Search

Polymorphisms of N-acetyltransferase 2 (NAT2) acetylation may influence drug toxicities and efficacy and are associated with a differential susceptibility to select cancers. Acetylation phenotype may have clinical implications. The purposes [...]

The lockdown of large parts of Chinese economy beginning in late January 2020 lead to significant regional changes of aerosol loads, which suggests a reduction of backscatter and consequently a regional warming in the following months. Using local data and a numerical experiment with a limited area model, we have examined how strong this response may have been. The observed (local and reanalysis) observations point to a warming of less than 1.0 K, the simulations to a warming of the order of 0.5 K. These numbers are uncertain, because of large-scale natural variability and an ad-hoc choice of aerosol optical depth anomaly in the simulation. Thus, the result was, in short, that there was actually a weak warming of a few tenth of degrees, while noteworthy changes in circulation or in precipitation were not detected. More specifically, we found that at selected central China stations temperatures were found to be higher than in previous two years. This warming goes with a marked diurnal signal, with a maximum warming in the early afternoon (06 UTC), weakest at night (18 UTC). This may be related to a general warming of large swaths of Asia (including Siberia, which is not related to local aerosol forcing). Indeed, also the stations outside the immediate strong lockdown region are showing warming, albeit a weaker one. Thus, the difference 2020 minus 2019/2018 may overestimate the effect. The ad-hoc series of numerical experiments indicates that the simulated changes are robust and suffer little from internal dynamical variability. In particular, the overall reduction of the aerosol optical depth does not lead to phases of larger intermittent divergence among the model simulations, irrespective of the aerosol load. Instead, the simulations with reduced anthropogenic aerosol load show more a mere locally increased temperature. This may indicate that the aerosol effect is mostly thermodynamic in all local air columns in the region.

Abstract The European Union has set ambitious CO2 reduction targets, stimulating renewable energy production and accelerating deployment of offshore wind energy in northern European waters, mainly the North Sea. With increasing size and clustering, offshore wind farms (OWFs) wake effects, which alter wind conditions and decrease the power generation efficiency of wind farms downwind become more important. We use a high-resolution regional climate model with implemented wind farm parameterizations to explore offshore wind energy production limits in the North Sea. We simulate near future wind farm scenarios considering existing and planned OWFs in the North Sea and assess power generation losses and wind variations due to wind farm wake. The annual mean wind speed deficit within a wind farm can reach 2–2.5 ms−1 depending on the wind farm geometry. The mean deficit, which decreases with distance, can extend 35–40 km downwind during prevailing southwesterly winds. Wind speed deficits are highest during spring (mainly March–April) and lowest during November–December. The large-size of wind farms and their proximity affect not only the performance of its downwind turbines but also that of neighboring downwind farms, reducing the capacity factor by 20% or more, which increases energy production costs and economic losses. We conclude that wind energy can be a limited resource in the North Sea. The limits and potentials for optimization need to be considered in climate mitigation strategies and cross-national optimization of offshore energy production plans are inevitable.

To accurately calculate the impact of renewables on power production in complex electric power grids, high-resolution and ideally seamless data within the planetary boundary layer are required. Therefore, the quality of different regional reanalyses and hindcasts is evaluated with respect to the representation of the planetery boundary layer and related sub-daily processes. On the one hand, high resolution regional reanalysis from the UERRA (UE-SMHI, UE-UKMO) and a similar project (COSMO-REA6) are considered. On the other hand, two hindcasts based on the COSMO-REA6 configuration are included in this study, i.e. a simulation with perfect boundaries and a simulation additionally utilizing spectral nudging. The focus of the evaluation is on measurements at four flux towers that are not part of any assimilation procedure. In this paper, we will show that the model’s quality depends on both the complete model system – assimilation method, resolution and physical parameterization – as well as on the performance measure. The daily cycle is best depicted by the hindcasts and even COSMO-REA6 hardly introduces spurious variability. UE-SMHI (3D-Var) suffers from spin-up in particular visible at the elevated levels, whereas the spin-up is damped in UE-UKMO (4D-Var). Investigation of atmospheric stability reveals that diurnal variation of stratification is for the most part well reproduced, but strong deficits were found for all COSMO simulations in reproducing strong stratification and corresponding wind speed gradients. Moreover, an overestimation of superadiabatic lapse rates and corresponding overly weak turbulent mixing is found for UE-UKMO. Furthermore, a combination of ramp statistics and contingency tables is utilized to detect a clear advantage of sophisticated assimilation systems over hindcasts. The evaluation framework presented underpins the importance of ramp statistics and vertical measurement profiles, especially with respect to assessing long-term simulations.

