NMR-Based Multi Parametric Quality Control of Fruit Juices: SGF Profiling

With SGF Profiling™ we introduce an NMR-based screening method for the quality control of fruit juices. This method has been developed in a joint effort by Bruker BioSpin GmbH and SGF International e.V. The system is fully automated with respect to sample transfer, measurement, data analysis and reporting and is set up on an Avance 400 MHz flow-injection NMR spectrometer. For each fruit juice a multitude of parameters related to quality and authenticity are evaluated simultaneously from a single data set acquired within a few minutes. This multimarker/multi-aspect NMR screening approach features low cost-per-sample and is highly competitive with conventional and targeted fruit juice quality control methods

The instrument suite of the European Spallation Source

An overview is provided of the 15 neutron beam instruments making up the initial instrument suite of the European Spallation Source (ESS), and being made available to the neutron user community. The ESS neutron source consists of a high-power accelerator and target station, providing a unique long-pulse time structure of slow neutrons. The design considerations behind the time structure, moderator geometry and instrument layout are presented. The 15-instrument suite consists of two small-angle instruments, two reflectometers, an imaging beamline, two single-crystal diffractometers; one for macromolecular crystallography and one for magnetism, two powder diffractometers, and an engineering diffractometer, as well as an array of five inelastic instruments comprising two chopper spectrometers, an inverse-geometry single-crystal excitations spectrometer, an instrument for vibrational spectroscopy and a high-resolution backscattering spectrometer. The conceptual design, performance and scientific drivers of each of these instruments are described. All of the instruments are designed to provide breakthrough new scientific capability, not currently available at existing facilities, building on the inherent strengths of the ESS long-pulse neutron source of high flux, flexible resolution and large bandwidth. Each of them is predicted to provide world-leading performance at an accelerator power of 2 MW. This technical capability translates into a very broad range of scientific capabilities. The composition of the instrument suite has been chosen to maximise the breadth and depth of the scientific impact o

Toleranzbereiche für 1H-NMR-Spektren von Neugeborenenurinen

In dieser Arbeit wird ein Verfahren zur Bestimmung von Toleranzbereichen für 1H-NMR-Spektren von Neugeborenenurinen zur Detektion von angeborenen Stoffwechselerkrankungen vorgestellt. Diese Krankheiten werden durch genetische Defekte ausgelöst, die eine schwerwiegende Funktionsstörung im Stoffwechselkreislauf verursachen. Die dadurch entstehenden Krankheitsbilder führen in der Regel zu Behinderungen und oftmals zum Tod. Eine frühe Diagnose und Behandlung können in vielen Fällen ein Überleben ohne Symptome ermöglichen. Beim derzeitigen Neugeborenenscreening werden in Deutschland zwölf der häufigsten Stoffwechselerkrankungen routinemäßig abgetestet - weit über hundert sind aktuell bekannt. Basierend auf einem Referenzdatensatz von 695 Neugeborenenurinspektren, werden in dieser Arbeit mathematische Methoden zur Bestimmung von Toleranzbereichen entwickelt, die eine ungezielte Detektion von Abweichungen ermöglichen, um schwerwiegende Krankheiten wie angeborene Stoffwechselerkrankungen frühzeitig und routinemäßig diagnostizieren zu können. Das Verfahren basiert dabei auf der robusten Ermittlung von Verteilungsfunktionen, Toleranzbereichen und Identifikation von Ausreißern für eindimensionale Stichproben von unbekannten Verteilungen. Mithilfe einer von der Box-Cox-Transformation abgeleiteten Transformationsfamilie, werden die gemessenen Kenngrößen in normalverteilte Stichproben überführt. Für die Bestimmung der optimalen Transformationsparameter wird die Teststatistik des Shapiro-Wilk-Tests auf Normalverteilung der transformierten Stichprobe verwendet. Die Betrachtung verschiedener links- und rechtsseitiger Trimmungen sichert dabei eine robuste Bestimmung, die nicht von Ausreißern innerhalb des Referenzdatensatzes beeinflusst wird. Anhand von Simulationsstudien wird die Leistung dieses Verfahrens an Stichproben mit bekannten Verteilungen ermittelt und demonstriert. Die Anwendbarkeit an abgeleiteten Kenngrößen aus den realen Urinspektren wird zunächst anhand von Metabolitenkonzentrationen gezeigt. Hierfür wurden im Rahmen dieser Arbeit Methoden zur Identifikation und Quantifikation von 22 ausgewählten Metaboliten entwickelt. Für die ungezielte Analyse werden aus den NMR-Spektren abstrakte Kenngrößen abgeleitet, welche die Protonenkonzentrationen in verschiedenen chemischen Verschiebungsbereichen zusammenfassen (sogenannte Bucketierung). Dadurch wird jedes Signal, unabhängig von Molekül oder funktioneller Gruppe, erfasst und ausgewertet. Bei der in dieser Arbeit verwendeten Strategie entstehen dadurch 500 Messwerte pro Spektrum, von denen 479 (96%) in normalverteilte Variablen überführt werden können. Für diese werden schließlich Toleranzbereiche definiert, um Messungen von weiteren Urinproben abzugleichen. Zusätzlich wird ausgehend von den transformierten Variablen eine Möglichkeit dargestellt, auch multivariate Toleranzbereiche auf Basis der Mahalanobisdistanz zu ermitteln, welche die Sensitivität des Tests auf abweichende Signale signifikant erhöht. Anhand einer Spiking-Simulationsstudie mit ca. 500.000 Spektren, bei denen die Signale von elf Verbindungen, die in Zusammenhang mit angeborenen Stoffwechselerkrankungen stehen, numerisch zu den Referenzspektren addiert werden, können Detektionsraten in Abhängigkeit der Konzentrationen dieser Verbindungen ermittelt werden.In this work a method for the determination of tolerance intervals for 1H-NMR-spectra of neonatal urines is presented in order to detect inborn errors of metabolism. These diseases lead to severe dysfunctions in metabolic pathways which can cause organ failures, disabilities and death. Based on a reference dataset of 695 1H-NMR-spectra of urines from healthy neonates, a method for an untargeted detection of deviations of any kind is developed which can be applied to further samples. The method is based on robust estimations of density functions, tolerance intervals and identification of outliers of one-dimensional samples with unknown distributions. With a modification of the Box-Cox-transformation the measured concentrations are transformed to parameters which are normally distributed. For the determination of the optimal transformation parameters the test statistic of the Shapiro-Wilk normality test is used. The usage of variable trimmings ensures a robust transformation which is not influenced by outliers in the reference dataset. The performance of the method is illustrated by several simulation studies on random samples with known distributions. The applicability on real data is firstly demonstrated on concentrations of metabolites. Therefore, methods for the identification and quantification of 22 common metabolites in neonate urine have been developed. For the untargeted analysis, a consecutive bucketation of the 1H-NMR-spectra is used which generates hundreds of abstract concentration values. This ensures that each signal will be evaluated, independent from the respective molecule or functional group. Additionally, an extension of this method for the determination of multivariate tolerance intervals based on the mahalanobis distance is described which increases the sensitivity. A numerical spiking study based on approximately 500.000 spectra is used to show the performance on the detection of deviating signals

