Long-term results of cyclosporine-steroid therapy in 131 non-matched cadaveric renal transplants.

One-hundred-and-twenty-eight recipients of 131 consecutive, non-matched cadaver renal allografts were treated with cyclosporine and steroids. They have been followed for 4 to 6 yr. Cumulative patient survival at 1-yr was 92.2% and at 6yr it is 77.8%. Cumulative graft survival at 1-yr was 79.4% and at 6 yr it is 50.0%. After the high-risk 1st yr, the rate of graft loss was even and similar to that reported after the 1st yr for grafts treated with azathioprine and steroids. This indicates that cyclosporine nephrotoxicity has not had an obvious adverse effect on the survival of chronically functioning grafts. The results were better with primary grafting versus retransplantation, but were not significantly influenced by age, diabetes mellitus, or a delayed switch in patients from cyclosporine to azathioprine. We have concluded that cyclosporine-steroid therapy is safe and effective for long-term use after cadaveric renal transplantation

SPIN-MIMS simplifying the SPIN-MAS instrumentation for online measurement of 15N-abundances of ammonium, nitrite and nitrate in aqueous solutions

Common methods for measuring selectively the 15N abundances in individual N-species such as NH4+, NO2- and NO3- in samples with multiple N-species are laborious and time consuming. The SPIN-MAS technique (Stange et al. 2007) offers an automated, rapid and selective determination of 15N abundances in NH4+, NO2- and NO3- in aqueous samples. During a SPIN-MAS measurement one of three different reaction solutions is mixed with the aqueous sample in a Sample Preparation unit for Inorganic N-species (SPIN). The reaction solution is chosen in dependence on the N-species of interest. The gaseous reaction products (N2 or NO) are then conducted to a quadrupole mass spectrometer (MAS) in a helium stream. This measurement technique is not commonly used due to its complex instrumentation. The instrumentation can be significantly simplified by the use of a membrane inlet mass spectrometer (MIMS). The presented SPIN-MIMS approach relies on the use of a reaction capillary in which the sample containing the N-species of interest is mixed with the corresponding reaction solution. The mixture of reaction solution and sample is pumped from the reaction capillary directly to the membrane inlet of the mass spectrometer. The reaction products (N2 or NO) formed during the reaction of NH4+, NO2- and NO3- with the reaction solutions are passed through the gas-permeable membrane of the inlet directly into the ion source of the mass spectrometer. 15N standards with different at% 15N (NH4+, NO2- and NO3- respectively in dist. Water) were used to assess the performance of the system. Overall, SPIN-MIMS measurements showed a good agreement between measured and expected 15N abundances (range 0.36 – 10 at% 15N deviations: <0.5 at% 15N for NH4+-, <0.23 for NO2-- and <0.15 at% 15N for NO3-- standards)

Validating soil denitrification models based on laboratory N2 and N2O fluxes and underlying processes derived by stable isotope approaches: concept, methods and regulation of measured fluxes

Robust denitrification data suitable to validate soil N2 fluxes in denitrification models are scarce due to methodical limitations and the extreme spatio-temporal heterogeneity of denitrification in soils. Numerical models have become essential tools to predict denitrification at different scales. Model performance could either be tested for total gaseous flux (NO + N2O + N2), individual denitrification products (e.g. N2O and/or NO) or for the effect of denitrification factors (e.g. C-availability, respiration, diffusivity, anaerobic volume, etc.). While there are numerous examples for validating N2O fluxes, there are neither robust field data of N2 fluxes nor sufficiently resolved measurements of control factors used as state variables in the models. Here we present the concept, methods and first results of collecting model validation data. This is part of the coordinated research unit “Denitrification in Agricultural Soils: Integrated Control and Modelling at Various Scales” (DASIM). Novel approaches are used including analysis of stable isotopes, microbial communities, pore structure and organic matter fractions to provide denitrification data sets comprising as much detail on activity and regulation as possible. This will be the basis to validate existing and calibrate new denitrification models that are applied and/or developed by DASIM subprojects. To allow model testing in a wide range of conditions, denitrification control factors are varied in the initial settings (pore volume, plant residues, mineral N, pH) but also over time, where moisture, temperature, and mineral N are manipulated according to typical time patterns in the field. This is realized by including precipitation events, fertilization (via irrigation), drainage (via water potential) and temperature in the course of incubations. Moreover, oxygen concentration is varied to simulate anaerobic events. The 15N gas flux method is employed to quantify N2 and N2O emissions from various pools and processes

High frequency oscillatory ventilation compared with conventional mechanical ventilation in adult respiratory distress syndrome: a randomized controlled trial [ISRCTN24242669]

