A novel safety assessment strategy for non-intentionally added substances (NIAS) in carton food contact materials

One of the main challenges in food contact materials research is to prove that the presence of non-intentionally added substances (NIAS) is not a safety issue. Migration extracts may contain many unknown substances present at low concentrations. It is difficult and time-consuming to identify all these potential NIAS and concurrently to assess their health risk upon exposure, whereas the health relevance at low exposure levels might not even be an issue. This paper describes a scientifically based, but pragmatic safety assessment approach for unknown substances present at low exposure levels in food contact matrices. This complex mixture safety assessment strategy (CoMSAS) enables one to distinguish toxicologically relevant from toxicologically less relevant substances, when related to their respective levels of exposure, and allows one to focus on the substances of potential health concern. In particular, substances for which exposure will be below certain thresholds may be considered not of health relevance in case specific classes of substances are excluded. This can reduce the amount of work needed for identification, characterisation and evaluation of unknown substances at low concentration. The CoMSAS approach is presented in this paper using a safety assessment of unknown NIAS that may migrate from three carton samples.     

Deconvolution using signal segmentation

Extraction of peak areas and mass spectral information from chromatography mass spectral data such as obtained in metabolomics measurements requires much effort and the quality is often subjective to the operator that handles the data at hand. In multiple file deconvolution, all samples are processed simultaneously and alignment issues are part of the modeling strategy. However, processing the total data set as a whole is an impossible task and therefore the data processing task requires segmentation. Two intertwined divide and conquer strategies are proposed. The first strategy divides the retention time axis into equal parts and the second strategy divides the total data set into a model and a prediction data set. Dividing the data into smaller segments allows us to conquer the total problem. Post processing of the resulting matrices with peak areas and mass spectra ensures that a matrix with peak areas ready for statistics and a matrix with mass spectral information ready for peak annotation is obtained. The proposed methodology is implemented within a package called TNO-DECO but can easily be implemented in other data pre-processing approaches.     

Automatic QRS onset and offset detection for body surface QRSintegral mapping of ventricular tachycardia

A QRS onset and offset detection algorithm has been developed for use in body surface QRS integral mapping of ventricular tachycardia. To determine QRS intervals, the algorithm uses two computed signals: the sum of the absolute values of the first derivatives of all leads and the sum of the absolute values of all leads. The second order derivative of the latter parameter is used to detect the time instants of QRS onset and offset. Using the algorithm, QRS integral maps are subsequently computed, which are correlated with a database of QRS integral maps in order to localize the site of origin of ventricular tachycardia. Comparison of the performance of the algorithm with visual evaluation by a human expert in this procedure revealed, in 95% of the cases, an identical or adjacent localization of the site of origin     

Correlative Phase Shift Keying--A Class of Constant Envelope Modulation Techniques

Correlative phase shift keying (CORPSK) is described. CORPSK is a constant envelope modulation technique with smooth transitions between fixed phase positions with successive transitions correlated. A number of CORPSK members for 2 and 4 input levels are analyzed, including tamed frequency modulation (TFM). Main lobe bandwidth is the same or less than in other constant envelope modulation techniques such as MSK, QPSK, and CPFSK, but the out-of-band radiation is much lower. Carrier extraction can be realized with simple techniques, so that coherent detection with optimum receiver performance is practically feasible. Simulation results are presented for coherent as well as noncoherent detection. A power efficiency 2 dB better than four MSK and DQPSK can be obtained for CORPSK with no more than for phase positions. A wide variety of modulations exists within the CORPSK class, with ample opportunity for tradeoffs between power, bandwidth, and complexity. Practical results for TFM are reported.     

Microbial metabolomics with gas chromatography/mass spectrometry

An analytical method was set up suitable for the analysis of microbial metabolomes, consisting of an oximation and silylation derivatization reaction and subsequent analysis by gas chromatography coupled to mass spectrometry. Microbial matrixes contain many compounds that potentially interfere with either the derivatization procedure or analysis, such as high concentrations of salts, complex media or buffer components, or extremely high substrate and product concentrations. The developed method was extensively validated using different microorganisms, i.e., Bacillus subtilis, Propionibacterium freudenreichii, and Escherichia coli. Many metabolite classes could be analyzed with the method: alcohols, aldehydes, amino acids, amines, fatty acids, (phospho-) organic acids, sugars, sugar acids, (acyl-) sugar amines, sugar phosphate, purines, pyrimidines, and aromatic compounds. The derivatization reaction proved to be efficient (>50% transferred to derivatized form) and repeatable (relative standard deviations <10%). Linearity for most metabolites was satisfactory with regression coefficients better than 0.996. Quantification limits were 40-500 pg on-column or 0.1-0.7 mmol/g of microbial cells (dry weight). Generally, intrabatch precision (repeatability) and interbatch precision (reproducibility) for the analysis of metabolites in cell extracts was better than 10 and 15%, respectively. Notwithstanding the nontargeted character of the method and complex microbial matrix, analytical performance for most metabolites fit the requirements for target analysis in bioanalysis. The suitability of the method was demonstrated by analysis of E. coli samples harvested at different growth phases.     

A bulky phosphite-modified rhodium catalyst for the hydroformylation of unsaturated fatty acid esters

A series of hydroformylation experiments was performed with a high-grade and a technical-grade-derived methyl oleate (MO) and a rhodium catalyst modified by the bulky tris(2-tert-butyl-4-methylphenyl)phosphite. In the hydroformylation of pure methyl oleate, relatively high turnover numbers were obtained (400–500 mol/mol/h) under mild conditions (molar ratio MO/Rh=910, 80–100°C and 20 bar; CO/H₂=1:1, solvent toluene), leading to about 95% conversion in 3 h. Fast isomerization occurs under these conditions to produce the trans oleate. Trans oleate reacts more slowly than cis oleate. At temperatures below 50°C, isomerization does not occur. The use of technical-grade methyl oleate, containing 14% 9,12 diene, methyl linoleate (ML), results in lower reaction rates because dienes form stable π-allylic intermediates, which slowly undergo hydroformylation. More severe conditions were applied to obtain higher rates. The rate varied from 50 to 400 mol/mol/h, depending on conditions (molar ratio MO/Rh=910, T=50–120°C, P = 50–80 bar; CO/H₂=1:1–1:6, solvent, toluene). Several isomers of ML were formed during the reaction. Subsequent hydroformylation of these isomers results in a complicated mixture of products. The product mixture consists predominantly of methyl formylstearate, methyl formyloleate, methyl diformylstearate, and some yet unidentified side products. A comparison of the classic triphenylphosphine-modified catalyst and the bulky phosphite-modified catalyst has shown that the latter is several times more active.