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Since modern foods are unnaturally enriched in single metabolites, it is important to understand which metabolites are sensed by the human body and which are not. We previously showed that the fatty acid stearic acid (C18:0) signals via a dedicated pathway to regulate mitofusin activity and thereby mitochondrial morphology and function in cell culture. Whether this pathway is poised to sense changes in dietary intake of C18:0 in humans is not known. We show here that C18:0 ingestion rapidly and robustly causes mitochondrial fusion in people within 3 h after ingestion. C18:0 intake also causes a drop in circulating long-chain acylcarnitines, suggesting increased fatty acid beta-oxidation in vivo. This work thereby identifies C18:0 as a dietary metabolite that is sensed by our bodies to control our mitochondria. This could explain part of the epidemiological differences between C16:0 and C18:0, whereby C16:0 increases cardiovascular and cancer risk whereas C18:0 decreases both. Dietary fatty acids have different effects on human health. Here, the authors show that ingestion of the fatty acid C18:0, but not of C16:0, rapidly leads to fusion of mitochondria and fatty acid oxidation in humans, possibly explaining the health benefits of C18:0.

Entanglement is an important resource in quantum-enhanced technologies, but it is difficult to generate, especially in solid-state systems. An experiment now demonstrates the entanglement of two nuclear spins via a parity measurement of the electron spin in a nitrogen-vacancy centre in diamond. Projective measurements are a powerful tool for manipulating quantum states 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 . In particular, a set of qubits can be entangled by measuring a joint property 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 such as qubit parity. These joint measurements do not require a direct interaction between qubits and therefore provide a unique resource for quantum information processing with well-isolated qubits. Numerous schemes for entanglement-by-measurement of solid-state qubits have been proposed 8 , 9 , 10 , 11 , 12 , 13 , but the demanding experimental requirements have so far hindered implementations. Here we realize a two-qubit parity measurement on nuclear spins localized near a nitrogen-vacancy centre in diamond by exploiting an electron spin as a readout ancilla. The measurement enables us to project the initially uncorrelated nuclear spins into maximally entangled states. By combining this entanglement with single-shot readout we demonstrate the first violation of Bell’s inequality with solid-state spins. These results introduce a new class of experiments in which projective measurements create, protect and manipulate entanglement between solid-state qubits.

Background The Implementation Leadership Scale (ILS) was developed to assess leadership behavior with regard to being proactive, knowledgeable, supportive, or perseverant in implementing evidence-based practices (EBPs). As part of a study on the implementation of a digitally supported polypharmacy management application in primary care, the original ILS was translated and validated for use in the German language. Rationale This study aimed to translate the original ILS into German and evaluate its psychometric properties. Methods The validation sample consisted of 198 primary care physicians in a cluster-randomized controlled trial in which the intervention group implemented a digitally supported clinical decision support system for polypharmacy management. The ILS was assessed using a 12-item scale. The study included a process evaluation with two evaluation waves between 2019 and 2021. The ILS was used within this process evaluation study to assess the leadership support with regard to the implementation of the polypharmacy management. The ILS was translated in a multi-step process, including pre-testing of the instrument and triple, back-and-forth translation of the instrument. We tested the reliability (Cronbach’s alpha) and validity (construct and criterion-related validity) of the scale. Results The four-dimensional structure of the instrument was confirmed (comparative fit index = .97; root mean square error of approximation = .06). Convergent validity was demonstrated by correlations with organizational innovation climate, social capital, and workload, which was consistent with the proposed hypothesis. Criterion-related validity of the ILS was demonstrated by predicting the organizational readiness for change scores using structural equation modeling. The reliability of the scale was good (α = .875). Conclusion The German version of the ILS created in this study is a reliable and valid measure. The original four-dimensional structure of the ILS was confirmed in a primary care setting. Further psychometric testing is needed to establish the validity and reliability of the ILS and to transfer it to other health care settings. It is a useful tool for identifying the areas for implementation leadership development. Further research is needed on how, why, and when distinct types of leadership behaviors have different effects on healthcare organizations in implementation processes.

In March 2020, following the annual International Committee on Taxonomy of Viruses (ICTV) ratification vote on newly proposed taxa, the phylum Negarnaviricota was amended and emended. At the genus rank, 20 new genera were added, two were deleted, one was moved, and three were renamed. At the species rank, 160 species were added, four were deleted, ten were moved and renamed, and 30 species were renamed. This article presents the updated taxonomy of Negarnaviricota as now accepted by the ICTV.

