980 resultados para Neuro-astroglial interaction model


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Drug-induced respiratory depression is a common side effect of the agents used in anesthesia practice to provide analgesia and sedation. Depression of the ventilatory drive in the spontaneously breathing patient can lead to severe cardiorespiratory events and it is considered a primary cause of morbidity. Reliable predictions of respiratory inhibition in the clinical setting would therefore provide a valuable means to improve the safety of drug delivery. Although multiple studies investigated the regulation of breathing in man both in the presence and absence of ventilatory depressant drugs, a unified description of respiratory pharmacodynamics is not available. This study proposes a mathematical model of human metabolism and cardiorespiratory regulation integrating several isolated physiological and pharmacological aspects of acute drug-induced ventilatory depression into a single theoretical framework. The description of respiratory regulation has a parsimonious yet comprehensive structure with substantial predictive capability. Simulations relative to the synergistic interaction of the hypercarbic and hypoxic respiratory drive and the global effect of drugs on the control of breathing are in good agreement with published experimental data. Besides providing clinically relevant predictions of respiratory depression, the model can also serve as a test bed to investigate issues of drug tolerability and dose finding/control under non-steady-state conditions.

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The solution structure of cupiennin 1a, a 35 residue, basic antibacterial peptide isolated from the venom of the spider Cupiennius salei, has been determined by nuclear magnetic resonance (NMR) spectroscopy. The peptide was found to adopt a helix−hinge−helix structure in a membrane mimicking solvent. The hinge may play a role in allowing the amphipathic N-terminal helix and polar C-terminal helix to orient independently upon membrane binding, in order to achieve maximal antibacterial efficacy. Solid-state 31P and 2H NMR was used to further study the effects of cupiennin 1a on the dynamic properties of lipid membranes, using zwitterionic chain deuterated dimyristoylphosphatidylcholine (d54-DMPC) and anionic dimyristoylphosphatidylglycerol (DMPG) multilamellar vesicles. In d54-DMPC alone, cupiennin 1a caused a decrease in the 31P chemical shift anisotropy, indicating some interaction with the lipid head groups, and a decrease in order over the entire acyl chain. In contrast, for the mixed (d54-DMPC/DMPG) lipid system cupiennin 1a appeared to induce lateral separation of the two lipids as evidenced by the 31P spectra, in which the peptide preferentially interacted with DMPG. Little effect was observed on the deuterated acyl chain order parameters in the d54-DMPC/DMPG model membranes. Furthermore, 31P NMR relaxation measurements confirmed a differential effect on the lipid motions depending upon the membrane composition. Therefore, subtle differences are likely in the mechanism by which cupiennin 1a causes membrane lysis in either prokaryotic or eukaryotic cells, and may explain the specific spectrum of activity.

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The molecular interactions between the host molecule, perthiolated beta-cyclodextrin (CD), and the guest molecules, adamantaneacetic acid (AD) and ferroceneacetic acid (FC), have been inestigated theoretically in both the gas and aqueous phases. The major computations have been carried out at the theoretical levels, RHF/6-31G and B3LYP/6- 31G. MP2 electronic energies were also computed based at the geometries optimized by both the RHF and B3LYP methods in the gas phase to establish a better estimate of the correlation effect. The solvent phase computations were completed at the RHF/6-31G and B3LYP/6-31G levels using the PCM model. The most stable structures optimized in gas phase by both the RHF and B3LYP methods were used for the computations in solution. A method to systematically manipulate the relative position and orientation between the interacting molecules is proposed. In the gas phase, six trials with different host-guest relative positions and orientations were completed successfully with the B3LYP method for both the CD-AD and CD-FC complexes. Only four trials were completed with RHF method. In the gas phase, the best results from the RHF method gives for the association Gibbs free energy (ΔG°) values equal to -32.21kj/mol for CD-AD and -25.73kj/mol for CD-FC. And the best results from the B3LYP method have ΔG° equal to -47.57kj/mol for CD-AD and -41.09kj/mol for CD-FC. The MP2 correction significantly lowers ΔG° based on the geometries from both methods. For the RHF structure, the MP2 computations lowered ΔG° to -60.64kj/mol for CD-AD and -54.10 for CD-FC. For the structure from the B3LYP method, it was reduced to -59.87 kj/mol for CD-AD and -54.84 kj/mol for CDFC. The RHF solvent phase calculations yielded following results: ΔG°(aq) equals 107.2kj/mol for CD-AD and 111.4kj/mol for CD-FC. Compared with the results from the RHF method, the B3LYP method provided clearly better solvent phase results with ΔG° (aq) equal to 38.64kj/mol for CD-AD and 39.61kj/mol for CD-FC. These results qualitatively explain the experimental observations. However quantitatively they are in poor agreement with the experimental values available in the literature and those recently published by Liu et al. And the reason is believed to be omission of hydrophobic contribution to the association. Determining the global geometrical minima for these very large systems was very difficult and computationally time consuming, but after a very thorough search, these were identified. A relevant result of this search is that when the complexes, CD-AD and CD-FC, are formed, the AD and FC molecules are only partially embedded inside the CD cavity. The totally embedded complexes were found to have significantly higher energies. The semiempirical method, ZINDO, was employed to investigate the effect of complexation on the first electronic excitation of CD anchored to a metal nano-particle. The computational results revealed that after complexation to FC, the transition intensity declines to about 25% of the original value, and after complexation with AD, the intensity drops almost 50%. The tighter binding and transition intensity of CD-AD qualitatively agrees with the experimental result that the addition of AD to a solution of CD and FC restores the fluorescence of CD that was quenched by the addition of FC. A method to evaluate the “hydrophobic force” effect is proposed for future work.

