901 resultados para Manufacturing processes -- Computer simulation
Resumo:
Intensity-modulated radiotherapy (IMRT) treatment plan verification by comparison with measured data requires having access to the linear accelerator and is time consuming. In this paper, we propose a method for monitor unit (MU) calculation and plan comparison for step and shoot IMRT based on the Monte Carlo code EGSnrc/BEAMnrc. The beamlets of an IMRT treatment plan are individually simulated using Monte Carlo and converted into absorbed dose to water per MU. The dose of the whole treatment can be expressed through a linear matrix equation of the MU and dose per MU of every beamlet. Due to the positivity of the absorbed dose and MU values, this equation is solved for the MU values using a non-negative least-squares fit optimization algorithm (NNLS). The Monte Carlo plan is formed by multiplying the Monte Carlo absorbed dose to water per MU with the Monte Carlo/NNLS MU. Several treatment plan localizations calculated with a commercial treatment planning system (TPS) are compared with the proposed method for validation. The Monte Carlo/NNLS MUs are close to the ones calculated by the TPS and lead to a treatment dose distribution which is clinically equivalent to the one calculated by the TPS. This procedure can be used as an IMRT QA and further development could allow this technique to be used for other radiotherapy techniques like tomotherapy or volumetric modulated arc therapy.
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In recent years, protein-ligand docking has become a powerful tool for drug development. Although several approaches suitable for high throughput screening are available, there is a need for methods able to identify binding modes with high accuracy. This accuracy is essential to reliably compute the binding free energy of the ligand. Such methods are needed when the binding mode of lead compounds is not determined experimentally but is needed for structure-based lead optimization. We present here a new docking software, called EADock, that aims at this goal. It uses an hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 A around the center of mass of the ligand position in the crystal structure, and on the contrary to other benchmarks, our algorithm was fed with optimized ligand positions up to 10 A root mean square deviation (RMSD) from the crystal structure, excluding the latter. This validation illustrates the efficiency of our sampling strategy, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures could be explained by the presence of crystal contacts in the experimental structure. Finally, the ability of EADock to accurately predict binding modes on a real application was illustrated by the successful docking of the RGD cyclic pentapeptide on the alphaVbeta3 integrin, starting far away from the binding pocket.
Resumo:
In the vast majority of bottom-up proteomics studies, protein digestion is performed using only mammalian trypsin. Although it is clearly the best enzyme available, the sole use of trypsin rarely leads to complete sequence coverage, even for abundant proteins. It is commonly assumed that this is because many tryptic peptides are either too short or too long to be identified by RPLC-MS/MS. We show through in silico analysis that 20-30% of the total sequence of three proteomes (Schizosaccharomyces pombe, Saccharomyces cerevisiae, and Homo sapiens) is expected to be covered by Large post-Trypsin Peptides (LpTPs) with M(r) above 3000 Da. We then established size exclusion chromatography to fractionate complex yeast tryptic digests into pools of peptides based on size. We found that secondary digestion of LpTPs followed by LC-MS/MS analysis leads to a significant increase in identified proteins and a 32-50% relative increase in average sequence coverage compared to trypsin digestion alone. Application of the developed strategy to analyze the phosphoproteomes of S. pombe and of a human cell line identified a significant fraction of novel phosphosites. Overall our data indicate that specific targeting of LpTPs can complement standard bottom-up workflows to reveal a largely neglected portion of the proteome.
Resumo:
A new type of high avidity binding molecule, termed "peptabody" was created by harnessing the effect of multivalent interaction. A short peptide ligand was fused via a semi-rigid hinge region with the coiled-coil assembly domain of the cartilage oligomeric matrix protein, resulting in a pentameric multivalent binding molecule. In the first peptabody (Pab-S) described here, a peptide (S) specific for the mouse B-cell lymphoma BCL1 surface Ig idiotype, was selected from a phage display library. A fusion gene was constructed encoding peptide S, followed by the 24 aa hinge region from camel IgG and a modified 55 aa cartilage oligomeric matrix protein pentamerization domain. The Pab-S fusion protein was expressed in Escherichia coli in a soluble form at high levels and purified in a single step by metal-affinity chromatography. Pab-S specifically bound the BCL1 surface idiotype with an avidity of about 1 nM, which corresponds to a 2 x 10(5)-fold increase compared with the affinity of the synthetic peptide S itself. Biochemical characterization showed that Pab-S is a stable homopentamer of about 85 kDa, with interchain disulfide bonds. Pab-S can be dissociated under denaturing and reducing conditions and reassociated as a pentamer with full-binding activity. This intrinsic feature provides an easy way to combine Pab molecules with two different peptide specificities, thus producing heteropentamers with bispecific and/or chelating properties.
