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Species distribution models (SDMs) are becoming an important tool for marine conservation and management. Yet while there is an increasing diversity and volume of marine biodiversity data for training SDMs, little practical guidance is available on how to leverage distinct data types to build robust models. We explored the effect of different data types on the fit, performance and predictive ability of SDMs by comparing models trained with four data types for a heavily exploited pelagic fish, the blue shark (Prionace glauca), in the Northwest Atlantic: two fishery dependent (conventional mark-recapture tags, fisheries observer records) and two fishery independent (satellite-linked electronic tags, pop-up archival tags). We found that all four data types can result in robust models, but differences among spatial predictions highlighted the need to consider ecological realism in model selection and interpretation regardless of data type. Differences among models were primarily attributed to biases in how each data type, and the associated representation of absences, sampled the environment and summarized the resulting species distributions. Outputs from model ensembles and a model trained on all pooled data both proved effective for combining inferences across data types and provided more ecologically realistic predictions than individual models. Our results provide valuable guidance for practitioners developing SDMs. With increasing access to diverse data sources, future work should further develop truly integrative modeling approaches that can explicitly leverage the strengths of individual data types while statistically accounting for limitations, such as sampling biases.

As the largest particle physics laboratory in the world, it is no surprise that CERN has a vast network of thousands of collaborators spread globally. Among CERN’s experiments, ATLAS stands out with over 6,000 active members and 300 associate institutes. This extensive community must go through the standard registering and maintenance procedures within CERN’s human resources database, called Foundation. Simultaneously, the Glance system, among other specific functions, also aims to fulfill the same objectives within the context of different CERN experiments, such as ATLAS, LHCb and ALICE. It achieves that by having its own database. Since members need to exist in the two databases, a lot of data was being duplicated. Manual updates by the ATLAS secretariat became necessary to maintain consistency over members and institutes data, such as names, employment information and authorship status. Today, the Glance system undergoes a transformative process to redefine its relationship with Foundation. The goal is to eliminate duplication of data by establishing a single source of truth. At the same time, the automation of a series of internal processes will be made to ensure synchronization between the two databases at all times, thus removing the need for manual intervention from the ATLAS secretariat. This requires some restructuring to Glance’s database, updates to the code and overall implementation of new tools that facilitate seamless communication with Foundation.

The ATLAS experiment is a particle physics experiment situated at the Large Hadron Collider (LHC) at CERN. It involves almost 6000 members from approximately 300 institutes spread all over the globe and more than 100 papers published every year. This dynamic environment brings some challenges such as how to ensure publication deadlines, communication between the groups involved, and the continuity of workflows. The solution found for those challenges was automation, which was achieved through the Glance project, more specifically through the Glance Analysis systems, developed to support the analysis and publications life cycle in 2011. Now, after twelve years, in order to satisfy the experiments’ most recent needs, the systems need code refactoring and database remodelling. The goal is to have only one system to accommodate all the analysis and publications workflows, the so-called ATLAS Publication Tracking system, an evolution of the current Analysis systems. This project includes a database remodelling that reflects the hierarchical relation between analyses and publications; a code base that supports non-standard workflows; the expansion of the current API so all the authorized ATLAS members can access ATLAS publication data programmatically; a service-oriented architecture for integration with external software, such as GitLab; the creation of an automatic test environment, which assures the quality of the systems on each update. The ATLAS Publication Tracking system is a long-term project being developed with an iterative and incremental approach, which ensures that the most valuable tools are implemented with priority while allowing a smooth transition between the old systems and the new one.

Global climate‐driven ocean warming has decreased dissolved oxygen (DO) levels (ocean deoxygenation) leading to expansions of hypoxic zones, which will affect the movements, behaviour, physiology and distributions of marine animals. However, the precise responses of animals to low DO remains poorly understood because movements and activity levels are seldom recorded alongside instantaneous DO in situ.We describe a new animal‐attached (dissolved oxygen measuring, DOME) archival tag with an optical oxygen sensor for recording DO, in addition to sensors for temperature and depth, a triaxial accelerometer for fine‐scale movements and activity, and a GPS for tag recovery. All sensors were integrated on a single electronic board.Calibration tests demonstrated small mean difference between DOME tag and factory‐calibrated DO sensors (mean relative error of 5%). No temporal drift occurred over a test period three times longer than the maximum deployment time. Deployments on four blue sharks (Prionace glauca) in the central North Atlantic Ocean showed regular vertical oscillations from the surface to a maximum of 404 m. Profiles from diving sharks recorded DO concentrations ranging from 217 to 272 μmol L−1, temperatures between 13°C and 23°C, and identified an oxygen maximum at ~45 m depth, all of which were consistent with ship‐based measurements. Interestingly, the percentage of time sharks spent burst swimming was greater in the top 85 m compared to deeper depths, potentially because of higher prey availability in the surface layer.The DOME tag described blue shark fine‐scale movements and activity levels in relation to accurately measured in situ DO and temperature, with the potential to offer new insights of animal performance in low oxygen environments. Development of a tag with physico‐chemical and movement sensors on a single electronic board is a first step towards satellite relay of these data over broader spatiotemporal scales (months over thousands of kilometres) to determine direct and indirect responses of marine animals to heatwave and deoxygenation events. [ABSTRACT FROM AUTHOR]

