Publications by authors named "M P Ko"

Spinal cord injury (SCI) remains a significant clinical challenge, with no fully effective treatment available despite advancements in various therapeutic approaches. This review examines the emerging role of induced neural stem cells (iNSCs) as promising candidates for SCI treatment, highlighting their potential for direct neural regeneration and integration with host tissue. We explore the biology of iNSCs, their mechanisms of action, and their interactions with host tissue, including modulating inflammatory responses, promoting axonal growth, and reconstructing neural circuits.

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Spinal cord injury (SCI) following high-energy trauma often leads to lasting neurologic deficits and severe socioeconomic impact. Effective neurointensive care, particularly in the early stages post-injury, is essential for optimizing outcomes. This review discusses the role of neurointensive care in managing SCI, emphasizing early assessment, stabilization, and intervention strategies based on recent evidence-based practices.

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Spinal cord injury (SCI) frequently results in persistent motor, sensory, or autonomic dysfunction, and the outcomes are largely determined by the location and severity of the injury. Despite significant technological progress, the intricate nature of the spinal cord anatomy and the difficulties associated with neuroregeneration make full recovery from SCI uncommon. This review explores the potential of artificial intelligence (AI), with a particular focus on machine learning, to enhance patient outcomes in SCI management.

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Tuberculous (TB) spondylitis, also known as Pott's disease, was first described by Percivall Pott in 1779. The diagnosis of TB spondylitis is often delayed because of the non-specific nature of the infection, which can lead to severe consequences. Differential diagnosis is especially critical in cancer patients undergoing chemotherapy who present with lymph node or bone metastasis.

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Background: Predicting complete liberation from mechanical ventilation (MV) is still challenging. Electrical impedance tomography (EIT) offers a non-invasive measure of regional ventilation distribution and could bring additional information.

Research Question: Whether the display of regional ventilation distribution during a Spontaneous Breathing Trial (SBT) could help at predicting early and successful liberation from MV.

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