Application and comparison of classification algorithms for recognition of Alzheimer's disease in electrical brain activity (EEG)

The early detection of subjects with probable Alzheimer's disease (AD) is crucial for effective appliance of treatment strategies. Here we explored the ability of a multitude of linear and non-linear classification algorithms to discriminate between the electroencephalograms (EEGs) of patients with varying degree of AD and their age-matched control subjects. Absolute and relative spectral power, distribution of spectral power, and measures of spatial synchronization were calculated from recordings of resting eyes-closed continuous EEGs of 45 healthy controls, 116 patients with mild AD and 81 patients with moderate AD, recruited in two different centers (Stockholm, New York). The applied classification algorithms were: principal component linear discriminant analysis (PC LDA), partial least squares LDA (PLS LDA), principal component logistic regression (PC LR), partial least squares logistic regression (PLS LR), bagging, random forest, support vector machines (SVM) and feed-forward neural network. Based on 10-fold cross-validation runs it could be demonstrated that even tough modern computer-intensive classification algorithms such as random forests, SVM and neural networks show a slight superiority, more classical classification algorithms performed nearly equally well. Using random forests classification a considerable sensitivity of up to 85% and a specificity of 78%, respectively for the test of even only mild AD patients has been reached, whereas for the comparison of moderate AD vs. controls, using SVM and neural networks, values of 89% and 88% for sensitivity and specificity were achieved. Such a remarkable performance proves the value of these classification algorithms for clinical diagnostics.

Underestimation of Standard Errors in Multi-Site Time Series Studies

Multi-site time series studies of air pollution and mortality and morbidity have figured prominently in the literature as comprehensive approaches for estimating acute effects of air pollution on health. Hierarchical models are generally used to combine site-specific information and estimate pooled air pollution effects taking into account both within-site statistical uncertainty, and across-site heterogeneity. Within a site, characteristics of time series data of air pollution and health (small pollution effects, missing data, highly correlated predictors, non linear confounding etc.) make modelling all sources of uncertainty challenging. One potential consequence is underestimation of the statistical variance of the site-specific effects to be combined. In this paper we investigate the impact of variance underestimation on the pooled relative rate estimate. We focus on two-stage normal-normal hierarchical models and on under- estimation of the statistical variance at the first stage. By mathematical considerations and simulation studies, we found that variance underestimation does not affect the pooled estimate substantially. However, some sensitivity of the pooled estimate to variance underestimation is observed when the number of sites is small and underestimation is severe. These simulation results are applicable to any two-stage normal-normal hierarchical model for combining information of site-specific results, and they can be easily extended to more general hierarchical formulations. We also examined the impact of variance underestimation on the national average relative rate estimate from the National Morbidity Mortality Air Pollution Study and we found that variance underestimation as much as 40% has little effect on the national average.

Stereoselective pharmacokinetics of ketamine and norketamine after racemic ketamine or S-ketamine administration in Shetland ponies sedated with xylazine

The pharmacokinetics of ketamine and norketamine enantiomers after administration of intravenous (IV) racemic ketamine (R-/S-ketamine; 2.2mg/kg) or S-ketamine (1.1mg/kg) to five ponies sedated with IV xylazine (1.1mg/kg) were compared. The time intervals to assume sternal and standing positions were recorded. Arterial blood samples were collected before and 1, 2, 4, 6, 8 and 13min after ketamine administration. Arterial blood gases were evaluated 5min after ketamine injection. Plasma concentrations of ketamine and norketamine enantiomers were determined by capillary electrophoresis and were evaluated by non-linear least square regression analysis applying a monocompartmental model. The first-order elimination rate constant was significantly higher and elimination half-life and mean residence time were lower for S-ketamine after S-ketamine compared to R-/S-ketamine administration. The maximum concentration of S-norketamine was higher after S-ketamine administration. Time to standing position was significantly diminished after S-ketamine compared to R-/S-ketamine. Blood gases showed low-degree hypoxaemia and hypercarbia.

