St James's University Hospital is in Leeds, West Yorkshire, England and is popularly known as Jimmy's. It is one of the United Kingdom's most famous hospitals due to its coverage on television. It is managed by the Leeds Teaching Hospitals NHS Trust.
Internal anatomical motion challenges precise radiation delivery during external beam radiotherapy. Estimating and compensating for anatomical motion are essential for improving planned dose delivery to target volumes while sparing organs-at-risk. This research achieves accurate motion prediction using only planar X-ray imaging from conventional linear accelerators, without surrogate signals or invasive fiducial markers. We propose Deep-Motion-Net: a patient-specific end-to-end graph neural network (GNN) enabling 3D volumetric organ reconstruction from single in-treatment kV planar X-ray images at arbitrary projection angles. A 2D convolutional neural network (CNN) encoder extracts image features, which four feature pooling networks fuse to a 3D template organ mesh. A ResNet-based graph attention network then deforms the feature-encoded mesh. Training uses synthetically generated organ motion instances and corresponding kV images, created by deforming a reference CT volume aligned with the template mesh, generating digitally reconstructed radiographs (DRRs) at required angles, and applying DRR-to-kV style transfer via conditional CycleGAN. Quantitative testing on synthetic respiratory motion scenarios and qualitative assessment on in-treatment images from four liver cancer patients demonstrated overall mean prediction errors of 0.16 ± 0.13 mm, 0.18 ± 0.19 mm, 0.22 ± 0.34 mm, and 0.12 ± 0.11 mm across datasets. Mean peak prediction errors were 1.39 mm, 1.99 mm, 3.29 mm, and 1.16 mm. This approach leverages accessible in-treatment imaging, avoiding expensive MRI systems or invasive markers. To the best of our knowledge, this is the first deep learning framework reconstructing volumetric 3D organ models from single-view images at arbitrary angles throughout an entire in-treatment scan series. Our approach achieves sub-millimetre accuracy when validated on synthetic motion instances and demonstrates clinical feasibility on real-treatment kV images, for which volumetric ground truth is inherently unavailable. The code is available at https://github.com/isurusuranga/DeepMotionNet .
Metabolic dysfunction-associated steatohepatitis (MASH), a potentially progressive form of metabolic dysfunction-associated steatotic liver disease (MASLD), increases risk of fibrosis progression, cirrhosis, and liver-related and cardiometabolic morbidity. The first licensed pharmacotherapies, resmetirom and semaglutide, mark a shift in management but practical guidance for real-world implementation is lacking. The British Association for the Study of the Liver and British Society of Gastroenterology MASLD special interest group developed consensus recommendations on patient selection, lifestyle management, and follow-up for MASLD-MASH-specific pharmacotherapy. 37 participants participated in a Delphi process where draft statements developed in working groups were anonymously rated, discussed, and refined. Consensus (≥80% agreement) was reached for 49 statements. The group agreed on the following general recommendation. Two-step non-invasive tests, including the Fibrosis-4 index and vibration-controlled transient elastography, are recommended to identify patients with presumed stage F2-F3 fibrosis (ie, at-risk MASH). Individuals with liver stiffness more than 10 kPa but without evidence of cirrhosis should be considered eligible for treatment. Lifestyle behaviour change intervention should accompany pharmacological treatment, delivered by suitably trained practitioners without delaying access to medication. Treatment discontinuation is advised with evidence of disease progression, cirrhosis development, or drug-induced liver injury. These recommendations offer pragmatic guidance to clinicians and consensus clinical opinion to regulatory bodies to support equitable and effective use of new MASLD-MASH therapies.
