On skillful decadal predictions of the subpolar North Atlantic

The North Atlantic is a crucial region for the prediction of weather and climate of North America and Europe and is the focus of this analysis. A skillful decadal prediction of the surface temperature was shown for several Earth system models, with the North Atlantic standing out as one region with higher predictive skill. This skill assessment concentrates on the rapid increase of the annual mean sea surface temperature of the North Atlantic subpolar gyre by about 1 K in the mid‑1990s and the adjacent years. This event-oriented analysis adds creditability to the decadal predictions and reveals the potential for improvements. The ability to simulate the observed sea surface temperature in the North Atlantic is quantified by using four versions of decadal predictions, which differ in model resolution, initialization technique, and the reanalysis data used in the assimilation run. While all four versions can reproduce the mid-1990s warming of the subpolar North Atlantic, the characteristics differ with lead time and version. The higher vertical resolution in the atmosphere and the higher horizontal resolution in the ocean improve the decadal prediction for longer lead times, and the anomaly initialization outperforms the full-field initialization for short lead times. The effect from the two different ocean reanalysis products on the predictive skill is strongest in the first two prediction years; a substantial cooling instead of the warming in the central North Atlantic reduces the skill score for the North Atlantic sea surface temperature in one version, whereas a too large interannual variability, compared with observations, lowers the skill score in the other version. The cooling patches are critical since the resulting gradients in sea surface temperature and their effect on atmospheric dynamics deviate from observations, and, moreover, hinder the skillful prediction of atmospheric variables

Internal vs. external forcing in shallow marine diatreme formation: a case study from the Iblean Mountains (SE-Siciliy, Central Mediterranean)

A model of diatreme evolution in a shallow marine setting is based on a multi-disciplinary analysis of diatremes in the Iblean Mountains (Sicily). The approach includes stratigraphic, volcanological, structural, petrologic and compositional data. We invoke a complex interplay of internal (rapid ascent and pyroclastic fragmentation of a volatile (CO2)-rich nephelinitic magma at depth) and external factors. These comprise hydroclastic explosions due to near-surface interaction of the rising particle/volatile mixture with seawater and water-saturated lime mud. Other external factors contributing to diatreme formation include regional and local tectonics (graben formation in pull-apart motion) combined with lateral pipe enlargement by bedrock-spalling and radial block subsidence into the diatreme pipe. We suggest that fragmentation of volatile-rich magma due to internal eruption forcing was fundamental in the formation of the Iblean shallow marine diatremes. Internal and external factors may act to a variable degree, however, during diatreme evolution in general

Roles of AUF1 isoforms, HuR and BRF1 in ARE‐dependent mRNA turnover studied by RNA interference

HT1080 cells stably expressing green fluorescent protein (GFP) linked to a 3′ terminal AU‐rich element (ARE) proved to be a convenient system to study the dynamics of mRNA stability, as changes in mRNA levels are reflected in increased or decreased fluorescence intensity. This study examined whether mRNA stability can be regulated by small interfering RNAs (siRNAs) targeted to AU‐binding proteins (AUBPs), which in turn should reveal their intrinsic role as stabilizers or destabilizers of ARE‐mRNAs. Indeed, siRNAs targeting HuR or BRF1 decreased or increased fluorescence, respectively. This effect was abolished if cells were treated with both siRNAs, thus indicating antagonistic control of ARE‐mRNA stability. Unexpectedly, downregulation of all four AUF1 isoforms by targeting common exons did not affect fluorescence whereas selective downregulation of p40AUF1/p45AUF1 strongly increased fluorescence by stabilizing the GFP-ARE reporter mRNA. This observation was fully confirmed by the finding that only selective reduction of p40AUF1/p45AUF1 induced the production of GM‐CSF, an endogenous target of AUF1. These data suggest that the relative levels of individual isoforms, rather than the absolute amount of AUF1, determine the net mRNA stability of ARE‐containing transcripts, consistent with the differing ARE‐binding capacities of the isoform

