998 resultados para Structural loads


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Background: Tuberculosis still remains one of the largest killer infectious diseases, warranting the identification of newer targets and drugs. Identification and validation of appropriate targets for designing drugs are critical steps in drug discovery, which are at present major bottle-necks. A majority of drugs in current clinical use for many diseases have been designed without the knowledge of the targets, perhaps because standard methodologies to identify such targets in a high-throughput fashion do not really exist. With different kinds of 'omics' data that are now available, computational approaches can be powerful means of obtaining short-lists of possible targets for further experimental validation. Results: We report a comprehensive in silico target identification pipeline, targetTB, for Mycobacterium tuberculosis. The pipeline incorporates a network analysis of the protein-protein interactome, a flux balance analysis of the reactome, experimentally derived phenotype essentiality data, sequence analyses and a structural assessment of targetability, using novel algorithms recently developed by us. Using flux balance analysis and network analysis, proteins critical for survival of M. tuberculosis are first identified, followed by comparative genomics with the host, finally incorporating a novel structural analysis of the binding sites to assess the feasibility of a protein as a target. Further analyses include correlation with expression data and non-similarity to gut flora proteins as well as 'anti-targets' in the host, leading to the identification of 451 high-confidence targets. Through phylogenetic profiling against 228 pathogen genomes, shortlisted targets have been further explored to identify broad-spectrum antibiotic targets, while also identifying those specific to tuberculosis. Targets that address mycobacterial persistence and drug resistance mechanisms are also analysed. Conclusion: The pipeline developed provides rational schema for drug target identification that are likely to have high rates of success, which is expected to save enormous amounts of money, resources and time in the drug discovery process. A thorough comparison with previously suggested targets in the literature demonstrates the usefulness of the integrated approach used in our study, highlighting the importance of systems-level analyses in particular. The method has the potential to be used as a general strategy for target identification and validation and hence significantly impact most drug discovery programmes.

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We had earlier proposed a hypothesis to explain the mechanism of perpetuation of immunological memory based on the operation of idiotypic network in the complete absence of antigen. Experimental evidences were provided for memory maintenance through anti-idiotypic antibody (Ab2) carrying the internal image of the antigen. In the present work, we describe a structural basis for such memory perpetuation by molecular modeling and structural analysis studies. A three-dimensional model of Ab2 was generated and the structure of the antigenic site on the hemagglutinin protein H of Rinderpest virus was modeled using the structural template of hemagglutinin protein of Measles virus. Our results show that a large portion of heavy chain containing the CDR regions of Ab2 resembles the domain of the hemagglutinin housing the epitope regions. The similarity demonstrates that an internal image of the H antigen is formed in Ab2, which provides a structural basis for functional mimicry demonstrated earlier. This work brings out the importance of the structural similarity between a domain of hemagglutinin protein to that of its corresponding Ab2. It provides evidence that Ab2 is indeed capable of functioning as surrogate antigen and provides support to earlier proposed relay hypothesis which has provided a mechanism for the maintenance of immunological memory.

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In this paper two nonlinear model based control algorithms have been developed to monitor the magnetorheological (MR) damper voltage. The main advantage of the proposed algorithms is that it is possible to directly monitor the voltage required to control the structural vibration considering the effect of the supplied and commanded voltage dynamics of the damper. The efficiency of the proposed techniques has been shown and compared taking an example of a base isolated three-storey building under a set of seismic excitations. Comparison of the performances with a fuzzy based intelligent control algorithm and a widely used clipped optimal strategy has also been shown.

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Cellular materials that are often observed in biological systems exhibit excellent mechanical properties at remarkably low densities. Luffa sponge is one of such materials with a complex interconnecting porous structure. In this paper, we studied the relationship between its structural and mechanical properties at different levels of its hierarchical organization from a single fiber to a segment of whole sponge. The tensile mechanical behaviors of three single fibers were examined by an Instron testing machine and the ultrastructure of a fractured single fiber was observed in a scanning electronic microscope. Moreover, the compressive mechanical behaviors of the foam-like blocks from different locations of the sponge were examined. The difference of the compressive stress-strain responses of four sets of segmental samples were also compared. The result shows that the single fiber is a porous composite material mainly consisting of cellulose fibrils and lignin/hemicellulose matrix, and its Young's modulus and strength are comparable to wood. The mechanical behavior of the block samples from the hoop wall is superior to that from the core part. Furthermore, it shows that the influence of the inner surface on the mechanical property of the segmental sample is stronger than that of the core part; in particular, the former's Young's modulus, strength and strain energy absorbed are about 1.6 times higher. The present work can improve our understanding of the structure-function relationship of the natural material, which may inspire fabrication of new biomimetic foams with desirable mechanical efficiency for further applications in anti-crushing devices and super-light sandwich panels.

