Regulation of System x\u3csub\u3ec\u3c/sub\u3e\u3csup\u3e-\u3c/sup\u3e by Pharmacological Manipulation of Cellular Thiols

The cystine/glutamate exchanger (system xc-) mediates the transport of cystine into the cell in exchange for glutamate. By releasing glutamate, system xc- can potentially cause excitotoxicity. However, through providing cystine to the cell, it regulates the levels of cellular glutathione (GSH), the main endogenous intracellular antioxidant, and may protect cells against oxidative stress. We tested two different compounds that deplete primary cortical cultures containing both neurons and astrocytes of intracellular GSH, L-buthionine-sulfoximine (L-BSO), and diethyl maleate (DEM). Both compounds caused significant concentration and time dependent decreases in intracellular GSH levels. However; DEM caused an increase in radiolabeled cystine uptake through system xc- , while unexpectedly BSO caused a decrease in uptake. The compounds caused similar low levels of neurotoxicity, while only BSO caused an increase in oxidative stress. The mechanism of GSH depletion by these two compounds is different, DEM directly conjugates to GSH, while BSO inhibits γ-glutamylcysteine synthetase, a key enzyme in GSH synthesis. As would be expected from these mechanisms of action, DEM caused a decrease in intracellular cysteine, while BSO increased cysteine levels. The results suggest that negative feedback by intracellular cysteine is an important regulator of system xc- in this culture system

Ejection and impact angles of saltating particles measured with a high-speed camera

3D and 2D trajectory data of sand grains saltating over a bed are presented from highspeed camera measurements. They were obtained at Zingst peninsula and in laboratory using a wind tunnel. Trajectories, calculated with a Runge-Kutta procedure, using values of the mean wind profile and the air flow were fitted to the measured ones. The trajectory with the lowest RMSE against the measured one was used to estimate the grain diameter of the saltating grain. Also ejection and impact angle, ejection and impact speed of the grain were determined. The results confirm earlier findings that ejection angles decreases with increasing grain diameter. Ejection angles between 57° and 27° for fine (63-200 μm) and middle (200-630 μm) ejecta and between 38° and 20° for coarse grains (630-2000 μm) were found. The impact angle β increases with increasing grain diameter. Impact angles between 8° and 15° for fine impactors and between 12° and 36° for middle and coarse grains were found. Additionally the ratio between the mean ejection angle α and mean impact angle β, which decrease with increasing grain diameter (Rice et al., 1995), could be confirmed. The ration between the ejection speed ue and impact speed ui was found nearly the same for all determined grain sizes, but the grains ejected from the bed had an average speed of one order of magnitude less than the impact speed

Do we (need to) care about canopy radiation schemes in DGVMs? Caveats and potential impacts

Dynamic global vegetation models (DGVMs) are an essential part of current state-of-the-art Earth system models. In recent years, the complexity of DGVMs has increased by incorporating new important processes like, e.g., nutrient cycling and land cover dynamics, while biogeophysical processes like surface radiation have not been developed much further. Canopy radiation models are however very important for the estimation of absorption and reflected fluxes and are essential for a proper estimation of surface carbon, energy and water fluxes. The present study provides an overview of current implementations of canopy radiation schemes in a couple of state-of-the-art DGVMs and assesses their accuracy in simulating canopy absorption and reflection for a variety of different surface conditions. Systematic deviations in surface albedo and fractions of absorbed photosynthetic active radiation (faPAR) are identified and potential impacts are assessed. The results show clear deviations for both, absorbed and reflected, surface solar radiation fluxes. FaPAR is typically underestimated, which results in an underestimation of gross primary productivity (GPP) for the investigated cases. The deviation can be as large as 25% in extreme cases. Deviations in surface albedo range between −0.15 ≤ Δα ≤ 0.36, with a slight positive bias on the order of Δα ≈ 0.04. Potential radiative forcing caused by albedo deviations is estimated at −1.25 ≤ RF ≤ −0.8 (W m−2), caused by neglect of the diurnal cycle of surface albedo. The present study is the first one that provides an assessment of canopy RT schemes in different currently used DGVMs together with an assessment of the potential impact of the identified deviations. The paper illustrates that there is a general need to improve the canopy radiation schemes in DGVMs and provides different perspectives for their improvement

Climate variability-induced uncertainty in mid-Holocene atmosphere-ocean-vegetation feedbacks

Previous modelling studies have shown that the response of the ocean and the vegetation to mid-Holocene insolation feeds back on the climate. There is less consensus, however, on the relative magnitude of the two feedbacks and the strength of the synergy between them. This discrepancy may arise partly from the statistical uncertainty caused by internal climate variability as the common analysis period is only about a century. Therefore, we have performed an ensemble of centennial-scale simulations using the general circulation model ECHAM5/JSBACH-MPIOM. The direct atmospheric response and the weak atmosphere-vegetation feedback are statistically robust. The synergy is always weak and it changes sign between the ensemble members. The simulations, including a dynamic ocean, show a large variability at sea-ice margins. This variability leads to a sampling error which affects the magnitude of the diagnosed feedbacks. Citation: Otto, J., T. Raddatz, and M. Claussen (2009), Climate variability-induced uncertainty in mid-Holocene atmosphere-ocean-vegetation feedbacks, Geophys. Res. Lett., 36, L23710, doi:10.1029/2009GL041457

Giving to Get Well: Patients’ Willingness to Manage and Share Health Information on AI-Driven Platforms