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The potential health effects of inhaled engineered nanoparticles are almost unknown. To avoid and replace toxicity studies with animals, a triple cell co-culture system composed of epithelial cells, macrophages and dendritic cells was established, which simulates the most important barrier functions of the epithelial airway. Using this model, the toxic potential of titanium dioxide was assessed by measuring the production of reactive oxygen species and the release of tumour necrosis factor alpha. The intracellular localisation of titanium dioxide nanoparticles was analyzed by energy filtering transmission electron microscopy. Titanium dioxide nanoparticles were detected as single particles without membranes and in membrane-bound agglomerates. Cells incubated with titanium dioxide particles showed an elevated production of reactive oxygen species but no increase of the release of tumour necrosis factor alpha. Our in vitro model of the epithelial airway barrier offers a valuable tool to study the interaction of particles with lung cells at a nanostructural level and to investigate the toxic potential of nanoparticles.

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Reducing the uncertainties related to blade dynamics by the improvement of the quality of numerical simulations of the fluid structure interaction process is a key for a breakthrough in wind-turbine technology. A fundamental step in that direction is the implementation of aeroelastic models capable of capturing the complex features of innovative prototype blades, so they can be tested at realistic full-scale conditions with a reasonable computational cost. We make use of a code based on a combination of two advanced numerical models implemented in a parallel HPC supercomputer platform: First, a model of the structural response of heterogeneous composite blades, based on a variation of the dimensional reduction technique proposed by Hodges and Yu. This technique has the capacity of reducing the geometrical complexity of the blade section into a stiffness matrix for an equivalent beam. The reduced 1-D strain energy is equivalent to the actual 3-D strain energy in an asymptotic sense, allowing accurate modeling of the blade structure as a 1-D finite-element problem. This substantially reduces the computational effort required to model the structural dynamics at each time step. Second, a novel aerodynamic model based on an advanced implementation of the BEM(Blade ElementMomentum) Theory; where all velocities and forces are re-projected through orthogonal matrices into the instantaneous deformed configuration to fully include the effects of large displacements and rotation of the airfoil sections into the computation of aerodynamic forces. This allows the aerodynamic model to take into account the effects of the complex flexo-torsional deformation that can be captured by the more sophisticated structural model mentioned above. In this thesis we have successfully developed a powerful computational tool for the aeroelastic analysis of wind-turbine blades. Due to the particular features mentioned above in terms of a full representation of the combined modes of deformation of the blade as a complex structural part and their effects on the aerodynamic loads, it constitutes a substantial advancement ahead the state-of-the-art aeroelastic models currently available, like the FAST-Aerodyn suite. In this thesis, we also include the results of several experiments on the NREL-5MW blade, which is widely accepted today as a benchmark blade, together with some modifications intended to explore the capacities of the new code in terms of capturing features on blade-dynamic behavior, which are normally overlooked by the existing aeroelastic models.