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The primary objective of this paper is to study the use of medical image-based finite element (FE) modelling in subjectspecific midsole design and optimisation for heel pressure reduction using a midsole plug under the calcaneus area (UCA). Plugs with different relative dimensions to the size of the calcaneus of the subject have been incorporated in the heel region of the midsole. The FE foot model was validated by comparing the numerically predicted plantar pressure with biomechanical tests conducted on the same subject. For each UCA midsole plug design, the effect of material properties and plug thicknesses on the plantar pressure distribution and peak pressure level during the heel strike phase of normal walking was systematically studied. The results showed that the UCA midsole insert could effectively modify the pressure distribution, and its effect is directly associated with the ratio of the plug dimension to the size of the calcaneus bone of the subject. A medium hardness plug with a size of 95% of the calcaneus has achieved the best performance for relieving the peak pressure in comparison with the pressure level for a solid midsole without a plug, whereas a smaller plug with a size of 65% of the calcaneus insert with a very soft material showed minimum beneficial effect for the pressure relief.

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Background: High-resolution magnetic resonance (MR) imaging has been used for MR imaging-based structural stress analysis of atherosclerotic plaques. The biomechanical stress profile of stable plaques has been observed to differ from that of unstable plaques; however, the role that structural stresses play in determining plaque vulnerability remains speculative. Methods: A total of 61 patients with previous history of symptomatic carotid artery disease underwent carotid plaque MR imaging. Plaque components of the index artery such as fibrous tissue, lipid content and plaque haemorrhage (PH) were delineated and used for finite element analysis-based maximum structural stress (M-C Stress) quantification. These patients were followed up for 2 years. The clinical end point was occurrence of an ischaemic cerebrovascular event. The association of the time to the clinical end point with plaque morphology and M-C Stress was analysed. Results: During a median follow-up duration of 514 days, 20% of patients (n=12) experienced an ischaemic event in the territory of the index carotid artery. Cox regression analysis indicated that M-C Stress (hazard ratio (HR): 12.98 (95% confidence interval (CI): 1.32-26.67, pZ0.02), fibrous cap (FC) disruption (HR: 7.39 (95% CI: 1.61e33.82), p Z 0.009) and PH (HR: 5.85 (95% CI: 1.27e26.77), p Z 0.02) are associated with the development of subsequent cerebrovascular events. Plaques associated with future events had higher M-C Stress than those which had remained asymptomatic (median (interquartile range, IQR): 330 kPa (229e494) vs. 254 kPa (166-290), p Z0.04). Conclusions: High biomechanical structural stresses, in addition to FC rupture and PH, are associated with subsequent cerebrovascular events.

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An inexpensive and effective simple method for the preparation of nano-crystalline titanium oxide (anatase) thin films at room temperature on different transparent substrates is presented. This method is based on the use of peroxo-titanium complex, i.e. titanium isopropoxide as a single initiating organic precursor. Post-annealing treatment is necessary to convert the deposited amorphous film into titanium oxide (TiO2) crystalline (anatase) phase. These films have been characterized for X-ray diffraction (XRD) studies, atomic force microscopic (AFM) studies and optical measurements. The optical constants such as refractive index and extinction coefficient have been estimated by using envelope technique. Also, the energy gap values have been estimated using Tauc's formula for on glass and quartz substrates are found to be 3.35 eV and 3.39 eV, respectively. (C) 2008 Elsevier B.V. All rights reserved.

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Background Because many acute cerebral ischemic events are caused by rupture of vulnerable carotid atheroma and subsequent thrombosis, the present study used both idealized and patient-specific carotid atheromatous plaque models to evaluate the effect of structural determinants on stress distributions within plaque. Methods and Results Using a finite element method, structural analysis was performed using models derived from in vivo high-resolution magnetic resonance imaging (MRI) of carotid atheroma in 40 non-consecutive patients (20 symptomatic, 20 asymptomatic). Plaque components were modeled as hyper-elastic materials. The effects of varying fibrous cap thickness, lipid core size and lumen curvature on plaque stress distributions were examined. Lumen curvature and fibrous cap thickness were found to be major determinants of plaque stress. The size of the lipid core did not alter plaque stress significantly when the fibrous cap was relatively thick. The correlation between plaque stress and lumen curvature was significant for both symptomatic (p = 0.01; correlation coefficient: 0.689) and asymptomatic patients (p = 0.01; correlation coefficient: 0.862). Lumen curvature in plaques of symptomatic patients was significantly larger than those of asymptomatic patients (1.50±1.0mm-1 vs 1.25±0.75 mm-1; p = 0.01). Conclusion Specific plaque morphology (large lumen curvature and thin fibrous cap) is closely related to plaque vulnerability. Structural analysis using high-resolution MRI of carotid atheroma may help in detecting vulnerable atheromatous plaque and aid the risk stratification of patients with carotid disease.

