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The Next Generation of Earth Modeling Systems (nextGEMS) project aimed to produce multidecadal climate simulations, for the first time, with resolved kilometer-scale (km-scale) processes in the ocean, land, and atmosphere. In only 3 years, nextGEMS achieved this milestone with the two km-scale Earth system models, ICOsahedral Non-hydrostatic model (ICON) and Integrated Forecasting System coupled to the Finite-volumE Sea ice-Ocean Model (IFS-FESOM). nextGEMS was based on three cornerstones: (1) developing km-scale Earth system models with small errors in the energy and water balance, (2) performing km-scale climate simulations with a throughput greater than 1 simulated year per day, and (3) facilitating new workflows for an efficient analysis of the large simulations with common data structures and output variables. These cornerstones shaped the timeline of nextGEMS, divided into four cycles. Each cycle marked the release of a new configuration of ICON and IFS-FESOM, which were evaluated at hackathons. The hackathon participants included experts from climate science, software engineering, and high-performance computing as well as users from the energy and agricultural sectors. The continuous efforts over the four cycles allowed us to produce 30-year simulations with ICON and IFS-FESOM, spanning the period 2020–2049 under the SSP3-7.0 scenario. The throughput was about 500 simulated days per day on the Levante supercomputer of the German Climate Computing Center (DKRZ). The simulations employed a horizontal grid of about 5 km resolution in the ocean and 10 km resolution in the atmosphere and land. Aside from this technical achievement, the simulations allowed us to gain new insights into the realism of ICON and IFS-FESOM. Beyond its time frame, nextGEMS builds the foundation of the Climate Change Adaptation Digital Twin developed in the Destination Earth initiative and paves the way for future European research on climate change.

The Climate Change Adaptation Digital Twin (Climate DT), developed as part of the European Commission's Destination Earth (DestinE) initiative, sets up an operational system for producing multi-decadal, multi-model global climate projections and translating climate data into climate impact information to support adaptation efforts. This system delivers data with local granularity at spatial resolutions of 5–10 km and hourly outputs, leading to globally consistent information at scales that matter for decision-making. It also enables the testing of what-if scenarios such as high-resolution storylines, which are physically consistent global simulations of extreme events under different climate conditions and provide contextual insights to support concrete adaptation decisions. They support the generation of more equitable (understood as accessible and relevant across regions) climate information. The Climate DT is built on cutting-edge infrastructure, expert collaboration, and digital innovation. It is designed to support on-demand responses to policy questions, with quantified uncertainty. It will foster interactivity by allowing users to influence simulation design, model output portfolios, and application integration through co-design. AI-based tools, including emulators and chatbots, are being developed in parallel to enhance climate information access. Sector-specific applications are embedded in the system to synchronously translate climate data into tailored climate-impact indicators, with examples provided for energy, water, and forest management. The applications have been co-designed with informed users. A unified, cross-platform workflow defines the orchestration of all components, which is handled by a single workflow manager and relies on containerised components, facilitating automation, portability, maintainability, and traceability. Data management is unified using standard grids (HEALPix), ensuring consistency and easing data usability under a strict governance policy. Streaming enables real-time data use by the data consumers and unlocks access to the unprecedented data wealth produced by the high-resolution simulations. Monitoring tools provide real-time quality control of data and model outputs and enable continuous assessment of the realism of the climate simulations during Climate DT operation. The compute-intensive system is powered by world-class supercomputing capabilities through a strategic partnership with the European High Performance Computing Joint Undertaking (EuroHPC). Despite high computational demands, the Climate DT sets a new benchmark for delivering equitable, credible, and actionable climate information. It complements existing initiatives like CMIP, CORDEX, and national and European climate services, and aligns with global climate science goals to support climate adaptation.

We introduce a representation of a 2D steady vector field \\( v\\) by two scalar fields \\(a\\), \\(b\\), such that the isolines of \\(a\\) correspond to stream lines of \\( v\\), and \\(b\\) increases with constant speed under integration of \\( v\\). This way, we get a direct encoding of stream lines, i.e., a numerical integration of \\( v\\) can be replaced by a local isoline extraction of \\(a\\). To guarantee a solution in every case, gradient-preserving cuts are introduced such that the scalar fields are allowed to be discontinuous in the values but continuous in the gradient. Along with a piecewise linear discretization and a proper placement of the cuts, the fields \\(a\\) and \\(b\\) can be computed. We show several evaluations on non-trivial vector fields.

