50 resultados para energy requirement model
Resumo:
DNA condensation observed in vitro with the addition of polyvalent counterions is due to intermolecular attractive forces. We introduce a quantitative model of these forces in a Brownian dynamics simulation in addition to a standard mean-field Poisson-Boltzmann repulsion. The comparison of a theoretical value of the effective diameter calculated from the second virial coefficient in cylindrical geometry with some experimental results allows a quantitative evaluation of the one-parameter attractive potential. We show afterward that with a sufficient concentration of divalent salt (typically approximately 20 mM MgCl(2)), supercoiled DNA adopts a collapsed form where opposing segments of interwound regions present zones of lateral contact. However, under the same conditions the same plasmid without torsional stress does not collapse. The condensed molecules present coexisting open and collapsed plectonemic regions. Furthermore, simulations show that circular DNA in 50% methanol solutions with 20 mM MgCl(2) aggregates without the requirement of torsional energy. This confirms known experimental results. Finally, a simulated DNA molecule confined in a box of variable size also presents some local collapsed zones in 20 mM MgCl(2) above a critical concentration of the DNA. Conformational entropy reduction obtained either by supercoiling or by confinement seems thus to play a crucial role in all forms of condensation of DNA.
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Protein-ligand docking has made important progress during the last decade and has become a powerful tool for drug development, opening the way to virtual high throughput screening and in silico structure-based ligand design. Despite the flattering picture that has been drawn, recent publications have shown that the docking problem is far from being solved, and that more developments are still needed to achieve high successful prediction rates and accuracy. Introducing an accurate description of the solvation effect upon binding is thought to be essential to achieve this goal. In particular, EADock uses the Generalized Born Molecular Volume 2 (GBMV2) solvent model, which has been shown to reproduce accurately the desolvation energies calculated by solving the Poisson equation. Here, the implementation of the Fast Analytical Continuum Treatment of Solvation (FACTS) as an implicit solvation model in small molecules docking calculations has been assessed using the EADock docking program. Our results strongly support the use of FACTS for docking. The success rates of EADock/FACTS and EADock/GBMV2 are similar, i.e. around 75% for local docking and 65% for blind docking. However, these results come at a much lower computational cost: FACTS is 10 times faster than GBMV2 in calculating the total electrostatic energy, and allows a speed up of EADock by a factor of 4. This study also supports the EADock development strategy relying on the CHARMM package for energy calculations, which enables straightforward implementation and testing of the latest developments in the field of Molecular Modeling.
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Developing a novel technique for the efficient, noninvasive clinical evaluation of bone microarchitecture remains both crucial and challenging. The trabecular bone score (TBS) is a new gray-level texture measurement that is applicable to dual-energy X-ray absorptiometry (DXA) images. Significant correlations between TBS and standard 3-dimensional (3D) parameters of bone microarchitecture have been obtained using a numerical simulation approach. The main objective of this study was to empirically evaluate such correlations in anteroposterior spine DXA images. Thirty dried human cadaver vertebrae were evaluated. Micro-computed tomography acquisitions of the bone pieces were obtained at an isotropic resolution of 93μm. Standard parameters of bone microarchitecture were evaluated in a defined region within the vertebral body, excluding cortical bone. The bone pieces were measured on a Prodigy DXA system (GE Medical-Lunar, Madison, WI), using a custom-made positioning device and experimental setup. Significant correlations were detected between TBS and 3D parameters of bone microarchitecture, mostly independent of any correlation between TBS and bone mineral density (BMD). The greatest correlation was between TBS and connectivity density, with TBS explaining roughly 67.2% of the variance. Based on multivariate linear regression modeling, we have established a model to allow for the interpretation of the relationship between TBS and 3D bone microarchitecture parameters. This model indicates that TBS adds greater value and power of differentiation between samples with similar BMDs but different bone microarchitectures. It has been shown that it is possible to estimate bone microarchitecture status derived from DXA imaging using TBS.
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The role played by autophagy after ischemia/reperfusion (I/R) in the retina remains unknown. Our study investigated whether ischemic injury in the retina, which causes an energy crisis, would induce autophagy. Retinal ischemia was induced by elevation of the intraocular pressure and modulation of autophagic markers was analyzed at the protein levels in an early and late phase of recovery. Following retinal ischemia an increase in LC3BII was first observed in the early phase of recovery but did not stay until the late phase of recovery. Post-ischemic induction of autophagy by intravitreal rapamycin administration did not provide protection against the lesion induced by the ischemic stress. On the contrary, an increase in the number of apoptotic cells was observed following I/R in the rapamycin treated retinas.
