Identification of novel biomarkers for predicting outcome of acute and chronic kidney disease

The global burden of human renal diseases continually increased in the last decades. To lower associated mortality and morbidity rates, early diagnosis as well as improved understanding of underlying biological mechanisms are essential. Here, metabolic investigations of biofluids by means of nuclear magnetic resonance (NMR) spectroscopy in the context of nephrology are presented to facilitate earlier detection and to enable new insights into renal disease manifestation. The detection of novel low-molecular-weight factors for improved early diagnosis and patient treatment in the context of acute kidney injury (AKI) was successfully conducted in a prospective study of 85 adult patients undergoing cardiac surgery with cardiopulmonary bypass (CPB) use. One-dimensional (1D) 1H NMR spectral data sets of filtered ethylenediaminetetraacetic acid (EDTA) plasma specimens collected 24 h after surgery were subjected to Random Forests based classification with t-test based feature filtering to prognosticate AKI. An average overall prognostication accuracy of 80 ± 0.9% with a corresponding area under the receiver-operating characteristic curve of 0.87 ± 0.01 could be obtained with, on average, 24 ± 2.8 spectral features. The set of discriminative ions and molecules included Mg2+, lactate and the glucuronide conjugate of propofol, an anesthetic agent which had been administered to all patients during surgery. In AKI patients, increased levels of propofol-glucuronide seem to be a surrogate marker for reduced glomerular filtration, whereas an elevation of Mg2+ levels might be explained by its use for the treatment of cardiac arrythmias, and ischemic injury as well as systemic hypoperfusion present in this group might be linked to elevated lactate levels. Furthermore, this thesis presents a novel endogenous biomarker panel consisting of absolutely quantified EDTA plasma concentrations of Mg2+, creatinine, and lactate, which would offer a reliable and swift diagnostic tool for the early detection of AKI after cardiac surgery with CPB use only requiring easily implementable point-of-care technologies. This biomarker panel was further employed to derive a novel Acute Kidney Injury Network (AKIN) index score, which illustrated that the metabolic profile of patients diagnosed with mildest renal injury was very similar to that of patients not developing AKI. This study was further utilized to elucidate the importance of appropriate data normalization prior to statistical analysis, which proofed to be crucial for correct data interpretation. The second part of this thesis presents first statistical data analysis results of 1D 1H NMR spectra of EDTA plasma or urine specimens, respectively, from two large-scale clinical trials on chronic kidney disease (CKD). The German Chronic Kidney Disease (GCKD) study includes the currently world-wide largest cohort of patients suffering from CKD, which will be prospectively followed in the next ten years, and the Trial to Reduce Cardiovascular Events with Aranesp® Therapy (TREAT) study comprises a large, homogeneous cohort of patients suffering from CKD, type-2 diabetes mellitus, and concomitant anemia. Distinct differences in metabolic fingerprints between various leading renal diseases, such as diabetic nephropathy and glomerulonephritis, in the GCKD study, or associated with adverse patient outcome in the TREAT study could be detected by t-tests in concordance with standard clinical pathologies of CKD. Additionally, the prediction of future kidney performance, which is crucial for improved patient care, with regression models based on either NMR derived EDTA plasma metabolic fingerprints or clinical parameters both assessed two years before was conducted within the GCKD study. Here, multiple regression models based on NMR fingerprints did not outperform simple regression models based on respective baseline clinical parameters. This probably reflects the fact that the renal function of most investigated CKD patients was fairly stable within these two years