Exposure to environmental pollutants and human microbiome composition are important predisposition factors for tumour development 1 , 2 . Similar to drug molecules, pollutants are typically metabolized in the body, which can change their carcinogenic potential and affect tissue distribution through altered toxicokinetics 3 . Although recent studies demonstrated that human-associated microorganisms can chemically convert a wide range of xenobiotics and influence the profile and tissue exposure of resulting metabolites 4 , 5 , the effect of microbial biotransformation on chemical-induced tumour development remains unclear. Here we show that the depletion of the gut microbiota affects the toxicokinetics of nitrosamines, which markedly reduces the development and severity of nitrosamine-induced urinary bladder cancer in mice 6 , 7 . We causally linked this carcinogen biotransformation to specific gut bacterial isolates in vitro and in vivo using individualized bacterial culture collections and gnotobiotic mouse models, respectively. We tested gut communities from different human donors to demonstrate that microbial carcinogen metabolism varies between individuals and we showed that this metabolic activity applies to structurally related nitrosamine carcinogens. Altogether, these results indicate that gut microbiota carcinogen metabolism may be a contributing factor for chemical-induced carcinogenesis, which could open avenues to target the microbiome for improved predisposition risk assessment and prevention of cancer. A study links environmental nitrosamines to bladder cancer through their metabolism by specific commensal microorganisms occurring in the gastrointestinal tract of humans and mice.

Existing guidelines recommend psychopharmacological treatment for the management of schizophrenia and bipolar disorder as part of holistic treatment concepts. About half of the patients do not take their medication regularly, although treatment adherence can prevent exacerbations and re-hospitalizations. To date, the relationship between medication adherence and cognitive performance is understudied. Therefore, this study investigated the relationship between medication adherence and cognitive performance by analyzing the data of 862 participants with schizophrenia-spectrum and bipolar disorders (mean [SD] age, 41.9 [12.48] years; 44.8% female) from a multicenter study (PsyCourse Study). Z-scores for three cognitive domains were calculated, global functioning was measured with the Global Assessment of Functioning Scale, and adherence was assessed by a self-rating questionnaire. We evaluated four multiple linear regression models and built three clusters with hierarchical cluster analyses. Higher adherence behavior (p < 0.001) was associated with better global functioning but showed no impact on the cognitive domains learning and memory, executive function, and psychomotor speed. The hierarchical cluster analysis resulted in three clusters with different cognitive performances, but patients in all clusters showed similar adherence behavior. The study identified cognitive subgroups independent of diagnoses, but no differences were found in the adherence behavior of the patients in these new clusters. In summary, medication adherence was associated with global but not cognitive functioning in patients with schizophrenia-spectrum and bipolar disorders. In both diagnostic groups, cognitive function might be influenced by various factors but not medication adherence.

While some individuals age without pathological memory impairments, others develop age‐associated cognitive diseases. Since changes in cognitive function develop slowly over time in these patients, they are often diagnosed at an advanced stage of molecular pathology, a time point when causative treatments fail. Thus, there is great need for the identification of inexpensive and minimal invasive approaches that could be used for screening with the aim to identify individuals at risk for cognitive decline that can then undergo further diagnostics and eventually stratified therapies. In this study, we use an integrative approach combining the analysis of human data and mechanistic studies in model systems to identify a circulating 3‐microRNA signature that reflects key processes linked to neural homeostasis and inform about cognitive status. We furthermore provide evidence that expression changes in this signature represent multiple mechanisms deregulated in the aging and diseased brain and are a suitable target for RNA therapeutics. SYNOPSIS Alzheimer’s disease (AD) is usually diagnosed at an advanced stage of molecular pathology, a time point when causative treatments fail. This study aimed to identify a minimally invasive biomarker that can help to identify individuals at risk for cognitive decline before clinical manifestation. Circulating microRNAs are linked to cognitive function in young and healthy humans. A circulating 3‐microRNA signature is identified using a longitudinal mouse model of age‐associated memory decline. The expression of the 3‐microRNA signature is increased in patients with mild cognitive impairment (MCI) and is associated with future conversion from MCI to AD. Targeting all 3‐ microRNAs using anti‐miRs ameliorates cognitive decline in AD mice. Graphical Abstract Alzheimer’s disease (AD) is usually diagnosed at an advanced stage of molecular pathology, a time point when causative treatments fail. This study aimed to identify a minimally invasive biomarker that can help to identify individuals at risk for cognitive decline before clinical manifestation.