Large-scale human metabolomics studies: a strategy for data (pre-) processing and validation

A large metabolomics study was performed on 600 plasma samples taken at four time points before and after a single intake of a high fat test meal by obese and lean subjects. All samples were analyzed by a liquid chromatography-mass spectrometry (LC-MS) lipidomic method for metabolic profiling. A pragmatic approach combining several well-established statistical methods was developed for processing this large data set in order to detect small differences in metabolic profiles in combination with a large biological variation. Such metabolomics studies require a careful analytical and statistical protocol. The strategy included data preprocessing, data analysis, and validation of statistical models. After several data preprocessing steps, partial least-squares discriminant analysis (PLS-DA) was used for finding biomarkers. To validate the found biomarkers statistically, the PLS-DA models were validated by means of a permutation test, biomarker models, and noninformative models. Univariate plots of potential biomarkers were used to obtain insight in up- or downregulation. The strategy proposed proved to be applicable for dealing with large-scale human metabolomics studies.     

Uncorrelated linear discriminant analysis (ULDA): A powerful tool for exploration of metabolomics data

The theory together with an algorithm for uncorrelated linear discriminant analysis (ULDA) is introduced and applied to explore metabolomics data. ULDA is a supervised method for feature extraction (FE), discriminant analysis (DA) and biomarker screening based on the Fisher criterion function. While principal component analysis (PCA) searches for directions of maximum variance in the data, ULDA seeks linearly combined variables called uncorrelated discriminant vectors (UDVs). The UDVs maximize the separation among different classes in terms of the Fisher criterion. The performance of ULDA is evaluated and compared with PCA, partial least squares discriminant analysis (PLS-DA) and target projection discriminant analysis (TP-DA) for two datasets, one simulated and one real from a metabolomic study. ULDA showed better discriminatory ability than PCA, PLS-DA and TP-DA. The shortcomings of PCA, PLS-DA and TP-DA are attributed to interference from linear correlations in data. PLS-DA and TP-DA performed successfully for the simulated data, but PLS-DA was slightly inferior to ULDA for the real data. ULDA successfully extracted optimal features for discriminant analysis and revealed potential biomarkers. Furthermore, by means of cross-validation, the classification model obtained by ULDA showed better predictive ability than PCA, PLS-DA and TP-DA. In conclusion, ULDA is a powerful tool for revealing discriminatory information in metabolomics data.     

Single wire transmission from HV environments of temperature measurements obtained with a smart sensor

The continuous progress in vacuum technology poses every day more stringent requirements on the measurements to be performed inside evacuated vessels. In this context, the adoption of new technologies combining “smart sensors” and “single wire transmission protocols” could be very advantageous, allowing sophisticated measurements to be performed with local intelligence and a minimum of cabling to send the data out of the vacuum chambers. In this paper, the tests aimed at qualifying a “smart temperature sensor” and a “single wire transceiver” for operation in High Vacuum (HV) conditions are reported. Pressure measurements and Residual Gas Analysis confirm that the chosen components do not pose any serious issue for matching HV standards. The combined use of the smart sensor and the transceiver to implement a sophisticated, compact, cost effective and versatile measuring system for vacuum environments is demonstrated. The prospects of the proposed solution are very promising and can be extended to a great variety of applications.     

Analysis of stress concentration during tension of round pultruded composite rods: Errata

“Analysis of stress concentration during tension of round pultruded composite rods (Composite Structures 2008;83:100–109)” had several errors without negative impact on the main results except for one. A sign error in Eq. (11) results in a tensile radial stress rather than compression in Fig. 6 according to the parameters provided in the article.     

