33)O(2-delta) have been synthesized by a new low temperature sonochemical method using diethylenetriamine as a complexing agent. Due to the substitution of Fe and Pt ions in CeO(2), lattice oxygen is activated in Ce(0.67)Fe(0.33)O(2-delta) and Ce(0.65)Fe(0.33)Pt(0.02)O(2-delta). Hydrogen uptake studies show strong reduction peaks at 125 C in Ce(0.65)Fe(0.33)Pt(0.02)O(2-delta) against a hydrogen uptake peak at 420 degrees C in Ce(0.67)Fe(0.33)O(2-delta). Fe substituted ceria, Ce(0.67)Fe(0.33)O(2-delta) itself acts as a catalyst for CO oxidation and water gas shift (WGS) reactions at moderate temperatures. The rate of CO conversion in WGS with Pt free Ce(0.65)Fe(0.33)O(2-delta) is 2.8 mu mol g(-1) s(-1) at 450 C and with Pt substituted Ce(0.65)Fe(0.33)Pt(0.02)O(2-delta) is 4.05 mu mol g(-1) s(-1) at 275 degrees C. Due to the synergistic interaction of the Pt ion with Ce and Fe ions in Ce(0.65)Fe(0.33)Pt(0.02)O(2-delta), the catalyst showed much higher activity for CO oxidation and WGS reactions compared to Ce(0.67)Fe(0.33)O(2-delta). A reverse WGS reaction does not occur over Ce(0.65)Fe(0.33)Pt(0.02)O(2-delta). The catalyst also does not deactivate even when operated for a long time. Nearly 100% conversion of CO to CO(2) with 100% H(2) selectivity is observed in WGS reactions even up to 550 degrees C. (C) 2011 Elsevier B.V. All rights reserved.
Resumo:
Carbon nanomaterials (CNMs), such as exfoliated graphene (EG), long-chain functionalized EG, single-walled carbon nanotubes (SWNTs), and fullerene (C-60), have been investigated for their interaction with two structurally different gelators based on all-trans tri-p-phenylenevinylene bis-aldoxime (1) and n-lauroyl-L-alanine (2) both in solution and in supramolecular organogels. Gelation occurs in toluene through hydrogen bonding and van der Waals interactions for 1 and 2 in addition to pp stacking specifically in the case of 1. These nanocomposites provide a thorough understanding in terms of molecular-level interactions of dimensionally different CNMs with structurally different gelators. The presence of densely wrapped CNMs encapsulated fibrous network in the resulting composites is evident from various spectroscopic and microscopic studies, indicating the presence of supramolecular interactions. Concentration- and temperature-dependent UV/Vis and fluorescence spectra show that CNMs promote aggregation of the gelator molecules, leading to hypochromism and quenching of the fluorescence intensity. Thermotropic mesophases of 1 are altered by the inclusion of a small amount of CNMs. The gelCNM composites show increased electrical conductivity compared with that of the native organogel. Rheological studies of the composites demonstrate the formation of rigid and viscoelastic solidlike assembly due to reinforced aggregation of the gelators on CNMs. Synergistic behavior is observed in case of the composite gel of 1, containing a mixture of EG and SWNT, when compared with other mixtures of CNMs in all combinations with EG. This affords new nanocomposites with interesting optical, thermal, electrical, and mechanical properties.
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A growing understanding of the ecology of seed dispersal has so far had little influence on conservation practice, while the needs of conservation practice have had little influence on seed dispersal research. Yet seed dispersal interacts decisively with the major drivers of biodiversity change in the 21st century: habitat fragmentation, overharvesting, biological invasions, and climate change. We synthesize current knowledge of the effects these drivers have on seed dispersal to identify research gaps and to show how this information can be used to improve conservation management. The drivers, either individually, or in combination, have changed the quantity, species composition, and spatial pattern of dispersed seeds in the majority of ecosystems worldwide, with inevitable consequences for species survival in a rapidly changing world. The natural history of seed dispersal is now well-understood in a range of landscapes worldwide. Only a few generalizations that have emerged are directly applicable to conservation management, however, because they are frequently confounded by site-specific and species-specific variation. Potentially synergistic interactions between disturbances are likely to exacerbate the negative impacts, but these are rarely investigated. We recommend that the conservation status of functionally unique dispersers be revised and that the conservation target for key seed dispersers should be a population size that maintains their ecological function, rather than merely the minimum viable population. Based on our analysis of conservation needs, seed dispersal research should be carried out at larger spatial scales in heterogenous landscapes, examining the simultaneous impacts of multiple drivers on community-wide seed dispersal networks. (C) 2011 Elsevier Ltd. All rights reserved.
