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Introduction Genetic variations impact drug response, driving the need for personalised medicine through pre-emptive pharmacogenetic testing. However, the adoption of pre-emptive pharmacogenetic testing for commonly prescribed drugs, such as statins, outside of tertiary hospitals is limited due to a lack of pharmacoeconomic evidence to support widespread implementation by healthcare policy-makers. The Spanish Consortium for the Implementation of Pharmacogenetics (iPHARMGx Consortium) addresses this by developing a clinical trial master protocol that will govern multiple nested adaptive clinical trials that compare genotype-guided treatments to standard care in specific drug–gene–population triads, asses their cost-efficacy and identify novel biomarkers through advanced sequencing techniques. The first of these studies aims to assess whether a pre-emptive statin therapy genotyping scheme reduces the incidence of statin-associated muscle symptoms (SAMS) in a population at risk of cardiovascular disease susceptible of receiving high-intensity or moderate-intensity doses of statins: The PREVESTATGx trial.Methods and analysis the PREVESTATGX trial is a multicentre, adaptive randomised controlled pragmatic phase IV clinical trial nested to the iPHARMGx master protocol with two parallel arms, aiming for superiority. Randomisation will be conducted on an individual basis with a centralised approach and stratification by centre. After inclusion in the trial and genotyping has been performed, subjects will be randomly allocated to experimental group (pharmacogenetic genotype-guided statin prescription) or standard-of-care statin prescription (as deemed by attending physician). The main objective is to assess the efficacy of a statin pre-emptive genotyping strategy in reducing the incidence of SAMS. A total of 225 subjects will be recruited among the 10 participating centres if no futility/efficacy boundary is reached in the prespecified interim analyses. Recruitment will be carried out during a 12-month period and subjects will be followed for a 9-month period.Ethics and dissemination The PREVESTATGx trial received ethical approval on 24 April 2024. Results will be disseminated via publication in peer-reviewed journals as well as presentation at international conferences. Trial results will be submitted for publication in an open-access peer-reviewed medical speciality-specific publication.Trial registration number EU CT number: 2023-509418-12-00/Clinical trial Identifier (ClinicalTrials.gov): NCT06262685. Protocol version 1.2 12 April 2024 (includes non-substantial modification number 14 June 2024). Trial registration of this study can be located at both the EU Clinical Trials Register available from https:// euclinicaltrials.eu/search-for-clinical-trials/?lang=en and https://clinicaltrials.gov. Registration on both websites was done before the enrolment of the first patient complying with European regulations. EU Clinical Trials Register is a primary registry according to the WHO.

RESUMEN Se trata de una mujer de 57 años con antecedentes de linfoma MALT gástrico y nefritis intersticial atribuida a la quimioterapia. En el estudio de diarrea crónica encontramos un páncreas atrófico, con deficiencia de elastasa. Se sospecha pancreatitis autoinmune. Se comprueba una elevación importante de IgG4 sérica. Con estos datos se procede a la revisión de la biopsia renal realizada 10 meses antes. La inmunohistoquímica revela un número significativo de células plasmáticas productoras de IgG4. En los pulmones la paciente tiene nódulos, adenopatías e infiltrados. El diagnóstico al que llegamos es Enfermedad relacionada con IgG4. ABSTRACT This is a 57-year-old woman with a history of gastric MALT lymphoma and interstitial nephritis attributed to chemotherapy. In the study of chronic diarrhea, we found an atrophic pancreas, with elastase deficiency. Autoimmune pancreatitis is suspected. There is a significant elevation of serum IgG4. With these data we proceed to the review of the renal biopsy performed 10 months before. Immunohistochemistry reveals a significant number of IgG4-producing plasma cells. In the lungs the patient has nodules, lymphadenopathy and infiltrates. The diagnosis we reached is IgG4-related disease.

