Finite-size effects in nonequilibrium correlation functions

We have shown that finite-size effects in the correlation functions away from equilibrium may be introduced through dimensionless numbers: the Nusselt numbers, accounting for both the nature of the boundaries and the size of the system. From an analysis based on fluctuating hydrodynamics, we conclude that the mean-square fluctuations satisfy scaling laws, since they depend only on the dimensionless numbers in addition to reduced variables. We focus on the case of diffusion modes and describe some physical situations in which finite-size effects may be relevant.

Dispersion of passive particles by a quasi-two-dimensional turbulent flow

Using the experimental data of Paret and Tabeling [Phys. Rev. Lett. 79, 4162 (1997)] we consider in detail the dispersion of particle pairs by a two-dimensional turbulent flow and its relation to the kinematic properties of the velocity field. We show that the mean square separation of a pair of particles is governed by rather rare, extreme events and that the majority of initially close pairs are not dispersed by the flow. Another manifestation of the same effect is the fact that the dispersion of an initially dense cluster is not the result of homogeneously spreading the particles within the whole system. Instead it proceeds through a splitting into smaller but also dense clusters. The statistical nature of this effect is discussed.

Trends and determinants of time in bed in Geneva, Switzerland

STUDY OBJECTIVES: There is limited information regarding sleep duration and determinants in Switzerland. We aimed to assess the trends and determinants of time in bed as a proxy for sleep duration in the Swiss canton of Geneva. METHODS: Data from repeated, independent cross-sectional representative samples of adults (≥ 18 years) of the Geneva population were collected between 2005 and 2011. Self-reported time in bed, education, monthly income, and nationality were assessed by questionnaire. RESULTS: Data from 3,853 participants (50% women, 51.7 ± 10.9 years) were analyzed. No significant trend was observed between 2005 and 2011 regarding time in bed or the prevalence of short (≤ 6 h/day) and long (> 9 h/day) time in bed. Elderly participants reported a longer time in bed (year-adjusted mean ± standard error: 7.67 ± 0.02, 7.82 ± 0.03, and 8.41 ± 0.04 h/day for 35-50, 50-65, and 65+ years, respectively, p < 0.001), while shorter time in bed was reported by non-Swiss participants (7.77 ± 0.03 vs. 7.92 ± 0.03 h/day for Swiss nationals, p < 0.001), participants with higher education (7.92 ± 0.02 for non-university vs. 7.74 ± 0.03 h/day for university, p < 0.001) or higher income (8.10 ± 0.04, 7.84 ± 0.03, and 7.70 ± 0.03 h/day for < 5,000 SFr; 5,000-9,500 SFr, and > 9,500 SFr, respectively, p < 0.001). Multivariable-adjusted polytomous logistic regression showed short and long time in bed to be positively associated with obesity and negatively associated with income. CONCLUSION: In a Swiss adult population, sleep duration as assessed by time in bed did not change significantly between 2005 and 2011. Both clinical and socioeconomic factors influence time in bed.

Statistical Modeling of the Eye for Multimodal Treatment Planning for External Beam Radiation Therapy of Intraocular Tumors.

PURPOSE: Ocular anatomy and radiation-associated toxicities provide unique challenges for external beam radiation therapy. For treatment planning, precise modeling of organs at risk and tumor volume are crucial. Development of a precise eye model and automatic adaptation of this model to patients' anatomy remain problematic because of organ shape variability. This work introduces the application of a 3-dimensional (3D) statistical shape model as a novel method for precise eye modeling for external beam radiation therapy of intraocular tumors. METHODS AND MATERIALS: Manual and automatic segmentations were compared for 17 patients, based on head computed tomography (CT) volume scans. A 3D statistical shape model of the cornea, lens, and sclera as well as of the optic disc position was developed. Furthermore, an active shape model was built to enable automatic fitting of the eye model to CT slice stacks. Cross-validation was performed based on leave-one-out tests for all training shapes by measuring dice coefficients and mean segmentation errors between automatic segmentation and manual segmentation by an expert. RESULTS: Cross-validation revealed a dice similarity of 95% ± 2% for the sclera and cornea and 91% ± 2% for the lens. Overall, mean segmentation error was found to be 0.3 ± 0.1 mm. Average segmentation time was 14 ± 2 s on a standard personal computer. CONCLUSIONS: Our results show that the solution presented outperforms state-of-the-art methods in terms of accuracy, reliability, and robustness. Moreover, the eye model shape as well as its variability is learned from a training set rather than by making shape assumptions (eg, as with the spherical or elliptical model). Therefore, the model appears to be capable of modeling nonspherically and nonelliptically shaped eyes.