Anti‐Spike IgG antibodies against SARS‐CoV‐2, which are elicited by vaccination and infection, are correlates of protection against infection with pre‐Omicron variants. Whether this association can be generalized to infections with Omicron variants is unclear. We conducted a retrospective cohort study with 8457 blood donors in Tyrol, Austria, analyzing 15,340 anti‐Spike IgG antibody measurements from March 2021 to December 2022 assessed by Abbott SARS‐CoV‐2 IgG II chemiluminescent microparticle immunoassay. Using a Bayesian joint model, we estimated antibody trajectories and adjusted hazard ratios for incident SARS‐CoV‐2 infection ascertained by self‐report or seroconversion of anti‐Nucleocapsid antibodies. At the time of their earliest available anti‐Spike IgG antibody measurement (median November 23, 2021), participants had a median age of 46.0 years (IQR 32.8–55.2), with 45.3% being female, 41.3% having a prior SARS‐CoV‐2 infection, and 75.5% having received at least one dose of a COVID‐19 vaccine. Among 6159 participants with endpoint data, 3700 incident SARS‐CoV‐2 infections with predominantly Omicron sublineages were recorded over a median of 8.8 months (IQR 5.7–12.4). The age‐ and sex‐adjusted hazard ratio for SARS‐CoV‐2 associated with having twice the anti‐Spike IgG antibody titer was 0.875 (95% credible interval 0.868–0.881) overall, 0.842 (0.827–0.856) during 2021, and 0.884 (0.877–0.891) during 2022 (all p < 0.001). The associations were similar in females and males (Pinteraction = 0.673) and across age (Pinteraction = 0.590). Higher anti‐Spike IgG antibody titers were associated with reduced risk of incident SARS‐CoV‐2 infection across the entire observation period. While the magnitude of association was slightly weakened in the Omicron era, anti‐Spike IgG antibody continues to be a suitable correlate of protection against newer SARS‐CoV‐2 variants. [ABSTRACT FROM AUTHOR]

Background: Childhood obesity presents a significant public health concern globally, with implications for cardiovascular health and metabolic syndrome. In Portugal, approximately 31.6% of children are affected, highlighting the urgency for intervention strategies. This study aimed to assess the prevalence of overweight and obesity in Portuguese school-aged children, with a focus on sex and age differences. Methods: Anthropometric measurements were conducted on 1564 children aged 6–10 years, including weight, height, and skinfold thickness. Body Mass Index (BMI) and the percentage of body fat were calculated using established methods. Results: The results revealed significant differences in BMI (≤0.001) and body fat percentage (≤0.001) among different BMI categories, with a notable prevalence of overweight and obesity, particularly among boys. A total of 37% of the studied population is overweight or obese, among which 40.1% and 33.9% are boys and girls, respectively. Conclusions: This study highlights statistically significant differences in BMI and body fat percentage for both sexes in different BMI categories. A large proportion of the population is overweight or obese, with a greater prevalence in boys. In short, childhood obesity has a negative impact on body composition and is associated with significant differences in anthropometric parameters, emphasizing the importance of preventative and intervention strategies to address this health problem. [ABSTRACT FROM AUTHOR]