A population-based study of inpatients admitted due to suffocation in Taiwan during 2005–2007

The objective of this study was to analyze the epidemiology and factors associated with prognoses (inpatient fatality) of patients hospitalized due to suffocation. Data from 2005 to 2007 were sourced from the Taiwanese National Health Insurance Research Database. Suffocation was defined as E911–E915 according to the ICD-9-CM classification. In total, 4062 hospitalizations occurred in Taiwan due to suffocation from 2005 to 2007, with an inpatient fatality rate of 6.5%. Among hospitalizations due to suffocation, “foreign body unintentionally entering other orifice”, “food causing obstruction”, and “other object causing obstruction” accounted for 58.4%, 17.9%, and 11.0%, respectively. There were more cases of male inpatients than female patients; in terms of age, infants under 1 year old and the elderly aged 65 and over had the highest rates of hospitalization. Factors associated with inpatient fatality included “age”, “cardiac arrest”, “received surgery or procedure”, “acute respiratory failure”, “anoxic brain damage”, and “foreign body in larynx”. Infants and the elderly were high-risk groups for hospitalization as a result of suffocation; the dominant cause among inpatient fatality was “food causing obstruction”, which accounted for 22.2% of cases. Medical institutions should focus on the factors associated with inpatient fatality to improve prognoses and decrease the fatality rates of inpatients.     

Metabolic profiling of glucuronides in human urine by LC-MS/MS and partial least-squares discriminant analysis for classification and prediction of gender

Mass spectrometry (MS) is increasingly being used for metabolic profiling, but detection modes such as constant neutral loss or multiple reaction monitoring have not often been reported. These modes allow focusing on structurally related compounds, which could be advantageous for situations in which the trait under investigation is associated with a particular class of metabolites. In this study, we analyzed endogenous glucuronides excreted in human urine by monitoring characteristic transitions of putative steroid glucuronides by LC-MS/MS for discrimination of females from males. Two methods for data extraction were used: (i) a manual procedure based on visual inspection of the chromatograms and selection of 23 peaks and (ii) a software-supported method (MarkerView) set to extract 100 peaks. Data from 10 female and 10 male students were analyzed by principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) using software SIMCA. With PCA, only the manual peak selection resulted in clustering males and females. With PLS-DA, the manual method provided full separation on the basis of one single discriminant; the software-supported approach required a two-component model for complete separation. Loading plots were analyzed for their ability to reveal peaks with high discriminating power, that is, potential biomarkers. The PLS-DA models were validated with urine samples collected from five new females and five new males. Gender was correctly assigned for all. Our results indicate that inclusion of biological criteria for variable selection coupled to class-specific MS analysis and data extraction by appropriate software may constitute a valuable addition to the methods available for metabolomics.     

Crystallized TiO2 film growth on unheated substrates by pulse-powered magnetron sputtering

Crystallized TiO₂ films were successfully grown in situ without heating by bipolar-pulse sputtering method at high deposition rates (∼40 nm/min). The optical emission study of the sputtering plasma during growth revealed that the “pulse geometry” had a great influence on the electron/ion temperature of the plasma. It was revealed that the crystallization and the accompanying enhancement in the photocatalytic activity were not caused by the “temperature effect” but caused by the “plasma effect”.     

Some observations on thin β-tin films by electron diffraction

Forbidden “110-type” reflections are present on some patterns of tin single-crystal films. Their intensities may vary in a large range and these reflections do not appear with polycrystalline samples. The other forbidden “002-type” reflections which were observed by other authors and ourselves are probably due to secondary elastic scattering, but the kind of “forbidden” spots studied here can be explained by dynamic interactions.     

Intelligent speed adaptation as an assistive device for drivers with acquired brain injury: A single-case field experiment

Intelligent speed adaptation (ISA) was tested as an assistive device for drivers with an acquired brain injury (ABI). The study was part of the “Pay as You Speed” project (PAYS) and used the same equipment and technology as the main study (0030 and 0035). Two drivers with ABI were recruited as subjects and had ISA equipment installed in their private vehicle. Their speed was logged with ISA equipment for a total of 30 weeks of which 12 weeks were with an active ISA user interface (6 weeks = Baseline 1; 12 weeks = ISA period; 12 weeks = Baseline 2). The subjects participated in two semi-structured interviews concerning their strategies for driving with ABI and for driving with ISA. Furthermore, they gave consent to have data from their clinical journals and be a part of the study. The two subjects did not report any instances of being distracted or confused by ISA, and in general they described driving with ISA as relaxed. ISA reduced the percentage of the total distance that was driven with a speed above the speed limit (PDA), but the subjects relapsed to their previous PDA level in Baseline 2. This suggests that ISA is more suited as a permanent assistive device (i.e. cognitive prosthesis) than as a temporary training device. As ABI is associated with a multitude of cognitive deficits, we developed a conceptual framework, which focused on the cognitive parameters that have been shown to relate to speeding behaviour, namely “intention to speed” and “inattention to speeding”. The subjects’ combined status on the two independent parameters made up their “speeding profile”. A comparison of the speeding profiles and the speed logs indicated that ISA in the present study was more efficient in reducing inattention to speeding than affecting intention to speed. This finding suggests that ISA might be more suited for some neuropsychological profiles than for others, and that customisation of ISA for different neuropsychological profiles may be required. However, further studies with more subjects are needed in order to be conclusive on these issues.     