This work demonstrates the feasibility of an individual pitch control strategy based on nacelle yaw misalignment measurements to mitigate the platform yaw drift in upwind floating offshore wind turbines, which is caused by the vertical moment produced by the rotor. This moment acts on the platform yaw degree of freedom, being of great importance in systems that have low yaw stiffness. Among them, single-point-mooring platforms are one of the most important ones. During recent years, several floating wind turbine concepts with single-point-mooring systems have been proposed, which can theoretically dispense with the yaw mechanism due to their ability to rotate and align with environmental conditions (weather-vaning). However, in this paper it is proven that the vertical moment overcomes the orienting ability, causing the yaw drift. With the intention of reducing the induced yaw response of a single-point-mooring floating wind turbine, an individual pitch control strategy based on nacelle yaw misalignment is applied, which introduces a counteracting moment. The control strategy is validated by numerical simulations using the 5 MW National Renewable Energy Laboratory (NREL) wind turbine mounted on a single-point-mooring version of the DeepCwind OC4 floating platform to demonstrate that it can mitigate the yaw drift and therefore maintain the alignment of the wind turbine rotor with the wind.

The field of pharmacogenetics (PGx) holds great promise in advancing personalized medicine by adapting treatments based on individual genetic profiles. Despite its benefits, there are still economic, ethical and institutional barriers that hinder its implementation in our healthcare environment. A retrospective analysis approach of anonymized data sourced from electronic health records was performed, encompassing a diverse patient population and evaluating key parameters such as prescribing patterns and test results, to assess the impact of pharmacogenetic testing. A head-to-head comparison with previously published activity results within the same pharmacogenetic laboratory was also conducted to contrast the progress made after 10 years. The analysis revealed significant utilization of pharmacogenetic testing in daily clinical practice, with 1,145 pharmacogenetic tests performed over a 1-year period and showing a 35% growth rate increase over time. Of the 17 different medical departments that sought PGx tests, the Oncology department accounted for the highest number, representing 58.47% of all genotyped patients. A total of 1,000 PGx tests were requested for individuals susceptible to receive a dose modification based on genotype, and 76 individuals received a genotype-guided dose adjustment. This study presents a comprehensive descriptive analysis of real-world data obtained from a public tertiary hospital laboratory specialized in pharmacogenetic testing, and presents data that strongly endorse the integration of pharmacogenetic testing into everyday clinical practice.

The EU and UK have made ambitious commitments under the net-zero plans to decarbonise their economies by 2050. For this, offshore wind will play a major role, significantly contributing to a paradigm shift in the power generation and greater volatility of electricity prices. The operating strategy of wind farms should therefore move from power maximisation to profit maximisation which includes income from providing power system services and the reduction of maintenance costs. Wind farm flow control (WFFC) is a key enabler for this shift through mitigation of wake effects in the design and operation phases. The results of the FarmConners market showcases presented here are the first attempt to economically assess WFFC strategies with respect to electricity market prices. Here, we present a conceptual simulation study starting from individual turbine control and extend it to layouts with 10 and 32 turbines operated with WFFC based on the results of five participants. Each participant belonged to a different research group with their respective simulation environments, flow models and WFFC strategies. Via a comparative analysis of relative WFFC benefits estimated per participant, the implications of wind farm size, the applied control strategy and the overall model fidelity are discussed in zero-subsidy scenarios. For all the participants, it is seen that the income gain can differ significantly from the power gain depending on the electricity price under the same inflow, and a favourable control strategy for dominant wind directions can pay off even for low electricity prices. However, a strong correlation between income and power gain is also observed for the analysed high-electricity-price scenarios, underlining the need for additional modelling capabilities to carry out a more comprehensive value optimisation including lower prices and system requirements driven cases.