EADock: docking of small molecules into protein active sites with a multiobjective evolutionary optimization.

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.

Reticulocyte dynamic and hemoglobin variability in hemodialysis patients treated with Darbepoetin alfa and C.E.R.A.: a randomized controlled trial.

BACKGROUND: In a simulation based on a pharmacokinetic model we demonstrated that increasing the erythropoiesis stimulating agents (ESAs) half-life or shortening their administration interval decreases hemoglobin variability. The benefit of reducing the administration interval was however lessened by the variability induced by more frequent dosage adjustments. The purpose of this study was to analyze the reticulocyte and hemoglobin kinetics and variability under different ESAs and administration intervals in a collective of chronic hemodialysis patients. METHODS: The study was designed as an open-label, randomized, four-period cross-over investigation, including 30 patients under chronic hemodialysis at the regional hospital of Locarno (Switzerland) in February 2010 and lasting 2 years. Four subcutaneous treatment strategies (C.E.R.A. every 4 weeks Q4W and every 2 weeks Q2W, Darbepoetin alfa Q4W and Q2W) were compared with each other. The mean square successive difference of hemoglobin, reticulocyte count and ESAs dose was used to quantify variability. We distinguished a short- and a long-term variability based respectively on the weekly and monthly successive difference. RESULTS: No difference was found in the mean values of biological parameters (hemoglobin, reticulocytes, and ferritin) between the 4 strategies. ESAs type did not affect hemoglobin and reticulocyte variability, but C.E.R.A induced a more sustained reticulocytes response over time and increased the risk of hemoglobin overshooting (OR 2.7, p = 0.01). Shortening the administration interval lessened the amplitude of reticulocyte count fluctuations but resulted in more frequent ESAs dose adjustments and in amplified reticulocyte and hemoglobin variability. Q2W administration interval was however more favorable in terms of ESAs dose, allowing a 38% C.E.R.A. dose reduction, and no increase of Darbepoetin alfa. CONCLUSIONS: The reticulocyte dynamic was a more sensitive marker of time instability of the hemoglobin response under ESAs therapy. The ESAs administration interval had a greater impact on hemoglobin variability than the ESAs type. The more protracted reticulocyte response induced by C.E.R.A. could explain both, the observed higher risk of overshoot and the significant increase in efficacy when shortening its administration interval.Trial registrationClinicalTrials.gov NCT01666301.

Effects of prior repeated-sprints with different recovery duration on oxygen uptake kinetics during subsequent heavy-exercise

Introduction: Prior repeated-sprints (6) has become an interesting method to resolve the debate surrounding the principal factors that limits the oxygen uptake (V'O2) kinetics at the onset of exercise [i.e., muscle O2 delivery (5) or metabolic inertia (3)]. The aim of this study was to compare the effects of two repeated-sprints sets of 6x6s separated by different recovery duration between the sprints on V'O2 and muscular de-oxygenation [HHb] kinetics during a subsequent heavy-intensity exercise. Methods: 10 male subjects performed a 6-min constant-load cycling test (T50) at intensity corresponding to half of the difference between V'O2max and the ventilatory threshold. Then, they performed two repeated-sprints sets of 6x6s all-out separated by different recovery duration between the sprints (S1:30s and S2:3min) followed, after 7-min-recovery, by the T50 (S1T50 and S2T50, respectively). V'O2, [HHb] of the vastus lateralis (VL) and surface electromyography activity [i.e., root-mean-square (RMS) and the median frequency of the power density spectrum (MDF)] from VL and vastus medialis (VM) were recorded throughout T50. Models using a bi-exponential function for the overall T50 and a mono-exponential for the first 90s of T50 were used to define V'O2 and [HHb] kinetics respectively. Results: V'O2 mean value was higher in S1 (2.9±0.3l.min-1) than in S2 (1.2±0.3l.min-1); (p<0.001). The peripheral blood flow was increased after sprints as attested by a higher basal heart rate (HRbaseline) (S1T50: +22%; S2T50: +17%; p≤0.008). Time delay [HHb] was shorter for S1T50 and S2T50 than for T50 (-22% for both; p≤0.007) whereas the mean response time of V'O2 was accelerated only after S1 (S1T50: 32.3±2.5s; S2T50: 34.4±2.6s; T50: 35.7±5.4s; p=0.031). There were no significant differences in RMS between the three conditions (p>0.05). MDF of VM was higher during the first 3-min in S1T50 than in T50 (+6%; p≤0.05). Conclusion: The study show that V'O2 kinetics was speeded by prior repeated-sprints with a short (30s) but not a long (3min) inter-sprints-recovery even though the [HHb] kinetics was accelerated and the peripheral blood flow was enhanced after both sprints. S1, inducing a greater PCr depletion (1) and change in the pattern of the fibres recruitment (increase in MDF) compared with S2, may decrease metabolic inertia (2), stimulate the oxidative phosphorylation activation (4) and accelerate V'O2 kinetics at the beginning of the subsequent high-intensity exercise.