The digitalization of healthcare makes for the widespread availability of patient-provided data. Artificial Intelligence (AI) relies on this data. In this information-intensive environment, it is imperative to understand the contributing factors of an individual’s willingness to manage and share personal health information (PHI). Drawing from the health belief model, we identify the factors that motivate individuals to manage and share their PHI in an AI-driven health platform to obtain its intended benefits. We recognize security risks and present the use of a blockchain database as a representative means of securely managing and controlling an individual’s PHI. Data collected from a nationally representative sample of allergy sufferers indicate that the health belief model strongly predicts willingness to share PHI on a personalized AI-supported platform. Our study makes significant contributions by investigating the factors that motivate patients to use an AI-driven health platform to manage their health

Past land use decisions have increased mitigation potential of reforestation

Anthropogenic land cover change (ALCC) influences global mean temperatures via counteracting effects: CO2 emissions contribute to global warming, while biogeophysical effects, in particular the increase in surface albedo, often impose a cooling influence. Previous studies of idealized, large-scale deforestation found that albedo cooling dominates over CO 2 warming in boreal regions, indicating that boreal reforestation is not an effective mitigation tool. Here we show the importance of past land use decisions in influencing the mitigation potential of reforestation on these lands. In our simulations, CO2 warming dominates over albedo cooling because past land use decisions resulted in the use of the most productive land with larger carbon stocks and less snow than on average. As a result past land use decisions extended CO2 dominance to most agriculturally important regions in the world, suggesting that in most places reversion of past land cover change could contribute to climate change mitigation. While the relative magnitude of CO2 and albedo effects remains uncertain, the historical land use pattern is found to be biased towards stronger CO2 and weaker albedo effects as compared to idealized large-scale deforestation. Copyright 2011 by the American Geophysical Union

Biogeophysical versus biogeochemical climate response to historical anthropogenic land cover change

Anthropogenic land cover change (ALCC) is one of the few climate forcings with still unknown sign of their climate response. Major uncertainty results from the often counteracting temperature responses to biogeochemical as compared to biogeophysical effects. Here, we separate the strength of these two effects for ALCC during the last millennium. We add unprecedented detail by (i) using a coupled atmosphere/ocean general circulation model (GCM), and (ii) applying a high-detail reconstruction of historical ALCC. We find that biogeophysical effects have a slight cooling influence on global mean temperature (-0.03 K in the 20th century), while biogeochemical effects lead to strong warming (0.16-0.18 K). During the industrial era, both effects cause significant changes in certain regions; only few regions, however, experience biogeophysical cooling strong enough to dominate the overall temperature response. This study therefore suggests that the climate response to historical ALCC, both globally and in most regions, is dominated by the rise in CO2 caused by ALCC emissions

Contribution of anthropogenic land cover change emissions to preindustrial atmospheric CO2

Based on a recent reconstruction of anthropogenic land cover change (ALCC), we derive the associated CO2 emissions since 800 AD by two independent methods: a bookkeeping approach and a process model. The results are compared with the pre-industrial development of atmospheric CO2 known from antarctic ice cores. Our results show that pre-industrial CO2 emissions from ALCC have been relevant for the pre-industrial carbon cycle, although before 1750 AD their trace in atmospheric CO2 is obscured by other processes of similar magnitude. After 1750 AD, the situation is different: the steep increase in atmospheric CO2 until 1850 AD-this is before fossil fuel emissions rose to significant values-is to a substantial part explained by growing emissions from ALCC. © 2010 The Authors Tellus B © 2010 International Meteorological Institute in Stockholm

Radiative forcing from anthropogenic land cover change since AD 800

We calculate the radiative forcing (RF) from surface albedo changes over the last millennium applying a recently published, population-based reconstruction of anthropogenic land cover change (ALCC). This study thus allows for the first time to assess anthropogenic effects on climate during the pre-industrial era at high spatial and temporal detail. We find that the RF is small throughout the pre-industrial period on the global scale (negative with a magnitude less than 0.05 W/m2) and not strong enough to explain the cooling reconstructed from climate proxies between A.D. 1000 and 1900. For the regional scale, however, our results suggest an early anthropogenic impact on climate: Already in A.D. 800, the surface energy balance was altered by ALCC at a strength comparable to present-day greenhouse gas forcing, e.g., −2.0 W/m2 are derived for parts of India for that time. Several other regions exhibit a distinct variability of RF as a result of major epidemics and warfare, with RF changes in the order of 0.1 W/m2 within just one century

Separation of atmosphere-ocean-vegetation feedbacks and synergies for mid-Holocene climate

We determine both the impact of atmosphere‐ocean and atmosphere‐vegetation feedback, and their synergy on northern latitude climate in response to the orbitally‐induced changes in mid‐Holocene insolation. For this purpose, we present results of eight simulations using the general circulation model ECHAM5‐MPIOM including the land surface scheme JSBACH with a dynamic vegetation module. The experimental set‐up allows us to apply a factor‐separation technique to isolate the contribution of dynamic Earth system components (atmosphere, atmosphere‐ocean, atmosphere‐vegetation, atmosphere‐ocean‐vegetation) to the total climate change signal. Moreover, in order to keep the definition of seasons consistent with insolation forcing, we define the seasons on an astronomical basis. Our results reveal that north of 40°N atmosphere‐vegetation feedback (maximum in spring of 0.08°C) and synergistic effects (maximum in winter of 0.25°C) are weaker than in previous studies. The most important modification of the orbital forcing is related to the atmosphere‐ocean component (maximum in autumn of 0.78°C)