Stereoselective pharmacokinetics of ketamine and norketamine after racemic ketamine or S-ketamine administration during isoflurane anaesthesia in Shetland ponies

BACKGROUND: The arterial pharmacokinetics of ketamine and norketamine enantiomers after racemic ketamine or S-ketamine i.v. administration were evaluated in seven gelding ponies in a crossover study (2-month interval). METHODS: Anaesthesia was induced with isoflurane in oxygen via a face-mask and then maintained at each pony's individual MAC. Racemic ketamine (2.2 mg kg(-1)) or S-ketamine (1.1 mg kg(-1)) was injected in the right jugular vein. Blood samples were collected from the right carotid artery before and at 1, 2, 4, 8, 16, 32, 64, and 128 min after ketamine administration. Ketamine and norketamine enantiomer plasma concentrations were determined by capillary electrophoresis. Individual R-ketamine and S-ketamine concentration vs time curves were analysed by non-linear least square regression two-compartment model analysis using PCNonlin. Plasma disposition curves for R-norketamine and S-norketamine were described by estimating AUC, C(max), and T(max). Pulse rate (PR), respiratory rate (R(f)), tidal volume (V(T)), minute volume ventilation (V(E)), end-tidal partial pressure of carbon dioxide (PE'(CO(2))), and mean arterial blood pressure (MAP) were also evaluated. RESULTS: The pharmacokinetic parameters of S- and R-ketamine administered in the racemic mixture or S-ketamine administered separately did not differ significantly. Statistically significant higher AUC and C(max) were found for S-norketamine compared with R-norketamine in the racemic group. Overall, R(f), V(E), PE'(CO(2)), and MAP were significantly higher in the racemic group, whereas PR was higher in the S-ketamine group. CONCLUSIONS: Norketamine enantiomers showed different pharmacokinetic profiles after single i.v. administration of racemic ketamine in ponies anaesthetised with isoflurane in oxygen (1 MAC). Cardiopulmonary variables require further investigation.

Experimental and modeling study of the filtration and oxidation characteristics of a diesel oxidation catalyst and a catalyzed particulate filter