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In many practical applications the state of field soils is monitored by recording the evolution of temperature and soil moisture at discrete depths. We theoretically investigate the systematic errors that arise when mass and energy balances are computed directly from these measurements. We show that, even with no measurement or model errors, large residuals might result when finite difference approximations are used to compute fluxes and storage term. To calculate the limits set by the use of spatially discrete measurements on the accuracy of balance closure, we derive an analytical solution to estimate the residual on the basis of the two key parameters: the penetration depth and the distance between the measurements. When the thickness of the control layer for which the balance is computed is comparable to the penetration depth of the forcing (which depends on the thermal diffusivity and on the forcing period) large residuals arise. The residual is also very sensitive to the distance between the measurements, which requires accurately controlling the position of the sensors in field experiments. We also demonstrate that, for the same experimental setup, mass residuals are sensitively larger than the energy residuals due to the nonlinearity of the moisture transport equation. Our analysis suggests that a careful assessment of the systematic mass error introduced by the use of spatially discrete data is required before using fluxes and residuals computed directly from field measurements.
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Today, there are still uncertainties about the role of exogenous fat on body fat regulation. Early models of energy utilization (for example, Kleiber's, early 20th century) failed to take into account the nature of substrate oxidized in the control of food intake, whereas more recent models (e.g., Flatt's model, end of 20th century) did. Excess body fat storage is ultimately a problem of chronic positive energy balance mediated by a poor control of energy intake or/and a blunted total energy expenditure. Excess fat storage can stem from exogenous fat and to a more limited extent by nonfat substrates precursors transformed into body fat, mostly from carbohydrates, a process known as de novo lipogenesis. When considered over periods of weeks, months or years, total fat balance is closely related to energy balance. Over periods of days, the net change in fat balance is quantitatively limited as compared to the size of endogenous fat storage. The issues discussed in this article primarily include the stimulation of de novo lipogenesis after acute or prolonged CHO overfeeding and whether de novo lipogenesis is a risk factor for obesity development.
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Energy metabolism supports both inhibitory and excitatory neurotransmission processes. This study investigated the specific contribution of astrocytic metabolism to γ-aminobutyric acid (GABA) synthesis and inhibitory GABAergic neurotransmission that remained to be ilucidated in vivo. Therefore, we measured (13) C incorporation into brain metabolites by dynamic (13) C nuclear magnetic resonance spectroscopy at 14.1 T in rats under α-chloralose anaesthesia during infusion of [1,6-(13) C]glucose. The enhanced sensitivity at 14.1 T allowed to quantify incorporation of (13) C into the three aliphatic carbons of GABA non-invasively. Metabolic fluxes were determined with a mathematical model of brain metabolism comprising glial, glutamatergic and GABAergic compartments. GABA synthesis rate was 0.11 ± 0.01 μmol/g/min. GABA-glutamine cycle was 0.053 ± 0.003 μmol/g/min and accounted for 22 ± 1% of total neurotransmitter cycling between neurons and glia. Cerebral glucose oxidation was 0.47 ± 0.02 μmol/g/min, of which 35 ± 1% and 7 ± 1% was diverted to the glutamatergic and GABAergic tricarboxylic acid cycles, respectively. The remaining fraction of glucose oxidation was in glia, where 12 ± 1% of the TCA cycle flux was dedicated to oxidation of GABA. 16 ± 2% of glutamine synthesis was provided to GABAergic neurons. We conclude that substantial metabolic activity occurs in GABAergic neurons and that glial metabolism supports both glutamatergic and GABAergic neurons in the living rat brain. We performed (13) C NMR spectroscopy in vivo at high magnetic field (14.1 T) upon administration of [1,6-(13) C]glucose. This allowed to measure (13) C incorporation into the three aliphatic carbons of GABA in the rat brain, in addition to those of glutamate, glutamine and aspartate. These data were then modelled to determine fluxes of energy metabolism in GABAergic and glutamatergic neurons and glial cells.