Effects of prior repeated-sprints with different recovery duration on oxygen uptake kinetics during subsequent heavy-exercise.

Introduction: Prior repeated-sprints (6) has become an interesting method to resolve the debate surrounding the principal factors that limits the oxygen uptake (V'O2) kinetics at the onset of exercise [i.e., muscle O2 delivery (5) or metabolic inertia (3)]. The aim of this study was to compare the effects of two repeated-sprints sets of 6x6s separated by different recovery duration between the sprints on V'O2 and muscular de-oxygenation [HHb] kinetics during a subsequent heavy-intensity exercise. Methods: 10 male subjects performed a 6-min constant-load cycling test (T50) at intensity corresponding to half of the difference between V'O2max and the ventilatory threshold. Then, they performed two repeated-sprints sets of 6x6s all-out separated by different recovery duration between the sprints (S1:30s and S2:3min) followed, after 7-min-recovery, by the T50 (S1T50 and S2T50, respectively). V'O2, [HHb] of the vastus lateralis (VL) and surface electromyography activity [i.e., root-mean-square (RMS) and the median frequency of the power density spectrum (MDF)] from VL and vastus medialis (VM) were recorded throughout T50. Models using a bi-exponential function for the overall T50 and a mono-exponential for the first 90s of T50 were used to define V'O2 and [HHb] kinetics respectively. Results: V'O2 mean value was higher in S1 (2.9±0.3l.min-1) than in S2 (1.2±0.3l.min-1); (p<0.001). The peripheral blood flow was increased after sprints as attested by a higher basal heart rate (HRbaseline) (S1T50: +22%; S2T50: +17%; p≤0.008). Time delay [HHb] was shorter for S1T50 and S2T50 than for T50 (-22% for both; p≤0.007) whereas the mean response time of V'O2 was accelerated only after S1 (S1T50: 32.3±2.5s; S2T50: 34.4±2.6s; T50: 35.7±5.4s; p=0.031). There were no significant differences in RMS between the three conditions (p>0.05). MDF of VM was higher during the first 3-min in S1T50 than in T50 (+6%; p≤0.05). Conclusion: The study show that V'O2 kinetics was speeded by prior repeated-sprints with a short (30s) but not a long (3min) inter-sprints-recovery even though the [HHb] kinetics was accelerated and the peripheral blood flow was enhanced after both sprints. S1, inducing a greater PCr depletion (1) and change in the pattern of the fibres recruitment (increase in MDF) compared with S2, may decrease metabolic inertia (2), stimulate the oxidative phosphorylation activation (4) and accelerate V'O2 kinetics at the beginning of the subsequent high-intensity exercise.