A diesel oxidation catalyst (DOC) with a catalyzed diesel particulate filter (CPF) is an effective exhaust aftertreatment device that reduces particulate emissions from diesel engines, and properly designed DOC-CPF systems provide passive regeneration of the filter by the oxidation of PM via thermal and NO2/temperature-assisted means under various vehicle duty cycles. However, controlling the backpressure on engines caused by the addition of the CPF to the exhaust system requires a good understanding of the filtration and oxidation processes taking place inside the filter as the deposition and oxidation of solid particulate matter (PM) change as functions of loading time. In order to understand the solid PM loading characteristics in the CPF, an experimental and modeling study was conducted using emissions data measured from the exhaust of a John Deere 6.8 liter, turbocharged and after-cooled engine with a low-pressure loop EGR system and a DOC-CPF system (or a CCRT® - Catalyzed Continuously Regenerating Trap®, as named by Johnson Matthey) in the exhaust system. A series of experiments were conducted to evaluate the performance of the DOC-only, CPF-only and DOC-CPF configurations at two engine speeds (2200 and 1650 rpm) and various loads on the engine ranging from 5 to 100% of maximum torque at both speeds. Pressure drop across the DOC and CPF, mass deposited in the CPF at the end of loading, upstream and downstream gaseous and particulate emissions, and particle size distributions were measured at different times during the experiments to characterize the pressure drop and filtration efficiency of the DOCCPF system as functions of loading time. Pressure drop characteristics measured experimentally across the DOC-CPF system showed a distinct deep-bed filtration region characterized by a non-linear pressure drop rise, followed by a transition region, and then by a cake-filtration region with steadily increasing pressure drop with loading time at engine load cases with CPF inlet temperatures less than 325 °C. At the engine load cases with CPF inlet temperatures greater than 360 °C, the deep-bed filtration region had a steep rise in pressure drop followed by a decrease in pressure drop (due to wall PM oxidation) in the cake filtration region. Filtration efficiencies observed during PM cake filtration were greater than 90% in all engine load cases. Two computer models, i.e., the MTU 1-D DOC model and the MTU 1-D 2-layer CPF model were developed and/or improved from existing models as part of this research and calibrated using the data obtained from these experiments. The 1-D DOC model employs a three-way catalytic reaction scheme for CO, HC and NO oxidation, and is used to predict CO, HC, NO and NO2 concentrations downstream of the DOC. Calibration results from the 1-D DOC model to experimental data at 2200 and 1650 rpm are presented. The 1-D 2-layer CPF model uses a ‘2-filters in series approach’ for filtration, PM deposition and oxidation in the PM cake and substrate wall via thermal (O2) and NO2/temperature-assisted mechanisms, and production of NO2 as the exhaust gas mixture passes through the CPF catalyst washcoat. Calibration results from the 1-D 2-layer CPF model to experimental data at 2200 rpm are presented. Comparisons of filtration and oxidation behavior of the CPF at sample load-cases in both configurations are also presented. The input parameters and selected results are also compared with a similar research work with an earlier version of the CCRT®, to compare and explain differences in the fundamental behavior of the CCRT® used in these two research studies. An analysis of the results from the calibrated CPF model suggests that pressure drop across the CPF depends mainly on PM loading and oxidation in the substrate wall, and also that the substrate wall initiates PM filtration and helps in forming a PM cake layer on the wall. After formation of the PM cake layer of about 1-2 µm on the wall, the PM cake becomes the primary filter and performs 98-99% of PM filtration. In all load cases, most of PM mass deposited was in the PM cake layer, and PM oxidation in the PM cake layer accounted for 95-99% of total PM mass oxidized during loading. Overall PM oxidation efficiency of the DOC-CPF device increased with increasing CPF inlet temperatures and NO2 flow rates, and was higher in the CCRT® configuration compared to the CPF-only configuration due to higher CPF inlet NO2 concentrations. Filtration efficiencies greater than 90% were observed within 90-100 minutes of loading time (starting with a clean filter) in all load cases, due to the fact that the PM cake on the substrate wall forms a very efficient filter. A good strategy for maintaining high filtration efficiency and low pressure drop of the device while performing active regeneration would be to clean the PM cake filter partially (i.e., by retaining a cake layer of 1-2 µm thickness on the substrate wall) and to completely oxidize the PM deposited in the substrate wall. The data presented support this strategy.

Simple virtual reality display of fetal volume ultrasound

Three-dimensional (3D) ultrasound volume acquisition, analysis and display of fetal structures have enhanced their visualization and greatly improved the general understanding of their anatomy and pathology. The dynamic display of volume data generally depends on proprietary software, usually supplied with the ultrasound system, and on the operator's ability to maneuver the dataset digitally. We have used relatively simple tools and an established storage, display and manipulation format to generate non-linear virtual reality object movies of prenatal images (including moving sequences and 3D-rendered views) that can be navigated easily and interactively on any current computer. This approach permits a viewing or learning experience that is superior to watching a linear movie passively.

Clinical versus pre-clinical FE models for vertebral body strength predictions

The finite element analysis is an accepted method to predict vertebral body compressive strength. This study compares measurements obtained from in vitro tests with the ones from two different simulation models: clinical quantitative computer tomography (QCT) based homogenized finite element (hFE) models and pre-clinical high-resolution peripheral QCT-based (HR-pQCT) hFE models. About 37 vertebral body sections were prepared by removing end-plates and posterior elements, scanned with QCT (390/450μm voxel size) as well as HR-pQCT (82μm voxel size), and tested in compression up to failure. Non-linear viscous damage hFE models were created from QCT/HT-pQCT images and compared to experimental results based on stiffness and ultimate load. As expected, the predictability of QCT/HR-pQCT-based hFE models for both apparent stiffness (r2=0.685/0.801r2=0.685/0.801) and strength (r2=0.774/0.924r2=0.774/0.924) increased if a better image resolution was used. An analysis of the damage distribution showed similar damage locations for all cases. In conclusion, HR-pQCT-based hFE models increased the predictability considerably and do not need any tuning of input parameters. In contrast, QCT-based hFE models usually need some tuning but are clinically the only possible choice at the moment.