Classification of magnetic resonance images from rabbit renal perfusion

The feasibility of using chemometric techniques for the automatic detection of whether a rabbit kidney is pathological or not is studied. Sequential images of the kidney are acquired using Dynamic Contrast-Enhanced Magnetic Resonance Imaging with contrast agent injection. A segmentation approach based upon principal component analysis (PCA) is used to separate out the cortex from the rest of the kidney including the medulla, the renal pelvic, and the background. Two classifiers (Soft Independent Method of Class Analogy, SIMCA; Partial Least Squares Discriminant Analysis, PLS-DA) are tested for various types of data pre-treatment including segmentation, feature extraction, centering, autoscaling, standard normal variate transformation, Savitsky-Golay smoothing, and normalization. It is shown that (i) the renal cortex contains more discriminating information on kidney perfusion changes than the whole kidney, and (ii) the PLS-DA classifiers outperform the SIMCA classifiers. PLS-DA, preceded by an automated PCA-based segmentation of kidney anatomical regions, correctly classified all kidneys and constitutes a classification tool of the renal function that can be useful for the clinical diagnosis of renovascular diseases.     

The influence of substrate morphology on the growth of thin silicon films: A GISAXS study

Thin Si films, with thickness between 100 and 300 nm, were deposited by PECVD (Plasma Enhanced Chemical Vapour Deposition) in silane gas (SiH₄) highly diluted by hydrogen. The degree of dilution and the discharge power were varied in order to obtain different crystalline to amorphous fractions in the films. Two types of substrates were used. The first one was amorphous and relatively flat while the second one was polycrystalline with a roughness of a few tens of nanometers. The crystal fraction in the deposited samples, as estimated by Raman spectroscopy, varied between 0 and 40%, and the individual crystal size was between 2 and 8 nm. The larger individual crystals are usually present in those samples with the highest crystal fraction. The sample density, estimated upon the spectral distribution of the dielectric function in the infra red, was 15-25% less than the density of crystalline silicon. The GISAXS pattern of all of the examined samples indicated the presence of not-spherical-like “particles” in the “bulk” of the thin films, with an average “particle” size between 1.5 and 4 nm. These “particles” are most probably voids and their shape indicates columnar growth. By applying the GISAXS technique on samples deposited on different substrates, the borderline deposition conditions between “transport limited growth” and “growth dominantly influenced by plasma surface reactions” was estimated.     

Identification of significant factors by an extension of ANOVA-PCA based on multi-block analysis

A modification of the ANOVA-PCA method, proposed by Harrington et al. to identify significant factors and interactions in an experimental design, is presented in this article. The modified method uses the idea of multiple table analysis, and looks for the common dimensions underlying the different data tables, or data blocks, generated by the “ANOVA-step” of the ANOVA-PCA method, in order to identify the significant factors. In this paper, the “Common Component and Specific Weights Analysis” method is used to analyse the calculated multi-block data set. This new method, called AComDim, was compared to the standard ANOVA-PCA method, by analysing four real data sets. Parameters computed during the AComDim procedure enable the computation of F-values to check whether the variability of each original data block is significantly greater than that of the noise.     