We introduce how the Galaxy research environment (Jalili et al. 2020) integrates with RO-Crate as an implementation of Findable Accessible Interoperable Reproducible Digital Objects (FAIR Digital Objects / FDO) (Wilkinson et al. 2016, Schultes and Wittenburg 2018) and how using RO-Crate as an exchange mechanism of workflows and their execution history helps integrate Galaxy with the wider ecosystem of ELIXIR (Harrow et al. 2021) and the European Open Science Cloud (EOSC-Life) to enable FAIR and reproducible data analysis.RO-Crate (Soiland-Reyes et al. 2022) is a generic packaging format containing datasets and their description using standards for FAIR Linked Data. The format is based on schema.org (Guha et al. 2016) annotations in JSON-LD, which allows for rich metadata representation. The RO-Crate effort aims to make best-practice in formal metadata description accessible and practical for use in a wider variety of situations, from an individual researcher working with a folder of data, to large data-intensive computational research environments.The RO-Crate community brings together practitioners from very different backgrounds, and with different motivations and use cases. Among the core target users are:researchers engaged with computation and data-intensive, workflow-driven analysis;digital repository managers and infrastructure providers;individual researchers looking for a straightforward tool or how-to guide to “FAIRify” their data;data stewards supporting research projects in creating and curating datasets.Given the wide applicability of RO-Crate and the lack of practical implementations of FDOs, ELIXIR (Harrow et al. 2021) co-opted this initiative as the project to define a common format for research data exchange and repository entries. Thus, during the last year it’s been implemented in a wide range of services, such as: WorkflowHub (Goble et al. 2021) (a registry for describing, sharing and publishing scientific computational workflows) uses RO-Crates as an exchange format to improve reproducibility of computational workflows that follow the Workflow RO-Crate profile (Bacall et al. 2022); LifeMonitor (Leo et al. 2022) (a service to support the sustainability of computational workflows being developed as part of the EOSC-Life project) uses RO-Crate as an exchange format for describing test suites associated with workflows. Tools have been developed towards aiding the previously mentioned use cases and increasing the general usability of RO-Crates by providing a user-friendly (programmatic) interface for consumption and production of RO-Crates through programmatic libraries for consuming/producing RO-Crates (ro-crate-py De Geest et al. 2022, ro-crate-ruby Bacall and Whitwell 2022, ro-crate-js Lynch et al. 2021).The Galaxy project provides a research environment with data analysis and data management functionalities as a multi user platform, aiming to make computational biology accessible to research scientists that do not have computer programming or systems administration experience. As such, it stores not just analysis related data but also the complete analytical workflow, including its metadata. The internal data model involves the history entity, including all steps performed in a specific analysis, and the workflow entity, defining the structure of an analytical pipeline. From the start, Galaxy aims to enable reproducible analyses by providing capabilities to export (and import) all the analysis history details and workflow data and metadata in a FAIR way. As such it helps its users with the daily research data management. The Galaxy community is continuously improving and adding features, the integration of the FAIR Digital Object principles is a natural next step in this. To be able to support these FDOs, Galaxy leverages the RO-Crate Python client library (De Geest et al. 2022) and provides multiple entry points to import and export different research data objects representing its internal entities and associated metadata. These objects include:a workflow definition, which is used to share/publish the details of an analysis pipeline, including the graph of tools that need to be executed, and metadata about the data types requiredindividual data files or a collection of datasets related to an analysis historya compressed archive of the entire analysis history including the metadata associated with it such as the tools used, their versions, the parameters chosen, workflow invocation related metadata, inputs, outputs, license, author, CWLProv description (Khan et al. 2019) of the workflow, contextual references in the form of Digital Object Identifiers (DOIs), ‘EMBRACE Data And Methods’ ontology (EDAM) terms (Ison et al. 2013), etc. The adoption of RO-crate by Galaxy allows a standardised exchange of FDOs with other platforms in the ELIXIR Tools ecosystem, such as WorkflowHub and LifeMonitor. Integrating RO-Crate deeply into Galaxy and offering import and export options of various Galaxy objects such as Research Objects allows for increased standardisation, improved Research Data Management (RDM) functionalities, smoother user experience (UX) as well as improved interoperability with other systems. The integration in a platform used by biologists to do data intensive analysis, facilitates the publication of workflows and workflow invocations for all skill levels and democratises the ability to perform Open Science.