ANALYTICAL MODELS OF EXOPLANETARY ATMOSPHERES. I. ATMOSPHERIC DYNAMICS VIA THE SHALLOW WATER SYSTEM

Within the context of exoplanetary atmospheres, we present a comprehensive linear analysis of forced, damped, magnetized shallow water systems, exploring the effects of dimensionality, geometry (Cartesian, pseudo-spherical, and spherical), rotation, magnetic tension, and hydrodynamic and magnetic sources of friction. Across a broad range of conditions, we find that the key governing equation for atmospheres and quantum harmonic oscillators are identical, even when forcing (stellar irradiation), sources of friction (molecular viscosity, Rayleigh drag, and magnetic drag), and magnetic tension are included. The global atmospheric structure is largely controlled by a single key parameter that involves the Rossby and Prandtl numbers. This near-universality breaks down when either molecular viscosity or magnetic drag acts non-uniformly across latitude or a poloidal magnetic field is present, suggesting that these effects will introduce qualitative changes to the familiar chevron-shaped feature witnessed in simulations of atmospheric circulation. We also find that hydrodynamic and magnetic sources of friction have dissimilar phase signatures and affect the flow in fundamentally different ways, implying that using Rayleigh drag to mimic magnetic drag is inaccurate. We exhaustively lay down the theoretical formalism (dispersion relations, governing equations, and time-dependent wave solutions) for a broad suite of models. In all situations, we derive the steady state of an atmosphere, which is relevant to interpreting infrared phase and eclipse maps of exoplanetary atmospheres. We elucidate a pinching effect that confines the atmospheric structure to be near the equator. Our suite of analytical models may be used to develop decisively physical intuition and as a reference point for three-dimensional magnetohydrodynamic simulations of atmospheric circulation.

Relating in situ gas measurements to the surface outgassing properties of cometary nuclei

The sensitivity of the gas flow field to changes in different initial conditions has been studied for the case of a highly simplified cometary nucleus model. The nucleus model simulated a homogeneously outgassing sphere with a more active ring around an axis of symmetry. The varied initial conditions were the number density of the homogeneous region, the surface temperature, and the composition of the flow (varying amounts of H2O and CO2) from the active ring. The sensitivity analysis was performed using the Polynomial Chaos Expansion (PCE) method. Direct Simulation Monte Carlo (DSMC) was used for the flow, thereby allowing strong deviations from local thermal equilibrium. The PCE approach can be used to produce a sensitivity analysis with only four runs per modified input parameter and allows one to study and quantify non-linear responses of measurable parameters to linear changes in the input over a wide range. Hence the PCE allows one to obtain a functional relationship between the flow field properties at every point in the inner coma and the input conditions. It is for example shown that the velocity and the temperature of the background gas are not simply linear functions of the initial number density at the source. As probably expected, the main influence on the resulting flow field parameter is the corresponding initial parameter (i.e. the initial number density determines the background number density, the temperature of the surface determines the flow field temperature, etc.). However, the velocity of the flow field is also influenced by the surface temperature while the number density is not sensitive to the surface temperature at all in our model set-up. Another example is the change in the composition of the flow over the active area. Such changes can be seen in the velocity but again not in the number density. Although this study uses only a simple test case, we suggest that the approach, when applied to a real case in 3D, should assist in identifying the sensitivity of gas parameters measured in situ by, for example, the Rosetta spacecraft to the surface boundary conditions and vice versa.