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PURPOSE: In the radiopharmaceutical therapy approach to the fight against cancer, in particular when it comes to translating laboratory results to the clinical setting, modeling has served as an invaluable tool for guidance and for understanding the processes operating at the cellular level and how these relate to macroscopic observables. Tumor control probability (TCP) is the dosimetric end point quantity of choice which relates to experimental and clinical data: it requires knowledge of individual cellular absorbed doses since it depends on the assessment of the treatment's ability to kill each and every cell. Macroscopic tumors, seen in both clinical and experimental studies, contain too many cells to be modeled individually in Monte Carlo simulation; yet, in particular for low ratios of decays to cells, a cell-based model that does not smooth away statistical considerations associated with low activity is a necessity. The authors present here an adaptation of the simple sphere-based model from which cellular level dosimetry for macroscopic tumors and their end point quantities, such as TCP, may be extrapolated more reliably. METHODS: Ten homogenous spheres representing tumors of different sizes were constructed in GEANT4. The radionuclide 131I was randomly allowed to decay for each model size and for seven different ratios of number of decays to number of cells, N(r): 1000, 500, 200, 100, 50, 20, and 10 decays per cell. The deposited energy was collected in radial bins and divided by the bin mass to obtain the average bin absorbed dose. To simulate a cellular model, the number of cells present in each bin was calculated and an absorbed dose attributed to each cell equal to the bin average absorbed dose with a randomly determined adjustment based on a Gaussian probability distribution with a width equal to the statistical uncertainty consistent with the ratio of decays to cells, i.e., equal to Nr-1/2. From dose volume histograms the surviving fraction of cells, equivalent uniform dose (EUD), and TCP for the different scenarios were calculated. Comparably sized spherical models containing individual spherical cells (15 microm diameter) in hexagonal lattices were constructed, and Monte Carlo simulations were executed for all the same previous scenarios. The dosimetric quantities were calculated and compared to the adjusted simple sphere model results. The model was then applied to the Bortezomib-induced enzyme-targeted radiotherapy (BETR) strategy of targeting Epstein-Barr virus (EBV)-expressing cancers. RESULTS: The TCP values were comparable to within 2% between the adjusted simple sphere and full cellular models. Additionally, models were generated for a nonuniform distribution of activity, and results were compared between the adjusted spherical and cellular models with similar comparability. The TCP values from the experimental macroscopic tumor results were consistent with the experimental observations for BETR-treated 1 g EBV-expressing lymphoma tumors in mice. CONCLUSIONS: The adjusted spherical model presented here provides more accurate TCP values than simple spheres, on par with full cellular Monte Carlo simulations while maintaining the simplicity of the simple sphere model. This model provides a basis for complementing and understanding laboratory and clinical results pertaining to radiopharmaceutical therapy.
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On the basis of literature values, the relationship between fat-free mass (FFM), fat mass (FM), and resting energy expenditure [REE (kJ/24 h)] was determined for 213 adults (86 males, 127 females). The objectives were to develop a mathematical model to predict REE based on body composition and to evaluate the contribution of FFM and FM to REE. The following regression equations were derived: 1) REE = 1265 + (93.3 x FFM) (r2 = 0.727, P < 0.001); 2) REE = 1114 + (90.4 x FFM) + (13.2 x FM) (R2 = 0.743, P < 0.001); and 3) REE = (108 x FFM) + (16.9 x FM) (R2 = 0.986, P < 0.001). FM explained only a small part of the variation remaining after FFM was accounted for. The models that include both FFM and FM are useful in examination of the changes in REE that occur with a change in both the FFM and FM. To account for more of the variability in REE, FFM will have to be divided into organ mass and skeletal muscle mass in future analyses.
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Glucose is an important signal that regulates glucose and energy homeostasis but its precise physiological role and signaling mechanism in the brain are still uncompletely understood. Over the recent years we have investigated the possibility that central glucose sensing may share functional similarities with glucose sensing by pancreatic beta-cells, in particular a requirement for the expression of the glucose transporter Glut2. Using mice with genetic inactivation of Glut2, but rescued pancreatic beta-cell function by transgenic expression of a glucose transporter, we have established that extrapancreatic glucose sensors are involved: i) in the control of glucagon secretion in response to hypoglycemia, ii) in the control of feeding and iii) of energy expenditure. We have more recently shown that central Glut2-dependent glucose sensors are involved in the regulation of NPY and POMC expression by arcuate nucleus neurons and that the sensitivity to leptin of these neurons is enhanced by Glut2-dependent glucose sensors. Using mice with genetic tagging of Glut2-expressing cells, we determined that the NPY and POMC neurons did not express Glut2 but were connected to Glut2 expressing neurons located most probably outside of the arcuate nucleus. We are now defining the electrophysiological behavior of these Glut2 expressing neurons. Our data provide an initial map of glucose sensing neurons expressing Glut2 and link these neurons with the control of specific physiological function.
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The flow of two immiscible fluids through a porous medium depends on the complex interplay between gravity, capillarity, and viscous forces. The interaction between these forces and the geometry of the medium gives rise to a variety of complex flow regimes that are difficult to describe using continuum models. Although a number of pore-scale models have been employed, a careful investigation of the macroscopic effects of pore-scale processes requires methods based on conservation principles in order to reduce the number of modeling assumptions. In this work we perform direct numerical simulations of drainage by solving Navier-Stokes equations in the pore space and employing the Volume Of Fluid (VOF) method to track the evolution of the fluid-fluid interface. After demonstrating that the method is able to deal with large viscosity contrasts and model the transition from stable flow to viscous fingering, we focus on the macroscopic capillary pressure and we compare different definitions of this quantity under quasi-static and dynamic conditions. We show that the difference between the intrinsic phase-average pressures, which is commonly used as definition of Darcy-scale capillary pressure, is subject to several limitations and it is not accurate in presence of viscous effects or trapping. In contrast, a definition based on the variation of the total surface energy provides an accurate estimate of the macroscopic capillary pressure. This definition, which links the capillary pressure to its physical origin, allows a better separation of viscous effects and does not depend on the presence of trapped fluid clusters.
