Predicting EQ-5D from the Parkinson's disease questionnaire PDQ-8 using multi-dimensional Bayesian network classifiers

The impact of the Parkinson's disease and its treatment on the patients' health-related quality of life can be estimated either by means of generic measures such as the european quality of Life-5 Dimensions (EQ-5D) or specific measures such as the 8-item Parkinson's disease questionnaire (PDQ-8). In clinical studies, PDQ-8 could be used in detriment of EQ-5D due to the lack of resources, time or clinical interest in generic measures. Nevertheless, PDQ-8 cannot be applied in cost-effectiveness analyses which require generic measures and quantitative utility scores, such as EQ-5D. To deal with this problem, a commonly used solution is the prediction of EQ-5D from PDQ-8. In this paper, we propose a new probabilistic method to predict EQ-5D from PDQ-8 using multi-dimensional Bayesian network classifiers. Our approach is evaluated using five-fold cross-validation experiments carried out on a Parkinson's data set containing 488 patients, and is compared with two additional Bayesian network-based approaches, two commonly used mapping methods namely, ordinary least squares and censored least absolute deviations, and a deterministic model. Experimental results are promising in terms of predictive performance as well as the identification of dependence relationships among EQ-5D and PDQ-8 items that the mapping approaches are unable to detect

Efficient Monte Carlo methods for multi-dimensional learning with classifier chains

Multi-dimensional classification (MDC) is the supervised learning problem where an instance is associated with multiple classes, rather than with a single class, as in traditional classification problems. Since these classes are often strongly correlated, modeling the dependencies between them allows MDC methods to improve their performance – at the expense of an increased computational cost. In this paper we focus on the classifier chains (CC) approach for modeling dependencies, one of the most popular and highest-performing methods for multi-label classification (MLC), a particular case of MDC which involves only binary classes (i.e., labels). The original CC algorithm makes a greedy approximation, and is fast but tends to propagate errors along the chain. Here we present novel Monte Carlo schemes, both for finding a good chain sequence and performing efficient inference. Our algorithms remain tractable for high-dimensional data sets and obtain the best predictive performance across several real data sets.

Multiresidue Analysis of Insecticides and Other Selected Environmental Contaminants in Poultry Manure by Gas Chromatography/Mass Spectrometry

An analytical method was developed for the simultaneous determination in poultry manure of 41 organic contaminants belonging to different chemical classes: pesticides, polycyclic aromatic hydrocarbons, polychlorinated biphenyls, and polybrominated diphenyl ethers. Poultry manure was extracted with a modified QuEChERS method, and the extracts were analyzed by isotope dilution GC/MS. Recovery of these contaminants from samples spiked at levels ranging from 25 to 100 ng/g was satisfactory for all the compounds. The developed procedure provided LODs from 0.8 to 9.6 ng/g. The analysis of poultry manure samples collected on different farms confirmed the presence of some of the studied contaminants. Pyrethroids and polycyclic aromatic hydrocarbons were the main contaminants detected.

Determination of selected pharmaceutical compounds in biosolids bysupported liquid extraction and gas chromatography?tandem massspectrometry

In this work, an analytical method was developed for the determination of pharmaceutical drugs inbiosolids. Samples were extracted with an acidic mixture of water and acetone (1:2, v/v) and supportedliquid extraction was used for the clean-up of extracts, eluting with ethyl acetate:methanol (90:10, v/v).The compounds were determined by gas chromatography?tandem mass spectrometry using matrix-match calibration after silylation to form their t-butyldimethylsilyl derivatives. This method presentsvarious advantages, such as a fairly simple operation for the analysis of complex matrices, the use ofinexpensive glassware and low solvent volumes. Satisfactory mean recoveries were obtained with thedeveloped method ranging from 70 to 120% with relative standard deviations (RSDs) ? 13%, and limitsof detection between 0.5 and 3.6 ng g?1. The method was then successfully applied to biosolids samplescollected in Madrid and Catalonia (Spain). Eleven of the sixteen target compounds were detected in thestudied samples, at levels up to 1.1 ?g g?1(salicylic acid). Ibuprofen, caffeine, paracetamol and fenofibratewere detected in all of the samples analyzed.

