Wachstumsminderung

X-ray absorption near edge structure (XANES) analysis in combination with synchrotron radiation induced total reflection X-ray fluorescence (SR-TXRF) acquisition was used to determine the oxidation state of Fe in human cancer cells and simultaneously their elemental composition by applying a simple sample preparation procedure consisting of pipetting the cell suspension onto the quartz reflectors. XANES spectra of several inorganic and organic iron compounds were recorded and compared to that of different cell lines. The XANES spectra of cells, independently from the phase of cell growth and cell type were very similar to that of ferritin, the main Fe store within the cell. The spectra obtained after CoCl2 or NiCl2 treatment, which could mimic a hypoxic state of cells, did not differ noticeably from that of the ferritin standard. After 5-fluorouracil administration, which could also induce an oxidative-stress in cells, the absorption edge position was shifted toward higher energies representing a higher oxidation state of Fe. Intense treatment with antimycin A, which inhibits electron transfer in the respiratory chain, resulted in minor changes in the spectrum, resembling rather the N-donor Fe-,′-dipyridyl complex at the oxidation energy of Fe(III), than ferritin. The incorporation of Co and Ni in the cells was followed by SR-TXRF measurements

On the approximation of local and linear radiative damping in the middle atmosphere

The validity of approximating radiative heating rates in the middle atmosphere by a local linear relaxation to a reference temperature state (i.e., ‘‘Newtonian cooling’’) is investigated. Using radiative heating rate and temperature output from a chemistry–climate model with realistic spatiotemporal variability and realistic chemical and radiative parameterizations, it is found that a linear regressionmodel can capture more than 80% of the variance in longwave heating rates throughout most of the stratosphere and mesosphere, provided that the damping rate is allowed to vary with height, latitude, and season. The linear model describes departures from the climatological mean, not from radiative equilibrium. Photochemical damping rates in the upper stratosphere are similarly diagnosed. Threeimportant exceptions, however, are found.The approximation of linearity breaks down near the edges of the polar vortices in both hemispheres. This nonlinearity can be well captured by including a quadratic term. The use of a scale-independentdamping rate is not well justified in the lower tropical stratosphere because of the presence of a broad spectrum of vertical scales. The local assumption fails entirely during the breakup of the Antarctic vortex, where large fluctuations in temperature near the top of the vortex influence longwave heating rates within the quiescent region below. These results are relevant for mechanistic modeling studies of the middle atmosphere, particularly those investigating the final Antarctic warming

Predicting climate change using response theory: global averages and spatial patterns

The provision of accurate methods for predicting the climate response to anthropogenic and natural forcings is a key contemporary scientific challenge. Using a simplified and efficient open-source general circulation model of the atmosphere featuring O(105105) degrees of freedom, we show how it is possible to approach such a problem using nonequilibrium statistical mechanics. Response theory allows one to practically compute the time-dependent measure supported on the pullback attractor of the climate system, whose dynamics is non-autonomous as a result of time-dependent forcings. We propose a simple yet efficient method for predicting—at any lead time and in an ensemble sense—the change in climate properties resulting from increase in the concentration of CO22 using test perturbation model runs. We assess strengths and limitations of the response theory in predicting the changes in the globally averaged values of surface temperature and of the yearly total precipitation, as well as in their spatial patterns. The quality of the predictions obtained for the surface temperature fields is rather good, while in the case of precipitation a good skill is observed only for the global average. We also show how it is possible to define accurately concepts like the inertia of the climate system or to predict when climate change is detectable given a scenario of forcing. Our analysis can be extended for dealing with more complex portfolios of forcings and can be adapted to treat, in principle, any climate observable. Our conclusion is that climate change is indeed a problem that can be effectively seen through a statistical mechanical lens, and that there is great potential for optimizing the current coordinated modelling exercises run for the preparation of the subsequent reports of the Intergovernmental Panel for Climate Change