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A clinical dashboard is a data-driven clinical decision support tool visualizing multiple key performance indicators in a single report while minimizing time and effort for data gathering. Studies have shown that including patient-reported outcome measures (PROMs) in clinical dashboards supports the clinician's understanding of how treatments impact patients' health status, helps identify changes in health-related quality of life at an early stage, and strengthens patient-physician communication. This study aims to determine design components for clinical dashboards incorporating PROMs to inform software producers and users (ie, physicians). We conducted interviews with software producers and users to test preselected design components. Furthermore, the interviews allowed us to derive additional components that are not outlined in existing literature. Finally, we used inductive and deductive coding to derive a guide on which design components need to be considered when building a clinical dashboard incorporating PROMs. A total of 25 design components were identified, of which 16 were already surfaced during the literature search. Furthermore, 9 additional components were derived inductively during our interviews. The design components are clustered in a generic dashboard, PROM-related, adjacent information, and requirements for adoption components. Both software producers and users agreed on the primary purpose of a clinical dashboard incorporating PROMs to enhance patient communication in outpatient settings. Dashboard benefits include enhanced data visualization and improved workflow efficiency, while interoperability and data collection were named as adoption challenges. Consistency in dashboard design components is preferred across different episodes of care, with adaptations only for disease-specific PROMs. Clinical dashboards have the potential to facilitate informed treatment decisions if certain design components are followed. This study establishes a comprehensive framework of design components to guide the development of effective clinical dashboards incorporating PROMs in health care practice.

Background As one of the main goals of hip and knee replacements is to improve patients’ health-related quality of life, a meaningful evaluation can be achieved by calculating minimal important changes (MICs) for improvements in patient-reported outcome measures (PROMs). This study aims at providing MICs adjusted for patient characteristics for EQ-5D-3L index score improvements after hip and knee replacements. It adds to existing literature by relying on a large national sample and precise clustering algorithms, and by employing a state-of-the-art methodology for the calculation of improved adjusted MICs. Methodology A retrospective observational study was conducted using the publicly available National Health Service (NHS) PROMs dataset for primary hip and knee replacements. We used information on 252,331 hip replacements and 279,668 knee replacements from all NHS-funded providers in England between 2013 and 2020. Clusters of patients were created based on pre-operative EQ-VAS, depression status, and sex. Unstratified and stratified estimates for meaningful EQ-5D-3L improvements were obtained through anchor-based predictive MICs corrected for the proportion of improved patients and the reliability of transition ratings. Results Stratifying patients showed that MICs varied across subgroups based on pre-operative EQ-VAS, depression status, and sex. MICs were larger for patients with worse pre-operative EQ-VAS scores, while patients with better pre-operative scores required smaller MICs to achieve a meaningful change. We show how after stratification the percentage of patients achieving their stratified MIC was better in line with the actual share of improved patients. Larger MICs were found for patients with depression and for female patients. MICs calculated for knee replacements were consistently lower than those for hip replacements. Conclusions Our findings show the importance of adjusting MICs for patients’ characteristics and should be considered for quality-related choices and policy initiatives.

Swiss mixed companies combine favorable tax treatment with real business presence. The favorable tax treatment extended to a mixed company applies only at the cantonal and communal level, not the federal level. In general, a company may qualify as a mixed company for tax purposes if it does not engage in commercial activities within Switzerland, or if it engages in such activities to only a minimal extent. A mixed company's income can be divided into 3 categories: 1. income from foreign source, 2. income from Swiss source, and 3. participation income from dividend or similar distributions. Swiss mixed companies can lead to an effective deferral of US income tax in: 1. joint ventures, 2. international trading, 3. international consulting and brokerage, 4. manufacturing, 5. centralized distribution, and 6. PFIC trap.

Switzerland's strong economic position and its strategic location in the heart of Europe, combined with its relatively small territory, have early on led Switzerland to conclude double taxation treaties (DTTs) with its surrounding neighbor states and trading partners. In DTT negotiations, the special needs of the Swiss economy, which to a great degree exports capital, goods, and services, are taken into consideration. The Mutual Agreement Procedure (MAP) article of DTTs is one of the most important treaty areas for which the Competent Authorities are responsible. The MAP in Switzerland is governed by provisions of Swiss DTTs corresponding to Article 25 of the OECD Model Treaty and the Federal Act on Administrative Procedures. Taxes covered by a MAP are in principle those covered by the pertinent DTTs. Since the introduction in 2002 of Article 27 of the OECD Model Treaty, which provides for assistance in collection, several countries have included such clauses in their DTTs.

The widespread implementation of antiretroviral therapy has significantly reduced HIV-related mortality and mother-to-child transmission. Despite being HIV-uninfected, HIV-exposed children (HEU) seem to face heightened risks of immune dysfunction, cardiometabolic diseases, growth delays, reduction in bone mineral density, and neurocognitive impairments compared to HIV-unexposed uninfected peers. These vulnerabilities can be attributed to maternal immune dysregulation during pregnancy, antiretroviral (ART) toxicity, HIV exposure, and adverse socioeconomic and nutritional environments. Emerging evidence highlights the impact of antiviral therapy exposure, particularly tenofovir disoproxil fumarate, on HEU mitochondrial dysfunction, bone resorption, neurocognitive delays, and zidovudine on cardiac abnormalities. This narrative review explores the multisystem effects of ART exposure in HEU children, focusing on immune function, neurodevelopment, cardiovascular health, growth, and bone metabolism. By synthesizing findings from diverse studies, the review aims to provide a comprehensive understanding of the potential risks associated with ART regimens and identify future research priorities to improve outcomes for HEU children.