Still’s disease exemplifies systemic inflammatory disorders existing on a continuum between autoinflammation and autoimmunity. This review examines Still’s disease through this spectrum lens, integrating recent advances in pathogenesis, clinical heterogeneity, and therapeutic approaches. Emerging mechanistic insights reveal complex innate-adaptive immune interactions. Type I interferon signalling and neutrophil extracellular trap formation drive inflammation, while hyperferritinemia actively perpetuates disease through Msr1-mediated signaling. mTORC1 has emerged as a central integration hub converging multiple cytokine signals. Adaptive mechanisms increasingly contribute to complications: both macrophage activation syndrome and lung disease demonstrate IFNγ-dominant pathology with T cell hyperactivation. Clinical phenotyping identifies distinct patient clusters—from hyperferritinemic monocyclic to catastrophic multiorgan phenotypes—reflecting varying innate-adaptive contributions. Current classification criteria permit considerable diagnostic latitude and may inadvertently group mechanistically distinct conditions under a single diagnostic label. IL-1 and IL-6 receptor blockade remain therapeutic cornerstones, with evidence supporting early intervention during a window of opportunity. Novel approaches including IL-18 binding protein, JAK inhibitors, and IFNγ blockade show promise in refractory disease. Still's disease predominantly reflects autoinflammatory pathology driven by innate immune dysregulation, yet adaptive mechanisms contribute meaningfully to disease heterogeneity and complications. Recognition as a spectrum disorder—with variable innate-adaptive contributions across patients and disease phases—supports unification of pediatric and adult forms, guides mechanistically targeted therapies, and emphasizes the need for biomarker-driven patient stratification to enable personalized treatment approaches.
The objective of this study was to describe the establishment, structure and influence of the United Kingdom national multidisciplinary team (MDT) for vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic (VEXAS) syndrome and to assess its clinical outputs and perceived value among participating clinicians. All patients discussed at the national VEXAS MDT between June 2024 and May 2025 were included. Clinical information was extracted from standardised referral forms, and MDT recommendations were reviewed. An anonymised questionnaire evaluated clinicians' experience of the MDT. Forty-two patients from 27 centres were reviewed; 36 (85.7%) had confirmed VEXAS syndrome and 6 had VEXAS-like disease. Almost all were male (41/42), with a median age of 70 years. Before MDT review, 62% received corticosteroid monotherapy. MDT recommendations favoured steroid-sparing strategies, with marked increases in the use of azacitidine (1-22 patients) and tocilizumab (5-15 patients), alongside reduced use of conventional disease-modifying anti-rheumatic drugs (DMARDs). Four patients were referred for haematopoietic stem cell transplantation. Twenty of 43 MDT members completed the survey, reporting greater confidence in managing VEXAS and valuing the MDT's educational and collaborative benefits. The national VEXAS MDT supported evidence-informed, multidisciplinary decision-making, promoted more targeted therapy and strengthened clinical confidence and collaboration in the absence of formal treatment guidelines.
Amelogenesis imperfecta (AI) is a group of rare inherited conditions causing tooth enamel defects. Human acid phosphatase 4 (ACP4) is a transmembrane protein involved in maintaining appositional enamel growth. Variants in ACP4 cause recessive hypoplastic AI. Here we identify further families and review published ACP4 variants causing AI. In three Pakistani families, we identified a new ACP4 variant, c.254T > C, p.(Pro85Leu), which long-read sequencing revealed to be a founder variant. Two further families were homozygous for previously reported pathogenic ACP4 variants. Further details are also reported for two families previously listed in a technical/cohort study by this group. In total, seventeen ACP4 variants had been reported in the literature causing AI in seventeen families prior to this study. This report adds an eighteenth variant and brings the total to 22 families. Nine families derive from a cohort of over 400 AI probands curated in Leeds, UK, and account for 9/129 families solved for recessive AI, suggesting ACP4 variants are a significant cause of recessive AI. ACP4 variants implicated in AI include fifteen missense, one splice and two frame-breaking deletions. Most missense variants are within the acid phosphatase domain, with one in the transmembrane domain. The consistent hypoplastic phenotype suggests a single mutational mechanism, and the report of a family with a homozygous frameshift variant likely to be subject to nonsense mediated decay points to loss of function. Missense variants alter amino acids at the catalytic core or affect protein stability, homodimerisation or membrane localisation, all likely to result in functional insufficiency.
