Biodiversity effects on nitrate concentrations in soil solution: a Bayesian model

Ecosystems are faced with high rates of species loss which has consequences for their functions and services. To assess the effects of plant species diversity on the nitrogen (N) cycle, we developed a model for monthly mean nitrate (NO3-N) concentrations in soil solution in 0-30 cm mineral soil depth using plant species and functional group richness and functional composition as drivers and assessing the effects of conversion of arable land to grassland, spatially heterogeneous soil properties, and climate. We used monthly mean NO3-N concentrations from 62 plots of a grassland plant diversity experiment from 2003 to 2006. Plant species richness (1-60) and functional group composition (1-4 functional groups: legumes, grasses, non-leguminous tall herbs, non-leguminous small herbs) were manipulated in a factorial design. Plant community composition, time since conversion from arable land to grassland, soil texture, and climate data (precipitation, soil moisture, air and soil temperature) were used to develop one general Bayesian multiple regression model for the 62 plots to allow an in-depth evaluation using the experimental design. The model simulated NO3-N concentrations with an overall Bayesian coefficient of determination of 0.48. The temporal course of NO3-N concentrations was simulated differently well for the individual plots with a maximum plot-specific Nash-Sutcliffe Efficiency of 0.57. The model shows that NO3-N concentrations decrease with species richness, but this relation reverses if more than approx. 25 % of legume species are included in the mixture. Presence of legumes increases and presence of grasses decreases NO3-N concentrations compared to mixtures containing only small and tall herbs. Altogether, our model shows that there is a strong influence of plant community composition on NO3-N concentrations.

Do different anesthesia regimes affect hippocampal apoptosis and neurologic deficits in a rodent cardiac arrest model?

Background Different anesthesia regimes are commonly used in experimental models of cardiac arrest, but the effects of various anesthetics on clinical outcome parameters are unknown. We conducted a study in which we subjected rats to cardiac arrest under medetomidine/ketamine or sevoflurane/fentanyl anesthesia. Methods Asystolic cardiac arrest for 8 minutes was induced in 73 rats with a mixture of potassium chloride and esmolol. Daily behavioral and neurological examination included the open field test (OFT), the tape removal test (TRT) and a neurodeficit score (NDS). Animals were randomized for sacrifice on day 2 or day 5 and brains were harvested for histology in the hippocampus cornus ammonis segment CA1. The inflammatory markers IL-6, TNF-α, MCP-1 and MIP-1α were assessed in cerebrospinal fluid (CSF). Proportions of survival were tested with the Fisher’s exact test, repeated measurements were assessed with the Friedman’s test; the baseline values were tested using Mann–Whitney U test and the difference of results of repeated measures were compared. Results In 31 animals that survived beyond 24 hours neither OFT, TRT nor NDS differed between the groups; histology was similar on day 2. On day 5, significantly more apoptosis in the CA1 segment of the hippocampus was found in the sevoflurane/fentanyl group. MCP-1 was higher on day 5 in the sevoflurane/fentanyl group (p = 0.04). All other cyto- and chemokines were below detection threshold. Conclusion In our cardiac arrest model neurological function was not influenced by different anesthetic regimes; in contrast, anesthesia with sevoflurane/fentanyl results in increased CSF inflammation and histologic damage at day 5 post cardiac arrest.

Gas transport in firn: multiple-tracer characterisation and model intercomparison for NEEM, Northern Greenland

Air was sampled from the porous firn layer at the NEEM site in Northern Greenland. We use an ensemble of ten reference tracers of known atmospheric history to characterise the transport properties of the site. By analysing uncertainties in both data and the reference gas atmospheric histories, we can objectively assign weights to each of the gases used for the depth-diffusivity reconstruction. We define an objective root mean square criterion that is minimised in the model tuning procedure. Each tracer constrains the firn profile differently through its unique atmospheric history and free air diffusivity, making our multiple-tracer characterisation method a clear improvement over the commonly used single-tracer tuning. Six firn air transport models are tuned to the NEEM site; all models successfully reproduce the data within a 1σ Gaussian distribution. A comparison between two replicate boreholes drilled 64 m apart shows differences in measured mixing ratio profiles that exceed the experimental error. We find evidence that diffusivity does not vanish completely in the lock-in zone, as is commonly assumed. The ice age- gas age difference (1 age) at the firn-ice transition is calculated to be 182+3−9 yr. We further present the first intercomparison study of firn air models, where we introduce diagnostic scenarios designed to probe specific aspects of the model physics. Our results show that there are major differences in the way the models handle advective transport. Furthermore, diffusive fractionation of isotopes in the firn is poorly constrained by the models, which has consequences for attempts to reconstruct the isotopic composition of trace gases back in time using firn air and ice core records.

An improved simple rat model for global cerebral ischaemia by induced cardiac arrest

OBJECTIVES Cerebral hypoxic-ischaemic injury following cardiac arrest is a devastating disease affecting thousands of patients each year. There is a complex interaction between post-resuscitation injury after whole-body ischaemia-reperfusion and cerebral damage which cannot be explored in in vitro systems only; there is a need for animal models. In this study, we describe and evaluate the feasibility and efficiency of our simple rodent cardiac arrest model. METHODS Ten wistar rats were subjected to 9 and 10 minutes of cardiac arrest. Cardiac arrest was introduced with a mixture of the short-acting beta-blocking drug esmolol and potassium chloride. RESULTS All animals could be resuscitated within 1 minute, and survived until day 5.General health score and neurobehavioural testing indicated substantial impairment after cardiac arrest, without differences between groups. Histological examination of the hippocampus CA1 segment, the most vulnerable segment of the cerebrum, demonstrated extensive damage in the cresyl violet staining, as well as in the Fluoro-Jade B staining and in the Iba-1 staining, indicating recruitment of microglia after the hypoxic-ischaemic event. Again, there were no differences between the 9- and 10-minute cardiac arrest groups. DISCUSSION We were able to establish a simple and reproducible 9- and 10-minute rodent cardiac arrest models with a well-defined no-flow-time. Extensive damage can be found in the hippocampus CA1 segment. The lack of difference between 9- and 10-minute cardiac arrest time in the neuropsychological, the open field test and the histological evaluations is mainly due to the small sample size.

