Repeated sprinting on natural grass impairs vertical stiffness but does not alter plantar loading in soccer players.

This study aimed to determine changes in spring-mass model (SMM) characteristics, plantar pressures, and muscle activity induced by the repetition of sprints in soccer-specific conditions; i.e., on natural grass with soccer shoes. Thirteen soccer players performed 6 × 20 m sprints interspersed with 20 s of passive recovery. Plantar pressure distribution was recorded via an insole pressure recorder device divided into nine areas for analysis. Stride temporal parameters allowed to estimate SMM characteristics. Surface electromyographic activity was monitored for vastus lateralis, rectus femoris, and biceps femoris muscles. Sprint time, contact time, and total stride duration lengthened from the first to the last repetition (+6.7, +12.9, and +9.3%; all P < 0.05), while flight time, swing time, and stride length remained constant. Stride frequency decrease across repetitions approached significance (-6.8%; P = 0.07). No main effect of the sprint number or any significant interaction between sprint number and foot region was found for maximal force, mean force, peak pressure and mean pressure (all P > 0.05). Center of mass vertical displacement increased (P < 0.01) with time, together with unchanged (both P > 0.05) peak vertical force and leg compression. Vertical stiffness decreased (-15.9%; P < 0.05) across trials, whereas leg stiffness changes were not significant (-5.9%; P > 0.05). Changes in root mean square activity of the three tested muscles over sprint repetitions were not significant. Although repeated sprinting on natural grass with players wearing soccer boots impairs their leg-spring behavior (vertical stiffness), there is no substantial concomitant alterations in muscle activation levels or plantar pressure patterns.

Hepatic amyloidosis increases liver stiffness measured by transient elastography.

Liver stiffness values in transient elastography (TE) have to be interpreted with caution. Steatosis, congestion, acute inflammation and extrahepatic cholestasis can indeed influence measurements. Obtained stiffness values in the cirrhotic range can also be present in the absence of fibrosis as in hepatic amyloidosis. Here we report two cases of systemic amyloidosis with hepatic involvement where high stiffness values were measured at TE. In fact, deposits of amyloid may increase the rigidity of the liver parenchyma resulting in higher liver stiffness values. Therefore, results of TE should always be interpreted in their clinical context and if inconsistent, the performance of a liver biopsy might be necessary.

Uncertainties in the prediction of spatial variability of soil CO2 emissions and related properties

The soil CO2 emission has high spatial variability because it depends strongly on soil properties. The purpose of this study was to (i) characterize the spatial variability of soil respiration and related properties, (ii) evaluate the accuracy of results of the ordinary kriging method and sequential Gaussian simulation, and (iii) evaluate the uncertainty in predicting the spatial variability of soil CO2 emission and other properties using sequential Gaussian simulations. The study was conducted in a sugarcane area, using a regular sampling grid with 141 points, where soil CO2 emission, soil temperature, air-filled pore space, soil organic matter and soil bulk density were evaluated. All variables showed spatial dependence structure. The soil CO2 emission was positively correlated with organic matter (r = 0.25, p < 0.05) and air-filled pore space (r = 0.27, p < 0.01) and negatively with soil bulk density (r = -0.41, p < 0.01). However, when the estimated spatial values were considered, the air-filled pore space was the variable mainly responsible for the spatial characteristics of soil respiration, with a correlation of 0.26 (p < 0.01). For all variables, individual simulations represented the cumulative distribution functions and variograms better than ordinary kriging and E-type estimates. The greatest uncertainties in predicting soil CO2 emission were associated with areas with the highest estimated values, which produced estimates from 0.18 to 1.85 t CO2 ha-1, according to the different scenarios considered. The knowledge of the uncertainties generated by the different scenarios can be used in inventories of greenhouse gases, to provide conservative estimates of the potential emission of these gases.

