URAT: astrometric requirements and design history

The U.S. Naval Observatory Robotic Astrometric Telescope (URAT) project aims at a highly accurate (5 mas), ground-based, all-sky survey. Requirements are presented for the optics and telescope for this 0.85 m aperture, 4.5 degree diameter field-of-view, specialized instrument, which are close to the capability of the industry. The history of the design process is presented as well as astrometric performance evaluations of the toleranced, optical design, with expected wavefront errors included.Comment: 12 pages, 7 figures, SPIE 2006 Orlando conf. proc. Vol. 626

Neurofascin induces neurites by heterophilic interactions with axonal NrCAM while NrCAM requires F11 on the axonal surface to extend neurites

Neurofascin and NrCAM are two axon-associated transmembrane glycoproteins belonging to the L1 subgroup of the Ig superfamily. In this study, we have analyzed the interaction of both proteins using neurite outgrowth and binding assays. A neurofascin-Fc chimera was found to stimulate the outgrowth of tectal cells when immobilized on an inert surface but not as a soluble form using polylysine as substrate. Antibody blocking experiments demonstrate that neurite extension on immobilized neurofascin is mediated by NrCAM on the axonal surface. Under the reverse experimental conditions where NrCAM induces neurite extension, F11, and not neurofascin, serves as axonal receptor. Binding studies using transfected COS7 cells and immunoprecipitations reveal a direct interaction between neurofascin and NrCAM. This binding activity was mapped to the Ig domains within neurofascin. The neurofascin-NrCAM binding can be modulated by alternative splicing of specific stretches within neurofascin. These studies indicate that heterophilic interactions between Ig-like proteins implicated in axonal extension underlie a regulation by the neuron

Penetrating abdominal injuries: management controversies

Penetrating abdominal injuries have been traditionally managed by routine laparotomy. New understanding of trajectories, potential for organ injury, and correlation with advanced radiographic imaging has allowed a shift towards non-operative management of appropriate cases. Although a selective approach has been established for stab wounds, the management of abdominal gunshot wounds remains a matter of controversy. In this chapter we describe the rationale and methodology of selecting patients for non-operative management. We also discuss additional controversial issues, as related to antibiotic prophylaxis, management of asymptomatic thoracoabdominal injuries, and the use of colostomy vs. primary repair for colon injuries

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

Semiparametric sieve-type generalized least squares inference

This article considers the problem of statistical inference in linear regression models with dependent errors. A sieve-type generalized least squares (GLS) procedure is proposed based on an autoregressive approximation to the generating mechanism of the errors. The asymptotic properties of the sieve-type GLS estimator are established under general conditions, including mixingale-type conditions as well as conditions which allow for long-range dependence in the stochastic regressors and/or the errors. A Monte Carlo study examines the finite-sample properties of the method for testing regression hypotheses

Analysis of frequency and intensity of European winter storm events from a multi-model perspective, at synoptic and regional scales

This study focuses on the analysis of winter (October-November-December-January-February-March; ONDJFM) storm events and their changes due to increased anthropogenic greenhouse gas concentrations over Europe. In order to assess uncertainties that are due to model formulation, 4 regional climate models (RCMs) with 5 high resolution experiments, and 4 global general circulation models (GCMs) are considered. Firstly, cyclone systems as synoptic scale processes in winter are investigated, as they are a principal cause of the occurrence of extreme, damage-causing wind speeds. This is achieved by use of an objective cyclone identification and tracking algorithm applied to GCMs. Secondly, changes in extreme near-surface wind speeds are analysed. Based on percentile thresholds, the studied extreme wind speed indices allow a consistent analysis over Europe that takes systematic deviations of the models into account. Relative changes in both intensity and frequency of extreme winds and their related uncertainties are assessed and related to changing patterns of extreme cyclones. A common feature of all investigated GCMs is a reduced track density over central Europe under climate change conditions, if all systems are considered. If only extreme (i.e. the strongest 5%) cyclones are taken into account, an increasing cyclone activity for western parts of central Europe is apparent; however, the climate change signal reveals a reduced spatial coherency when compared to all systems, which exposes partially contrary results. With respect to extreme wind speeds, significant positive changes in intensity and frequency are obtained over at least 3 and 20% of the European domain under study (35–72°N and 15°W–43°E), respectively. Location and extension of the affected areas (up to 60 and 50% of the domain for intensity and frequency, respectively), as well as levels of changes (up to +15 and +200% for intensity and frequency, respectively) are shown to be highly dependent on the driving GCM, whereas differences between RCMs when driven by the same GCM are relatively small