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Introduction Birth cohorts are valuable resources for studying early life, the determinants of health, disease, and development. They are essential for studying life course. Dynamic longitudinal electronic cohorts use routinely collected data, are live, and can reduce selection bias specifically associated with direct recruitment in traditional birth cohorts. However, they are limited to health and administrative data and may lack contextual information. The MIREDA (Mother and Infant Research Electronic Data Analysis) partnership creates a UK-wide birth cohort by aligning existing electronic birth cohorts to have the same structure, content, and vocabularies, enabling UK-wide federated analyses. Objectives 1) Create a core dynamic, live UK-wide electronic birth cohort with approximately 500,000 new births per year using a common data model (CDM). 2) Provide data linkage and automation for long-term follow up of births from the Clinical Practice Research Datalink (CPRD), MuM-PreDiCT and the `Born in' initiatives of Bradford, Wales, Scotland, and South London for comparable analyses. Methods We will establish core data content and collate linkable data. A suite of extraction, transformation, and load (ETL) tools will be used to transform data for each birth cohort into the CDM. Transformed datasets will remain within each cohort's trusted research environment (TRE). Metadata will be uploaded for the public to the Health Data Research (HDRUK) Innovation Gateway. We will develop a single online data access request for researchers. A cohort profile will be developed for researchers to reference the resource. Ethics Each cohort has approval from their TRE through compliance with their project application processes and information governance. Dissemination We will engage with researchers in the field to promote our resource through partnership networking, publication, research collaborations, conferences, social media, and marketing communications strategies.

Objective Construct an innovative open-learning solution that provides comprehensive training specific to Trusted Research Environments (TRE) and the broader research community of administrative data users, irrespective of their proficiency levels. DOL offers training opportunities tailored to meet each user's unique learning needs, enabling them to utilise complex, linked administrative datasets confidently and effectively for meaningful research outcomes, thereby building capacity for sustainable national data infrastructure. Approach DOL’s innovative open-learning solution offers two learning formats: adaptive and experiential. Adaptive learning provides registered users with bitesize self-paced training based on Administrative Data Research UK's priorities. Experiential learning involves online workgroups with real-world context and practical application. They meet twice a year and are designed around specific topics with frequent guest speakers who are experts in their fields. Conclusion DOL’s innovative open-learning solution empowers TREs, such as SAIL Databank, to provide well-rounded learning that fosters community support, knowledge-sharing, and networking opportunities for its users, while gathering valuable user feedback. Users can personalise learning and test their knowledge in a flexible training environment, allowing them to take charge of their learning journey. Implication In response to the increasing demand for training services from novice to advanced users, SAIL Databank adopted DOL's dual learning approach by (1) developing training courses that cover access, process, methodology, integration, and analytical tools for SAIL TRE users, (2) engaging users in a series of workgroups focused on themed datasets including Justice, Environmental, Maternal, Education, and Core Health.

Introduction When a child has suffered, or is at risk of suffering, significant harm from parents or caregivers, the local authority may issue Section 31 (s.31) Care and Supervision proceedings under the Children Act (1989). Objectives We compared the healthcare use of infants less than one year old subject to s.31 proceedings in Wales (n = 1,332),to that of a comparison group of infants not subject to s.31 proceedings (n = 204,417), between January 2011 and February 2020. Methods Population-based e-cohort study utilising data held in the Secure Anonymised Information Linkage (SAIL) Databank. Infants in s.31 proceedings were identified using the Children and Family Court Advisory and Support Service dataset. This was linked to demographic and healthcare datasets, to identify General Practice (GP) visits, emergency department (ED) attendances, and hospital admissions (emergency and elective); before the study end date or the child's first birthday for the comparison group, orbefore the s.31 application date.Regression analysis calculated event rate ratios [RR] and incidence rate ratios [IRR] for healthcare events, adjusting for widerdeterminants of health (e.g. perinatal factors, maternal mental health, deprivation), and investigated reasons for healthcare use. Results Infants in s.31 proceedings had ahigher number and incidence of healthcare events compared with the comparison group, across all healthcare settings. Differences were greatest for emergency hospital admissions (IRR = 4.03, 95% confidence interval [CI] = 3.53 - 4.59; RR = 4.60, CI = 3.90 - 5.41). "Injury and poisoning" was the main reason for emergency admissions amongst infants in s.31 proceedings. For ED presentations, emergency hospital admissions, and GP visits, there were proportionally more events for these infants across all top ten reasons for healthcare. Conclusions Findings highlight greater healthcare utilisation for infants involved in s.31 proceedings in Wales, helping to build a better understanding of their needs and vulnerabilities.

A mixed metal oxide W-TiO2 nanopowder photocatalyst was prepared by using the sol–gel method with a broad range of elemental compositions x = CW/(CW + CTi), including TiO2 and WO3. The material was structurally characterized and evaluated in adsorption and photocatalytic processes by testing its removal capacity of a representative pollutant methylene blue (MB) in aqueous solutions and under UV-A and sunlight illuminations. The nanopowders appeared to be more effective adsorbents than pure TiO2 and WO3 materials, showing a maximum at 15 mol% W, which was set as the tungsten solubility limit in anatase titania. At the same time, the photocatalytic decomposition of MB peaked at 2 mol% W. The examination of different compositions showed that the most effective MB removal took place at 15 mol% W, which was attributed to the combined action of adsorption and heterogeneous photocatalysis. Moreover, MB decomposition under sunlight was stronger than under UV-A, suggesting photocatalyst activation by visible light. The pollutant removal efficiency of the material with 15 mol% W was enhanced by a factor of ~10 compared to pure TiO2 at the beginning of the process, which shows its high potential for use in depollution processes in emergency cases of a great pollutant leak. As a result, a Wx=0.15-TiO2 catalyst could be of high interest for wastewater purification in industrial plants. [ABSTRACT FROM AUTHOR]