This paper describes the results of a wave tank test campaign of a 1/49 scaled SATH 10 MW floating platform. The software-in-the-loop (SiL) hybrid method was used to include the wind turbine thrust and the in-plane rotor moments. Experimental results are compared with a numerical model developed in OpenFAST of the floating wind turbine. The tank test campaign was carried out in the scaled model tested at the deep ocean basin from the Lir National Ocean Test Facility at Cork, Ireland. This floating substructure design was adapted by Saitec to support the 10 MW wind turbine within the ARCWIND project (Adaptation and Implementation of Floating Wind Energy Conversion Technology for the Atlantic Region) with the aim of withstanding the environmental conditions of the European Atlantic Area region. CENER provided the wind turbine controller specially designed for the SATH 10 MW configuration. A description of the experimental setup, force actuator configuration and the numeric aerodynamic parameters is provided in this work. The most relevant experimental results under wind and wave loading are shown in time series and frequency domain. The influence of the submerged geometry variations in the pitch natural frequency is discussed. The paper shows the simulation of a case with rated wind speed, where the tilted geometry for the computation of the hydrostatic and hydrodynamic properties of the submerged substructure is considered. This case provides a better agreement of the pitch natural frequency with the experiments than an equivalent simulation using the undisplaced geometry mesh for the computation of the hydrodynamic and hydrostatic properties.

Wind farm flow control (WFFC) is a topic of interest at several research institutes and industry and certification agencies worldwide. For reliable performance assessment of the technology, the efficiency and the capability of the models applied to WFFC should be carefully evaluated. To address that, the FarmConners consortium has launched a common benchmark for code comparison under controlled operation to demonstrate its potential benefits, such as increased power production. The benchmark builds on available data sets from previous field campaigns, wind tunnel experiments, and high-fidelity simulations. Within that database, four blind tests are defined and 13 participants in total have submitted results for the analysis of single and multiple wakes under WFFC. Here, we present Part I of the FarmConners benchmark results, focusing on the blind tests with large-scale rotors. The observations and/or the model outcomes are evaluated via direct power comparisons at the upstream and downstream turbine(s), as well as the power gain at the wind farm level under wake steering control strategy. Additionally, wake loss reduction is also analysed to support the power performance comparison, where relevant. The majority of the participating models show good agreement with the observations or the reference high-fidelity simulations, especially for lower degrees of upstream misalignment and narrow wake sector. However, the benchmark clearly highlights the importance of the calibration procedure for control-oriented models. The potential effects of limited controlled operation data in calibration are particularly visible via frequent model mismatch for highly deflected wakes, as well as the power loss at the controlled turbine(s). In addition to the flow modelling, the sensitivity of the predicted WFFC benefits to the turbine representation and the implementation of the controller is also underlined. The FarmConners benchmark is the first of its kind to bring a wide variety of data sets, control settings, and model complexities for the (initial) assessment of farm flow control benefits. It forms an important basis for more detailed benchmarks in the future with extended control objectives to assess the true value of WFFC.