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Background: More than half of all cerebral ischemic events are the result of rupture of extracranial plaques. The clinical determination of carotid plaque vulnerability is currently based solely on luminal stenosis; however, it has been increasingly suggested that plaque morphology and biomechanical stress should also be considered. We used finite element analysis based on in vivo magnetic resonance imaging (MRI) to simulate the stress distributions within plaques of asymptomatic and symptomatic individuals. Methods: Thirty nonconsecutive subjects (15 symptomatic and 15 asymptomatic) underwent high-resolution multisequence in vivo MRI of the carotid bifurcation. Stress analysis was performed based on the geometry derived from in vivo MRI of the carotid artery at the point of maximal stenosis. The finite element analysis model considered plaque components to be hyperelastic. The peak stresses within the plaques of symptomatic and asymptomatic individuals were compared. Results: High stress concentrations were found at the shoulder regions of symptomatic plaques, and the maximal stresses predicted in this group were significantly higher than those in the asymptomatic group (508.2 ± 193.1 vs 269.6 ± 107.9 kPa; P = .004). Conclusions: Maximal predicted plaque stresses in symptomatic patients were higher than those predicted in asymptomatic patients by finite element analysis, suggesting the possibility that plaques with higher stresses may be more prone to be symptomatic and rupture. If further validated by large-scale longitudinal studies, biomechanical stress analysis based on high resolution in vivo MRI could potentially act as a useful tool for risk assessment of carotid atheroma. It may help in the identification of patients with asymptomatic carotid atheroma at greatest risk of developing symptoms or mild-to-moderate symptomatic stenoses, which currently fall outside current clinical guidelines for intervention.

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Although globular proteins are endowed with well defined three-dimensional structures, they exhibit substantial mobility within the framework of the given threedimensional structure. The different types of mobility found in proteins by and large correspond to the different levels of organisational hierarchy in protein architecture. They are of considerable structural and functional significance, and can be broadly classified into(a) thermal and conformational fluctuations, (b) segmental mobility, (c) interdomain mobility and (d) intersubunit mobility. Protein crystallographic studies has provided a wealth of information on all of them. The temperature factors derived from X-ray diffraction studies provide a measure of atomic displacements caused by thermal and conformational fluctuations. The variation of displacement along the polypeptide chain have provided functionally significant information on the flexibility of different regions of the molecule in proteins such as myoglobin, lysozyme and prealbumin. Segmental mobility often involves the movement of a region or a segment of a molecule with respect to the rest, as in the transition between the apo and the holo structures of lactate dehydrogenase. It may also involve rigidification of a disordered region of the molecule as in the activation of the zymogens of serine proteases. Transitions between the apo and the holo structures of alcohol dehydrogenase,and between the free and the sugar bound forms of hexokinase, are good examples of interdomain mobility caused by hinge-bending. The capability of different domains to move semi-independently contributes greatly to the versatility of immunoglobulin molecules. Interdomain mobility in citrate synthase appears to be more complex and its study has led to an alternative description of domain closure. The classical and the most thoroughly studied case of intersubunit mobility is that in haemoglobin. The stereochemical mechanism of the action of this allosteric protein clearly brings out the functional subtilities that could be achieved through intersubunit movements. In addition to ligand binding and activation,environmental changes also often cause structural transformations. The reversible transformation between 2 Zn insulin and 4 Zn insulin is caused by changes in the ionic strength of the medium. Adenylate Kinase provides a good example for functionally significant reversible conformational transitions induced by variation in pH. Available evidences indicate that reversible structural transformations in proteins could also be caused by changes in the aqueous environment, including those in the amount of water surrounding protein molecules.

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Recent experiments in this laboratory on structural transformations caused by controlled dehydration of protein crystals have been reviewed. X-ray diffraction patterns of the following crystals have been examined under varying conditions of environmental humidity in the relative humidity range of 100-75%: a new crystal form of bovine pancreatic ribonuclease A grown from acetone solution in tris buffer (I), the well-known monoclinic form of the protein grown from aqueous ethanol (II), the same form grown from a solution of 2-methyl pentan-2,4-diol in phosphate buffer (III), tetragonal (IV), orthorhombic (V), monoclinic (VI) and triclinic (VII) hen egg white lysozyme, porcine 2 Zn insulin (VIII), porcine 4 Zn insulin (IX) and the crystals of concanavalin A(X). I, II, IV, V and VI undergo one or more transformations as evidenced by discontinuous changes in the unit cell dimensions, the diffraction pattern and the solvent content. Such water-mediated transformations do not appear to occur in the remaining crystals in the relative humidity range explored. The relative humidity at which the transformation occurs is reduced when 2-methyl pentan-2,4-diol is present in the mother liquor. The transformations are affected by the crystal structure but not by the amount of solvent in the crystals. The X-ray investigations reviewed here and other related investigations emphasize the probable importance of water-mediated transformations in exploring hydration of proteins and conformational transitions in them.