A stereotaxic, population-averaged T1w ovine brain atlas including cerebral morphology and tissue volumes

Standard stereotaxic reference systems play a key role in human brain studies. Stereotaxic coordinate systems have also been developed for experimental animals including non-human primates, dogs, and rodents. However, they are lacking for other species being relevant in experimental neuroscience including sheep. Here, we present a spatial, unbiased ovine brain template with tissue probability maps (TPM) that offer a detailed stereotaxic reference frame for anatomical features and localization of brain areas, thereby enabling inter-individual and cross-study comparability. Three-dimensional data sets from healthy adult Merino sheep (Ovis orientalis aries, 12 ewes and 26 neutered rams) were acquired on a 1.5 T Philips MRI using a T1w sequence. Data were averaged by linear and non-linear registration algorithms. Moreover, animals were subjected to detailed brain volume analysis including examinations with respect to body weight (BW), age, and sex. The created T1w brain template provides an appropriate population-averaged ovine brain anatomy in a spatial standard coordinate system. Additionally, TPM for gray (GM) and white (WM) matter as well as cerebrospinal fluid (CSF) classification enabled automatic prior-based tissue segmentation using statistical parametric mapping (SPM). Overall, a positive correlation of GM volume and BW explained about 15% of the variance of GM while a positive correlation between WM and age was found. Absolute tissue volume differences were not detected, indeed ewes showed significantly more GM per bodyweight as compared to neutered rams. The created framework including spatial brain template and TPM represent a useful tool for unbiased automatic image preprocessing and morphological characterization in sheep. Therefore, the reported results may serve as a starting point for further experimental and/or translational research aiming at in vivo analysis in this species.

Nonlinear quasi-static finite element simulations predict in vitro strength of human proximal femora assessed in a dynamic sideways fall setup

Osteoporotic proximal femur fractures are caused by low energy trauma, typically when falling on the hip from standing height. Finite element simulations, widely used to predict the fracture load of femora in fall, usually include neither mass-related inertial effects, nor the viscous part of bone's material behavior. The aim of this study was to elucidate if quasi-static non-linear homogenized finite element analyses can predict in vitro mechanical properties of proximal femora assessed in dynamic drop tower experiments. The case-specific numerical models of thirteen femora predicted the strength (R2=0.84, SEE=540 N, 16.2%), stiffness (R2=0.82, SEE=233 N/mm, 18.0%) and fracture energy (R2=0.72, SEE=3.85 J, 39.6%); and provided fair qualitative matches with the fracture patterns. The influence of material anisotropy was negligible for all predictions. These results suggest that quasi-static homogenized finite element analysis may be used to predict mechanical properties of proximal femora in the dynamic sideways fall situation.

Whence a healthy mind: Correlation of physical fitness and academic performance among schoolchildren

Background. Public schools are a key forum in the fight for child health because of the opportunities they present for physical activity and fitness surveillance. However, because schools are evaluated and funded on the basis of standardized academic performance rather than physical activity, empirical research evaluating the connections between fitness and academic performance is needed to justify curriculum allocations to physical activity. ^ Methods. Analyses were based on a convenience sample of 315,092 individually-matched standardized academic (TAKS™) and fitness (FITNESSGRAM®) test records collected by 13 Texas school districts under state mandates. We categorized each fitness result in quintiles by age and gender and used a mixed effects regression model to compare the academic performance of the top and bottom fitness groups for each fitness test and grade level combination. ^ Results. All fitness variables except BMI showed significant, positive associations with academic performance after sociodemographic covariate adjustments, with effect sizes ranging from 0.07 (95% CI: 0.05,0.08) in girls trunklift-TAKS reading to 0.34 (0.32,0.35) in boys cardiovascular-TAKS math. Cardiovascular fitness showed the largest inter-quintile difference in TAKS score (32-75 points), followed by curl-ups. After an additional adjustment for BMI and curl-ups, cardiovascular associations peaked in 8th-9 th grades (maximum inter-quintile difference 142 TAKS points; effect size 0.75 (0.69,0.82) for 8th grade girls math) and showed dose-response characteristics across quintiles (p<0.001 for both genders and outcomes). BMI analysis demonstrated limited, non-linear association with academic performance after adjustment for sociodemographic, cardiovascular fitness and curl-up variables. Low-BMI Hispanic high school boys showed significantly lower TAKS scores than the moderate (but not high) BMI group. High-BMI non-Hispanic white high school girls showed significantly lower scores than the moderate (but not low) BMI group. ^ Conclusions. In this study, fitness was strongly and significantly related to academic performance. Cardiovascular fitness showed a distinct dose-response association with academic performance independent of other sociodemographic and fitness variables. The association peaked in late middle to early high school. The independent association of BMI to academic performance was only found in two sub-groups and was non-linear, with both low and high BMI posing risk relative to moderate BMI but not to each other. In light of our findings, we recommend that policymakers consider PE mandates in middle-high school and require linkage of academic and fitness records to facilitate longitudinal surveillance. School administrators should consider increasing PE time in pursuit of higher academic test scores, and PE practitioners should emphasize cardiovascular fitness over BMI reduction.^

