Composition of cometary particles collected during two periods of the Rosetta mission: multivariate evaluation of mass spectral data.

The instrument COSIMA (COmetary Secondary Ion Mass Analyzer) onboard of the European Space Agency mission Rosetta collected and analyzed dust particles in the neighborhood of comet 67P/Churyumov-Gerasimenko. The chemical composition of the particle surfaces was characterized by time-of-flight secondary ion mass spectrometry. A set of 2213 spectra has been selected, and relative abundances for CH-containing positive ions as well as positive elemental ions define a set of multivariate data with nine variables.

A laser desorption ionization/matrix-assisted laser desorption ionization target system applicable for three distinct types of instruments (LinTOF/curved field RTOF, LinTOF/RTOF and QqRTOF) with different performance characteristics from three vendors.

Rationale: We have developed a target system which enables the use of only one target (i.e. target preparation set) for three different laser desorption ionization (LDI)/matrix-assisted laser desorption ionization (MALDI) mass spectrometric instruments.

Mechanical and electrostatic experiments with dust particles collected in the inner coma of comet 67P by COSIMA onboard Rosetta.

The cometary dust particle instrument COSIMA (COmetary Secondary Ion Mass Analyser) onboard ESA's Rosetta mission has collected about 31 000 dust particles in the inner coma of comet 67P/Churyumov-Gerasimenko since August 2014. The particles are identified by optical microscope imaging and analysed by time-of-flight secondary ion mass spectrometry. After dust particle collection by low speed impact on metal targets, the collected particle morphology points towards four families of cometary dust particles.

High-molecular-weight organic matter in the particles of comet 67P/Churyumov-Gerasimenko.

The presence of solid carbonaceous matter in cometary dust was established by the detection of elements such as carbon, hydrogen, oxygen and nitrogen in particles from comet 1P/Halley. Such matter is generally thought to have originated in the interstellar medium, but it might have formed in the solar nebula-the cloud of gas and dust that was left over after the Sun formed. This solid carbonaceous material cannot be observed from Earth, so it has eluded unambiguous characterization.

Comet 67P/Churyumov-Gerasimenko sheds dust coat accumulated over the past four years.

Comets are composed of dust and frozen gases. The ices are mixed with the refractory material either as an icy conglomerate, or as an aggregate of pre-solar grains (grains that existed prior to the formation of the Solar System), mantled by an ice layer. The presence of water-ice grains in periodic comets is now well established.

Severe drought stress is affecting selected primary metabolites, polyphenols, and volatile metabolites in grapevine leaves (Vitis vinifera cv. Pinot noir).

Extreme weather conditions with prolonged dry periods and high temperatures as well as heavy rain events can severely influence grapevine physiology and grape quality. The present study evaluates the effects of severe drought stress on selected primary metabolites, polyphenols and volatile metabolites in grapevine leaves. Among the 11 primary metabolites, 13 polyphenols and 95 volatiles which were analyzed, a significant discrimination between control and stressed plants of 7 primary metabolites, 11 polyphenols and 46 volatile metabolites was observed.

Multivariate linear QSPR/QSAR models: Rigorous evaluation of variable selection for PLS.

Basic chemometric methods for making empirical regression models for QSPR/QSAR are briefly described from a user's point of view. Emphasis is given to PLS regression, simple variable selection and a careful and cautious evaluation of the performance of PLS models by repeated double cross validation (rdCV). A demonstration example is worked out for QSPR models that predict gas chromatographic retention indices (values between 197 and 504 units) of 209 polycyclic aromatic compounds (PAC) from molecular descriptors generated by Dragon software.

RMol: a toolset for transforming SD/Molfile structure information into R objects.

Background: The graph-theoretical analysis of molecular networks has a long tradition in chemoinformatics. As demonstrated frequently, a well designed format to encode chemical structures and structure-related information of organic compounds is the Molfile format. But when it comes to use modern programming languages for statistical data analysis in Bio- and Chemoinformatics, R as one of the most powerful free languages lacks tools to process Molfile data collections and import molecular network data into R.

Information indices with high discriminative power for graphs.

In this paper, we evaluate the uniqueness of several information-theoretic measures for graphs based on so-called information functionals and compare the results with other information indices and non-information-theoretic measures such as the well-known Balaban J index. We show that, by employing an information functional based on degree-degree associations, the resulting information index outperforms the Balaban J index tremendously. These results have been obtained by using nearly 12 million exhaustively generated, non-isomorphic and unweighted graphs.

Random projection for dimensionality reduction--applied to time-of-flight secondary ion mass spectrometry data.

Random projection (RP) is a simple and fast linear method for dimensionality reduction of high-dimensional multivariate data, independent from the data. The method is briefly described and a new memory-saving algorithm is presented for the generation of random projection vectors. Application of RP to data from scanning experiments with a time-of-flight secondary ion mass spectrometer (TOF-SIMS) showed that data reduced by RP have a satisfying discriminant property for separating target material and minerals without using any knowledge about the composition of the sample.

Novel topological descriptors for analyzing biological networks.

Background: Topological descriptors, other graph measures, and in a broader sense, graph-theoretical methods, have been proven as powerful tools to perform biological network analysis. However, the majority of the developed descriptors and graph-theoretical methods does not have the ability to take vertex- and edge-labels into account, e.g.

A large scale analysis of information-theoretic network complexity measures using chemical structures.

This paper aims to investigate information-theoretic network complexity measures which have already been intensely used in mathematical- and medicinal chemistry including drug design. Numerous such measures have been developed so far but many of them lack a meaningful interpretation, e.g.

On entropy-based molecular descriptors: statistical analysis of real and synthetic chemical structures.

This paper presents an analysis of entropy-based molecular descriptors. Specifically, we use real chemical structures, as well as synthetic isomeric structures, and investigate properties of and among descriptors with respect to the used data set by a statistical analysis. Our numerical results provide evidence that synthetic chemical structures are notably different to real chemical structures and, hence, should not be used to investigate molecular descriptors.

Chemometric evaluation of time-of-flight secondary ion mass spectrometry data of minerals in the frame of future in situ analyses of cometary material by COSIMA onboard ROSETTA.

Chemometric data evaluation methods for time-of-flight secondary ion mass spectrometry (TOF-SIMS) have been tested for the characterization and classification of minerals. Potential applications of these methods include the expected data from cometary material to be measured by the COSIMA instrument onboard the ESA mission ROSETTA in the year 2014. Samples of the minerals serpentine, enstatite, olivine, and talc have been used as proxies for minerals existing in extraterrestrial matter.

Exploration of anthropological specimens by GC-MS and chemometrics.

Anthropological specimens combine a variety of unfavorable characteristics, rendering their evaluation an analytical challenge. Their remarkable status is primarily based on two characteristics: (i) these very rare samples of human origin are testimonies of human history and are, therefore, available only in minute amounts for analytical purposes, and (ii) the analysis of these samples is extremely limited by the decomposition of molecules, which are easily detected in living organisms, such as nucleic acids and proteins, but are subject to rapid post-mortem decay. In this article, we review the methods and results of archaeometry, emphasizing the role of MS combined with chemometrics.

Fatty acid composition and preservation of the Tyrolean Iceman and other mummies.

In anthropology, objective parameters to adequately describe storage conditions and the preservation of mummies have yet to be identified. Considering that fatty acids degrade to stable products, we analysed their profile in human mummies and in control samples by gas chromatography coupled to mass spectrometry (GC/MS). Originating from different epochs and civilizations, samples of the Tyrolean Iceman, other glacier corpses, a freeze dried mummy, corpses from a permafrost region, a corpse mummified immersed in water, and a desert mummy were evaluated.