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As an important Civil Engineering material, asphalt concrete (AC) is commonly used to build road surfaces, airports, and parking lots. With traditional laboratory tests and theoretical equations, it is a challenge to fully understand such a random composite material. Based on the discrete element method (DEM), this research seeks to develop and implement computer models as research approaches for improving understandings of AC microstructure-based mechanics. In this research, three categories of approaches were developed or employed to simulate microstructures of AC materials, namely the randomly-generated models, the idealized models, and image-based models. The image-based models were recommended for accurately predicting AC performance, while the other models were recommended as research tools to obtain deep insight into the AC microstructure-based mechanics. A viscoelastic micromechanical model was developed to capture viscoelastic interactions within the AC microstructure. Four types of constitutive models were built to address the four categories of interactions within an AC specimen. Each of the constitutive models consists of three parts which represent three different interaction behaviors: a stiffness model (force-displace relation), a bonding model (shear and tensile strengths), and a slip model (frictional property). Three techniques were developed to reduce the computational time for AC viscoelastic simulations. It was found that the computational time was significantly reduced to days or hours from years or months for typical three-dimensional models. Dynamic modulus and creep stiffness tests were simulated and methodologies were developed to determine the viscoelastic parameters. It was found that the DE models could successfully predict dynamic modulus, phase angles, and creep stiffness in a wide range of frequencies, temperatures, and time spans. Mineral aggregate morphology characteristics (sphericity, orientation, and angularity) were studied to investigate their impacts on AC creep stiffness. It was found that aggregate characteristics significantly impact creep stiffness. Pavement responses and pavement-vehicle interactions were investigated by simulating pavement sections under a rolling wheel. It was found that wheel acceleration, steadily moving, and deceleration significantly impact contact forces. Additionally, summary and recommendations were provided in the last chapter and part of computer programming codes wree provided in the appendixes.

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The CopA copper ATPase of Enterococcus hirae belongs to the family of heavy metal pumping CPx-type ATPases and shares 43% sequence similarity with the human Menkes and Wilson copper ATPases. Due to a lack of suitable protein crystals, only partial three-dimensional structures have so far been obtained for this family of ion pumps. We present a structural model of CopA derived by combining topological information obtained by intramolecular cross-linking with molecular modeling. Purified CopA was cross-linked with different bivalent reagents, followed by tryptic digestion and identification of cross-linked peptides by mass spectrometry. The structural proximity of tryptic fragments provided information about the structural arrangement of the hydrophilic protein domains, which was integrated into a three-dimensional model of CopA. Comparative modeling of CopA was guided by the sequence similarity to the calcium ATPase of the sarcoplasmic reticulum, Serca1, for which detailed structures are available. In addition, known partial structures of CPx-ATPase homologous to CopA were used as modeling templates. A docking approach was used to predict the orientation of the heavy metal binding domain of CopA relative to the core structure, which was verified by distance constraints derived from cross-links. The overall structural model of CopA resembles the Serca1 structure, but reveals distinctive features of CPx-type ATPases. A prominent feature is the positioning of the heavy metal binding domain. It features an orientation of the Cu binding ligands which is appropriate for the interaction with Cu-loaded metallochaperones in solution. Moreover, a novel model of the architecture of the intramembranous Cu binding sites could be derived.

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Sustained growth of solid tumours can rely on both the formation of new and the co-option of existing blood vessels. Current models suggest that binding of angiopoietin-2 (Ang-2) to its endothelial Tie2 receptor prevents receptor phosphorylation, destabilizes blood vessels, and promotes vascular permeability. In contrast, binding of angiopoietin-1 (Ang-1) induces Tie2 receptor activation and supports the formation of mature blood vessels covered by pericytes. Despite the intense research to decipher the role of angiopoietins during physiological neovascularization and tumour angiogenesis, a mechanistic understanding of angiopoietin function on vascular integrity and remodelling is still incomplete. We therefore assessed the vascular morphology of two mouse mammary carcinoma xenotransplants (M6378 and M6363) which differ in their natural angiopoietin expression. M6378 displayed Ang-1 in tumour cells but no Ang-2 in tumour endothelial cells in vivo. In contrast, M6363 tumours expressed Ang-2 in the tumour vasculature, whereas no Ang-1 expression was present in tumour cells. We stably transfected M6378 mouse mammary carcinoma cells with human Ang-1 or Ang-2 and investigated the consequences on the host vasculature, including ultrastructural morphology. Interestingly, M6378/Ang-2 and M6363 tumours displayed a similar vascular morphology, with intratumoural haemorrhage and non-functional and abnormal blood vessels. Pericyte loss was prominent in these tumours and was accompanied by increased endothelial cell apoptosis. Thus, overexpression of Ang-2 converted the vascular phenotype of M6378 tumours into a phenotype similar to M6363 tumours. Our results support the hypothesis that Ang-1/Tie2 signalling is essential for vessel stabilization and endothelial cell/pericyte interaction, and suggest that Ang-2 is able to induce a switch of vascular phenotypes within tumours.