Experimental and analytical variation in human urine in 1H NMR spectroscopy-based metabolic phenotyping studies

1H NMR spectroscopy potentially provides a robust approach for high-throughput metabolic screening of biofluids such as urine and plasma, but sample handling and preparation need careful optimization to ensure that spectra accurately report biological status or disease state. We have investigated the effects of storage temperature and time on the 1H NMR spectral profiles of human urine from two participants, collected three times a day on four different days. These were analyzed using modern chemometric methods. Analytical and preparation variation (tested between -40 degrees C and room temperature) and time of storage (to 24 h) were found to be much less influential than biological variation in sample classification. Statistical total correlation spectroscopy and discriminant function methods were used to identify the specific metabolites that were hypervariable due to preparation and biology. Significant intraindividual variation in metabolite profiles were observed even for urine collected on the same day and after at least 6 h fasting. The effect of long-term storage at different temperatures was also investigated, showing urine is stable if frozen for at least 3 months and that storage at room temperature for long periods (1-3 months) results in a metabolic profile explained by bacterial activity. Presampling (e.g., previous day) intake of food and medicine can also strongly influence the urinary metabolic profiles indicating that collective detailed participant historical meta data are important for interpretation of metabolic phenotypes and for avoiding false biomarker discovery.     

Exploring the effects of lifestyle, sleep factors and driving behaviors on sleep-related road risk: A study of Greek drivers

Purpose

The present study explored the effect of various lifestyle patterns and sleep-related factors on the sleep-related road risk. Sleep-related factors included daytime sleepiness, drowsy driving and quality/quantify of sleep.

Methods

A sample of 1366 non-professional drivers aged 19–65 was selected from the broader Athens area of Greece, using stratified random sampling. The questionnaire solicited information on the participants’ socio-demographic characteristics, driving background, lifestyle patterns, sleep quality and quantity, daytime sleepiness, drowsy driving behavior and sleep-related road risk.

Results

Sleep-related road risk was affected by gender, quantity of night sleep and drowsy driving behavior. Drowsy driving behavior was shown to be related to gender, daytime sleepiness, sleep quality and the lifestyle of “amusement”. Daytime sleepiness was correlated with sleep quality and the lifestyles of “amusement” and “sport”. Finally, sleep quality and quantity were significantly affected by the lifestyles of “amusement” and “yuppies-workaholic”.

Conclusion

The current study has identified a number of risk factors in sleep-related crash risk in the general population of drivers. By raising public awareness the health and safety community can play an important role in reducing, if not preventing, the consequences of this public health problem.     

Investigation of diffusional intermixing in Si/Co/Ta system by Secondary Neutral Mass Spectrometry

Low temperature analysis of diffusion and intermixing of Co-Si systems are very important in applications for microelectronics and Ultra Large Scale Integration (ULSI). In this communication a comprehensive report has been given on degradation and diffusion processes in the Si(substrate)/Co(150 nm)/Ta(10 nm) system. The samples were prepared by DC magnetron sputtering and were annealed in argon ambient at several temperatures ranging from 400 to 623 K for various times. The composition of the samples was investigated by Secondary Neutral Mass Spectrometry (SNMS). The degradation/intermixing starts with fast (grain boundary (GB)) diffusion of the Si into the Co layer. After some incubation time Si atoms appear and spread over the Co/Ta interface. This amount of Si accumulated at the Co/Ta interface acts as a reservoir for back-diffusion into the Co layer from the Co/Ta interface through the slower grain boundaries. At higher temperatures the formation of a Co-Si phase was detected at the Co/Si and Co/Ta interface. Three different diffusion coefficients were calculated from the SNMS concentration-depth profiles using “Central-gradient” (CG) and “First-appearance” methods. The observed intermixing was interpreted as a mixture of different “C-type” grain boundary diffusion processes. Furthermore, the experimental results are also compared with computer simulations modelling the grain-boundary diffusion through different grain-boundary paths. From the SNMS profiles measured at different temperatures the activation energy of the GB interdiffusion coefficients was deduced using the “CG method”.     

