Hemicrania continua (HC) is a rare trigeminal–autonomic cephalalgia characterized by continuous, strictly unilateral headache with ipsilateral cranial autonomic symptoms (CAS) and complete response to indomethacin. Although typically considered a primary headache disorder, various structural and vascular lesions may produce secondary HC phenotypes. We report a case of indomethacin-responsive, HC-like headache caused by a cavernous sinus inflammatory pseudotumor (IPT). A 54-year-old man presented with a 2-month history of continuous, right-sided headache accompanied by ipsilateral CAS. The headache resolved completely with indomethacin treatment; however, persistent focal neurological deficits prompted further diagnostic evaluation. Electrophysiological testing demonstrated abnormalities in the right trigeminofacial reflex pathway, and subsequent brain magnetic resonance imaging (MRI) revealed enhancing lesions in the right cavernous sinus and orbital apex, which were consistent with an IPT. Corticosteroid therapy resulted in a complete clinical recovery with near-complete radiological resolution. This case demonstrates that complete indomethacin responsiveness does not exclude a secondary etiology. This finding highlights the vital role of contrast-enhanced MRI and electrophysiological testing when atypical neurological features are present.
The development of molecular virology, genetic engineering, and immunology has enabled the transformation of viruses into versatile platforms, including vaccine vectors, cancer therapeutics, gene delivery systems, and antimicrobial agents. Live-attenuated vaccines and inactivated vaccines are well-established strategies that continue to play a critical role in public health. Viral vectors have demonstrated potential in solving health crises globally in recent years. Oncolytic viruses, including talimogene laherparepvec, have been approved by regulators, and many others are in clinical trials for a wide range of cancers. Viral vectors have also become important tools in gene therapy. Adeno-associated virus vectors have been clinically validated for disorders including spinal muscular atrophy and inherited retinal dystrophy, whereas lentiviral vectors are widely used ex vivo in approved therapies for selected hematologic, immunologic, and metabolic disorders. In addition to conventional therapeutics, virus-based antimicrobial strategies, including phage-based enzymes and bacteriophages, are being investigated as alternatives to antibiotics to address antimicrobial resistance. Diagnostics and biotechnology have also been significantly advanced with the application of viral components and enzymes. Despite their promise, virus-based therapeutics face challenges including safety concerns, immunogenicity, manufacturing complexities, and regulatory requirements. Advances in synthetic virology, including improved vector design and combination approaches, will continue to expand the medical applications of viruses. This review provides a detailed discussion of the development and applications of virus-based medicines, as well as the challenges and future perspectives in this rapidly evolving field.
Purpose: Stroke survivors remain at risk of recurrent stroke and cardiovascular events. Lifestyle risk factor modification is central to secondary prevention, yet changes across multiple risk factors after stroke remain poorly characterized. We evaluated changes in lifestyle risk factors among stroke survivors.Methods: Using the Korean National Health Insurance Service database, we conducted a population-based cohort study comparing changes in smoking, alcohol consumption, regular physical activity, and obesity status between 120,874 stroke survivors and 209,348 participants without stroke. We further stratified stroke survivors by the presence and severity of post-stroke disability.Results: Compared with participants without stroke, stroke survivors had higher rates of smoking cessation (54.5% vs. 22.9%) and alcohol cessation (51.0% vs. 21.3%). Nevertheless, 45.5% of those who smoked before stroke continued smoking, and 49.0% of those who consumed alcohol before stroke continued drinking. Stroke survivors were less likely to maintain regular physical activity than participants without stroke (38.1% vs. 43.8%). Stroke survivors with severe disability had the lowest rates of maintaining (29.1%) or initiating (12.7%) regular physical activity. Changes in obesity status were more frequent among stroke survivors in both directions: from obesity to non-obesity (20.6% vs. 15.6%) and from non-obesity to obesity (11.9% vs. 9.3%). Unfavorable lifestyle patterns were most pronounced among stroke survivors with severe post-stroke disability.Conclusion: A substantial proportion of stroke survivors did not adopt favorable lifestyle changes, particularly those with post-stroke disability. Comprehensive lifestyle risk factor modification requires multidisciplinary, individualized interventions tailored to disability status.
Synthetic data is emerging as a strategic solution to persistent barriers in medical artificial intelligence (AI) development, including data scarcity, privacy constraints, and dataset bias. This perspective examines the landscape of synthetic multimodal data in healthcare, including its mechanisms, demonstrated benefits, technical and ethical challenges, and a proposed validation framework linking fidelity to clinical utility. We integrate evidence from recent empirical studies, the generative AI literature, and regulatory developments. We discuss how synthetic data is generated across four healthcare domains: medical imaging, electronic health records, clinical text, and genomics. We also review methods such as generative adversarial networks, diffusion models, large language models, and rule-based simulators. Synthetic multimodal data demonstrably improves AI model performance, addresses class imbalance, enables privacy- preserving data-sharing, and supports regulatory evaluation pathways. Illustrative case studies suggest potential gains in model performance, although systematic quantitative evidence across modalities remains limited. Key challenges include re-identification risks, the perpetuation of bias, computational inequity, and the absence of cross-modal coherence standards. A seven-dimensional validation scorecard is proposed, covering statistical fidelity, privacy risk, clinical utility, robustness, cross-modal coherence, and governance. Synthetic multimodal data can catalyze medical AI innovation, but only if paired with rigorous validation, transparent governance, and a firm commitment to equity. Priority actions include international benchmark consortia, regulatory sandboxes, investment in federated learning, and mandatory intersectional bias auditing.