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The past few years, multimodal interaction has been gaining importance in virtual environments. Although multimodality renders interacting with an environment more natural and intuitive, the development cycle of such an application is often long and expensive. In our overall field of research, we investigate how modelbased design can facilitate the development process by designing environments through the use of highlevel diagrams. In this scope, we present ‘NiMMiT’, a graphical notation for expressing and evaluating multimodal user interaction; we elaborate on the NiMMiT primitives and demonstrate its use by means of a comprehensive example.

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This paper develops a process model of how and why complementarity and substitution form over time between contractual and relational governance in the context of information systems outsourcing. Our analysis identifies four distinct process patterns that explain this formation as the outcome of interaction processes between key elements of both contractual and relational governance. These patterns unveil the dynamic nature of complementarity and substitution. In particular, we show that the relationship between contractual and relational governance oscillates between complementarity and substitution. Those oscillations are triggered mainly by three types of contextual events (goal fuzziness, goal conflict, and goal misalignment). Surprisingly, substitution of informal control did not occur as an immediate reaction to external events but emerged as a consequence of preceding complementarity. Thus, our study challenges the prevailing view of an either/or dichotomy of complementarity and substitution by showing that they are causally connected over time.

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Numerical simulations based on plans for a deep geothermal system in Basel, Switzerland are used here to understand chemical processes that occur in an initially dry granitoid reservoir during hydraulic stimulation and long-term water circulation to extract heat. An important question regarding the sustainability of such enhanced geothermal systems (EGS), is whether water–rock reactions will eventually lead to clogging of flow paths in the reservoir and thereby reduce or even completely block fluid throughput. A reactive transport model allows the main chemical reactions to be predicted and the resulting evolution of porosity to be tracked over the expected 30-year operational lifetime of the system. The simulations show that injection of surface water to stimulate fracture permeability in the monzogranite reservoir at 190 °C and 5000 m depth induces redox reactions between the oxidised surface water and the reduced wall rock. Although new calcite, chlorite, hematite and other minerals precipitate near the injection well, their volumes are low and more than compensated by those of the dissolving wall-rock minerals. Thus, during stimulation, reduction of injectivity by mineral precipitation is unlikely. During the simulated long-term operation of the system, the main mineral reactions are the hydration and albitization of plagioclase, the alteration of hornblende to an assemblage of smectites and chlorites and of primary K-feldspar to muscovite and microcline. Within a closed-system doublet, the composition of the circulated fluid changes only slightly during its repeated passage through the reservoir, as the wall rock essentially undergoes isochemical recrystallization. Even after 30 years of circulation, the calculations show that porosity is reduced by only ∼0.2%, well below the expected fracture porosity induced by stimulation. This result suggests that permeability reduction owing to water–rock interaction is unlikely to jeopardize the long-term operation of deep, granitoid-hosted EGS systems. A peculiarity at Basel is the presence of anhydrite as fracture coatings at ∼5000 m depth. Simulated exposure of the circulating fluid to anhydrite induces a stronger redox disequilibrium in the reservoir, driving dissolution of ferrous minerals and precipitation of ferric smectites, hematite and pyrite. However, even in this scenario the porosity reduction is at most 0.5%, a value which is unproblematic for sustainable fluid circulation through the reservoir.

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The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis. The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method (Chou and Talalay, 1984). The Median-Effect Principle/Combination Index method leads to inefficiency by ignoring important sources of variation inherent in dose-response data and discarding data points that do not fit the Median-Effect Principle. Previous work has shown that the conventional method yields a high rate of false positives (Boik, Boik, Newman, 2008; Hennessey, Rosner, Bast, Chen, 2010) and, in some cases, low power to detect synergy. There is a great need for improving the current methodology. We developed a Bayesian framework for dose-response modeling and drug-drug interaction analysis. First, we developed a hierarchical meta-regression dose-response model that accounts for various sources of variation and uncertainty and allows one to incorporate knowledge from prior studies into the current analysis, thus offering a more efficient and reliable inference. Second, in the case that parametric dose-response models do not fit the data, we developed a practical and flexible nonparametric regression method for meta-analysis of independently repeated dose-response experiments. Third, and lastly, we developed a method, based on Loewe additivity that allows one to quantitatively assess interaction between two agents combined at a fixed dose ratio. The proposed method makes a comprehensive and honest account of uncertainty within drug interaction assessment. Extensive simulation studies show that the novel methodology improves the screening process of effective/synergistic agents and reduces the incidence of type I error. We consider an ovarian cancer cell line study that investigates the combined effect of DNA methylation inhibitors and histone deacetylation inhibitors in human ovarian cancer cell lines. The hypothesis is that the combination of DNA methylation inhibitors and histone deacetylation inhibitors will enhance antiproliferative activity in human ovarian cancer cell lines compared to treatment with each inhibitor alone. By applying the proposed Bayesian methodology, in vitro synergy was declared for DNA methylation inhibitor, 5-AZA-2'-deoxycytidine combined with one histone deacetylation inhibitor, suberoylanilide hydroxamic acid or trichostatin A in the cell lines HEY and SKOV3. This suggests potential new epigenetic therapies in cell growth inhibition of ovarian cancer cells.

