Seasonal-to-decadal predictions with the ensemble Kalman filter and the Norwegian Earth System Model: a twin experiment

Here, we firstly demonstrate the potential of an advanced flow dependent data assimilation method for performing seasonal-to-decadal prediction and secondly, reassess the use of sea surface temperature (SST) for initialisation of these forecasts. We use the Norwegian Climate Prediction Model (NorCPM), which is based on the Norwegian Earth System Model (NorESM) and uses the deterministic ensemble Kalman filter to assimilate observations. NorESM is a fully coupled system based on the Community Earth System Model version 1, which includes an ocean, an atmosphere, a sea ice and a land model. A numerically efficient coarse resolution version of NorESM is used. We employ a twin experiment methodology to provide an upper estimate of predictability in our model framework (i.e. without considering model bias) of NorCPM that assimilates synthetic monthly SST data (EnKF-SST). The accuracy of EnKF-SST is compared to an unconstrained ensemble run (FREE) and ensemble predictions made with near perfect (i.e. microscopic SST perturbation) initial conditions (PERFECT). We perform 10 cycles, each consisting of a 10-yr assimilation phase, followed by a 10-yr prediction. The results indicate that EnKF-SST improves sea level, ice concentration, 2 m atmospheric temperature, precipitation and 3-D hydrography compared to FREE. Improvements for the hydrography are largest near the surface and are retained for longer periods at depth. Benefits in salinity are retained for longer periods compared to temperature. Near-surface improvements are largest in the tropics, while improvements at intermediate depths are found in regions of large-scale currents, regions of deep convection, and at the Mediterranean Sea outflow. However, the benefits are often small compared to PERFECT, in particular, at depth suggesting that more observations should be assimilated in addition to SST. The EnKF-SST system is also tested for standard ocean circulation indices and demonstrates decadal predictability for Atlantic overturning and sub-polar gyre circulations, and heat content in the Nordic Seas. The system beats persistence forecast and shows skill for heat content in the Nordic Seas that is close to PERFECT

Efficacy of Fumaric Acid Esters in the R6/2 and YAC128 Models of Huntington's Disease

Huntington's disease (HD) is an autosomal dominantly inherited progressive neurodegenerative disease. The exact sequel of events finally resulting in neurodegeneration is only partially understood and there is no established protective treatment so far. Some lines of evidence speak for the contribution of oxidative stress to neuronal tissue damage. The fumaric acid ester dimethylfumarate (DMF) is a new disease modifying therapy currently in phase III studies for relapsing-remitting multiple sclerosis. DMF potentially exerts neuroprotective effects via induction of the transcription factor “nuclear factor E2-related factor 2” (Nrf2) and detoxification pathways. Thus, we investigated here the therapeutic efficacy of DMF in R6/2 and YAC128 HD transgenic mice which mimic many aspects of HD and are characterized by an enhanced generation of free radicals in neurons. Treatment with DMF significantly prevented weight loss in R6/2 mice between postnatal days 80–90. At the same time, DMF treatment led to an attenuated motor impairment as measured by the clasping score. Average survival in the DMF group was 100.5 days vs. 94.0 days in the placebo group. In the histological analysis on day 80, DMF treatment resulted in a significant preservation of morphologically intact neurons in the striatum as well as in the motor cortex. DMF treatment resulted in an increased Nrf2 immunoreactivity in neuronal subpopulations, but not in astrocytes. These beneficial effects were corroborated in YAC128 mice which, after one year of DMF treatment, also displayed reduced dyskinesia as well as a preservation of neurons. In conclusion, DMF may exert beneficial effects in mouse models of HD. Given its excellent side effect profile, further studies with DMF as new therapeutic approach in HD and other neurodegenerative diseases are warranted

Dimethyl fumarate blocks pro-inflammatory cytokine production via inhibition of TLR induced M1 and K63 ubiquitin chain formation

Dimethyl fumarate (DMF) possesses anti-inflammatory properties and is approved for the treatment of psoriasis and multiple sclerosis. While clinically effective, its molecular target has remained elusive - although it is known to activate anti-oxidant pathways. We find that DMF inhibits pro-inflammatory cytokine production in response to TLR agonists independently of the Nrf2-Keap1 anti-oxidant pathway. Instead we show that DMF can inhibit the E2 conjugating enzymes involved in K63 and M1 polyubiquitin chain formation both in vitro and in cells. The formation of K63 and M1 chains is required to link TLR activation to downstream signaling, and consistent with the block in K63 and/or M1 chain formation, DMF inhibits NFκB and ERK1/2 activation, resulting in a loss of pro-inflammatory cytokine production. Together these results reveal a new molecular target for DMF and show that a clinically approved drug inhibits M1 and K63 chain formation in TLR induced signaling complexes. Selective targeting of E2s may therefore be a viable strategy for autoimmunity

Safety Standards of Flood Defenses

Hazard