Applied statistics in field and semi-field studies with bees

Field and semi-field studies are important tools in the ecotoxicological risk assessment of plant protection products for bees (honey bees, bumblebees and solitary bees). While these studies represent far more realistic conditions than laboratory tests, they also present a challenge for the analysis and interpretation due to the large and complex datasets. Therefore, in order to correctly answer the underlying ecotoxicological questions, it is crucial that these studies are not only thoroughly planned and conducted, it is also important that they are subjected to adequate statistical analysis. Our aim is to provide a better understanding on how to conduct and interpret statistical analyses in field and semi-field studies with bees made for regulatory purposes. An overview of how study design and statistics should be aligned with each other is given including the specific challenges of (semi-) field trials, as for instance how to address the problem of pseudoreplication if hives are regarded as experimental units. Different statistical tools are compared and their suitability for different data types and questions are discussed. Generalized Linear (Mixed) Models (GLMMs) are evaluated in more detail as they provide a flexible and robust tool for the analysis of honey bee (semi-) field data. Furthermore, some more light is shed on what p-values really tell us, how they can help to interpret data and how they should not be misinterpreted.Field and semi-field studies are important tools in the ecotoxicological risk assessment of plant protection products for bees (honey bees, bumblebees and solitary bees). While these studies represent far more realistic conditions than laboratory tests, they also present a challenge for the analysis and interpretation due to the large and complex datasets. Therefore, in order to correctly answer the underlying ecotoxicological questions, it is crucial that these studies are not only thoroughly planned and conducted, it is also important that they are subjected to adequate statistical analysis. Our aim is to provide a better understanding on how to conduct and interpret statistical analyses in field and semi-field studies with bees made for regulatory purposes. An overview of how study design and statistics should be aligned with each other is given including the specific challenges of (semi-) field trials, as for instance how to address the problem of pseudoreplication if hives are regarded as experimental units. Different statistical tools are compared and their suitability for different data types and questions are discussed. Generalized Linear (Mixed) Models (GLMMs) are evaluated in more detail as they provide a flexible and robust tool for the analysis of honey bee (semi-) field data. Furthermore, some more light is shed on what p-values really tell us, how they can help to interpret data and how they should not be misinterpreted

Protectors or Traitors: The Roles of PON2 and PON3 in Atherosclerosis and Cancer

Cancer and atherosclerosis are major causes of death in western societies. Deregulated cell death is common to both diseases, with significant contribution of inflammatory processes and oxidative stress. These two form a vicious cycle and regulate cell death pathways in either direction. This raises interest in antioxidative systems. The human enzymes paraoxonase-2 (PON2) and PON3 are intracellular enzymes with established antioxidative effects and protective functions against atherosclerosis. Underlying molecular mechanisms, however, remained elusive until recently. Novel findings revealed that both enzymes locate to mitochondrial membranes where they interact with coenzyme Q10 and diminish oxidative stress. As a result, ROS-triggered mitochondrial apoptosis and cell death are reduced. From a cardiovascular standpoint, this is beneficial given that enhanced loss of vascular cells and macrophage death forms the basis for atherosclerotic plaque development. However, the same function has now been shown to raise chemotherapeutic resistance in several cancer cells. Intriguingly, PON2 as well as PON3 are frequently found upregulated in tumor samples. Here we review studies reporting PON2/PON3 deregulations in cancer, summarize most recent findings on their anti-oxidative and antiapoptotic mechanisms, and discuss how this could be used in putative future therapies to target atherosclerosis and cancer

Glucose and Fat Tolerance Tests Induce Differential Responses in Plasma Choline Metabolites in Healthy Subjects

Plasma choline shows associations with plasma glucose and lipids. We studied changes of choline metabolites after oral glucose tolerance test (OGTT) and fat tolerance test (OFTT). Eighteen healthy subjects (mean age 54.3 years; BMI 26.8 kg/m2) underwent 2 tests. First, OFTT (80 g fat) was applied and blood was collected at baseline and 4 h after OFTT. Seven days later, 75 g glucose was applied and blood was collected at baseline and 2 h after OGTT. Plasma concentrations of choline, betaine, trimethylamine N-oxide (TMAO), dimethylglycine, S-adenosylmethionine (SAM), lipids and glucose were measured. After OFTT, plasma choline declined (10.6 to 9.2 µmol/L; p = 0.004), betaine declined (33.4 to 31.7 µmol/L; p = 0.003), TMAO slightly increased (4.1 to 5.6 µmol/L; p = 0.105), glucose declined (5.39 to 4.98 mmol/L; p < 0.001), and triglycerides increased (1.27 to 2.53 mmol/L; p < 0.001). After OGTT, plasma choline increased (10.1 to 11.1 µmol/L; p < 0.001), TMAO declined (4.0 to 3.5 µmol/L; p = 0.029), dimethylglycine declined (2.0 to 1.7 µmol/L; p = 0.005), SAM declined (103 to 96 nmol/L; p = 0.041), but betaine, glucose, and SAM were unchanged. In conclusion, OFTT lowered plasma betaine and choline and caused heterogeneous changes in plasma TMAO. OGTT reduced the flow of methyl groups and plasma TMAO