Measurement of 8-hydroxy-2′-deoxyguanosine in DNA by high-performance liquid chromatography-mass spectrometry: comparison with measurement by gas chromatography-mass spectrometry

Measurement of 8-hydroxy-2′-deoxyguanosine (8-OH-dGuo) in DNA by high-performance liquid chromatography/mass spectrometry (LC/MS) was studied. A methodology was developed for separation by LC of 8-OH-dGuo from intact and modified nucleosides in DNA hydrolyzed by a combination of four enzymes: DNase I, phosphodiesterases I and II and alkaline phosphatase. The atmospheric pressure ionization-electrospray process was used for mass spectral measurements. A stable isotope-labeled analog of 8-OH-dGuo was used as an internal standard for quantification by isotope-dilution MS (IDMS). Results showed that LC/IDMS with selected ion-monitoring (SIM) is well suited for identification and quantification of 8-OH-dGuo in DNA at background levels and in damaged DNA. The sensitivity level of LC/IDMS-SIM was found to be comparable to that reported previously using LC-tandem MS (LC/MS/MS). It was found that approximately five lesions per 106 DNA bases can be detected using amounts of DNA as low as 2 µg. The results also suggest that this lesion may be quantified in DNA at levels of one lesion per 106 DNA bases, or even lower, when more DNA is used. Up to 50 µg of DNA per injection were used without adversely affecting the measurements. Gas chromatography/isotope-dilution MS with selected-ion monitoring (GC/IDMS-SIM) was also used to measure this compound in DNA following its removal from DNA by acidic hydrolysis or by hydrolysis with Escherichia coli Fpg protein. The background levels obtained by LC/IDMS-SIM and GC/IDMS-SIM were almost identical. Calf thymus DNA and DNA isolated from cultured HeLa cells were used for this purpose. This indicates that these two techniques can provide similar results in terms of the measurement of 8-OH-dGuo in DNA. In addition, DNA in buffered aqueous solution was damaged by ionizing radiation at different radiation doses and analyzed by LC/IDMS-SIM and GC/IDMS-SIM. Again, similar results were obtained by the two techniques. The sensitivity of GC/MS-SIM for 7,8-dihydro-8-oxoguanine was also examined and found to be much greater than that of LC/MS-SIM and the reported sensitivity of LC/MS/MS for 8-OH-dGuo. Taken together, the results unequivocally show that LC/IDMS-SIM is well suited for sensitive and accurate measurement of 8-OH-dGuo in DNA and that both LC/IDMS-SIM and GC/IDMS-SIM can provide similar results.

Contribution of Malic Enzyme, Pyruvate Kinase, Phosphoenolpyruvate Carboxylase, and the Krebs Cycle to Respiration and Biosynthesis and to Intracellular pH Regulation during Hypoxia in Maize Root Tips Observed by Nuclear Magnetic Resonance Imaging and Gas Chromatography-Mass Spectrometry1

In vivo pyruvate synthesis by malic enzyme (ME) and pyruvate kinase and in vivo malate synthesis by phosphoenolpyruvate carboxylase and the Krebs cycle were measured by 13C incorporation from [1-13C]glucose into glucose-6-phosphate, alanine, glutamate, aspartate, and malate. These metabolites were isolated from maize (Zea mays L.) root tips under aerobic and hypoxic conditions. 13C-Nuclear magnetic resonance spectroscopy and gas chromatography-mass spectrometry were used to discern the positional isotopic distribution within each metabolite. This information was applied to a simple precursor-product model that enabled calculation of specific metabolic fluxes. In respiring root tips, ME was found to contribute only approximately 3% of the pyruvate synthesized, whereas pyruvate kinase contributed the balance. The activity of ME increased greater than 6-fold early in hypoxia, and then declined coincident with depletion of cytosolic malate and aspartate. We found that in respiring root tips, anaplerotic phosphoenolpyruvate carboxylase activity was high relative to ME, and therefore did not limit synthesis of pyruvate by ME. The significance of in vivo pyruvate synthesis by ME is discussed with respect to malate and pyruvate utilization by isolated mitochondria and intracellular pH regulation under hypoxia.