Langmuir probe diagnostic for measurement of recombination rates of positive ions with electrons in stationary afterglow system

We attempted to compare several probe theories that described collection of charged particles by Langmuir probe at elevated pressures. We used stationary afterglow environment with well-defined ionic composition to measure the electron density as a function of time. Afterglow plasma has the advantage that probability of secondary electron emission from probe surface when the probe works in positive ion acceleration regime is negligible and hence the probe data are more dependable. Since estimation of the rate of recombination required knowledge of absolute values of plasma density, we were able, in case of the ions the rate of recombination of which was known, to calculate the electron density, which corresponded to the known rate of recombination. Consequently we were able to compare apparent electron density calculated from the probe data using different theories with the “reference” electron density that we obtained from the known rate of recombination. Up to several mbar pressure the differences between the “reference” value of electron density and value calculated using the collisionless theories of electron collection by Langmuir probe stay within reasonable error limits.     

Metabonomics and biomarker discovery: LC-MS metabolic profiling and constant neutral loss scanning combined with multivariate data analysis for mercapturic acid analysis

In the field of metabonomics, 1H NMR and full scan mass spectrometry methods have usually been combined with principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) to detect patterns in biofluids that correspond to specific effects, usually a toxic site effect of a compound. Confounders together with great interindividual variation complicate such analysis in humans, and therefore, metabonomic data are almost restricted to animals. In our study, a constant neutral loss (CNL) scan on a linear ion trap demonstrated increased sensitivity and specificity compared to a full scan approach and was performed to detect mercapturic acids (MA), a class of effect markers. The method was applied to human volunteers administered 50 and 500 mg of acetaminophen (AAP), a model compound known to form MAs. Using a new algorithm to prepare the CNL data for chemometrics, discrimination of control and postdose samples could be performed using PCA and PLS-DA. The loadings plots clearly revealed AAP-MA as a marker, even at low-dose levels. Orthogonal signal correction (OSC) was carried out to investigate background information that is not due to exposure. Surprisingly, the OSC data provided a classification of male and female subjects showing the performance of the new approach.     

Quantification and statistical significance analysis of group separation in NMR-based metabonomics studies

Currently, no standard metrics are used to quantify cluster separation in PCA or PLS-DA scores plots for metabonomics studies or to determine if cluster separation is statistically significant. Lack of such measures makes it virtually impossible to compare independent or inter-laboratory studies and can lead to confusion in the metabonomics literature when authors putatively identify metabolites distinguishing classes of samples based on visual and qualitative inspection of scores plots that exhibit marginal separation. While previous papers have addressed quantification of cluster separation in PCA scores plots, none have advocated routine use of a quantitative measure of separation that is supported by a standard and rigorous assessment of whether or not the cluster separation is statistically significant. Here quantification and statistical significance of separation of group centroids in PCA and PLS-DA scores plots are considered. The Mahalanobis distance is used to quantify the distance between group centroids, and the two-sample Hotelling's T² test is computed for the data, related to an F-statistic, and then an F-test is applied to determine if the cluster separation is statistically significant. We demonstrate the value of this approach using four datasets containing various degrees of separation, ranging from groups that had no apparent visual cluster separation to groups that had no visual cluster overlap. Widespread adoption of such concrete metrics to quantify and evaluate the statistical significance of PCA and PLS-DA cluster separation would help standardize reporting of metabonomics data.     

Photocatalytic TiO2 films deposited by reactive magnetron sputtering with unipolar pulsing and plasma emission control systems

TiO₂ films with thickness of about 500 nm were deposited on unheated non-alkali glass substrates by reactive magnetron sputtering using one Ti metal target with unipolar pulsed powering of 50 kHz and the plasma emission feedback system (PCU). In order to keep the very high deposition rate, the depositions were carried out in the “transition region” between the metallic and the reactive (oxide) sputter mode where the target surface was metallic and oxidized, respectively. Stable deposition was successfully carried out in the whole “transition region” with PCU at total gas pressure of 3.0 Pa. All the as-deposited films deposited in the “transition region” showed amorphous structure, which performed very low photocatalytic activity. After the post-annealing in air at higher than 300 °C, all the films crystallized to anatase polycrystalline structure. They performed both photoinduced decomposition of acetaldehyde and photoinduced hydrophilicity under UV light illumination. The highest deposition rate in this study to deposit the photocatalytic TiO₂ films in the “transition region” was 90 nm/min, which was over twenty times higher than that for conventional sputter deposition processes.