Objectives German statutory health insurance budgets are driven by escalation to advanced systemic therapies for atopic dermatitis (AD). Effective and affordable novel options for adults with AD are needed to reduce the economic burden. Our objective was to estimate the 5-year budget impact of adopting the topical Janus kinase inhibitor, 1.5% ruxolitinib cream, for adults with moderate AD, affected body surface area ≤ 20%, and clinical eligibility for systemic therapy from a German population perspective. Methods We developed a budget impact model that compares the current systemic treatment mix with a forward-looking intervention scenario in which 1.5% ruxolitinib cream is adopted for adult AD from 2026 onward. Uptake increases linearly to 25% by 2030 and proportionally displaces systemic therapies. Ruxolitinib cream costs were modeled based on real-world evidence. Direct costs included drug acquisition and nondrug medical costs; the societal perspective incorporated out-of-pocket costs and productivity losses. Results The systemic-eligible population was estimated at 330 600 patients in 2025, growing to 402 200 by 2030. Among those were 90 000 patients treated with 1.5% ruxolitinib cream in 2030. Over 2026 to 2030, costs were €39.8bn with ruxolitinib cream versus €44.1bn with current systemic treatments, yielding a cumulative budget impact of €4.3bn. Statutory health insurance savings accounted for 80% (€3.4bn) of those savings. Conclusions Under the modeled uptake and displacement assumptions, ruxolitinib cream could represent a cost-mitigating option that could reduce the economic burden of AD. Postlaunch evidence on utilization, persistence, and therapy switching is needed to validate and refine budget impact estimates.
Renal replacement therapy (RRT) is frequently used in critically ill patients with acute kidney injury (AKI). Here, we provide guidelines for the management of RRT in critically ill patients on the intensive care unit (ICU). We convened a systemic literature research and a Delphi process with a bi-national multidisciplinary consensus panel including 22 clinicians of 12 different German-speaking societies (Germany and Austria) with expertise in RRT. This structured guideline process was the basis for the evidence-based statements and recommendations. We identified seven clinical areas needing guidance: (1) start, (2) modality (diffusion and convection), (3) continuous/ intermittent, (4) anticoagulation, (5) dose (6) pharmacotherapy, (7) stopping criteria. The consensus produced 73 statements and recommendations regarding key clinical areas, the most important 47 statements and recommendations are summarized in this overview. This evidence-based bi-national guideline should provide physicians with guidance for delivering best practice to critically ill patients with a dialysis-dependent AKI.
The present study utilizes highly resolved Lagrange particle tracking measurements to analyze the time-dependent three-dimensional fluid dynamics in the wake of air bubbles rising in quiescent bidistilled water. Two bubble sizes are studied with regard to the velocity fields and the temporal evolution of the generated vorticity in their wakes. The range of bubble sizes is of particular interest, as it corresponds to other recent studies. The bubbles are reconstructed in three dimensions to determine the bubble rise trajectory and the bubble shape. The analysis of the aforementioned measurements, particularly the calculation of the Q-criterion, supports prior numerical findings of a wake mode exhibiting secondary vortex loops. Additionally, the energy spectra of the velocity fields and their temporal evolution are analyzed, providing a unique experimental dataset for the validation of numerical simulations and the further study of bubbly flows.
Universities have significant carbon emissions impact and face pressure to cut their operational carbon emissions around the world. This leads to growing interest of the academic and practice community in effective pathways for carbon reduction within higher education. In this context, the aim of the research is to investigate the strategies for decarbonising university operations and challenges being faced. Drawing from a mixed-method approach, a review of case studies, and a survey involving Higher Education Institutions (HEIs) in nearly 40 countries, it explores the interconnectedness of awareness, cultural and political dimensions, internal institutional structures, and technical approaches in achieving decarbonisation goals. The findings underscore awareness initiatives that enhance understanding of decarbonisation among educators and students in universities, and communities. The case studies as a review of experiences from diverse geographical regions illustrate varying strategies for carbon emissions reduction in HEIs, underscoring the adaptability of decarbonisation efforts across contexts. Additionally, cultural and political factors emerge as key determinants, requiring tailored strategies to navigate diverse contexts and garner public support. Finally, institutional structures, including financial constraints and regulatory barriers, and ageing infraestructure are identified as key barriers to effective decarbonisation efforts. The novelty of the paper resides on the fact that it highlights the need for integrating decarbonisation goals into institutional governance and planning mechanisms is essential for achieving long-term goal of net zero carbon and aligning with the global UN Sustainable Development Goals (SDGs). The study advocates for a holistic approach that considers social, economic, environmental and institutional dimensions in advancing decarbonisation within HEIs, rather than treating emissions as a purely technical issue. The effectiveness of decarbonisation measures is dependent on breaking down chronic structural and financial factors in the implementation, and is substantially supported by institutional practices that promote the engagement of all stakeholders and an open, transparent measurement of its impact. By addressing barriers, HEIs can pave the way for a sustainable and low carbon future while serving as catalysts for broader societal change.
Electrochemical impedance spectroscopy (EIS) provides a sensitive probe for investigating internal physicochemical processes in lithium-ion batteries and has been widely considered for diagnostic applications. However, impedance measurements obtained under practical conditions are often affected by non-ideal excitation signals, environmental noise, and systematic distortions, which complicate the interpretation of EIS data using physics-based electrochemical models. In this study, a distortion-aware framework is developed for physics-based impedance modeling of commercial 21,700 lithium-ion batteries. A pseudo-two-dimensional (P2D) model with double-layer capacitance is employed to simulate impedance responses over a broad frequency range. A frequency-resolved parameter sensitivity analysis is conducted to quantify the contributions of key electrochemical parameters across the impedance spectrum and to identify the dominant factors governing different frequency regimes. Building on this sensitivity analysis, the model is further evaluated under realistic measurement conditions. Ambient noise and waveform distortions are identified through hardware impedance testing, reconstructed as biased excitation inputs, and processed using an FFT-based approach to extract impedance spectra from time-domain signals. The model shows excellent agreement with experiments in both the DC and AC validation sets. Under low-rate discharge conditions (0.1C), the simulated voltage profile matches the experimental response, with an RMSE of 0.0423 V, and most deviations occur near the end-of-discharge knee at very low SoC. For impedance validation, the model reproduces the measured spectra with RMSE values of 0.282 mS2 and 0.224 mS2 for the real and imaginary parts, respectively. Under distorted excitations, including non-sinusoidal waveforms, Gaussian noise, and clipping, the median complex least-squares (CLS) error stays stable between 0.330 and 0.367 mS2, and the maximum CLS error remains below 0.49 mS2. This work provides a practical methodology for interpreting impedance spectra of commercial lithium-ion batteries when signal distortions and noise cannot be neglected.