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BACKGROUND: Variants in the complement cascade genes and the LOC387715/HTRA1, have been widely reported to associate with age-related macular degeneration (AMD), the most common cause of visual impairment in industrialized countries. METHODS/PRINCIPAL FINDINGS: We investigated the association between the LOC387715 A69S and complement component C3 R102G risk alleles in the Finnish case-control material and found a significant association with both variants (OR 2.98, p = 3.75 x 10(-9); non-AMD controls and OR 2.79, p = 2.78 x 10(-19), blood donor controls and OR 1.83, p = 0.008; non-AMD controls and OR 1.39, p = 0.039; blood donor controls), respectively. Previously, we have shown a strong association between complement factor H (CFH) Y402H and AMD in the Finnish population. A carrier of at least one risk allele in each of the three susceptibility loci (LOC387715, C3, CFH) had an 18-fold risk of AMD when compared to a non-carrier homozygote in all three loci. A tentative gene-gene interaction between the two major AMD-associated loci, LOC387715 and CFH, was found in this study using a multiplicative (logistic regression) model, a synergy index (departure-from-additivity model) and the mutual information method (MI), suggesting that a common causative pathway may exist for these genes. Smoking (ever vs. never) exerted an extra risk for AMD, but somewhat surprisingly, only in connection with other factors such as sex and the C3 genotype. Population attributable risks (PAR) for the CFH, LOC387715 and C3 variants were 58.2%, 51.4% and 5.8%, respectively, the summary PAR for the three variants being 65.4%. CONCLUSIONS/SIGNIFICANCE: Evidence for gene-gene interaction between two major AMD associated loci CFH and LOC387715 was obtained using three methods, logistic regression, a synergy index and the mutual information (MI) index.

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The tail-withdrawal circuit of Aplysia provides a useful model system for investigating synaptic dynamics. Sensory neurons within the circuit manifest several forms of synaptic plasticity. Here, we developed a model of the circuit and investigated the ways in which depression (DEP) and potentiation (POT) contributed to information processing. DEP limited the amount of motor neuron activity that could be elicited by the monosynaptic pathway alone. POT within the monosynaptic pathway did not compensate for DEP. There was, however, a synergistic interaction between POT and the polysynaptic pathway. This synergism extended the dynamic range of the network, and the interplay between DEP and POT made the circuit responded preferentially to long-duration, low-frequency inputs.

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People often use tools to search for information. In order to improve the quality of an information search, it is important to understand how internal information, which is stored in user’s mind, and external information, represented by the interface of tools interact with each other. How information is distributed between internal and external representations significantly affects information search performance. However, few studies have examined the relationship between types of interface and types of search task in the context of information search. For a distributed information search task, how data are distributed, represented, and formatted significantly affects the user search performance in terms of response time and accuracy. Guided by UFuRT (User, Function, Representation, Task), a human-centered process, I propose a search model, task taxonomy. The model defines its relationship with other existing information models. The taxonomy clarifies the legitimate operations for each type of search task of relation data. Based on the model and taxonomy, I have also developed prototypes of interface for the search tasks of relational data. These prototypes were used for experiments. The experiments described in this study are of a within-subject design with a sample of 24 participants recruited from the graduate schools located in the Texas Medical Center. Participants performed one-dimensional nominal search tasks over nominal, ordinal, and ratio displays, and searched one-dimensional nominal, ordinal, interval, and ratio tasks over table and graph displays. Participants also performed the same task and display combination for twodimensional searches. Distributed cognition theory has been adopted as a theoretical framework for analyzing and predicting the search performance of relational data. It has been shown that the representation dimensions and data scales, as well as the search task types, are main factors in determining search efficiency and effectiveness. In particular, the more external representations used, the better search task performance, and the results suggest the ideal search performance occurs when the question type and corresponding data scale representation match. The implications of the study lie in contributing to the effective design of search interface for relational data, especially laboratory results, which are often used in healthcare activities.