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Human-induced habitat fragmentation constitutes a major threat to biodiversity. Both genetic and demographic factors combine to drive small and isolated populations into extinction vortices. Nevertheless, the deleterious effects of inbreeding and drift load may depend on population structure, migration patterns, and mating systems and are difficult to predict in the absence of crossing experiments. We performed stochastic individual-based simulations aimed at predicting the effects of deleterious mutations on population fitness (offspring viability and median time to extinction) under a variety of settings (landscape configurations, migration models, and mating systems) on the basis of easy-to-collect demographic and genetic information. Pooling all simulations, a large part (70%) of variance in offspring viability was explained by a combination of genetic structure (F(ST)) and within-deme heterozygosity (H(S)). A similar part of variance in median time to extinction was explained by a combination of local population size (N) and heterozygosity (H(S)). In both cases the predictive power increased above 80% when information on mating systems was available. These results provide robust predictive models to evaluate the viability prospects of fragmented populations.
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In mammography, the image contrast and dose delivered to the patient are determined by the x-ray spectrum and the scatter to primary ratio S/P. Thus the quality of the mammographic procedure is highly dependent on the choice of anode and filter material and on the method used to reduce the amount of scattered radiation reaching the detector. Synchrotron radiation is a useful tool to study the effect of beam energy on the optimization of the mammographic process because it delivers a high flux of monochromatic photons. Moreover, because the beam is naturally flat collimated in one direction, a slot can be used instead of a grid for scatter reduction. We have measured the ratio S/P and the transmission factors for grids and slots for monoenergetic synchrotron radiation. In this way the effect of beam energy and scatter rejection method were separated, and their respective importance for image quality and dose analyzed. Our results show that conventional mammographic spectra are not far from optimum and that the use of a slot instead of a grid has an important effect on the optimization of the mammographic process. We propose a simple numerical model to quantify this effect.
Resumo:
Pallido-pyramidal syndromes combine dystonia with or without parkinsonism and spasticity as part of a mixed neurodegenerative disorder. Several causative genes have been shown to lead to pallido-pyramidal syndromes, including FBXO7, ATP13A2, PLA2G6, PRKN and SPG11. Among these, ATP13A2 and PLA2G6 are inconsistently associated with brain iron deposition. Using homozygosity mapping and direct sequencing in a multiplex consanguineous Saudi Arabian family with a pallido-pyramidal syndrome, iron deposition and cerebellar atrophy, we identified a homozygous p.G53R mutation in C19orf12. Our findings add to the phenotypic spectrum associated with C19orf12 mutations.
Resumo:
This paper presents a new non parametric atlas registration framework, derived from the optical flow model and the active contour theory, applied to automatic subthalamic nucleus (STN) targeting in deep brain stimulation (DBS) surgery. In a previous work, we demonstrated that the STN position can be predicted based on the position of surrounding visible structures, namely the lateral and third ventricles. A STN targeting process can thus be obtained by registering these structures of interest between a brain atlas and the patient image. Here we aim to improve the results of the state of the art targeting methods and at the same time to reduce the computational time. Our simultaneous segmentation and registration model shows mean STN localization errors statistically similar to the most performing registration algorithms tested so far and to the targeting expert's variability. Moreover, the computational time of our registration method is much lower, which is a worthwhile improvement from a clinical point of view.