Recent climate talks in Copenhagen reaffirmed the crucial role of reducing emissions from deforestation and degradation (REDD). Creating and strengthening indigenous lands and other protected areas represents an effective, practical, and immediate REDD strategy that addresses both biodiversity and climate crises at once.

In March 2022, following the annual International Committee on Taxonomy of Viruses (ICTV) ratification vote on newly proposed taxa, the phylum Negarnaviricota was amended and emended. The phylum was expanded by two new families (bunyaviral Discoviridae and Tulasviridae), 41 new genera, and 98 new species. Three hundred forty-nine species were renamed and/or moved. The accidentally misspelled names of seven species were corrected. This article presents the updated taxonomy of Negarnaviricota as now accepted by the ICTV.

Objective Formative evaluation of the implementation process for a digitally supported intervention in polypharmacy in Germany. Qualitative research was conducted within a cluster randomized controlled trial (C-RCT). It focused on understanding how the intervention influences behavior-related outcomes in the prescription and medication review process. Methods/setting Twenty-seven general practitioners (GPs) were included in the study in the two groups of the C-RCT, the intervention, and the wait list control group. Behavior-related outcomes were investigated using three-step data analysis (content analytic approach, documentary method, and design of a model of implementation pathways). Results Content analysis showed that physicians were more intensely aware of polypharmacy-related risks, described positive learning effects of the digital technology on their prescribing behavior, and perceived a change in communication with patients and pharmacists. Conversely, they felt uncertain about their own responsibility when prescribing. Three main dimensions were discovered which influenced adoption behavior: (1) the physicians’ interpretation of the relevance of pharmaceutical knowledge provided by the intervention in changing decision-making situations in polypharmacy; (2) their medical code of ethics for clinical decision making in the context of progressing digitalization; and (3) their concepts of evidence-based medicine on the basis of professional experiences with polypharmacy in primary care settings. In our sample, both simple and complex pathways from sensitization to adoption were observed. The resulting model on adoption behavior includes a paradigmatic description of different pathways and a visualization of different observed levels and applied methodological approaches. We assumed that the GP habitus can weaken or strengthen interventional effects towards intervention uptake. This formative evaluation strategy is beneficial for the identification of behavior-related implementation barriers and facilitators. Conclusion Our analyses of the adoption behavior of a digitally supported intervention in polypharmacy revealed both simple and complex pathways from awareness to adoption, which may impact the implementation of the intervention and therefore, its effectiveness. Future consideration of adoption behavior in the planning and evaluation of digitally supported interventions may enhance uptake and support the interpretation of effects. Trial registration NCT03430336 , 12 February 2018.

IntroductionClinically complex patients often require multiple medications. Polypharmacy is associated with inappropriate prescriptions, which may lead to negative outcomes. Few effective tools are available to help physicians optimise patient medication. This study assesses whether an electronic medication management support system (eMMa) reduces hospitalisation and mortality and improves prescription quality/safety in patients with polypharmacy.Methods and analysisPlanned design: pragmatic, parallel cluster-randomised controlled trial; general practices as randomisation unit; patients as analysis unit. As practice recruitment was poor, we included additional data to our primary endpoint analysis for practices and quarters from October 2017 to March 2021. Since randomisation was performed in waves, final study design corresponds to a stepped-wedge design with open cohort and step-length of one quarter. Scope: general practices, Westphalia-Lippe (Germany), caring for BARMER health fund-covered patients. Population: patients (≥18 years) with polypharmacy (≥5 prescriptions). Sample size: initially, 32 patients from each of 539 practices were required for each study arm (17 200 patients/arm), but only 688 practices were randomised after 2 years of recruitment. Design change ensures that 80% power is nonetheless achieved. Intervention: complex intervention eMMa. Follow-up: at least five quarters/cluster (practice). recruitment: practices recruited/randomised at different times; after follow-up, control group practices may access eMMa. Outcomes: primary endpoint is all-cause mortality and hospitalisation; secondary endpoints are number of potentially inappropriate medications, cause-specific hospitalisation preceded by high-risk prescribing and medication underuse. Statistical analysis: primary and secondary outcomes are measured quarterly at patient level. A generalised linear mixed-effect model and repeated patient measurements are used to consider patient clusters within practices. Time and intervention group are considered fixed factors; variation between practices and patients is fitted as random effects. Intention-to-treat principle is used to analyse primary and key secondary endpoints.Ethics and disseminationTrial approved by Ethics Commission of North-Rhine Medical Association. Results will be disseminated through workshops, peer-reviewed publications, local and international conferences.Trial registrationNCT03430336. ClinicalTrials.gov (https://clinicaltrials.gov/ct2/show/NCT03430336).

