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How climate change will unfold in the years to come is a central topic in today’s environmental debate, in particular at the regional level. While projections using large ensembles of global climate models consistently indicate a future decrease in summer precipitation over southern Europe and an increase over northern Europe, individual models substantially modulate these distinct signals of change in precipitation. So far model improvements and higher resolution from regional downscaling have not been seen as able to resolve these disagreements. In this paper we assess whether 2 decades of investments in large ensembles of downscaling experiments with regional climate model simulations for Europe have contributed to a more robust model assessment of the future climate at a range of geographical scales. We study climate change projections of European seasonal temperature and precipitation using an ensemble-suite comprised by all readily available pan-European regional model projections for the twenty-first-century, representing increasing model resolution from ~ 50 to ~ 12 km grid distance, as well as lateral boundary and sea surface temperature conditions from a variety of global model simulations. Employing a simple scaling with global mean temperature change we identify emerging robust signals of future seasonal temperature and precipitation changes also found to resemble current observed trends, where these are judged to be statistically significant.

Chronic inflammation is considered a major driving force for clonal expansion and evolution in the Philadelphia-negative myeloproliferative neoplasms, which include essential thrombocythemia, polycythemia vera and primary myelofibrosis (MPNs). One of the key mutation drivers is the JAK2V617F mutation, which has been shown to induce the generation of reactive oxygen species (ROS). Using whole blood gene expression profiling, deregulation of several oxidative stress and anti-oxidative defense genes has been identified in MPNs, including significant downregulation of TP53 , the NFE2L2 or NRF2 genes. These genes have a major role for maintaining genomic stability, regulation of the oxidative stress response and in modulating migration or retention of hematopoietic stem cells. Therefore, their deregulation might give rise to increasing genomic instability, increased chronic inflammation and disease progression with egress of hematopoietic stem cells from the bone marrow to seed in the spleen, liver and elsewhere. Interferon-alpha2 (rIFNα) is increasingly being recognized as the drug of choice for the treatment of patients with MPNs. Herein, we report the first gene expression profiling study on the impact of rIFNα upon oxidative stress and antioxidative defense genes in patients with MPNs (n = 33), showing that rIFNα downregulates several upregulated oxidative stress genes and upregulates downregulated antioxidative defense genes. Treatment with rIFNα induced upregulation of 19 genes in ET and 29 genes in PV including CXCR4 and TP53 . In conclusion, this rIFNα- mediated dampening of genotoxic damage to hematopoietic cells may ultimately diminish the risk of additional mutations and accordingly clonal evolution and disease progression towards myelofibrotic and leukemic transformation.

In this paper, we present a multi-modal dataset for obstacle detection in agriculture. The dataset comprises approximately 2 h of raw sensor data from a tractor-mounted sensor system in a grass mowing scenario in Denmark, October 2016. Sensing modalities include stereo camera, thermal camera, web camera, 360 ∘ camera, LiDAR and radar, while precise localization is available from fused IMU and GNSS. Both static and moving obstacles are present, including humans, mannequin dolls, rocks, barrels, buildings, vehicles and vegetation. All obstacles have ground truth object labels and geographic coordinates.

Benthic N₂ production by microbial denitrification and anammox is the largest sink for fixed nitrogen in the oceans. Most N₂ production occurs on the continental shelves, where a high flux of reactive organic matter fuels the depletion of nitrate close to the sediment surface. By contrast, N₂ production rates in abyssal sediments are low due to low inputs of reactive organics, and nitrogen transformations are dominated by aerobic nitrification and the release of nitrate to the bottom water. Here, we demonstrate that this trend is reversed in the deepest parts of the oceans, the hadal trenches, where focusing of reactive organic matter enhances benthic microbial activity. Thus, at ∼8-km depth in the Atacama Trench, underlying productive surface waters, nitrate is depleted within a few centimeters of the sediment surface, N₂ production rates reach those reported from some continental margin sites, and fixed nitrogen loss is mainly conveyed by anammox bacteria. These bacteria are closely related to those known from shallow oxygen minimum zone waters, and comparison of activities measured in the laboratory and in situ suggest they are piezotolerant. Even the Kermadec Trench, underlying oligotrophic surface waters, exhibits substantial fixed N removal. Our results underline the role of hadal sediments as hot spots of deep-sea biological activity, revealing a fully functional benthic nitrogen cycle at high hydrostatic pressure and pointing to hadal sediments as a previously unexplored niche for anaerobic microbial ecology and diagenesis.

The genetic composition of marine microbial communities varies at the microscale between particle-associated (PA; >1.6 μm) and free-living (FL; 0.2–1.6 μm) niches. It remains unclear, however, how metabolic activities differ between PA and FL fractions. We combined rate measurements with metatranscriptomics to quantify PA and FL microbial activity in the oxygen minimum zone (OMZ) of the Eastern Tropical North Pacific, focusing on dissimilatory processes of the nitrogen (N) cycle. Bacterial gene counts were 8- to 15-fold higher in the FL compared with the PA fraction. However, rates of all measured N cycle processes, excluding ammonia oxidation, declined significantly following particle (>1.6 μm) removal. Without particles, rates of nitrate reduction to nitrite (1.5–9.4n M Nd −1 ) fell to zero and N 2 production by denitrification (0.5–1.7n M Nd −1 ) and anammox (0.3–1.9n M Nd −1 ) declined by 53–85%. The proportional representation of major microbial taxa and N cycle gene transcripts in metatranscriptomes followed fraction-specific trends. Transcripts encoding nitrate reductase were uniform among PA and FL fractions, whereas anammox-associated transcripts were proportionately enriched up to 15-fold in the FL fraction. In contrast, transcripts encoding enzymes for N 2 O and N 2 production by denitrification were enriched up to 28-fold in PA samples. These patterns suggest that the majority of N cycle activity, excluding N 2 O and N 2 production by denitrification, is confined to a FL majority that is critically dependent on access to particles, likely as a source of organic carbon and inorganic N. Variable particle distributions may drive heterogeneity in N cycle activity and gene expression in OMZs.