Post-exercise parasympathetic reactivation and sensibility to hypoxia

Introduction Exposure to hypoxia leads to several reactions of the organism, which try to compensate the reduced oxygen level in the blood. Acute response is characterized by an increase in pulmonary ventilation (Hypoxia Ventilatory Response, HVR) and in cardiac output (cardiac response to hypoxia). Heart rate (HR) at rest and during exercise is higher at high altitude than at sea level, whereas HRmax is lower. These cardiac adaptations are partially explained by an increased sympathetic stimulation associated with a reduced parasympathetic tone (12). The precise mechanisms of HRmax decline in acute hypoxia are however still to be identified, although several hypothesis have been suggested, such as a direct effect of hypoxia on the electrophysiological properties, an influence of skeletal maximal VO2 or a modulation of the autonomic nervous system (8). Some authors have reported that endurance trained athletes present an increased sensitivity to hypoxia shown by a large reduction in VO2max and an important decrease in arterial saturation. (9,11, 13) A hypoxia test can assess the sensibility of chemoreceptors to the reduction of oxygen by calculating hypoxic ventilatory and cardiac responses, knowing that low sensibility is correlated with poor acclimatization. Two parameters results from the differences in ventilation (and heart rate) divided by the difference in the arterial oxygen saturation between normoxia and hypoxia (18). Objective The hypothesis tested by this study is that parasympathetic reactivation after moderate effort in hypoxic condition can be used as a marker of individual sensibility to hypoxia. Parasympathetic reactivation is a marker of vagal tone that predict endurance capacity and aerobic fitness (2,7). Methods Subjects This study uses data obtained from two groups of athletes participating into two larger studies about adaptation to hypoxia. One group is composed of elite athletes (Swiss ski mountaineering team), the other one of mid-level athletes (ski mountaineering amateurs). The particularity of this target population is that they often train at high altitude, and therefore could show a better response to hypoxia than athleltes of other disciplines. Protocol The athletes performed a submaximal exercise (6min run at 9 km/h, flat) followed by 10 min of seated rest either in an hypoxic chamber (simulated altitude of 3000m) or in normoxic conditions. During the resting phase parasympathetic reactivation was assessed by beat-to-beat HR measurements.A test of tolerance to altitude was also performed. Analysis Parasympathetic reactivation, assessed by the calculation of the root mean square of successive differences in the R-R intervals (RMSSD)(4), is compared to individual responses at altitude, in order to appreciate the correlation between the two phenomena.

Multiway Array Decomposition Analysis of EEGs in Alzheimer’s Disease

Methods for the extraction of features from physiological datasets are growing needs as clinical investigations of Alzheimer’s disease (AD) in large and heterogeneous population increase. General tools allowing diagnostic regardless of recording sites, such as different hospitals, are essential and if combined to inexpensive non-invasive methods could critically improve mass screening of subjects with AD. In this study, we applied three state of the art multiway array decomposition (MAD) methods to extract features from electroencephalograms (EEGs) of AD patients obtained from multiple sites. In comparison to MAD, spectral-spatial average filter (SSFs) of control and AD subjects were used as well as a common blind source separation method, algorithm for multiple unknown signal extraction (AMUSE). We trained a feed-forward multilayer perceptron (MLP) to validate and optimize AD classification from two independent databases. Using a third EEG dataset, we demonstrated that features extracted from MAD outperformed features obtained from SSFs AMUSE in terms of root mean squared error (RMSE) and reaching up to 100% of accuracy in test condition. We propose that MAD maybe a useful tool to extract features for AD diagnosis offering great generalization across multi-site databases and opening doors to the discovery of new characterization of the disease.

Cardiac motion estimation by joint alignment of tagged MRI sequences

Image registration has been proposed as an automatic method for recovering cardiac displacement fields from Tagged Magnetic Resonance Imaging (tMRI) sequences. Initially performed as a set of pairwise registrations, these techniques have evolved to the use of 3D+t deformation models, requiring metrics of joint image alignment (JA). However, only linear combinations of cost functions defined with respect to the first frame have been used. In this paper, we have applied k-Nearest Neighbors Graphs (kNNG) estimators of the -entropy (H ) to measure the joint similarity between frames, and to combine the information provided by different cardiac views in an unified metric. Experiments performed on six subjects showed a significantly higher accuracy (p < 0.05) with respect to a standard pairwise alignment (PA) approach in terms of mean positional error and variance with respect to manually placed landmarks. The developed method was used to study strains in patients with myocardial infarction, showing a consistency between strain, infarction location, and coronary occlusion. This paper also presentsan interesting clinical application of graph-based metric estimators, showing their value for solving practical problems found in medical imaging.

The effect of workplace smoking bans on heart rate variability and pulse wave velocity of non-smoking hospitality workers

OBJECTIVES: To investigate the effect of a change in second-hand smoke (SHS) exposure on heart rate variability (HRV) and pulse wave velocity (PWV), this study utilized a quasi-experimental setting when a smoking ban was introduced. METHODS: HRV, a quantitative marker of autonomic activity of the nervous system, and PWV, a marker of arterial stiffness, were measured in 55 non-smoking hospitality workers before and 3-12 months after a smoking ban and compared to a control group that did not experience an exposure change. SHS exposure was determined with a nicotine-specific badge and expressed as inhaled cigarette equivalents per day (CE/d). RESULTS: PWV and HRV parameters significantly changed in a dose-dependent manner in the intervention group as compared to the control group. A one CE/d decrease was associated with a 2.3 % (95 % CI 0.2-4.4; p = 0.031) higher root mean square of successive differences (RMSSD), a 5.7 % (95 % CI 0.9-10.2; p = 0.02) higher high-frequency component and a 0.72 % (95 % CI 0.40-1.05; p < 0.001) lower PWV. CONCLUSIONS: PWV and HRV significantly improved after introducing smoke-free workplaces indicating a decreased cardiovascular risk.

