Genuine cross-correlations: Which surrogate based measure reproduces analytical results best?

The analysis of short segments of noise-contaminated, multivariate real world data constitutes a challenge. In this paper we compare several techniques of analysis, which are supposed to correctly extract the amount of genuine cross-correlations from a multivariate data set. In order to test for the quality of their performance we derive time series from a linear test model, which allows the analytical derivation of genuine correlations. We compare the numerical estimates of the four measures with the analytical results for different correlation pattern. In the bivariate case all but one measure performs similarly well. However, in the multivariate case measures based on the eigenvalues of the equal-time cross-correlation matrix do not extract exclusively information about the amount of genuine correlations, but they rather reflect the spatial organization of the correlation pattern. This may lead to failures when interpreting the numerical results as illustrated by an application to three electroencephalographic recordings of three patients suffering from pharmacoresistent epilepsy.

Collapsed cone convolution and analytical anisotropic algorithm dose calculations compared to VMC++ Monte Carlo simulations in clinical cases

The purpose of this work was to study and quantify the differences in dose distributions computed with some of the newest dose calculation algorithms available in commercial planning systems. The study was done for clinical cases originally calculated with pencil beam convolution (PBC) where large density inhomogeneities were present. Three other dose algorithms were used: a pencil beam like algorithm, the anisotropic analytic algorithm (AAA), a convolution superposition algorithm, collapsed cone convolution (CCC), and a Monte Carlo program, voxel Monte Carlo (VMC++). The dose calculation algorithms were compared under static field irradiations at 6 MV and 15 MV using multileaf collimators and hard wedges where necessary. Five clinical cases were studied: three lung and two breast cases. We found that, in terms of accuracy, the CCC algorithm performed better overall than AAA compared to VMC++, but AAA remains an attractive option for routine use in the clinic due to its short computation times. Dose differences between the different algorithms and VMC++ for the median value of the planning target volume (PTV) were typically 0.4% (range: 0.0 to 1.4%) in the lung and -1.3% (range: -2.1 to -0.6%) in the breast for the few cases we analysed. As expected, PTV coverage and dose homogeneity turned out to be more critical in the lung than in the breast cases with respect to the accuracy of the dose calculation. This was observed in the dose volume histograms obtained from the Monte Carlo simulations.

Provenance discrimination of Lower Cretaceous synrift sandstones (eastern Iberian Chain Spain) Constraints from detrital modes heavy minerals and geochemistry

Petrography, geochemical whole-rock composition, and chemical analyses of tourmaline were performed in order to determine the source areas of Lower Cretaceous Mora, El Castellar, and uppermost Camarillas Formation sandstones from the Iberian Chain, Spain. Sandstones were deposited in intraplate subbasins, which are bound by plutonic and volcanic rocks of Permian, Triassic, and Jurassic age, Paleozoic metamorphic rocks, and Triassic sedimentary rocks. Modal analyses together with petrographic and cathodoluminescence observations allowed us to define three quartz-feldspathic petrofacies and recognize diagenetic processes that modified the original framework composition. Results from average restored petrofacies are: Mora petrofacies = P/F >1 and Q(r)70 F(r)22 R(r)9; El Castellar petrofacies = P/F >1 and Q(r)57 F(r)25 R(r)18; and Camarillas petrofacies = P/F ∼ zero and Q(r)64 F(r)28 R(r)7 (P—plagioclase; F—feldspar; Q—quartz; R—rock fragments; r—restored composition). Trace-element and rare earth element abundances of whole-rock analyses discriminate well between the three petrofacies based on: (1) the Rb concentration, which is indicative of the K content and reflects the amount of K-feldspar modal abundance, and (2) the relative modal abundance of heavy minerals (tourmaline, zircon, titanite, and apatite), which is reproduced by the elements hosted in the observed heavy mineral assemblage (i.e., B and Li for tourmaline; Zr, Hf, and Ta for zircon; Ti, Ta, Nb, and their rare earth elements for titanite; and P, Y, and their rare earth elements for apatite). Tourmaline chemical composition for the three petrofacies ranges from Fe-tourmaline of granitic to Mg-tourmaline of metamorphic origin. The three defined petrofacies suggest a mixed provenance from plutonic and metamorphic source rocks. However, a progressively major influence of granitic source rocks was detected from the lowermost Mora petrofacies toward the uppermost Camarillas petrofacies. This provenance trend is consistent with the uplift and erosion of the Iberian Massif, which coincided with the development of the latest Berriasian synrift regional unconformity and affected all of the Iberian intraplate basins. The uplifting stage of Iberian Massif pluton caused a significant dilution of Paleozoic metamorphic source areas, which were dominant during the sedimentation of the lowermost Mora and El Castellar petrofacies. The association of petrographic data with whole-rock geochemical compositions and tourmaline chemical analysis has proved to be useful for determining source area characteristics, their predominance, and the evolution of source rock types during the deposition of quartz-feldspathic sandstones in intraplate basins. This approach ensures that provenance interpretation is consistent with the geological context.

Mass spectrometry-based analytical tools for the molecular protein characterization of human plasma lipoproteins

Lipoproteins are a heterogeneous population of blood plasma particles composed of apolipoproteins and lipids. Lipoproteins transport exogenous and endogenous triglycerides and cholesterol from sites of absorption and formation to sites of storage and usage. Three major classes of lipoproteins are distinguished according to their density: high-density (HDL), low-density (LDL) and very low-density lipoproteins (VLDL). While HDLs contain mainly apolipoproteins of lower molecular weight, the two other classes contain apolipoprotein B and apolipoprotein (a) together with triglycerides and cholesterol. HDL concentrations were found to be inversely related to coronary heart disease and LDL/VLDL concentrations directly related. Although many studies have been published in this area, few have concentrated on the exact protein composition of lipoprotein particles. Lipoproteins were separated by density gradient ultracentrifugation into different subclasses. Native gel electrophoresis revealed different gel migration behaviour of the particles, with less dense particles having higher apparent hydrodynamic radii than denser particles. Apolipoprotein composition profiles were measured by matrix-assisted laser desorption/ionization-mass spectrometry on a macromizer instrument, equipped with the recently introduced cryodetector technology, and revealed differences in apolipoprotein composition between HDL subclasses. By combining these profiles with protein identifications from native and denaturing polyacrylamide gels by liquid chromatography-tandem mass spectrometry, we characterized comprehensively the exact protein composition of different lipoprotein particles. We concluded that the differential display of protein weight information acquired by macromizer mass spectrometry is an excellent tool for revealing structural variations of different lipoprotein particles, and hence the foundation is laid for the screening of cardiovascular disease risk factors associated with lipoproteins.