Characterization of the Axial Jet Separator with a CO2/Helium Mixture: Toward GC-AMS Hyphenation

Development of interfaces for sample introduction from high pressures is important for real-time online hyphenation of chromatographic and other separation devices with mass spectrometry (MS) or accelerator mass spectrometry (AMS). Momentum separators can reduce unwanted low-density gases and introduce the analyte into the vacuum. In this work, the axial jet separator, a new momentum interface, is characterized by theory and empirical optimization. The mathematical model describes the different axial penetration of the components of a jetgas mixture and explains the empirical results for injections of CO2 in helium into MS and AMS instruments. We show that the performance of the new interface is sensitive to the nozzle size, showing good qualitative agreement with the mathematical model. Smaller nozzle sizes are more preferable due to their higher inflow capacity. The CO2 transmission efficiency of the interface into a MS instrument is ~14% (CO2/helium separation factor of 2.7). The interface receives and delivers flows of ~17.5 mL/min and ~0.9 mL/min, respectively. For the interfaced AMS instrument, the ionization and overall efficiencies are 0.7-3% and 0.1-0.4%, respectively, for CO2 amounts of 4-0.6 µg C, which is only slightly lower compared to conventional systems using intermediate trapping. The ionization efficiency depends on to the carbon mass flow in the injected pulse and is suppressed at high CO2 flows. Relative to a conventional jet separator, the transmission efficiency of the axial jet separator is lower, but its performance is less sensitive to misalignments.

Global Optimization with Sparse and Local Gaussian Process Models

We present a novel surrogate model-based global optimization framework allowing a large number of function evaluations. The method, called SpLEGO, is based on a multi-scale expected improvement (EI) framework relying on both sparse and local Gaussian process (GP) models. First, a bi-objective approach relying on a global sparse GP model is used to determine potential next sampling regions. Local GP models are then constructed within each selected region. The method subsequently employs the standard expected improvement criterion to deal with the exploration-exploitation trade-off within selected local models, leading to a decision on where to perform the next function evaluation(s). The potential of our approach is demonstrated using the so-called Sparse Pseudo-input GP as a global model. The algorithm is tested on four benchmark problems, whose number of starting points ranges from 102 to 104. Our results show that SpLEGO is effective and capable of solving problems with large number of starting points, and it even provides significant advantages when compared with state-of-the-art EI algorithms.

A randomized trial of the effects of the noble gases helium and argon on neuroprotection in a rodent cardiac arrest model.

BACKGROUND The noble gas xenon is considered as a neuroprotective agent, but availability of the gas is limited. Studies on neuroprotection with the abundant noble gases helium and argon demonstrated mixed results, and data regarding neuroprotection after cardiac arrest are scant. We tested the hypothesis that administration of 50% helium or 50% argon for 24 h after resuscitation from cardiac arrest improves clinical and histological outcome in our 8 min rat cardiac arrest model. METHODS Forty animals had cardiac arrest induced with intravenous potassium/esmolol and were randomized to post-resuscitation ventilation with either helium/oxygen, argon/oxygen or air/oxygen for 24 h. Eight additional animals without cardiac arrest served as reference, these animals were not randomized and not included into the statistical analysis. Primary outcome was assessment of neuronal damage in histology of the region I of hippocampus proper (CA1) from those animals surviving until day 5. Secondary outcome was evaluation of neurobehavior by daily testing of a Neurodeficit Score (NDS), the Tape Removal Test (TRT), a simple vertical pole test (VPT) and the Open Field Test (OFT). Because of the non-parametric distribution of the data, the histological assessments were compared with the Kruskal-Wallis test. Treatment effect in repeated measured assessments was estimated with a linear regression with clustered robust standard errors (SE), where normality is less important. RESULTS Twenty-nine out of 40 rats survived until day 5 with significant initial deficits in neurobehavioral, but rapid improvement within all groups randomized to cardiac arrest. There were no statistical significant differences between groups neither in the histological nor in neurobehavioral assessment. CONCLUSIONS The replacement of air with either helium or argon in a 50:50 air/oxygen mixture for 24 h did not improve histological or clinical outcome in rats subjected to 8 min of cardiac arrest.

On ANOVA Decompositions of Kernels and Gaussian Random Field Paths

The FANOVA (or “Sobol’-Hoeffding”) decomposition of multivariate functions has been used for high-dimensional model representation and global sensitivity analysis. When the objective function f has no simple analytic form and is costly to evaluate, computing FANOVA terms may be unaffordable due to numerical integration costs. Several approximate approaches relying on Gaussian random field (GRF) models have been proposed to alleviate these costs, where f is substituted by a (kriging) predictor or by conditional simulations. Here we focus on FANOVA decompositions of GRF sample paths, and we notably introduce an associated kernel decomposition into 4 d 4d terms called KANOVA. An interpretation in terms of tensor product projections is obtained, and it is shown that projected kernels control both the sparsity of GRF sample paths and the dependence structure between FANOVA effects. Applications on simulated data show the relevance of the approach for designing new classes of covariance kernels dedicated to high-dimensional kriging.