Utilizing techniques for reducing multivariate data is essential for comprehensively understanding the variations and relationships within both biomechanical and physiological datasets in the context of youth football training. Therefore, the objective of this study was to identify the primary factors influencing training sessions within a standard microcycle among young sub-elite football players. A total of 60 male Portuguese youth sub-elite footballers (15.19 ± 1.75 years) were continuous monitored across six weeks during the 2019–2020 in-season, comprising the training days from match day minus (MD-) 3, MD-2, and MD-1. The weekly training load was collected by an 18 Hz global positioning system (GPS), 1 Hz heart rate (HR) monitors, the perceived exertion (RPE) and the total quality recovery (TQR). A principal component approach (PCA) coupled with a Monte Carlo parallel analysis was applied to the training datasets. The training datasets were condensed into three to five principal components, explaining between 37.0% and 83.5% of the explained variance (proportion and cumulative) according to the training day (p < 0.001). Notably, the eigenvalue for this study ranged from 1.20% to 5.21% within the overall training data. The PCA analysis of the standard microcycle in youth sub-elite football identified that, across MD-3, MD-2, and MD-1, the first was dominated by the covered distances and sprinting variables, while the second component focused on HR measures and training impulse (TRIMP). For the weekly microcycle, the first component continued to emphasize distance and intensity variables, with the ACC and DEC being particularly influential, whereas the second and subsequent components included HR measures and perceived exertion. On the three training days analyzed, the first component primarily consisted of variables related to the distance covered, running speed, high metabolic load, sprinting, dynamic stress load, accelerations, and decelerations. The high intensity demands have a high relative weight throughout the standard microcycle, which means that the training load needs to be carefully monitored and managed. [ABSTRACT FROM AUTHOR]

Migrant students tend to underperform in Science, Technology, Engineering, and Mathematics (STEM) subjects and are less likely to pursue higher education in STEM when compared with their nonmigrant peers. Given the substantial increase in migration, this disparity has been a central concern in science education in many European countries. The purpose of this study was to investigate the effectiveness of an innovative science outreach program that brings together migrant students and STEM professionals with the same linguistic and cultural backgrounds. The program consists of one‐off workshops that follow an inquiry‐based approach and include hands‐on activities and science communication in the students' heritage language. Using surveys with adapted scales and open‐ended questions, we applied a randomized block design with waitlist control groups and repeated measures. Eighty‐three Portuguese‐speaking migrant students aged 6–17 years participated in the workshops in Germany and the United Kingdom. Results indicate that both the students and STEM professionals evaluated the program positively and that students who participated in the workshops tended to demonstrate an increase in their attainment value for science and an increase in their self‐concept of ability for the heritage language 4 weeks after the intervention when compared with students in the control condition. These effects were particularly pronounced for students with low prior motivation to study science or speak the heritage language. Our results thus show that it is possible to foster migrant students' attainment value for science and increase their self‐concept of ability regarding the heritage language through a brief science outreach intervention. [ABSTRACT FROM AUTHOR]

Background Immunocompromised patients (ICPs) have an increased risk for a severe and prolonged COVID-19. SARS-CoV-2 monoclonal antibodies (mAbs) were extensively used in these patients, but data from randomized trials that focus on ICPs are lacking. We evaluated the clinical and virological outcome of COVID-19 in ICPs treated with mAbs across SARS-CoV-2 variants. Methods In this multicenter prospective cohort study, we enrolled B-cell– and/or T-cell–deficient patients treated with casirivimab/imdevimab, sotrovimab, or tixagevimab/cilgavimab. SARS-CoV-2 RNA was quantified and sequenced weekly, and time to viral clearance, viral genome mutations, hospitalization, and death rates were registered. Results Two hundred and forty five patients infected with the Delta (50%) or Omicron BA.1, 2, or 5 (50%) variant were enrolled. Sixty-seven percent were vaccinated; 78 treated as outpatients, of whom 2 required hospital admission, but both survived. Of the 159 patients hospitalized at time of treatment, 43 (27%) required mechanical ventilation or died. The median time to viral clearance was 14 days (interquartile range, 7–22); however, it took >30 days in 15%. Resistance-associated spike mutations emerged in 9 patients in whom the median time to viral clearance was 63 days (95% confidence interval, 57–69; P <.001). Spike mutations were observed in 1 of 42 (2.4%) patients after treatment with 2 active mAbs, in 5 of 34 (14.7%) treated with actual monotherapy (sotrovimab), and 3 of 20 (12%) treated with functional monotherapy (ie, tixagevimab/cilgavimab against tixagevimab-resistant variant). Conclusions Despite treatment with mAbs, morbidity and mortality of COVID-19 in ICPs remained substantial. Combination antiviral therapy should be further explored and may be preferred in severely ICPs. [ABSTRACT FROM AUTHOR]