Fluid dynamical prediction of changed v1 flow at energies available at the CERN Large Hadron Collider

Substantial collective flow is observed in collisions between lead nuclei at Large Hadron Collider (LHC) as evidenced by the azimuthal correlations in the transverse momentum distributions of the produced particles. Our calculations indicate that the global v1-flow, which at RHIC peaked at negative rapidities (named third flow component or antiflow), now at LHC is going to turn toward forward rapidities (to the same side and direction as the projectile residue). Potentially this can provide a sensitive barometer to estimate the pressure and transport properties of the quark-gluon plasma. Our calculations also take into account the initial state center-of-mass rapidity fluctuations, and demonstrate that these are crucial for v1 simulations. In order to better study the transverse momentum flow dependence we suggest a new "symmetrized" v1S(pt) function, and we also propose a new method to disentangle global v1 flow from the contribution generated by the random fluctuations in the initial state. This will enhance the possibilities of studying the collective Global v1 flow both at the STAR Beam Energy Scan program and at LHC.

Antibiotic-induced modifications of the stiffness of bacterial membranes.

In the latest years the importance of high resolution analysis of the microbial cell surface has been increasingly recognized. Indeed, in order to better understand bacterial physiology and achieve rapid diagnostic and treatment techniques, a thorough investigation of the surface modifications induced on bacteria by different environmental conditions or drugs is essential. Several instruments are nowadays available to observe at high resolution specific properties of microscopic samples. Among these, AFM can routinely study single cells in physiological conditions, measuring the mechanical properties of their membrane at a nanometric scale (force volume). Such analyses, coupled with high resolution investigation of their morphological properties, are increasingly used to characterize the state of single cells. In this work we exploit such technique to characterize bacterial systems. We have performed an analysis of the mechanical properties of bacteria (Escherichia coli) exposed to different conditions. Such measurements were performed on living bacteria, by changing in real-time the liquid environment: standard phosphate buffered saline, antibiotic (ampicillin) in PBS and growth medium. In particular we have focused on the determination of the membrane stiffness modifications induced by these solutions, in particular between stationary and replicating phases and what is the effect of the antibiotic on the bacterial structure.

Prediction of Infant Drug Exposure Through Breastfeeding: Population PK Modeling and Simulation of Fluoxetine Exposure.

The likelihood of significant exposure to drugs in infants through breast milk is poorly defined, given the difficulties of conducting pharmacokinetics (PK) studies. Using fluoxetine (FX) as an example, we conducted a proof-of-principle study applying population PK (popPK) modeling and simulation to estimate drug exposure in infants through breast milk. We simulated data for 1,000 mother-infant pairs, assuming conservatively that the FX clearance in an infant is 20% of the allometrically adjusted value in adults. The model-generated estimate of the milk-to-plasma ratio for FX (mean: 0.59) was consistent with those reported in other studies. The median infant-to-mother ratio of FX steady-state plasma concentrations predicted by the simulation was 8.5%. Although the disposition of the active metabolite, norfluoxetine, could not be modeled, popPK-informed simulation may be valid for other drugs, particularly those without active metabolites, thereby providing a practical alternative to conventional PK studies for exposure risk assessment in this population.

Major impact of body position on arterial stiffness indices derived from radial applanation tonometry in pregnant and non pregnant woman