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This article presents the deformation behavior of high-strength pearlitic steel deformed by triaxial compression to achieve ultra-fine ferrite grain size with fragmented cementite. The consequent evolution of microstructure and texture has been studied using scanning electron microscopy, electron back-scatter diffraction, and X-ray diffraction. The synergistic effect of diffusion and deformation leads to the uniform dissolution of cementite at higher temperature. At lower temperature, significant grain refinement of ferrite phase occurs by deformation and exhibits a characteristic deformation texture. In contrast, the high-temperature deformed sample shows a weaker texture with cube component for the ferrite phase, indicating the occurrence of recrystallization. The different mechanisms responsible for the refinement of ferrite as well as the fragmentation of cementite and their interaction with each other have been analyzed. Viscoplastic self-consistent simulation was employed to understand deformation texture in the ferrite phase during triaxial compression.
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The Morse-Smale complex is a topological structure that captures the behavior of the gradient of a scalar function on a manifold. This paper discusses scalable techniques to compute the Morse-Smale complex of scalar functions defined on large three-dimensional structured grids. Computing the Morse-Smale complex of three-dimensional domains is challenging as compared to two-dimensional domains because of the non-trivial structure introduced by the two types of saddle criticalities. We present a parallel shared-memory algorithm to compute the Morse-Smale complex based on Forman's discrete Morse theory. The algorithm achieves scalability via synergistic use of the CPU and the GPU. We first prove that the discrete gradient on the domain can be computed independently for each cell and hence can be implemented on the GPU. Second, we describe a two-step graph traversal algorithm to compute the 1-saddle-2-saddle connections efficiently and in parallel on the CPU. Simultaneously, the extremasaddle connections are computed using a tree traversal algorithm on the GPU.
Resumo:
Clustered architecture processors are preferred for embedded systems because centralized register file architectures scale poorly in terms of clock rate, chip area, and power consumption. Although clustering helps by improving the clock speed, reducing the energy consumption of the logic, and making the design simpler, it introduces extra overheads by way of inter-cluster communication. This communication happens over long global wires having high load capacitance which leads to delay in execution and significantly high energy consumption. Inter-cluster communication also introduces many short idle cycles, thereby significantly increasing the overall leakage energy consumption in the functional units. The trend towards miniaturization of devices (and associated reduction in threshold voltage) makes energy consumption in interconnects and functional units even worse, and limits the usability of clustered architectures in smaller technologies. However, technological advancements now permit the design of interconnects and functional units with varying performance and power modes. In this paper, we propose scheduling algorithms that aggregate the scheduling slack of instructions and communication slack of data values to exploit the low-power modes of functional units and interconnects. Finally, we present a synergistic combination of these algorithms that simultaneously saves energy in functional units and interconnects to improves the usability of clustered architectures by achieving better overall energy-performance trade-offs. Even with conservative estimates of the contribution of the functional units and interconnects to the overall processor energy consumption, the proposed combined scheme obtains on average 8% and 10% improvement in overall energy-delay product with 3.5% and 2% performance degradation for a 2-clustered and a 4-clustered machine, respectively. We present a detailed experimental evaluation of the proposed schemes. Our test bed uses the Trimaran compiler infrastructure. (C) 2012 Elsevier Inc. All rights reserved.