Hubble Space Telescope Imaging of the Outburst Site of M31 RV

M31 RV is a luminous red variable star that appeared for several months in the bulge of M31 during 1988. Unlike classical novae, M31 RV was cool throughout its outburst. Interest in this object has revived recently because of its strong resemblance to V838 Mon, a luminous Galactic variable star that appeared in 2002 and is illuminating a spectacular light echo, and has evolved to ever-cooler surface temperatures. V4332 Sgr is a third object which was also a red supergiant throughout its eruption. We have examined archival Hubble Space Telescope (HST) images of the site of M31 RV, obtained fortuitously in 1999 with the WFPC2 camera in parallel mode during spectroscopic observations of the nucleus of M31. We located the site of M31 RV in the HST frames precisely through astrometric registration with ground-based CCD images, including several taken during the outburst. No light echo is seen at the M31 RV site, implying that M31 RV is not surrounded by circumstellar (or interstellar) dust similar to that around V838 Mon, or that its extent is less than ~1.7 pc. The stellar population at the outburst site consists purely of old red giants; there is no young population, such as seen around V838 Mon. There are no stars of unusual color at the site, suggesting that M31 RV had faded below HST detectability in the 11 years since outburst, that it is an unresolved companion of one of the red giants in the field, or that it is one of the red giants. We suggest future observations that may help decide among these possibilities.Comment: 16 pages, 3 figures, 2 tables; AJ accepte

Chemical Inhomogeneities in the Milky Way Stellar Halo

We have compiled a sample of 699 stars from the recent literature with detailed chemical abundance information (spanning -4.2 < [Fe/H] < +0.3), and we compute their space velocities and Galactic orbital parameters. We identify members of the inner and outer stellar halo populations in our sample based only on their kinematic properties and then compare the abundance ratios of these populations as a function of [Fe/H]. In the metallicity range where the two populations overlap (-2.5 < [Fe/H] < -1.5), the mean [Mg/Fe] of the outer halo is lower than the inner halo by ~0.1 dex. For [Ni/Fe] and [Ba/Fe], the star-to-star abundance scatter of the inner halo is consistently smaller than in the outer halo. The [Na/Fe], [Y/Fe], [Ca/Fe], and [Ti/Fe] ratios of both populations show similar means and levels of scatter. Our inner halo population is chemically homogeneous, suggesting that a significant fraction of the Milky Way stellar halo originated from a well-mixed ISM. In contrast, our outer halo population is chemically diverse, suggesting that another significant fraction of the Milky Way stellar halo formed in remote regions where chemical enrichment was dominated by local supernova events. We find no abundance trends with maximum radial distance from the Galactic center or maximum vertical distance from the Galactic disk. We also find no common kinematic signature for groups of metal-poor stars with peculiar abundance patters, such as the alpha-poor stars or stars showing unique neutron-capture enrichment patterns. Several stars and dSph systems with unique abundance patterns spend the majority of their time in the distant regions of the Milky Way stellar halo, suggesting that the true outer halo of the Galaxy may have little resemblance to the local stellar halo.Comment: Accepted for publication in AJ. Full tables available upon reques

URANOS v1.0 – the Ultra Rapid Adaptable Neutron-Only Simulation for Environmental Research

The understanding of neutron transport by Monte Carlo simulations led to major advancements towards precise interpretation of measurements. URANOS (Ultra Rapid Neutron-Only Simulation) is a free software package which has been developed in the last few years in cooperation with particle physics and environmental sciences, specifically for the purposes of cosmic-ray neutron sensing (CRNS). Its versatile user interface and input/output scheme tailored for CRNS applications offers hydrologists straightforward access to model individual scenarios and to directly perform advanced neutron transport calculations. The geometry can be modeled layer-wise, whereas in each layer a voxel geometry is extruded using a two-dimensional map from pixel images representing predefined materials and allowing for the construction of objects on the basis of pixel graphics without a three-dimensional editor. It furthermore features predefined cosmic-ray neutron spectra and detector configurations and also allows for a replication of important site characteristics of study areas – from a small pond to the catchment scale. The simulation thereby gives precise answers to questions like from which location do neutrons originate? How do they propagate to the sensor? What is the neutron's response to certain environmental changes? In recent years, URANOS has been successfully employed by a number of studies, for example, to calculate the cosmic-ray neutron footprint, signals in complex geometries like mobile applications on roads, urban environments and snow patterns.</p