Pendant la grossesse, la pression artérielle reste stable malgré une nette augmentation du volume d'éjection systolique et du débit cardiaque. Cette stabilité vient d'un côté d'une vasodilatation périphérique entraînant une diminution des résistances périphériques et d'un autre côté d'une moindre rigidité des principales artères notamment l'aorte. En conséquence, l'amplitude des ondes de pouls est atténuée, de même que leur vitesse de propagation dans le sens tant antérogade que rétrograde (ondes réfléchies). Les ondes réfléchies tendent ainsi à atteindre l'aorte ascendante plus tard durant la systole, voire durant la diastole, ce qui peut contribuer à diminuer la pression puisée. La prééclampsie perturbe massivement ce processus d'adaptation. Il s'agit d'une maladie hypertensive de la grossesse engendrant une importante morbidité et mortalité néonatale et maternelle. Il est à remarquer que la diminution de la rigidité artérielle n'est pas observée chez les patientes atteintes avec pour conséquence une forte augmentation de la pression systolique centrale (aortique) par les ondes réfléchies. Ce fait a été établi grâce à l'existence de la tonométrie d'aplanation, une méthode permettant l'évaluation non invasive de l'onde de pouls centrale. Dans cette méthode, un senseur de pression piézo-électrique permet de capter l'onde de pouls périphérique, le plus souvent sur l'artère radiale. Par la suite, un algorithme validé permet d'en déduire la forme de l'onde de pouls centrale et de visualiser à quel moment du cycle cardiaque s'y ajoutent les ondes réfléchies. Plusieurs études font état d'une forte augmentation de la pression systolique centrale par les ondes réfléchies chez les patientes atteintes de prééclampsie, suggérant l'utilisation de cette méthode pour le diagnostic et le monitoring voire pour le dépistage de ces patientes. Pour atteindre ce but, il est nécessaire d'établir des normes en rapport notamment avec l'âge gestationnel. Dans la littérature, les données pertinentes actuellement disponibles sont variables, voire contradictoires. Par exemple, les ondes réfléchies proéminentes dans la partie diastolique de l'onde de pouls centrale disparaissaient chez des patientes enceintes au 3eme trimestre comparées à des contrôles non enceintes dans une étude lausannoise, alors que deux autres études présentent l'observation contraire. Autre exemple, certains auteurs décrivent une diminution progressive de l'augmentation systolique jusqu'à l'accouchement alors que d'autres rapportent un nadir aux environs du 6ème mois, suivi d'un retour à des valeurs plus élevées en fin de grossesse. Les mesures effectuées dans toutes ces études différaient dans leur exécution, les patientes étant notamment dans des postions corporelles différentes (couchées, semi-couchées, assises, en décubitus latéral). Or nous savons que le status hémodynamique est très sensible aux changements de position, particulièrement durant la grossesse où l'utérus gravide est susceptible d'avoir des interactions mécaniques avec les veines et possiblement les artères abdominales. Ces différences méthodologiques pourraient donc expliquer, au moins en partie, l'hétérogénéité des résultats concernant l'onde de pouls chez la femme enceinte, ce qui à notre connaissance n'a jamais été exploré. Nous avons mesuré l'onde de pouls dans les positions assise et couchée chez des femmes enceintes, au 3eme trimestre d'une grossesse non compliquée, et nous avons effectué une comparaison avec des données similaire obtenues chez des femmes non enceintes en bonne santé habituelle. Les résultats montrent que la position du corps a un impact majeur sur la forme de l'onde de pouls centrale. Comparée à la position assise, la position couchée se caractérise par une moindre augmentation systolique et, par contraste, une augmentation diastolique plus marquée. De manière inattendue, cet effet s'observe aussi bien en présence qu'en l'absence de grossesse, suggérant que la cause première n'en réside pas dans les interactions mécaniques de l'utérus gravide avec les vaisseaux sanguins abdominaux. Nos observations pourraient par contre être expliquées par l'influence de la position du corps, via un phénomène hydrostatique simple, sur la pression transmurale des artères éloignées du coeur, tout particulièrement celles des membres inférieurs et de l'étage abdominal. En position verticale, ces vaisseaux augmenteraient leur rigidité pour résister à la distension de leur paroi, ce qui y accroîtrait la vitesse de propagation des ondes de pression. En l'état, cette explication reste hypothétique. Mais quoi qu'il en soit, nos résultats expliquent certaines discordances entre les études conduites à ce jour pour caractériser l'influence de la grossesse physiologique sur la forme de l'onde de pouls central. De plus, ils indiquent que la position du corps doit être prise en compte lors de toute investigation utilisant la tonométrie d'applanation pour déterminer la rigidité des artères chez les jeunes femmes enceintes ou non. Il sera aussi nécessaire d'en tenir compte pour établir des normes en vue d'une utilisation de la tonométrie d'aplanation pour dépister ou suivre les patientes atteintes de prééclampsie. Il serait enfin intéressant d'évaluer si l'effet de la position sur la forme de l'onde de pouls central existe également dans l'autre sexe et chez des personnes plus âgées.