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The export of sediments from coastal catchments can have detrimental impacts on estuaries and near shore reef ecosystems such as the Great Barrier Reef. Catchment management approaches aimed at reducing sediment loads require monitoring to evaluate their effectiveness in reducing loads over time. However, load estimation is not a trivial task due to the complex behaviour of constituents in natural streams, the variability of water flows and often a limited amount of data. Regression is commonly used for load estimation and provides a fundamental tool for trend estimation by standardising the other time specific covariates such as flow. This study investigates whether load estimates and resultant power to detect trends can be enhanced by (i) modelling the error structure so that temporal correlation can be better quantified, (ii) making use of predictive variables, and (iii) by identifying an efficient and feasible sampling strategy that may be used to reduce sampling error. To achieve this, we propose a new regression model that includes an innovative compounding errors model structure and uses two additional predictive variables (average discounted flow and turbidity). By combining this modelling approach with a new, regularly optimised, sampling strategy, which adds uniformity to the event sampling strategy, the predictive power was increased to 90%. Using the enhanced regression model proposed here, it was possible to detect a trend of 20% over 20 years. This result is in stark contrast to previous conclusions presented in the literature. (C) 2014 Elsevier B.V. All rights reserved.

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There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates by minimizing the biases and making use of possible predictive variables. The load estimation procedure can be summarized by the following four steps: - (i) output the flow rates at regular time intervals (e.g. 10 minutes) using a time series model that captures all the peak flows; - (ii) output the predicted flow rates as in (i) at the concentration sampling times, if the corresponding flow rates are not collected; - (iii) establish a predictive model for the concentration data, which incorporates all possible predictor variables and output the predicted concentrations at the regular time intervals as in (i), and; - (iv) obtain the sum of all the products of the predicted flow and the predicted concentration over the regular time intervals to represent an estimate of the load. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized regression (rating-curve) approach with additional predictors that capture unique features in the flow data, namely the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and cumulative discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. The model also has the capacity to accommodate autocorrelation in model errors which are the result of intensive sampling during floods. Incorporating this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach using the concentrations of total suspended sediment (TSS) and nitrogen oxide (NOx) and gauged flow data from the Burdekin River, a catchment delivering to the Great Barrier Reef. The sampling biases for NOx concentrations range from 2 to 10 times indicating severe biases. As we expect, the traditional average and extrapolation methods produce much higher estimates than those when bias in sampling is taken into account.

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Mr= 361.3, triclinic, P1, a = 6-239 (2), b=11.280(2), c=12-451(2)A, a=101.2 (1), B= 92.3 (1), 7=99.9(1)°, V=844.123 A3, Z=2, Dx= 1.42, D m = 1.42 (1) Mg m -3, n(Cu Ka) = 1.5418 ,A., g = 1-102 mm -1, F(000) = 376, T= 293 K. Final R = 0.064 for 2150 observed reflections. The niflumic acid anions consist essentially of three planar groupings, namely, two six-membered rings and a carboxylate group attached to one of them. The invariant common structural features observed in the crystal structures of fenamates, namely, the coplanarity of the carboxyl group and the six-membered ring bearing it, and the internal hydrogen bond between the carboxyl group and the imino N atom that bridges the two sixmembered rings, are retained in the complex. The amino N atom is gauche with respect to the terminal hydroxyl group in the ethanolamine cation. The complexation between the two molecules is achieved through ionic and hydrogen-bonded interactions involving the carboxylate group in niflumic acid.

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We had earlier proposed a hypothesis to explain the mechanism of perpetuation of immunological memory based on the operation of idiotypic network in the complete absence of antigen. Experimental evidences were provided for memory maintenance through anti-idiotypic antibody (Ab(2)) carrying the internal image of the antigen. In the present work, we describe a structural basis for such memory perpetuation by molecular modeling and structural analysis studies. A three-dimensional model of Ab(2) was generated and the structure of the antigenic site on the hemagglutinin protein H of Rinderpest virus was modeled using the structural template of hemagglutinin protein of Measles virus. Our results show that a large portion of heavy chain containing the CDR regions of Ab(2) resembles the domain of the hemagglutinin housing the epitope regions. The similarity demonstrates that an internal image of the H antigen is formed in Ab(2), which provides a structural basis for functional mimicry demonstrated earlier. This work brings out the importance of the structural similarity between a domain of hemagglutinin protein to that of its corresponding Ab(2). It provides evidence that Ab(2) is indeed capable of functioning as surrogate antigen and provides support to earlier proposed relay hypothesis which has provided a mechanism for the maintenance of immunological memory.