Publications by authors named "A McNulty"

Introduction: Artificial intelligence (AI) has gained significant attention in medicine, particularly in neurosurgery, where its potential is often discussed and occasionally feared. Large language models (LLMs), such as ChatGPT-4.0 (OpenAI) and Gemini (formerly known as Bard, Google DeepMind), have shown promise in text-based tasks but remain under explored in image-based domains, which are essential for neurosurgery.

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Although various joint injuries result in post-traumatic osteoarthritis (PTOA), differences in chondrocyte response to specific injuries, such as blunt compression or fracture, are unclear. Furthermore, the role of underlying joint inflammation, or synovitis, is often not considered. We investigated how injury mechanisms and underlying synovitis affect chondrocyte gene expression using osteochondral injury models with synovial co-culture.

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Background: Heart failure (HF) is a chronic disease characterized by high mortality and healthcare expenditures. Digital health solutions, including mobile health applications (apps), offer opportunities to enhance patients' self-care and quality of life. This qualitative study aimed to explore expectations, experiences, and usage behaviour of HF-patients regarding a self-care app ( app).

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Meniscus tissue is commonly injured due to sports-related injuries and age-related degeneration and approximately 50% of individuals with a meniscus tear will develop post-traumatic osteoarthritis (PTOA). Given that the meniscus has limited healing potential, new therapeutic strategies are required to enhance meniscus repair. Porcine meniscus-derived matrix (MDM) scaffolds improve meniscus integrative repair, but sources of human meniscus tissue have not been investigated.

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Meniscus injuries are common and while surgical strategies have improved, there is a need for alternative therapeutics to improve long-term outcomes and prevent post-traumatic osteoarthritis. Current research efforts in regenerative therapies and tissue engineering are hindered by a lack of understanding of meniscus cell biology and a poorly defined meniscus cell phenotype. This study utilized bulk RNA-sequencing to identify unique and overlapping transcriptomic profiles in cartilage, inner and outer zone meniscus tissue, and passaged inner and outer zone meniscus cells.

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