Validation of a clinical prediction score for ruling out coronary heart disease in primary care patients with chest pain.

Background: A patient's chest pain raises concern for the possibility of coronary heart disease (CHD). An easy to use clinical prediction rule has been derived from the TOPIC study in Lausanne. Our objective is to validate this clinical score for ruling out CHD in primary care patients with chest pain. Methods: This secondary analysis used data collected from a oneyear follow-up cohort study attending 76 GPs in Germany. Patients attending their GP with chest pain were questioned on their age, gender, duration of chest pain (1-60 min), sternal pain location, pain increases with exertion, absence of tenderness point at palpation, cardiovascular risks factors, and personal history of cardiovascular disease. Area under the curve (ROC), sensitivity and specificity of the Lausanne CHD score were calculated for patients with full data. Results: 1190 patients were included. Full data was available for 509 patients (42.8%). Missing data was not related to having CHD (p = 0.397) or having a cardiovascular risk factor (p = 0.275). 76 (14.9%) were diagnosed with a CHD. Prevalence of CHD were respectively of 68/344 (19.8%), 2/62 (3.2%), 6/103 (5.8%) in the high, intermediate and low risk category. ROC was of 72.9 (CI95% 66.8; 78.9). Ruling out patients with low risk has a sensitivity of 92.1% (CI95% 83.0; 96.7) and a specificity of 22.4% (CI95% 18.6%; 26.7%). Conclusion: The Lausanne CHD score shows reasonably good sensitivity and can be used to rule out coronary events in patients with chest pain. Patients at risk of CHD for other rarer reasons should nevertheless also be investigated.

Ruling out coronary artery disease in primary care: development and validation of a simple prediction rule.

BACKGROUND: Chest pain can be caused by various conditions, with life-threatening cardiac disease being of greatest concern. Prediction scores to rule out coronary artery disease have been developed for use in emergency settings. We developed and validated a simple prediction rule for use in primary care. METHODS: We conducted a cross-sectional diagnostic study in 74 primary care practices in Germany. Primary care physicians recruited all consecutive patients who presented with chest pain (n = 1249) and recorded symptoms and findings for each patient (derivation cohort). An independent expert panel reviewed follow-up data obtained at six weeks and six months on symptoms, investigations, hospital admissions and medications to determine the presence or absence of coronary artery disease. Adjusted odds ratios of relevant variables were used to develop a prediction rule. We calculated measures of diagnostic accuracy for different cut-off values for the prediction scores using data derived from another prospective primary care study (validation cohort). RESULTS: The prediction rule contained five determinants (age/sex, known vascular disease, patient assumes pain is of cardiac origin, pain is worse during exercise, and pain is not reproducible by palpation), with the score ranging from 0 to 5 points. The area under the curve (receiver operating characteristic curve) was 0.87 (95% confidence interval [CI] 0.83-0.91) for the derivation cohort and 0.90 (95% CI 0.87-0.93) for the validation cohort. The best overall discrimination was with a cut-off value of 3 (positive result 3-5 points; negative result <or= 2 points), which had a sensitivity of 87.1% (95% CI 79.9%-94.2%) and a specificity of 80.8% (77.6%-83.9%). INTERPRETATION: The prediction rule for coronary artery disease in primary care proved to be robust in the validation cohort. It can help to rule out coronary artery disease in patients presenting with chest pain in primary care.

Artificial neural networks applied for soil class prediction in mountainous landscape of the Serra do Mar¹

Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.

Comparing the artificial neural network with parcial least squares for prediction of soil organic carbon and pH at different moisture content levels using visible and near-infrared spectroscopy

Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.