Resumo:
Ami, ou ennemi, le soleil ? Qui n'a jamais maudit un petit excès de bain de soleil sanctionné par une peau brûlée ? Mais en hiver, quand il se fait rare, l'huile de foie de morue est la panacée que prescrit la sagesse de nos grands-mères pour remplacer la vitamine D qu'en temps normal il nous aide à synthétiser. Pour pouvoir faire le point sur les dangers et les bénéfices du rayonnement solaire, il faut connaître son intensité et en particulier celle du rayonnement ultraviolet (UV) qui a une forte influence sur la santé.Durant ces dernières décades, une forte augmentation des cancers de la peau a été constatée dans les pays développés. La communauté médicale suppose que cette augmentation est liée à une plus forte exposition aux UV, qui serait elle-même due à des changements d'habitudes de la population (engouement pour les loisirs en plein air, pour les vacances sous les tropiques, popularité du bronzage, etc.) et éventuellement à un accroissement du rayonnement UV. [Auteurs]
Resumo:
We present an agent-based model with the aim of studying how macro-level dynamics of spatial distances among interacting individuals in a closed space emerge from micro-level dyadic and local interactions. Our agents moved on a lattice (referred to as a room) using a model implemented in a computer program called P-Space in order to minimize their dissatisfaction, defined as a function of the discrepancy between the real distance and the ideal, or desired, distance between agents. Ideal distances evolved in accordance with the agent's personal and social space, which changed throughout the dynamics of the interactions among the agents. In the first set of simulations we studied the effects of the parameters of the function that generated ideal distances, and in a second set we explored how group macrolevel behavior depended on model parameters and other variables. We learned that certain parameter values yielded consistent patterns in the agents' personal and social spaces, which in turn led to avoidance and approaching behaviors in the agents. We also found that the spatial behavior of the group of agents as a whole was influenced by the values of the model parameters, as well as by other variables such as the number of agents. Our work demonstrates that the bottom-up approach is a useful way of explaining macro-level spatial behavior. The proposed model is also shown to be a powerful tool for simulating the spatial behavior of groups of interacting individuals.
Resumo:
The Iowa Department of Transportation has been using the Bureau of Public Roads (BPR) Roughometer as part of its detour analysis process for more than 20 years. Advances in technology have made the BPR Roughometer obsolete for ride quality testing. High-speed profilers that can collect the profile of the road at highway speeds are the standard ride instruments for determining ride quality on pavements. The objective of the project was to develop a correlation between the BPR Roughometer and the high-speed laser South Dakota type Profiler (SD Profiler). Nineteen pavement sections were chosen to represent the range of types and conditions for detours. Three computer simulation models were tested on the profiler profiles. The first model is the International Ride Index (IRI) which is considered the standard index for reporting ride quality in the United States. The second model is the Ride Number (RN) developed by the University of Michigan Transportation Research Institute and the third model used is a quarter-car simulation of the BPR Roughometer (ASTM E-1170) which should match the speed and range of roadway features experienced by Iowa's BPR Roughometer Unit. The BPR Roughometer quarter-car model provided the best overall correlation with Iowa's BPR Roughometer.
Resumo:
FGFR1 mutations have been identified in both Kallmann syndrome and normosmic HH (nIHH). To date, few mutations in the FGFR1 gene have been structurally or functionally characterized in vitro to identify molecular mechanisms that contribute to the disease pathogenesis. We attempted to define the in vitro functionality of two FGFR1 mutants (R254W and R254Q), resulting from two different amino acid substitutions of the same residue, and to correlate the in vitro findings to the patient phenotypes. Two unrelated GnRH deficient probands were found to harbor mutations in FGFR1 (R254W and R254Q). Mutant signaling activity and expression levels were evaluated in vitro and compared to a wild type (WT) receptor. Signaling activity was determined by a FGF2/FGFR1 dependent transcription reporter assay. Receptor total expression levels were assessed by Western blot and cell surface expression was measured by a radiolabeled antibody binding assay. The R254W maximal receptor signaling capacity was reduced by 45% (p<0.01) while R254Q activity was not different from WT. However, both mutants displayed diminished total protein expression levels (40 and 30% reduction relative to WT, respectively), while protein maturation was unaffected. Accordingly, cell surface expression levels of the mutant receptors were also significantly reduced (35% p<0.01 and 15% p<0.05, respectively). The p.R254W and p.R254Q are both loss-of-function mutations as demonstrated by their reduced overall and cell surface expression levels suggesting a deleterious effect on receptor folding and stability. It appears that a tryptophan substitution at R254 is more disruptive to receptor structure than the more conserved glutamine substitution. No clear correlation between the severity of in vitro loss-of-function and phenotypic presentation could be assigned.