In a randomized trial, 1006 patients with intermediate-risk pulmonary embolism were assigned to tenecteplase or placebo in addition to standard heparin therapy. The tenecteplase group had a lower rate of hemodynamic decompensation but more frequent major hemorrhage and stroke. Acute pulmonary embolism occurs frequently and may cause death or serious disability. 1 Case fatality rates vary widely, 2 , 3 but approximately 10% of all patients with acute pulmonary embolism die within 3 months after the diagnosis. 4 , 5 Acute right ventricular pressure overload at diagnosis is an important determinant of the severity and early clinical outcome of pulmonary embolism. 6 High-risk pulmonary embolism 7 is characterized by overt hemodynamic instability and warrants immediate advanced therapy, including consideration of fibrinolysis. In contrast, for patients presenting without systemic hypotension or hemodynamic compromise, standard anticoagulation is generally considered adequate treatment. 8 However, patients who have acute right ventricular . . .

Creative problem solving involves search processes, and it is known to be hard to motivate. Reward cues have been found to enhance performance across a range of tasks, even when cues are presented subliminally, without being consciously detected. It is uncertain whether motivational processes, such as reward, can influence problem solving. We tested the effect of supraliminal and subliminal reward on participant performance on problem solving that can be solved by deliberate analysis or by insight . Forty-one participants attempted to solve 100 compound remote associate problems. At the beginning of each problem, a potential reward cue (1 or 25 cents) was displayed, either subliminally (17 ms) or supraliminally (100 ms). Participants earned the displayed reward if they solved the problem correctly. Results showed that the higher subliminal reward increased the percentage of problems solved correctly overall. Second, we explored if subliminal rewards preferentially influenced solutions that were achieved via a sudden insight (mostly processed below awareness) or via a deliberate analysis. Participants solved more problems via insight following high subliminal reward when compared with low subliminal reward, and compared with high supraliminal reward, with no corresponding effect on analytic solving. Striatal dopamine (DA) is thought to influence motivation, reinforce behavior, and facilitate cognition. We speculate that subliminal rewards activate the striatal DA system, enhancing the kinds of automatic integrative processes that lead to more creative strategies for problem solving, without increasing the selectivity of attention, which could impede insight.

Dopamine is a key neurotransmitter involved in physiological processes such as motor control, motivation, reward, cognitive function, and maternal and reproductive behaviors. Therefore, dysfunctions of the dopaminergic system are related to a plethora of human diseases. Dopamine, via different circuitries implicated in compulsive behavior, reward, and habit formation, also represents a key player in substance use disorder and the formation and perpetuation of mechanisms leading to addiction. Here, we propose dopamine as a model not only of neurotransmission but also of neuromodulation capable of modifying neuronal architecture. Abuse of substances like methamphetamine, cocaine, and alcohol and their consumption over time can induce changes in neuronal activities. These modifications lead to synaptic plasticity and finally to morphological and functional changes, starting from maladaptive neuro-modulation and ending in neurodegeneration.

The contraction of striated muscle (skeletal and cardiac muscle) is generated by ATP-dependent interactions between the molecular motor myosin II and the actin filament. The myosin motors are mechanically coupled along the thick filament in a geometry not achievable by single-molecule experiments. Here we show that a synthetic one-dimensional nanomachine, comprising fewer than ten myosin II dimers purified from rabbit psoas, performs isometric and isotonic contractions at 2 mM ATP, delivering a maximum power of 5 aW. The results are explained with a kinetic model fitted to the performance of mammalian skeletal muscle, showing that the condition for the motor coordination that maximises the efficiency in striated muscle is a minimum of 32 myosin heads sharing a common mechanical ground. The nanomachine offers a powerful tool for investigating muscle contractile-protein physiology, pathology and pharmacology without the potentially disturbing effects of the cytoskeletal—and regulatory—protein environment. There is interest in mimicking striated muscle for a range of applications including nanomachines. Here, the authors report on synthetic 1D nanomachines which are used to study an ensemble of myosin motors interacting with an actin filament with potential to create assays of muscle related diseases

The rise of AI-generated synthetic media, or deepfakes, has introduced unprecedented opportunities and challenges across various fields, including entertainment, cybersecurity, and digital communication. Using advanced frameworks such as Generative Adversarial Networks (GANs) and Diffusion Models (DMs), deepfakes are capable of producing highly realistic yet fabricated content, while these advancements enable creative and innovative applications, they also pose severe ethical, social, and security risks due to their potential misuse. The proliferation of deepfakes has triggered phenomena like “Impostor Bias”, a growing skepticism toward the authenticity of multimedia content, further complicating trust in digital interactions. This paper is mainly based on the description of a research project called FF4ALL (FF4ALL-Detection of Deep Fake Media and Life-Long Media Authentication) for the detection and authentication of deepfakes, focusing on areas such as forensic attribution, passive and active authentication, and detection in real-world scenarios. By exploring both the strengths and limitations of current methodologies, we highlight critical research gaps and propose directions for future advancements to ensure media integrity and trustworthiness in an era increasingly dominated by synthetic media.