Resumo:
A new two-step synthesis of ZrO2-MCM nanocomposites using the gel combustion technique was accomplished; the resulting material had a high-surface area and showed very high adsorption activity. The deposition of 25 nm ZrO2 particles over MCM was achieved using gel combustion technique with glycine as a fuel, and the formation of nanocomposites was confirmed using transmission electron microscopy. The composites were also characterized by XRD, SEM, FTIR and N2 adsorption-desorption analysis. The nanocomposites were tested for the adsorption of cationic dyes. High rates of adsorption and large dye uptake were observed over the nanocomposites. The rate of adsorption over the nanocomposites was higher than that observed for physical ZrO2-MCM mixtures and commercial activated carbon. The nanocomposite with 10 wt % ZrO2 showed the highest rate of adsorption owing to the synergistic effects of ZrO2 surface groups, smaller particle size, fine dispersion and high-surface area of the composite. (c) 2012 American Institute of Chemical Engineers AIChE J, 58: 29872996, 2012
Resumo:
We report the first observation and analytical model of deformation and spreading of droplets on a vibrating surface under the influence of an ultrasonic standing pressure field. The standing wave allows the droplet to spread, and the spreading rate varies inversely with viscosity. In low viscosity droplets, the synergistic effect of radial acoustic force and the transducer surface acceleration also leads to capillary waves. These unstable capillary modes grow to cause ultimate disintegration into daughter droplets. We find that using nanosuspensions, spreading and disintegration can be prevented by suppressing the development of capillary modes and subsequent break-up. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.4757567]
Resumo:
S100A2, an EF hand calcium-binding protein, is a potential biomarker in several cancers and is also a TGF-beta (transforming growth factor-beta)-regulated gene in melanoma and lung cancer cells. However, the mechanism of S100A2 regulation by TGF-beta and its significance in cancer progression remains largely unknown. In the present study we report the mechanism of S100A2 regulation by TGF-beta and its possible role in TGF-beta-mediated tumour promotion. Characterization of the S100A2 promoter revealed an AP-1 (activator protein-1) element at positions -1161 to -1151 as being the most critical factor for the TGF-beta 1 response. Chromatin immunoprecipitation and electrophoretic mobility-shift assays confirmed the functional binding of the AP-1 complex, predominantly JunB, to the S100A2 promoter in response to TGF-beta 1 in HaCaT keratinocytes. JunB overexpression markedly stimulated the S100A2 promoter which was blocked by the dominant-negative JunB and MEK1 MAPK (mitogen-activated protein kinase)/ERK (extracellular-signal-regulated kinase) kinase 1] inhibitor, PD98059. Intriguingly, despite the presence of a putative SMAD-binding element, S100A2 regulation by TGF-beta 1 was found to be SMAD3 independent. Interestingly, p53 protein and TGF-beta 1 show synergistic regulation of the S100A2 promoter. Finally, knockdown of S100A2 expression compromised TGF-beta 1-induced cell migration and invasion of Hep3B cells. Together our findings highlight an important link between the TGF-beta 1-induced MAPK and p53 signalling pathways in the regulation of S100A2 expression and pro-tumorigenic actions.
Resumo:
Theoretical and computational frameworks for synaptic plasticity and learning have a long and cherished history, with few parallels within the well-established literature for plasticity of voltage-gated ion channels. In this study, we derive rules for plasticity in the hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, and assess the synergy between synaptic and HCN channel plasticity in establishing stability during synaptic learning. To do this, we employ a conductance-based model for the hippocampal pyramidal neuron, and incorporate synaptic plasticity through the well-established Bienenstock-Cooper-Munro (BCM)-like rule for synaptic plasticity, wherein the direction and strength of the plasticity is dependent on the concentration of calcium influx. Under this framework, we derive a rule for HCN channel plasticity to establish homeostasis in synaptically-driven firing rate, and incorporate such plasticity into our model. In demonstrating that this rule for HCN channel plasticity helps maintain firing rate homeostasis after bidirectional synaptic plasticity, we observe a linear relationship between synaptic plasticity and HCN channel plasticity for maintaining firing rate homeostasis. Motivated by this linear relationship, we derive a calcium-dependent rule for HCN-channel plasticity, and demonstrate that firing rate homeostasis is maintained in the face of synaptic plasticity when moderate and high levels of cytosolic calcium influx induced depression and potentiation of the HCN-channel conductance, respectively. Additionally, we show that such synergy between synaptic and HCN-channel plasticity enhances the stability of synaptic learning through metaplasticity in the BCM-like synaptic plasticity profile. Finally, we demonstrate that the synergistic interaction between synaptic and HCN-channel plasticity preserves robustness of information transfer across the neuron under a rate-coding schema. Our results establish specific physiological roles for experimentally observed plasticity in HCN channels accompanying synaptic plasticity in hippocampal neurons, and uncover potential links between HCN-channel plasticity and calcium influx, dynamic gain control and stable synaptic learning.
