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The 2018 international SMA care guidelines were developed before disease-modifying treatments transformed SMA progression and prognosis. Focused on paediatric care, they were based on minimal standards and did not address the evolving phenotypes resulting from new treatments.SMA CARE UK, a collaborative initiative involving patients, healthcare professionals and stakeholders, was created to update, harmonise and support the implementation of evidence-based care standards for SMA across the UK. The project is hosted by SMA UK and rolled out over 3 years with the support of the University of Newcastle and the SMA Reach clinical networks. Expert working groups, including patient representatives and clinical specialists, focus on specific care topics.The current guidelines are being reviewed to identify areas needing revision based on new evidence, changing practices and unmet needs. It aims to create relevant, evidence-based recommendations for specific care areas, highlight knowledge gaps and explore strategies to gather necessary evidence.Final recommendations will be published in professional and patient-friendly formats after consultation with clinical and patient networks. Endorsement will be sought from professional bodies and findings will be presented at conferences.The initiative also aims to establish a UK minimum standard of care to address regional inequalities, support families and promote dialogue about optimal management. Collaboration with global networks will enhance research, data collection, and alignment with international standards.vanessa.christie-brown@smauk.org.uk

The article introduces a conceptual system design of AI systems as self-healing distributed networks that can ensure the integrity of operation in cloud, edge, and device environments. The increasingly sophisticated AI deployments are not kept alive by traditional fault tolerance mechanisms, which are not sufficient in maintaining their continuity of learning and quality of inferences through failures. The architecture suggested integrates intelligence into every layer of the infrastructure and algorithm, which allows the infrastructure to keep sensing, diagnosing, and adapting via a multi-layered feedback loop that was based on the biological homeostasis. By arranging self-healing skills into micro, meso, and macro-level control systems, the system can react suitably to varying forms of failures and be coherent globally. The framework incorporates specialized elements of health monitoring, diagnosis, recovery planning, execution, and adaptation that all make up a closed-loop learning system. The case studies show how these principles are implemented in the edge-cloud collaborative systems, large-scale model training, and real-time AI services. Although the results are promising, there are still major challenges in complexity management, observability, resource overhead, and validation methodologies, which indicate research opportunities in formal methods and causal learning, meta-learning, and human-AI collaboration.

BackgroundUK low vision services are historically fragmented. Lack of standardised commissioning or clinical framework means many people with sight loss cannot access fit for purpose services. The Adult Low Vision Service Quality Framework was developed with extensive cross-sector collaboration to help improve commissioning and support the planning and evaluation of new/existing low vision services.MethodsLiterature searches on low vision standards, governance and service guidance were conducted. Following a survey of UK low vision practitioners we created a group of representatives from the hospital eye service, primary care optometry, orthoptics, universities, vision rehabilitation specialists, people with lived experience and third sector organisations to collaboratively determine the components of a high-quality low vision service and potential barriers to providing care. A draft framework was piloted within low vision sites before creating a final version. Good Practice Guidelines were produced to support and explain each of the criteria.ResultsThe result of this extensive 4-year collaboration is the publication of The Adult Low Vision Services Quality Framework, endorsed by 12 sector organisations plus supporting Good Practice Guidance.ConclusionIf the framework is adopted as a quality standard by all UK low vision services patients will be able to access timely, high-quality support wherever they live, and commissioners will be upskilled to make good decisions in terms of funding new services. The RNIB Adult Low Vision Services Quality Framework forms a key part of the commitment of the NHS to provide an eye care support pathway alongside the clinical care pathways.