Digoxin poisonings are relatively common and potentially fatal, requiring immediate therapeutic intervention, with special attention to the patient's hemodynamic status and the presence of electrocardiographic and electrolytic disturbances. To identify factors associated with seven-day and thirty-day mortality in digoxin poisoning. A retrospective, observational, multicenter study was conducted across 15 Hospital Emergency Departments (HED) in Spain. All patients over 18 years of age who presented to participating HEDs from 2015 to 2021 were included. The inclusion criteria encompassed individuals meeting the criteria for digoxin poisoning, whether acute or chronic. To identify independent factors associated with 7-day and 30-day mortality, a multivariate analysis was conducted. This analysis included variables of clinical significance, as well as those exhibiting a trend (p < 0.1) or significance in the bivariate analysis. A total of 658 cases of digoxin poisoning were identified. Mortality rates were 4.5% (30 patients) at seven days and 11.1% (73 patients) at thirty days. Regarding 7-day mortality, the mean age of deceased patients was comparable to survivors (84.7 (8.9) vs 83.9 (7.9) years; p = ns). The multivariate analysis revealed that factors independently associated with 7-day mortality encompassed the extent of dependence assessed by the Barthel Index (BI 60–89 OR 0.28; 95% CI 0.10–0.77; p = 0.014 and BI>90 OR 0.22; 95% CI 0.08–0.63; p = 0.005), the identification of ventricular arrhythmias (OR 1.34; 95% CI 1.34–25.21; p = 0.019), and the presence of circulatory (OR 2.84; 95% CI 1.19–6.27; p = 0.019) and neurological manifestations (OR 2.67; 95% CI 1.13–6.27; p = 0.025). Factors independently associated with 30-day mortality encompassed extent of dependence (BI 60–89 OR 0.37; 95% CI 0.20–0.71; p = 0.003 and BI>90 OR 0.18; 95% CI 0.09–0.39; p < 0.001) and the identification of circulatory (OR 2.13; 95% CI 1.10–4.15; p = 0.025) and neurological manifestations (OR 2.39; 95% CI 1.25–3.89; p = 0.006). The study identifies the degree of dependency assessed by the Barthel Index and the presence of cardiovascular and neurological symptoms as independent predictors of both 7-day and 30-day mortality. Additionally, the detection of ventricular arrhythmia is also an independent factor for 7-day mortality. • Digoxin poisoning is a common, life-threatening issue. • Frailty and comorbidities should be considered, given the high prevalence of this poisoning in the elderly. • Identifying factors linked to mortality in the initial assessment warrants closer patient monitoring. [ABSTRACT FROM AUTHOR]

The current state of much of the Wuhan pneumonia virus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) research shows a regrettable lack of data sharing and considerable analytical obfuscation. This impedes global research cooperation, which is essential for tackling public health emergencies and requires unimpeded access to data, analysis tools, and computational infrastructure. Here, we show that community efforts in developing open analytical software tools over the past 10 years, combined with national investments into scientific computational infrastructure, can overcome these deficiencies and provide an accessible platform for tackling global health emergencies in an open and transparent manner. Specifically, we use all SARS-CoV-2 genomic data available in the public domain so far to (1) underscore the importance of access to raw data and (2) demonstrate that existing community efforts in curation and deployment of biomedical software can reliably support rapid, reproducible research during global health crises. All our analyses are fully documented at https://github.com/galaxyproject/SARS-CoV-2.

For mass spectrometry-based peptide and protein quantification, label-free quantification (LFQ) based on precursor mass peak (MS1) intensities is considered reliable due to its dynamic range, reproducibility, and accuracy. LFQ enables peptide-level quantitation, which is useful in proteomics (analyzing peptides carrying post-translational modifications) and multi-omics studies such as metaproteomics (analyzing taxon-specific microbial peptides) and proteogenomics (analyzing non-canonical sequences). Bioinformatics workflows accessible via the Galaxy platform have proven useful for analysis of such complex multi-omic studies. However, workflows within the Galaxy platform have lacked well-tested LFQ tools. In this study, we have evaluated moFF and FlashLFQ, two open-source LFQ tools, and implemented them within the Galaxy platform to offer access and use via established workflows. Through rigorous testing and communication with the tool developers, we have optimized the performance of each tool. Software features evaluated include: (a) match-between-runs (MBR); (b) using multiple file-formats as input for improved quantification; (c) use of containers and/or conda packages; (d) parameters needed for analyzing large datasets; and (e) optimization and validation of software performance. This work establishes a process for software implementation, optimization, and validation, and offers access to two robust software tools for LFQ-based analysis within the Galaxy platform.