A wealth of clinically relevant information is only obtainable within unstructured clinical narratives, leading to great interest in clinical natural language processing (NLP). While a multitude of approaches to NLP exist, current algorithm development approaches have limitations that can slow the development process. These limitations are exacerbated when the task is emergent, as is the case currently for NLP extraction of signs and symptoms of COVID-19 and postacute sequelae of SARS-CoV-2 infection (PASC). This study aims to highlight the current limitations of existing NLP algorithm development approaches that are exacerbated by NLP tasks surrounding emergent clinical concepts and to illustrate our approach to addressing these issues through the use case of developing an NLP system for the signs and symptoms of COVID-19 and PASC. We used 2 preexisting studies on PASC as a baseline to determine a set of concepts that should be extracted by NLP. This concept list was then used in conjunction with the Unified Medical Language System to autonomously generate an expanded lexicon to weakly annotate a training set, which was then reviewed by a human expert to generate a fine-tuned NLP algorithm. The annotations from a fully human-annotated test set were then compared with NLP results from the fine-tuned algorithm. The NLP algorithm was then deployed to 10 additional sites that were also running our NLP infrastructure. Of these 10 sites, 5 were used to conduct a federated evaluation of the NLP algorithm. An NLP algorithm consisting of 12,234 unique normalized text strings corresponding to 2366 unique concepts was developed to extract COVID-19 or PASC signs and symptoms. An unweighted mean dictionary coverage of 77.8% was found for the 5 sites. The evolutionary and time-critical nature of the PASC NLP task significantly complicates existing approaches to NLP algorithm development. In this work, we present a hybrid approach using the Open Health Natural Language Processing Toolkit aimed at addressing these needs with a dictionary-based weak labeling step that minimizes the need for additional expert annotation while still preserving the fine-tuning capabilities of expert involvement.

Background:The identification of moderators of exposure-based cognitive behavioral therapy (EXCBT) outcomes has the potential to (1) guide the judicious application of the limited resource that is EXCBT and (2) identify additional treatment targets for ameliorating the deleterious effects of an identified moderator, thereby enhancing clinical response. Experimental and clinical studies have yielded intriguing findings for the moderating influence of positive affect on EXCBT outcomes. Mixed findings for state positive affect (at the time of extinction or exposure trials) as a predictor of EXCBT outcomes stand in contrast to evidence that baseline levels of trait positive affect may be a more effective predictor. As such, questions remain about the best way to assess positive affect as a potential treatment moderator.Objective:This study was designed to investigate (1) the relative value of state and trait positive affect for predicting the outcome of a single-session virtual reality exposure intervention for public speaking anxiety in adults attending college and (2) the role of 3 related constructs—optimism, hopefulness, and mental health self-efficacy—that may explain the predictive significance of trait positive affect.Methods:State affect will be manipulated at an experimental level using affect induction procedures; trait positive affect will be measured at baseline. Three dependent measures—a primary outcome of public speaking anxiety and secondary outcomes of social phobia and self-reported valence—will be examined. This study relies on a team science approach and is being conducted across 12 collaborating sites through the Exposure Therapy Consortium, allowing for replication of all findings across diverse study sites worldwide.Results:Data collection for this study began in October 2024 and ended in August 2025. We expect to complete data analysis and submit results for publication in approximately November 2025.Conclusions:This study will help clarify the relationship among positive affect (state and trait), exposure learning, and 3 related constructs (optimism, hopefulness, and mental health self-efficacy). These findings will illuminate strategies for future treatment improvement and enhanced efficacy.Trial Registration:ClinicalTrials.gov NCT06593847; https://clinicaltrials.gov/study/NCT06593847International Registered Report Identifier (IRRID):DERR1-10.2196/80010