Total intravenous anaesthesia is a core safety standard for absolute indications, such as malignant hyperthermia susceptibility, yet little is known about institutional readiness to deliver total intravenous anaesthesia for obstetric patients. We conducted a national cross-sectional service evaluation of all 19 Irish maternity units via the Irish Society of Obstetric Anaesthesia network. Responses were received from 13/19 units, representing over 80% of the national birth activity. Most units (8/13) reported reliable access to target-controlled infusion pumps and processed electroencephalography monitoring (12/13), but 5/13 had fewer than one target-controlled infusion pump per obstetric theatre and 4/13 lacked an immediate backup pump. No unit had a written protocol for obstetric total intravenous anaesthesia, and 7/13 reported no resident training. Reported total intravenous anaesthesia use for obstetric general anaesthesia was low (0% in 8/13 units). Lack of exposure (11/13) and institutional preference for volatile agents (10/13) were the most common barriers. Readiness to deliver total intravenous anaesthesia for obstetric patients without delay is variable across Irish maternity units. Given that total intravenous anaesthesia remains mandatory in certain high-risk patient groups, including those susceptible to malignant hyperthermia, deficiencies in equipment redundancy, monitoring, training and governance are patient safety concerns which should be addressed.

Rheumatoid arthritis (RA) is a chronic autoimmune disease affecting approximately 1% of the global population and is associated with a substantial reduction in both life expectancy and quality of life. Although current treatments, primarily disease-modifying antirheumatic drugs, have been shown to suppress inflammation, clinical responses vary widely between individuals, reflecting the heterogeneity of the disease. Consequently, identifying reliable biomarkers to predict therapeutic response has become a key priority for improving clinical management. In this focused review, we summarise recent advances in the discovery of predictive biomarkers for RA and compare their reported specificity and sensitivity using published data. We also highlight key limitations in the existing literature that undermine reproducibility in this field. Coordinated efforts across the rheumatology community to address these challenges will be essential to translate biomarker research into personalised treatment strategies for RA.

Traditional tennis trainers employing passive return mechanisms (springs or rubber bands) suffer from fixed return angles, non-adjustable damping, inability to measure hitting speed, and monotonous training modes. To overcome these limitations, this paper presents an active return device based on a joint motor and proposes a low-overshoot control method using Nonlinear Active Disturbance Rejection Control (NLADRC). The device integrates a joint motor with an encoder, an embedded controller, and a striking target mounted on a rotating arm, enabling real-time speed calculation, adjustable damping, and precise active return. To the best of our knowledge, this is the first application of ADRC to an active return device for striking-sports training, and it constitutes the primary innovation of this work. In MATLAB simulations, NLADRC reduces the 0°→180° step-response overshoot by 82% and the post-disturbance settling time by 62.5% compared with a tuned PID controller. Hardware experiments on a prototype closely match the simulations, with a step-response overshoot of about 2.8% and a disturbance recovery time of about 0.4 s under NLADRC. A four-unit cooperative training system demonstrates sequential and random multi-target modes with audio-visual feedback, and a preliminary usability survey with 30 amateur players yields mean ratings above 4.2 out of 5 on five dimensions. These results validate the proposed device and controller and demonstrate the superiority of NLADRC over PID for this application together with acceptable preliminary usability; direct effects on tennis skill acquisition or training outcomes are beyond the scope of this study and remain to be examined in future longitudinal work.

Diamond-Blackfan anaemia (DBA) is a rare inherited bone marrow failure syndrome causing pure red cell aplasia. Patients frequently require long-term red cell transfusions, predisposing them to iron overload. This case describes a patient with DBA with rapid ejection fraction decline secondary to acute-onset iron overload cardiomyopathy. A 28-year-old male patient with known transfusion-dependent DBA and established iron overload and on deferasirox, presented with a one-week history of orthopnoea, dyspnoea and peripheral oedema. Echocardiography demonstrated severe biventricular impairment with an ejection fraction of 15-25%. This represented a marked decline from an estimated ejection fraction of 45% two years prior. His course was then complicated by fast atrial fibrillation and severe refractory hypokalaemia, leading to escalation to the critical care unit. Cardiac MRI confirmed significant myocardial and hepatic iron loading. He was then managed with intravenous deferrioxamine, heart failure pharmacotherapy and rate control, with subsequent escalation of oral chelation. He was then discharged with combined cardiology and haematology follow-up. This case illustrates a severe complication of DBA: acute-onset iron overload cardiomyopathy causing rapid ejection fraction decline despite ongoing oral chelation. Markedly elevated ferritin, transferrin saturation and serum iron, alongside a normal CRP, supported a diagnosis of severe systemic iron overload. Management required a rapid switch from oral deferasirox to intravenous desferrioxamine. This case demonstrates that severe, acute iron overload cardiomyopathy can occur in patients with transfusion-dependent DBA despite ongoing chelation. It supports the value of further study of cardiac outcomes in this patient group.

Cardiometabolic diseases remain a primary global health challenge, with nutritional interventions serving as a critical pillar of management. However, the rapidly expanding volume of nutritional research, spanning high-dimensional multiomics, real-world continuous monitoring, and highly heterogeneous clinical trials, has created fragmented knowledge silos, leading to a profound translation lag between scientific discovery and clinical practice. To overcome this methodological bottleneck, we propose a conceptual framework for an "AI-Driven Evidence Ecosystem." This perspective outlines a four-phase closed-loop architecture: (1) AI-assisted mechanistic decoding of multiomics and the development of digital gut twins; (2) data-optimized clinical research integrating traditional trials with real-world digital biomarkers; (3) a methodologically agnostic, multi-agent living evidence synthesis engine capable of automating complex data extraction and mitigating the translation gap; and (4) the deployment of conversational AI for public knowledge translation and personalized patient empowerment. By addressing concurrent ethical challenges, algorithmic biases, and the risk of researcher de-skilling, this ecosystem paradigm leverages artificial intelligence not merely as an automation tool, but as an indispensable bridge. Ultimately, it transforms isolated, stagnant data into a dynamic, translatable evidence network, reshaping the future of precision cardiometabolic care.