Brazilian maize genotypes sensitivity to water deficit estimated through a simple crop yield model

The objective of this work was to determine the sensitivity of maize (Zea mays) genotypes to water deficit, using a simple agrometeorological crop yield model. Crop actual yield and agronomic data of 26 genotypes were obtained from the Maize National Assays carried out in ten locations, in four Brazilian states, from 1998 to 2006. Weather information for each experimental location and period were obtained from the closest weather station. Water deficit sensitivity index (Ky) was determined using the crop yield depletion model. Genotypes can be divided into two groups according to their resistance to water deficit. Normal resistance genotypes had Ky ranging from 0.4 to 0.5 in vegetative period, 1.4 to 1.5 in flowering, 0.3 to 0.6 in fruiting, and 0.1 to 0.3 in maturing period, whereas the higher resistance genotypes had lower values, respectively 0.2-0.4, 0.7-1.2, 0.2-0.4, and 0.1-0.2. The general Ky for the total growing season was 2.15 for sensitive genotypes and 1.56 for the resistant ones. Model performance was acceptable to evaluate crop actual yield, whose average errors estimated for each genotype ranged from -5.7% to +5.8%, and whose general mean absolute error was 960 kg ha-1 (10%).

EADock : design of a new molecular docking algorithm and some of its applications

3 Summary 3. 1 English The pharmaceutical industry has been facing several challenges during the last years, and the optimization of their drug discovery pipeline is believed to be the only viable solution. High-throughput techniques do participate actively to this optimization, especially when complemented by computational approaches aiming at rationalizing the enormous amount of information that they can produce. In siiico techniques, such as virtual screening or rational drug design, are now routinely used to guide drug discovery. Both heavily rely on the prediction of the molecular interaction (docking) occurring between drug-like molecules and a therapeutically relevant target. Several softwares are available to this end, but despite the very promising picture drawn in most benchmarks, they still hold several hidden weaknesses. As pointed out in several recent reviews, the docking problem is far from being solved, and there is now a need for methods able to identify binding modes with a high accuracy, which is essential to reliably compute the binding free energy of the ligand. This quantity is directly linked to its affinity and can be related to its biological activity. Accurate docking algorithms are thus critical for both the discovery and the rational optimization of new drugs. In this thesis, a new docking software aiming at this goal is presented, EADock. It uses a 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 R around the center of mass of the ligand position in the crystal structure, and conversely to other benchmarks, our algorithms was fed with optimized ligand positions up to 10 A root mean square deviation 2MSD) from the crystal structure. This validation illustrates the efficiency of our sampling heuristic, 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 in this benchmark could be explained by the presence of crystal contacts in the experimental structure. EADock has been used to understand molecular interactions involved in the regulation of the Na,K ATPase, and in the activation of the nuclear hormone peroxisome proliferatoractivated receptors a (PPARa). It also helped to understand the action of common pollutants (phthalates) on PPARy, and the impact of biotransformations of the anticancer drug Imatinib (Gleevec®) on its binding mode to the Bcr-Abl tyrosine kinase. Finally, a fragment-based rational drug design approach using EADock was developed, and led to the successful design of new peptidic ligands for the a5ß1 integrin, and for the human PPARa. In both cases, the designed peptides presented activities comparable to that of well-established ligands such as the anticancer drug Cilengitide and Wy14,643, respectively. 3.2 French Les récentes difficultés de l'industrie pharmaceutique ne semblent pouvoir se résoudre que par l'optimisation de leur processus de développement de médicaments. Cette dernière implique de plus en plus. de techniques dites "haut-débit", particulièrement efficaces lorsqu'elles sont couplées aux outils informatiques permettant de gérer la masse de données produite. Désormais, les approches in silico telles que le criblage virtuel ou la conception rationnelle de nouvelles molécules sont utilisées couramment. Toutes deux reposent sur la capacité à prédire les détails de l'interaction moléculaire entre une molécule ressemblant à un principe actif (PA) et une protéine cible ayant un intérêt thérapeutique. Les comparatifs de logiciels s'attaquant à cette prédiction sont flatteurs, mais plusieurs problèmes subsistent. La littérature récente tend à remettre en cause leur fiabilité, affirmant l'émergence .d'un besoin pour des approches plus précises du mode d'interaction. Cette précision est essentielle au calcul de l'énergie libre de liaison, qui est directement liée à l'affinité du PA potentiel pour la protéine cible, et indirectement liée à son activité biologique. Une prédiction précise est d'une importance toute particulière pour la découverte et l'optimisation de nouvelles molécules actives. Cette thèse présente un nouveau logiciel, EADock, mettant en avant une telle précision. Cet algorithme évolutionnaire hybride utilise deux pressions de sélections, combinées à une gestion de la diversité sophistiquée. EADock repose sur CHARMM pour les calculs d'énergie et la gestion des coordonnées atomiques. Sa validation a été effectuée sur 37 complexes protéine-ligand cristallisés, incluant 11 protéines différentes. L'espace de recherche a été étendu à une sphère de 151 de rayon autour du centre de masse du ligand cristallisé, et contrairement aux comparatifs habituels, l'algorithme est parti de solutions optimisées présentant un RMSD jusqu'à 10 R par rapport à la structure cristalline. Cette validation a permis de mettre en évidence l'efficacité de notre heuristique de recherche car des modes d'interactions présentant un RMSD inférieur à 2 R par rapport à la structure cristalline ont été classés premier pour 68% des complexes. Lorsque les cinq meilleures solutions sont prises en compte, le taux de succès grimpe à 78%, et 92% lorsque la totalité de la dernière génération est prise en compte. La plupart des erreurs de prédiction sont imputables à la présence de contacts cristallins. Depuis, EADock a été utilisé pour comprendre les mécanismes moléculaires impliqués dans la régulation de la Na,K ATPase et dans l'activation du peroxisome proliferatoractivated receptor a (PPARa). Il a également permis de décrire l'interaction de polluants couramment rencontrés sur PPARy, ainsi que l'influence de la métabolisation de l'Imatinib (PA anticancéreux) sur la fixation à la kinase Bcr-Abl. Une approche basée sur la prédiction des interactions de fragments moléculaires avec protéine cible est également proposée. Elle a permis la découverte de nouveaux ligands peptidiques de PPARa et de l'intégrine a5ß1. Dans les deux cas, l'activité de ces nouveaux peptides est comparable à celles de ligands bien établis, comme le Wy14,643 pour le premier, et le Cilengitide (PA anticancéreux) pour la seconde.