Resumo:
Heterogeneity in tumors has led to the development of combination therapies that enable enhanced cell death. Previously explored combination therapies mostly involved the use of bioactive molecules. In this work, we explored a non-conventional strategy of using carbon nanostructures (CNs) single walled carbon nanotube (SWNT) and graphene oxide (GO)] for potentiating the efficacy of a bioactive molecule paclitaxel (Tx)] for the treatment of lung cancer. The results demonstrated enhanced cell death following combination treatment of SWNT/GO and Tx indicating a synergistic effect. In addition, synergism was abrogated in the presence of an anti-oxidant, N-acetyl cysteine (NAC), and was therefore shown to be reactive oxygen species (ROS) dependent. It was further demonstrated using bromodeoxyuridine (BrdU) incorporation assay that treatment with CNs was associated with enhanced mitogen associated protein kinase (MAPK) activation that was ROS mediated. Hence, these results for the first time demonstrated the potential of SWNT/GO as co-therapeutic agents with Tx for the treatment of lung cancer.
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Welding parameters like welding speed, rotation speed, plunge depth, shoulder diameter etc., influence the weld zone properties, microstructure of friction stir welds, and forming behavior of welded sheets in a synergistic fashion. The main aims of the present work are to (1) analyze the effect of welding speed, rotation speed, plunge depth, and shoulder diameter on the formation of internal defects during friction stir welding (FSW), (2) study the effect on axial force and torque during welding, (c) optimize the welding parameters for producing internal defect-free welds, and (d) propose and validate a simple criterion to identify defect-free weld formation. The base material used for FSW throughout the work is Al 6061T6 having a thickness value of 2.1 mm. Only butt welding of sheets is aimed in the present work. It is observed from the present analysis that higher welding speed, higher rotation speed, and higher plunge depth are preferred for producing a weld without internal defects. All the shoulder diameters used for FSW in the present work produced defect-free welds. The axial force and torque are not constant and a large variation is seen with respect to FSW parameters that produced defective welds. In the case of defect-free weld formation, the axial force and torque are relatively constant. A simple criterion, (a,tau/a,p)(defective) > (a,tau/a,p)(defect free) and (a,F/a,p)(defective) > (a,F/a,p)(defect free), is proposed with this observation for identifying the onset of defect-free weld formation. Here F is axial force, tau is torque, and p is welding speed or tool rotation speed or plunge depth. The same criterion is validated with respect to Al 5xxx base material. Even in this case, the axial force and torque remained constant while producing defect-free welds.
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We present a comprehensive study of two of the most experimentally relevant extensions of Kitaev's spinless model of a one-dimensional p-wave superconductor: those involving (i) longer-range hopping and superconductivity and (ii) inhomogeneous potentials. We commence with a pedagogical review of the spinless model and, as a means of characterizing topological phases exhibited by the systems studied here, we introduce bulk topological invariants as well as those derived from an explicit consideration of boundary modes. In time-reversal symmetric systems, we find that the longer range hopping leads to topological phases characterized by multiple Majorana modes. In particular, we investigate a spin model that respects a duality and maps to a fermionic model with multiple Majorana modes; we highlight the connection between these topological phases and the broken symmetry phases in the original spin model. In the presence of time-reversal symmetry breaking terms, we show that the topological phase diagram is characterized by an extended gapless regime. For the case of inhomogeneous potentials, we explore phase diagrams of periodic, quasiperiodic, and disordered systems. We present a detailed mapping between normal state localization properties of such systems and the topological phases of the corresponding superconducting systems. This powerful tool allows us to leverage the analyses of Hofstadter's butterfly and the vast literature on Anderson localization to the question of Majorana modes in superconducting quasiperiodic and disordered systems, respectively. We briefly touch upon the synergistic effects that can be expected in cases where long-range hopping and disorder are both present.