Copyright of Strahlentherapie und Onkologie is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Relapse of malignant disease remains the major complication in patients with acute myeloid leukemia (AML) or myelodysplastic syndrome (MDS) after hematopoietic cell transplantation (HCT) with reduced-intensity conditioning (RIC). In this study, we investigated the predictive value of disease-specific markers (DSMs), donor chimerism (DC) analysis of unsorted (UDC) or CD34+ sorted cells and Wilms' tumor gene 1 (WT1) expression. Eighty-eight patients with AML or MDS were monitored after allogenic HCT following 2 Gy total-body irradiation with (n=84) or without (n=4) fludarabine 3 × 30 mg/m2, followed by cyclosporin A and mycophenolate mofetil. DSMs were determined by fluorescence in situ hybridization (FISH) and WT1 expression by real-time polymerase chain reaction. Chimerism analysis was performed on unsorted or CD34+ sorted cells, by FISH or short tandem repeat polymerase chain reaction. Twenty-one (24%) patients relapsed within 4 months after HCT. UDC, CD34+ DC and WT1 expression were each significant predictors of relapse with sensitivities ranging from 53 to 79% and specificities of 82-91%. Relapse within 28 days was excluded almost entirely on the basis of WT1 expression combined with CD34+ DC kinetics. Monitoring of WT1 expression and CD34+ DC predict relapse of AML and MDS after RIC-HCT. [ABSTRACT FROM AUTHOR]

Simulations of a Regional Climate Model (RCM) driven by identical lateral boundary conditions but initialized at different times exhibit the phenomenon of so-called internal model variability (or in short, Internal Variability—IV), which is defined as the inter-member spread between members in an ensemble of simulations. Our study investigates the effects of air-sea coupling on IV of the regional atmospheric model COSMO-CLM (CCLM) of the new regional coupled system model GCOAST-AHOI (Geesthacht Coupled cOAstal model SysTem: Atmosphere, Hydrology, Ocean and Sea Ice). We specifically address physical processes parameterized in CCLM, which may cause a large IV during an extreme event, and where this IV is affected by the air-sea coupling. Two six-member ensemble simulations were conducted with GCOAST-AHOI and the stand-alone CCLM (CCLM_ctr) for a period of 1 September−31 December 2013 over Europe. IV is expressed by spreads within the two sets of ensembles. Analyses focus on specific events during this period, especially on the storm Christian occurring from 27 to 29 October 2013 in northern Europe. Results show that simulations of CCLM_ctr vary largely amongst ensemble members during the storm. By analyzing two members of CCLM_ctr with opposite behaviors, we found that the large uncertainty in CCLM_ctr is caused by a combination of two factors (1) uncertainty in parameterization of cloud-radiation interaction in the atmospheric model. and (2) lack of an active two-way air-sea interaction. When CCLM is two-way coupled with the ocean model, the ensemble means of GCOAST-AHOI and CCLM_ctr are relatively similar, but the spread is reduced remarkably in GCOAST-AHOI, not only over the ocean where the coupling is done but also over land due to the land-sea interactions.

Copyright of Klinische Wochenschrift is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Klinische Wochenschrift is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Variants of chronic myeloproliferative disorders (CMPD) were compared according to their clinical features and classified by bone marrow biopsy appearances. Subsequently, this classification was further evaluated using survival data and histological variables from iliac crest biopsy specimens of an additional 1391 patients, making a total of 2241 patients available for analysis of outcome. The patients were grouped again into three main classes: "typical"; "variant"; and "transformed". "Typical" comprised the "classic" groups. "Variant" included the less uniform myeloproliferative syndromes, distinguished also by more variable clinical features, a different prognosis, and a greater tendency to fibrotic and blastic transformation. "Transformed" defined the end stages of both "typical" and "variant" types. Ten subgroups were distinguished by different histology and prognosis. Particular prognostic importance was assigned to atypia and immaturity of haemopoiesis, predominance of individual haemopoietic cell line, number and anomalies of megakaryocytes and progressive fibrosis. It is suggested that the proposed subclassification would be helpful for studies of epidemiology and therapeutic trials by allowing more homogeneous groups to be recognised. [ABSTRACT FROM PUBLISHER]