Resumo:
We analyze the short-time dynamical behavior of a colloidal suspension in a confined geometry. We analyze the relevant dynamical response of the solvent, and derive the temporal behavior of the velocity autocorrelation function, which exhibits an asymptotic negative algebraic decay. We are able to compare quantitatively with theoretical expressions, and analyze the effects of confinement on the diffusive behavior of the suspension.
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An effect of drift is investigated on the segregation pattern in diffusion-limited aggregation (DLA) with two components (A and B species). The sticking probability PAB (=PBA) between the different species is introduced into the DLA model with drift, where the sticking probability PAA (=PBB) between the same species equals 1. By using computer simulation it is found that the drift has an important effect on not only the morphology but also the segregation pattern. Under the drift and the small sticking probability, a characteristic pattern appears where elongated clusters of A species and of B species are periodically dispersed. The period decreases with increasing drift. The periodic structure of the deposits is characterized by an autocorrelation function. The shape of the cluster consisting of only A species (or B species) shows a vertically elongated filamentlike structure. Each cluster becomes vertically longer with decreasing sticking probability PAB. The segregation pattern is distinctly different from that with no drift and a small sticking probability PAA. The effect of the concentration on the segregation pattern is also shown.
Resumo:
Human biomonitoring is a widely used method in the assessment of occupational exposure to chemical substances and recommended biological limits are published periodically for interpretation and decision-making. However, it is increasingly recognized that a large variability is associated with biological monitoring, making interpretation less efficient than assumed. In order to improve the applicability of biological monitoring, specific factors responsible for this variability should be identified and their contribution quantified. Among these factors, age and sex are easily identifiable, and present knowledge about pharmaceutical chemicals suggests that they play an important role on the toxicokinetics of occupational chemical agents, and therefore on the biological monitoring results.The aim of the present research project was to assess the influence of age and sex on biological indicators corresponding to organic solvents. This has been done experimentally and by toxicokinetic computer simulation. Another purpose was to explore the effect of selected CYP2E1 polymorphisms on the toxicokinetic profile.Age differences were identified by numerical simulations using a general toxicokinetic model from a previous study which was applied to 14 chemicals, representing 21 specific biological entities, with, among others, toluene, phenol, lead and mercury. These models were runn with the modified parameters, indicating in some cases important differences due to age. The expected changes are mostly of the order of 10-20 %, but differences up to 50 % were observed in some cases. These differences appear to depend on the chemical and on the biological entity considered.Sex differences were quantified by controlled human exposures, which were carried out in a 12 m3 exposure chamber for three organic solvents separately: methyl ethyl ketone, 1-methoxy-2-propanol and 1,1,1-trichloroethane. The human volunteer groups were composed 12 of ten young men and fifteen young women, the latter subdivided into those with and without hormonal contraceptive. They were exposed during six hours at rest and at half of the threshold limit value. The kinetics of the parent compounds (organic volatiles) and their metabolite(s) were followed in blood, urine and expired air over time. Analyses of the solvent and their metabolites were performed by using headspace gas chromatography, CYP2E1 genotypes by using PCR-based RFLP methods. Experimental data were used to calibrate the toxicokinetic models developed for the three solvents. The results obtained for the different biomarkers of exposure mainly showed an effect on the urinary levels of several biomarkers among women due to the use of hormonal contraceptive, with an increase of about 50 % in the metabolism rate. The results also showed a difference due to the genotype CYP2E1*6, when exposed to methyl ethyl ketone, with a tendency to increase CYP2E1 activity when volunteers were carriers of the mutant allele. Simulations showed that it is possible to use simple toxicokinetic tools in order to predict internal exposure when exposed to organic solvents. Our study suggests that not only physiological differences but also exogenous sex hormones could influence CYP2E1 enzyme activity. The variability among the urinary biological indicators levels gives evidence of an interindividual susceptibility, an aspect that should have its place in the approaches for setting limits of occupational exposure.