EOT11a - Global Empirical Ocean Tide model from multi-mission satellite altimetry, with links to model results

EOT11a is a global (E)mpirical (O)cean (T)ide model derived in 2011 by residual analysis of multi-mission satellite (a)ltimeter data. EOT11a includes amplitudes and phases of the main astronomical tides M2, S2, N2, K2, 2N2, O1, K1, P2, and Q1, the non-linear constituent M4, the long period tides Mm and Mf, and the radiational tide S1. Ocean tides as well as loading tides are provided. EOT11a was computed by means of residual tidal analysis of multi-mission altimeter data from TOPEX/Poseidon, ERS-2, ENVISAT, and Jason-1/2, as far as acquired between September 1992 and April 2010. The resolution of 7.5'x7.5' is identical with FES2004 which was used as reference model for the residual tide analysis. The development of EOT11a was funded by the Deutsche Forschungsgemeinschaft (DFG) under grant BO1228/6-2.

Temperature-dependent phenology of Plutella xylostella (Lepidoptera: Plutellidae)

Temperature-dependent population growth of diamondback moth (DBM) Plutella xylostella (L.), a prolific insect pest of crucifer vegetables, was studied under six constant temperatures in the laboratory. The objective of the study was to predict the impacts of temperature changes on the population of DBM at high-resolution scales along altitudinal gradients and under climate change scenarios. Non-linear functions were fitted on the data for modeling the development, mortality, longevity and oviposition of the pest. The best-fitted functions for each life stage were compiled for estimating the life table parameters of the species by stochastic simulations. To quantify the impacts on the pest, three indices (establishment, generation and activity) were computed using the estimates of life table parameters and temperature data obtained at local scale (current scenario 2013) and downscaled climate change data (future scenario 2055) from the AFRICLIM database. To measure and represent the impacts of temperature change along the altitude on the pest; the indices were mapped along the altitudinal gradients of Kilimanjaro and Taita Hills, in Tanzania and Kenya, respectively. Potential impact of the changes between climate scenarios 2013 and 2055 was assessed. The data files included in this database were utilized for the above analysis to develop temperature dependent phenology of Plutella xylostella to assess current and future distribution along eastern African Afromontanes.

Magnetic susceptibility, XRF and color reflectance data of DSDP Hole 72-516F, cores 113 and 114

Deep marine successions of early Campanian age from DSDP site 516F drilled at low paleolatitudes in the South Atlantic reveal distinct sub-Milankovitch variability in addition to precession and eccentricity related variations. Elemental abundance ratios point to a similar 5 climatic origin for these variations and exclude a quadripartite structure - as observed in the Mediterranean Neogene - of the precession related cycles as an explanation for the inferred semi-precession cyclicity in MS. However, the semi-precession cycle itself is likely an artifact, reflecting the first harmonic of the precession signal. The sub-Milankovitch variability is best approximated by a ~ 7 kyr cycle as shown by 10 spectral analysis and bandpass filtering. The presence of sub-Milankovitch cycles with a period similar to that of Heinrich events of the last glacial cycle is consistent with linking the latter to low-latitude climate change caused by a non-linear response to precession induced variations in insolation between the tropics.