Effects of prior short multiple-sprint exercises with different intersprint recoveries on the slow component of oxygen uptake during high-intensity exercise.

This study compares the effects of two short multiple-sprint exercise (MSE) (6 × 6 s) sessions with two different recovery durations (30 s or 180 s) on the slow component of oxygen uptake ([Formula: see text]O(2)) during subsequent high-intensity exercise. Ten male subjects performed a 6-min cycling test at 50% of the difference between the gas exchange threshold and [Formula: see text]O(2peak) (Δ50). Then, the subjects performed two MSEs of 6 × 6 s separated by two intersprint recoveries of 30 s (MSE(30)) and 180 s (MSE(180)), followed 10 min later by the Δ50 (Δ50(30) and Δ50(180), respectively). Electromyography (EMG) activities of the vastus medialis and lateralis were measured throughout each exercise bout. During MSE(30), muscle activity (root mean square) increased significantly (p ≤ 0.04), with a significant leftward-shifted median frequency of the power density spectrum (MDF; p ≤ 0.01), whereas MDF was significantly rightward-shifted during MSE(180) (p = 0.02). The mean [Formula: see text]O(2) value was significantly higher in MSE(30) than in MSE(180) (p < 0.001). During Δ50(30), [Formula: see text]O(2) and the deoxygenated hemoglobin ([HHb]) slow components were significantly reduced (-27%, p = 0.02, and -34%, p = 0.003, respectively) compared with Δ50. There were no significant modifications of the [Formula: see text]O(2) slow component in Δ50(180) compared with Δ50 (p = 0.32). The neuromuscular and metabolic adaptations during MSE(30) (preferential activation of type I muscle fibers evidenced by decreased MDF and a greater aerobic metabolism contribution to the required energy demands), but not during MSE(180), may lead to reduced [Formula: see text]O(2) and [HHb] slow components, suggesting an alteration in motor units recruitment profile (i.e., change in the type of muscle fibers recruited) and (or) an improved muscle O(2) delivery during subsequent exercise.