INTRODUCTION: To compare the safety and efficacy of high frequency oscillatory ventilation (HFOV) with conventional mechanical ventilation (CV) for early intervention in adult respiratory distress syndrome (ARDS), a multi-centre randomized trial in four intensive care units was conducted. METHODS: Patients with ARDS were randomized to receive either HFOV or CV. In both treatment arms a priority was given to maintain lung volume while minimizing peak pressures. CV ventilation strategy was aimed at reducing tidal volumes. In the HFOV group, an open lung strategy was used. Respiratory and circulatory parameters were recorded and clinical outcome was determined at 30 days of follow up. RESULTS: The study was prematurely stopped. Thirty-seven patients received HFOV and 24 patients CV (average APACHE II score 21 and 20, oxygenation index 25 and 18 and duration of mechanical ventilation prior to randomization 2.1 and 1.5 days, respectively). There were no statistically significant differences in survival without supplemental oxygen or on ventilator, mortality, therapy failure, or crossover. Adjustment by a priori defined baseline characteristics showed an odds ratio of 0.80 (95% CI 0.22–2.97) for survival without oxygen or on ventilator, and an odds ratio for mortality of 1.15 (95% CI 0.43–3.10) for HFOV compared with CV. The response of the oxygenation index (OI) to treatment did not differentiate between survival and death. In the HFOV group the OI response was significantly higher than in the CV group between the first and the second day. A post hoc analysis suggested that there was a relatively better treatment effect of HFOV compared with CV in patients with a higher baseline OI. CONCLUSION: No significant differences were observed, but this trial only had power to detect major differences in survival without oxygen or on ventilator. In patients with ARDS and higher baseline OI, however, there might be a treatment benefit of HFOV over CV. More research is needed to establish the efficacy of HFOV in the treatment of ARDS. We suggest that future studies are designed to allow for informative analysis in patients with higher OI

Spin correlations and Dzyaloshinskii-Moriya interaction in Cs2_2CuCl4_4

We report on electron spin resonance (ESR) studies of the spin relaxation in Cs$_2$CuCl$_4$. The main source of the ESR linewidth at temperatures $T \leq 150$ K is attributed to the uniform Dzyaloshinskii-Moriya interaction. The vector components of the Dzyaloshinskii-Moriya interaction are determined from the angular dependence of the ESR spectra using a high-temperature approximation. Both the angular and temperature dependence of the ESR linewidth have been analyzed using a self-consistent quantum-mechanical approach. In addition analytical expressions based on a quasi-classical picture for spin fluctuations are derived, which show good agreement with the quantum-approach for temperatures $T \geq 2J/k_{\rm B} \approx 15$ K. A small modulation of the ESR linewidth observed in the $ac$-plane is attributed to the anisotropic Zeeman interaction, which reflects the two magnetically nonequivalent Cu positions

A 15-year-old girl with a large pericardial effusion

Pericarditis is a rare manifestation of tuberculosis and can be fatal. We describe a 15-year-old girl admitted for a large pericardial effusion. Subxiphoid pericardial biopsy was performed. Biopsy samples were positive for M. tuberculosis DNA by PCR, which confirmed the diagnosis of tuberculous pericarditis

Indirect Nitrous Oxide Emission Factors for Agricultural Field Drains and Headwater Streams

Agriculture is a major source of nitrous oxide (N2O) emissions, a potent greenhouse gas. While direct N2O emissions from soils have been widely investigated, indirect N2O emissions from nitrogen (N) enriched surface water and groundwater bodies are poorly understood. In this contribution, indirect N2O emissions from subsurface agricultural field drains and headwater streams were monitored over a two-year period (2013–2015) in an intensive arable catchment in eastern England. Indirect N2O emission factors for groundwater (EF5g) and surface runoff (EF5r) were calculated for both field drain and streamwater samples, respectively, using two approaches: the N2O–N/NO3–N ratio and the IPCC (2006) methodology. Mean EF5g values derived from the N2O–N/NO3–N ratio were 0.0012 for field drains and 0.0003 for streamwater. Using the IPCC (2006) methodology, the mean EF5g values were 0.0011 for field drains and 0.0001 for streamwater. Thus, EF values derived from both methods were below the current IPCC (2006) default value of 0.0025 and a downward revision to 0.0012 for EF5g and 0.0002 for EF5r is recommended. Such revision would halve current estimates of N2O emissions associated with nitrogen leaching and runoff from agriculture for both the UK and globally

Validating soil denitrification models based on laboratory N2 and N2O fluxes and underlying processes: evaluation of DailyDayCent and COUP models

Denitrification is an anaerobic key process by microbes where the NO3- is step-by-step reduced and emitted as NO, N2O and finally N2 gas from the soil. Accurate knowledge on denitrification dynamics is important because the N2O is further reduced to N2 and constitutes the main emission source of this greenhouse gas from agricultural soils. Hence, our understanding and ability to quantify soil denitrification is crucial for mitigating nitrogen fertilizer loss as well as for reducing N2O emissions. Models can be an important tool to predict mitigation effects and help to develop climate smart mitigation strategies. Ideally, commonly used biogeochemical models could provide adequate predictions of denitrification processes of agricultural soils but often simplified process descriptions and inadequate model parameters prevent models from simulating adequate fluxes of N2 and N2O on field scale. Model development and parametrization often suffers from limited availability of empirical data describing denitrification processes in agricultural soils. While in many studies N2O emissions are used to develop and train models, detailed measurements on NO, N2O, N2 fluxes and concentrations and related soil conditions are necessary to develop and test adequate model algorithms. To address this issue the coordinated research unit „Denitrification in Agricultural Soils: Integrated Control and Modelling at Various Scales (DASIM)” was initiated to more closely investigate N-fluxes caused by denitrification in response to environmental effects, soil properties and microbial communities. Here, we present how we will use these data to evaluate common biogeochemical process models (DailyDayCent, Coup) with respect to modeled NO, N2O and N2 fluxes from denitrification. The models are used with different settings. The first approximation is the basic “factory” setting of the models. The next step would show the precision in the results of the modeling after adjusting the appropriate parameters from the result of the measurement values and the “factory” results. The better adjustment and the well-controlled input and output measured parameters could provide a better understanding of the probable scantiness of the tested models which will be a basis for future model improvement