We investigate the simulated temperature and precipitation of the HIRHAM regional climate model using systematic variations in domain size, resolution and detailed location in a total of eight simulations. HIRHAM was forced by ERA-Interim boundary data and the simulations focused on higher resolutions in the range of 5.5–12 km. HIRHAM outputs of seasonal precipitation and temperature were assessed by calculating distributed model errors against a higher resolution data set covering Denmark and a 0.25° resolution data set covering Europe. Furthermore the simulations were statistically tested against the Danish data set using bootstrap statistics. The results from the distributed validation of precipitation showed lower errors for the winter (DJF) season compared to the spring (MAM), fall (SON) and, in particular, summer (JJA) seasons for both validation data sets. For temperature, the pattern was in the opposite direction, with the lowest errors occurring for the JJA season. These seasonal patterns between precipitation and temperature are seen in the bootstrap analysis. It also showed that using a 4,000 × 2,800 km simulation with an 11 km resolution produced the highest significance levels. Also, the temperature errors were more highly significant than precipitation. In similarly sized domains, 12 of 16 combinations of variables, observation validation data and seasons showed better results for the highest resolution domain, but generally the most significant improvements were seen when varying the domain size.

Acute critical illness is often preceded by deterioration of routinely measured clinical parameters, e.g., blood pressure and heart rate. Early clinical prediction is typically based on manually calculated screening metrics that simply weigh these parameters, such as early warning scores (EWS). The predictive performance of EWSs yields a tradeoff between sensitivity and specificity that can lead to negative outcomes for the patient. Previous work on electronic health records (EHR) trained artificial intelligence (AI) systems offers promising results with high levels of predictive performance in relation to the early, real-time prediction of acute critical illness. However, without insight into the complex decisions by such system, clinical translation is hindered. Here, we present an explainable AI early warning score (xAI-EWS) system for early detection of acute critical illness. xAI-EWS potentiates clinical translation by accompanying a prediction with information on the EHR data explaining it. Acute critical illness is often preceded by deterioration of routinely measured clinical parameters, e.g., blood pressure and heart rate. Here, the authors develop an explainable artificial intelligence early warning score system for its early detection.

Extreme sea levels are a major global concern due to their potential to cause fatalities and significant economic losses in coastal areas. Consequently, accurate projections of these extremes for the coming century are crucial for effective coastal planning. While it is well established that relative sea level rise driven by ongoing climate change is a key factor influencing future extreme sea levels, changes in storm surges resulting from shifts in storm climatology may also play a critical role. In this study, we project future daily maximum storm tides (the combination of storm surge and tides) using a random forest machine learning approach for 59 stations around the Baltic Sea, based on atmospheric variables such as surface pressure, wind speed, and wind direction derived from climate datasets. The results suggest both positive and negative changes, with sub-regional variations, in 50-year storm tide return levels across the Baltic Sea when comparing the period of 2070–2099 to 1850–1879. Localized increases of up to 10 cm are projected along the west coast of Sweden and the northern Baltic Sea, while decreases of up to 6 cm are anticipated along the south coast of Sweden, the Gulf of Riga, and the mouth of the Gulf of Finland. Negligible levels of change are expected in other parts of the Baltic Sea. The variability in atmospheric drivers across the four climate models contributes to a high degree of uncertainty in future climate projections.

The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies.

Purpose Within a population-based follow-up study, to examine the 10-year incidence of pseudoexfoliation syndrome (PEX), possible risk factors for PEX and its association with ocular aging of the cornea, lens and retina. Methods The baseline examination was conducted in 2006 on a random sample of 1,033 adult participants from Kaunas city (Lithuania) population of whom 631 had ophthalmic examination data at attendance of the 10-year follow-up in 2016. Detailed examination of the anterior and posterior segment of the eye was carried out. After diagnostic mydriasis PEX was diagnosed by the presence of typical grayish-white exfoliation material on the anterior capsule surface of the lens. The participants were divided to PEX and non-PEX groups. Results PEX prevalence increased from 9.8 to 34.2% from baseline to 10-year follow-up. Nuclear cataract was common both in the PEX group (66.7%) and in those without PEX (72.2%), but this difference did not reach statistically significantly increased risk of developing cataract in those with PEX (OR 1.2; p  = 0.61). Central corneal thickness (CCT) was thinner in the PEX group (529 ± 34 μm) and in the oldest group (525 ± 36 μm) ( p  < 0.001). Compared to baseline, corneal curvature (CC) became flatter in both groups (7.6 ± 0.27 vs 7.7 ± 0.26 mm; p  < 0.001) during the follow-up, but the difference did not reach significance between groups. Corneal astigmatism was most commonly with-the-rule in both groups (37 (50.0%) vs 148 (68.5%); p  > 0.05). Age, sex and PEX had no influence on age-related macular degeneration distribution. Conclusion The prevalence of PEX increased significantly with age in our population, with those with PEX having thinner and flatter corneae, but no difference in cataract and age-related macular degeneration characteristics.