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Exposure to solar ultraviolet (UV) light is the main causative factor for skin cancer. UV exposure depends on environmental and individual factors. Individual exposure data remain scarce and development of alternative assessment methods is greatly needed. We developed a model simulating human exposure to solar UV. The model predicts the dose and distribution of UV exposure received on the basis of ground irradiation and morphological data. Standard 3D computer graphics techniques were adapted to develop a rendering engine that estimates the solar exposure of a virtual manikin depicted as a triangle mesh surface. The amount of solar energy received by each triangle was calculated, taking into account reflected, direct and diffuse radiation, and shading from other body parts. Dosimetric measurements (n = 54) were conducted in field conditions using a foam manikin as surrogate for an exposed individual. Dosimetric results were compared to the model predictions. The model predicted exposure to solar UV adequately. The symmetric mean absolute percentage error was 13%. Half of the predictions were within 17% range of the measurements. This model provides a tool to assess outdoor occupational and recreational UV exposures, without necessitating time-consuming individual dosimetry, with numerous potential uses in skin cancer prevention and research.
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Monocarboxylate transporters (MCTs) are essential for the use of lactate, an energy substrate known to be overproduced in brain during an ischemic episode. The expression of MCT1 and MCT2 was investigated at 48 h of reperfusion from focal ischemia induced by unilateral extradural compression in Wistar rats. Increased MCT1 mRNA expression was detected in the injured cortex and hippocampus of compressed animals compared to sham controls. In the contralateral, uncompressed hemisphere, increases in MCT1 mRNA level in the cortex and MCT2 mRNA level in the hippocampus were noted. Interestingly, strong MCT1 and MCT2 protein expression was found in peri-lesional macrophages/microglia and in an isolectin B4+/S100beta+ cell population in the corpus callosum. In vitro, MCT1 and MCT2 protein expression was observed in the N11 microglial cell line, whereas an enhancement of MCT1 expression by tumor necrosis factor-alpha (TNF-alpha) was shown in these cells. Modulation of MCT expression in microglia suggests that these transporters may help sustain microglial functions during recovery from focal brain ischemia. Overall, our study indicates that changes in MCT expression around and also away from the ischemic area, both at the mRNA and protein levels, are a part of the metabolic adaptations taking place in the brain after ischemia.
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PURPOSE: Low tidal volume ventilation and permissive hypercapnia are required in patients with sepsis complicated by ARDS. The effects of hypercapnia on tissue oxidative metabolism in this setting are unknown. We therefore determined the effects of moderate hypercapnia on markers of systemic and splanchnic oxidative metabolism in an animal model of endotoxemia. METHODS: Anesthetized rats maintained at a PaCO(2) of 30, 40 or 60 mmHg were challenged with endotoxin. A control group (PaCO(2) 40 mmHg) received isotonic saline. Hemodynamic variables, arterial lactate, pyruvate, and ketone bodies were measured at baseline and after 4 h. Tissue adenosine triphosphate (ATP) and lactate were measured in the small intestine and the liver after 4 h. RESULTS: Endotoxin resulted in low cardiac output, increased lactate/pyruvate ratio and decreased ketone body ratio. These changes were not influenced by hypercapnia, but were more severe with hypocapnia. In the liver, ATP decreased and lactate increased independently from PaCO(2) after endotoxin. In contrast, the drop of ATP and the rise in lactate triggered by endotoxin in the intestine were prevented by hypercapnia. CONCLUSIONS: During endotoxemia in rats, moderate hypercapnia prevents the deterioration of tissue energetics in the intestine.
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The flexibility of different regions of HIV-1 protease was examined by using a database consisting of 73 X-ray structures that differ in terms of sequence, ligands or both. The root-mean-square differences of the backbone for the set of structures were shown to have the same variation with residue number as those obtained from molecular dynamics simulations, normal mode analyses and X-ray B-factors. This supports the idea that observed structural changes provide a measure of the inherent flexibility of the protein, although specific interactions between the protease and the ligand play a secondary role. The results suggest that the potential energy surface of the HIV-1 protease is characterized by many local minima with small energetic differences, some of which are sampled by the different X-ray structures of the HIV-1 protease complexes. Interdomain correlated motions were calculated from the structural fluctuations and the results were also in agreement with molecular dynamics simulations and normal mode analyses. Implications of the results for the drug-resistance engendered by mutations are discussed briefly.