Individual human phenotypes in metabolic space and time

Differences between individual phenotypes are due both to differences in genotype and to exposure to different environmental factors. A fundamental contribution to the definition of the individual phenotype for clinical and therapeutic applications would come from a deeper understanding of the metabolic phenotype. The existence of unique individual metabolic phenotypes has been hypothesized, but the experimental evidence has been only recently collected. Analysis of individual phenotypes over the timescale of years shows that the metabolic phenotypes are largely invariant. The present work also supports the idea that the individual metabolic phenotype can also be considered a metagenomic entity that is strongly affected by both gut microbiome and host metabolic phenotype, the latter defined by both genetic and environmental contributions.</p

Heterocovariance based metabolomics as a powerful tool accelerating bioactive natural product identification

The discovery of new active natural products is hampered by laborious purification processes that often end up to the re-isolation of known compounds. We demonstrate here that, spectral data reflecting concentration fluctuations of components can correlate statistically with measurable dose-dependent properties on the basis of a Heterocovariance approach deconvoluting the active components structure. Variance of extract constituents was achieved through statistically meaningful collections of plants from different families, genus, and species. This fluctuation was also obtained through the fractionation of a single plant extract by separation techniques. The NMR and HRMS spectra of the extracts and fractions were recorded, as well as their ability to inhibit tyrosinase or 5-lipoxygenase enzymes. Biological activity was statistically correlated with spectral data deciphering the active compounds through the Heterocovariance approach prior to any purification

Towards harmonization of ecological quality classification: Establishing common grounds in European macrophyte assessment for rivers

Different national assessment concepts impede the harmonization of river quality classifications using macrophytes in Europe. This study describes a procedure to identify similarities between the national methods for ecological quality assessment of Austria, Belgium (Flanders and Wallonia), France, Germany, Great Britain and Poland. Based on an international data set covering three European stream types we identified sites commonly assessed as high status by most methods. A mean index derived from averaging the national assessment results per stream site was then correlated with the abundance of each macrophyte taxon. We defined common macrophyte indicator scores using these correlation coefficients. This enabled the description of type-specific macrophyte communities under near-natural and degraded conditions, and the development of a common metric (mICM) that was correlated with all national methods. The weaker relations of the Flemish and German methods were improved by adjusting national indicator scores of selected macrophyte taxa that deviated from the common indicator scores. The analysis of common high status sites provided mICM reference values. This study offers a general approach to harmonize the national assessment methods for biological elements of any water category