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.

Lag-one autocorrelation in short series: Estimation and hypothesis testing

In the first part of the study, nine estimators of the first-order autoregressive parameter are reviewed and a new estimator is proposed. The relationships and discrepancies between the estimators are discussed in order to achieve a clear differentiation. In the second part of the study, the precision in the estimation of autocorrelation is studied. The performance of the ten lag-one autocorrelation estimators is compared in terms of Mean Square Error (combining bias and variance) using data series generated by Monte Carlo simulation. The results show that there is not a single optimal estimator for all conditions, suggesting that the estimator ought to be chosen according to sample size and to the information available of the possible direction of the serial dependence. Additionally, the probability of labelling an actually existing autocorrelation as statistically significant is explored using Monte Carlo sampling. The power estimates obtained are quite similar among the tests associated with the different estimators. These estimates evidence the small probability of detecting autocorrelation in series with less than 20 measurement times.

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.

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.

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.

Electromyographic, cerebral, and muscle hemodynamic responses during intermittent, isometric contractions of the biceps brachii at three submaximal intensities.

This study examined the electromyographic, cerebral and muscle hemodynamic responses during intermittent isometric contractions of biceps brachii at 20, 40, and 60% of maximal voluntary contraction (MVC). Eleven volunteers completed 2 min of intermittent isometric contractions (12/min) at an elbow angle of 90° interspersed with 3 min rest between intensities in systematic order. Surface electromyography (EMG) was recorded from the right biceps brachii and near infrared spectroscopy (NIRS) was used to simultaneously measure left prefrontal and right biceps brachii oxyhemoglobin (HbO2), deoxyhemoglobin (HHb), and total hemoglobin (Hbtot). Transcranial Doppler ultrasound was used to measure middle cerebral artery velocity (MCAv) bilaterally. Finger photoplethysmography was used to record beat-to-beat blood pressure and heart rate. EMG increased with force output from 20 to 60% MVC (P < 0.05). Cerebral HbO2 and Hbtot increased while HHb decreased during contractions with differences observed between 60% vs. 40% and 20% MVC (P < 0.05). Muscle HbO2 decreased while HHb increased during contractions with differences being observed among intensities (P < 0.05). Muscle Hbtot increased from rest at 20% MVC (P < 0.05), while no further change was observed at 40 and 60% MVC (P > 0.05). MCAv increased from rest to exercise but was not different among intensities (P > 0.05). Force output correlated with the root mean square EMG and changes in muscle HbO2 (P < 0.05), but not changes in cerebral HbO2 (P > 0.05) at all three intensities. Force output declined by 8% from the 1st to the 24th contraction only at 60% MVC and was accompanied by systematic increases in RMS, cerebral HbO2 and Hbtot with a leveling off in muscle HbO2 and Hbtot. These changes were independent of alterations in mean arterial pressure. Since cerebral blood flow and oxygenation were elevated at 60% MVC, we attribute the development of fatigue to reduced muscle oxygen availability rather than impaired central neuronal activation.

Robust power allocation algorithms for MIMO OFDM systems with imperfect CSI

This paper presents a Bayesian approach to the design of transmit prefiltering matrices in closed-loop schemes robust to channel estimation errors. The algorithms are derived for a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Two different optimizationcriteria are analyzed: the minimization of the mean square error and the minimization of the bit error rate. In both cases, the transmitter design is based on the singular value decomposition (SVD) of the conditional mean of the channel response, given the channel estimate. The performance of the proposed algorithms is analyzed,and their relationship with existing algorithms is indicated. As withother previously proposed solutions, the minimum bit error rate algorithmconverges to the open-loop transmission scheme for very poor CSI estimates.

Motion estimation using higher-order statistics

The objective of this paper is to introduce a fourth-order cost function of the displaced frame difference (DFD) capable of estimatingmotion even for small regions or blocks. Using higher than second-orderstatistics is appropriate in case the image sequence is severely corruptedby additive Gaussian noise. Some results are presented and compared to those obtained from the mean kurtosis and the mean square error of the DFD.

Methods for the analysis of two dimensional measurement data of paper web

This work is devoted to the problem of reconstructing the basis weight structure at paper web with black{box techniques. The data that is analyzed comes from a real paper machine and is collected by an o®-line scanner. The principal mathematical tool used in this work is Autoregressive Moving Average (ARMA) modelling. When coupled with the Discrete Fourier Transform (DFT), it gives a very flexible and interesting tool for analyzing properties of the paper web. Both ARMA and DFT are independently used to represent the given signal in a simplified version of our algorithm, but the final goal is to combine the two together. Ljung-Box Q-statistic lack-of-fit test combined with the Root Mean Squared Error coefficient gives a tool to separate significant signals from noise.

Relation between sequence and structure of HIV-1 protease inhibitor complexes: a model system for the analysis of protein flexibility.

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.

Cardiorespiratory and Cardiac Autonomic Responses to 30-15 Intermittent Fitness Test in Team Sport Players

Buchheit, M, Al Haddad, H, Millet GP, Lepretre, PM, Newton, M, and Ahmaidi, S. Cardiorespiratory and cardiac autonomic responses to 30-15 Intermittent Fitness Test in team sport players. J Strength Cond Res 23(1): xxx-xxx, 2009-The 30-15 Intermittent Fitness Test (30-15IFT) is an attractive alternative to classic continuous incremental field tests for defining a reference velocity for interval training prescription in team sport athletes. The aim of the present study was to compare cardiorespiratory and autonomic responses to 30-15IFT with those observed during a standard continuous test (CT). In 20 team sport players (20.9 +/- 2.2 years), cardiopulmonary parameters were measured during exercise and for 10 minutes after both tests. Final running velocity, peak lactate ([La]peak), and rating of perceived exertion (RPE) were also measured. Parasympathetic function was assessed during the postexercise recovery phase via heart rate (HR) recovery time constant (HRRtau) and HR variability (HRV) vagal-related indices. At exhaustion, no difference was observed in peak oxygen uptake (&OV0312;o2peak), respiratory exchange ratio, HR, or RPE between 30-15IFT and CT. In contrast, 30-15IFT led to significantly higher minute ventilation, [La]peak, and final velocity than CT (p < 0.05 for all parameters). All maximal cardiorespiratory variables observed during both tests were moderately to well correlated (e.g., r = 0.76, p = 0.001 for &OV0312;o2peak). Regarding ventilatory thresholds (VThs), all cardiorespiratory measurements were similar and well correlated between the 2 tests. Parasympathetic function was lower after 30-15IFT than after CT, as indicated by significantly longer HHRtau (81.9 +/- 18.2 vs. 60.5 +/- 19.5 for 30-15IFT and CT, respectively, p < 0.001) and lower HRV vagal-related indices (i.e., the root mean square of successive R-R intervals differences [rMSSD]: 4.1 +/- 2.4 and 7.0 +/- 4.9 milliseconds, p < 0.05). In conclusion, the 30-15IFT is accurate for assessing VThs and &OV0312;o2peak, but it alters postexercise parasympathetic function more than a continuous incremental protocol.