Estimating the monthly pCO2 distribution in the North Atlantic using a self-organizing neural network

[EN] Here we present monthly, basin-wide maps of the partial pressure of carbon dioxide (pCO2) for the North Atlantic on a latitude by longitude grid for years 2004 through 2006 inclusive. The maps have been computed using a neural network technique which reconstructs the non-linear relationships between three biogeochemical parameters and marine pCO2. A self organizing map (SOM) neural network has been trained using 389 000 triplets of the SeaWiFSMODIS chlorophyll-a concentration, the NCEP/NCAR reanalysis sea surface temperature, and the FOAM mixed layer depth. The trained SOM was labelled with 137 000 underway pCO2 measurements collected in situ during 2004, 2005 and 2006 in the North Atlantic, spanning the range of 208 to 437atm. The root mean square error (RMSE) of the neural network fit to the data is 11.6?atm, which equals to just above 3 per cent of an average pCO2 value in the in situ dataset. The seasonal pCO2 cycle as well as estimates of the interannual variability in the major biogeochemical provinces are presented and discussed. High resolution combined with basin-wide coverage makes the maps a useful tool for several applications such as the monitoring of basin-wide air-sea CO2 fluxes or improvement of seasonal and interannual marine CO2 cycles in future model predictions. The method itself is a valuable alternative to traditional statistical modelling techniques used in geosciences.

Impact of increasing pCO2 on marine potential respiratory activity

[EN]Due to the increasing atmospheric CO2, several on-going research programs, including the German-led KOSMOS GC14 experiment, are evaluating the impact of acidification on marine organisms, intent to predict their future. In the KOSMOS GC14 mesocosm experiment we assessed the effect of different CO2 concentrations on metabolism in microplankton (0.7-50µm size) and in biogenic particles harvested by sediment traps.

PET of somatostatin receptor-positive tumors using 64Cu- and 68Ga-somatostatin antagonists: the chelate makes the difference

Somatostatin-based radiolabeled peptides have been successfully introduced into the clinic for targeted imaging and radionuclide therapy of somatostatin receptor (sst)-positive tumors, especially of subtype 2 (sst2). The clinically used peptides are exclusively agonists. Recently, we showed that radiolabeled antagonists may be preferable to agonists because they showed better pharmacokinetics, including higher tumor uptake. Factors determining the performance of radioantagonists have only scarcely been studied. Here, we report on the development and evaluation of four (64)Cu or (68)Ga radioantagonists for PET of sst2-positive tumors.

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