Determination of cyclic and linear siloxanes in wastewater samples by ultrasound-assisted dispersive liquid-liquid microextraction followed by gas chromatography-mass spectrometry

A fast, simple and environmentally friendly ultrasound-assisted dispersive liquid-liquid microextraction (USA-DLLME) procedure has been developed to preconcentrate eight cyclic and linear siloxanes from wastewater samples prior to quantification by gas chromatography-mass spectrometry (GC-MS). A two-stage multivariate optimization approach has been developed employing a Plackett-Burman design for screening and selecting the significant factors involved in the USA-DLLME procedure, which was later optimized by means of a circumscribed central composite design. The optimum conditions were: extractant solvent volume, 13 µL; solvent type, chlorobenzene; sample volume, 13 mL; centrifugation speed, 2300 rpm; centrifugation time, 5 min; and sonication time, 2 min. Under the optimized experimental conditions the method gave levels of repeatability with coefficients of variation between 10 and 24% (n=7). Limits of detection were between 0.002 and 1.4 µg L−1. Calculated calibration curves gave high levels of linearity with correlation coefficient values between 0.991 and 0.9997. Finally, the proposed method was applied for the analysis of wastewater samples. Relative recovery values ranged between 71–116% showing that the matrix had a negligible effect upon extraction. To our knowledge, this is the first time that combines LLME and GC-MS for the analysis of methylsiloxanes in wastewater samples.

Development of a novel pyrolysis-gas chromatography/mass spectrometry method for the analysis of poly(lactic acid) thermal degradation products

Thermal degradation of PLA is a complex process since it comprises many simultaneous reactions. The use of analytical techniques, such as differential scanning calorimetry (DSC) and thermogravimetry (TGA), yields useful information but a more sensitive analytical technique would be necessary to identify and quantify the PLA degradation products. In this work the thermal degradation of PLA at high temperatures was studied by using a pyrolyzer coupled to a gas chromatograph with mass spectrometry detection (Py-GC/MS). Pyrolysis conditions (temperature and time) were optimized in order to obtain an adequate chromatographic separation of the compounds formed during heating. The best resolution of chromatographic peaks was obtained by pyrolyzing the material from room temperature to 600 °C during 0.5 s. These conditions allowed identifying and quantifying the major compounds produced during the PLA thermal degradation in inert atmosphere. The strategy followed to select these operation parameters was by using sequential pyrolysis based on the adaptation of mathematical models. By application of this strategy it was demonstrated that PLA is degraded at high temperatures by following a non-linear behaviour. The application of logistic and Boltzmann models leads to good fittings to the experimental results, despite the Boltzmann model provided the best approach to calculate the time at which 50% of PLA was degraded. In conclusion, the Boltzmann method can be applied as a tool for simulating the PLA thermal degradation.

User's guide for the gas chromatography automation system /

Mode of access: Internet.

Performance tests for the evaluation of computerized gas chromatography/mass spectrometry equipment and laboratories /

"April 1980"--Cover.

Method of analysis and quality-assurance practices for determination of pesticides in water by solid-phase extraction and capillary-column gas chromatography/mass spectrometry at the U.S. Geological Survey California District Organic Chemistry Laboratory, 1996-99 /

Mode of access: Internet.

Optimisation of poly-b-hydroxyalkanoate analysis using gas chromatography for enhanced biological phosphorus removal systems

Poly-beta-hydroxyalkanoate (PHA) is a polymer commonly used in carbon and energy storage for many different bacterial cells. Polyphosphate accumulating organisms (PAOs) and glycogen accumulating organisms (GAOs), store PHA anaerobically through metabolism of carbon substrates such as acetate and propionate. Although poly-beta-hydroxybutyrate (PHB)and poly-beta-hydroxyvalerate (PHV) are commonly quantified using a previously developed gas chromatography (GC) method, poly-beta-hydroxy-2-methyl valerate (PH2MV) is seldom quantified despite the fact that it has been shown to be a key PHA fraction produced when PAOs or GAOs metabolise propionate. This paper presents two GC-based methods modified for extraction and quantification of PHB, PHV and PH2MV from enhanced biological phosphorus removal (EBPR) systems. For the extraction Of PHB and PHV from acetate fed PAO and GAO cultures, a 3% sulfuric acid concentration and a 2-20 h digestion time is recommended, while a 10% sulfuric acid solution digested for 20 h is recommended for PHV and PH2MV analysis from propionate fed EBPR systems. (c) 2005 Elsevier B.V. All rights reserved.