Outcome Prediction after Cardiac Arrest Treated with Hypothermia

Rationale: Clinical and electrophysiological prognostic markers of brain anoxia have been mostly evaluated in comatose survivors of out hospital cardiac arrest (OHCA) after standard resuscitation, but their predictive value in patients treated with mild induced hypothermia (IH) is unknown. The objective of this study was to identify a predictive score of independent clinical and electrophysiological variables in comatose OHCA survivors treated with IH, aiming at a maximal positive predictive value (PPV) and a high negative predictive value (NPV) for mortality. Methods: We prospectively studied consecutive adult comatose OHCA survivors from April 2006 to May 2009, treated with mild IH to 33-34_C for 24h at the intensive care unit of the Lausanne University Hospital, Switzerland. IH was applied using an external cooling method. As soon as subjects passively rewarmed (body temperature >35_C) they underwent EEG and SSEP recordings (off sedation), and were examined by experienced neurologists at least twice. Patients with status epilepticus were treated with AED for at least 24h. A multivariable logistic regression was performed to identify independent predictors of mortality at hospital discharge. These were used to formulate a predictive score. Results: 100 patients were studied; 61 died. Age, gender and OHCA etiology (cardiac vs. non-cardiac) did not differ among survivors and nonsurvivors. Cardiac arrest type (non-ventricular fibrillation vs. ventricular fibrillation), time to return of spontaneous circulation (ROSC) >25min, failure to recover all brainstem reflexes, extensor or no motor response to pain, myoclonus, presence of epileptiform discharges on EEG, EEG background unreactive to pain, and bilaterally absent N20 on SSEP, were all significantly associated with mortality. Absent N20 was the only variable showing no false positive results. Multivariable logistic regression identified four independent predictors (Table). These were used to construct the score, and its predictive values were calculated after a cut-off of 0-1 vs. 2-4 predictors. We found a PPV of 1.00 (95% CI: 0.93-1.00), a NPV of 0.81 (95% CI: 0.67-0.91) and an accuracy of 0.93 for mortality. Among 9 patients who were predicted to survive by the score but eventually died, only 1 had absent N20. Conclusions: Pending validation in a larger cohort, this simple score represents a promising tool to identify patients who will survive, and most subjects who will not, after OHCA and IH. Furthermore, while SSEP are 100% predictive of poor outcome but not available in most hospitals, this study identifies EEG background reactivity as an important predictor after OHCA. The score appears robust even without SSEP, suggesting that SSEP and other investigations (e.g., mismatch negativity, serum NSE) might be principally needed to enhance prognostication in the small subgroup of patients failing to improve despite a favorable score.

Surface Complexation Modeling in Variable Charge Soils: Prediction of Cadmium Adsorption

ABSTRACT Intrinsic equilibrium constants for 22 representative Brazilian Oxisols were estimated from a cadmium adsorption experiment. Equilibrium constants were fitted to two surface complexation models: diffuse layer and constant capacitance. Intrinsic equilibrium constants were optimized by FITEQL and by hand calculation using Visual MINTEQ in sweep mode, and Excel spreadsheets. Data from both models were incorporated into Visual MINTEQ. Constants estimated by FITEQL and incorporated in Visual MINTEQ software failed to predict observed data accurately. However, FITEQL raw output data rendered good results when predicted values were directly compared with observed values, instead of incorporating the estimated constants into Visual MINTEQ. Intrinsic equilibrium constants optimized by hand calculation and incorporated in Visual MINTEQ reliably predicted Cd adsorption reactions on soil surfaces under changing environmental conditions.

Rgtsp: a generalized top scoring pairs package for class prediction.

SUMMARY: A top scoring pair (TSP) classifier consists of a pair of variables whose relative ordering can be used for accurately predicting the class label of a sample. This classification rule has the advantage of being easily interpretable and more robust against technical variations in data, as those due to different microarray platforms. Here we describe a parallel implementation of this classifier which significantly reduces the training time, and a number of extensions, including a multi-class approach, which has the potential of improving the classification performance. AVAILABILITY AND IMPLEMENTATION: Full C++ source code and R package Rgtsp are freely available from http://lausanne.isb-sib.ch/~vpopovic/research/. The implementation relies on existing OpenMP libraries.