Abstract
Ischaemic stroke is extremely common in western societies contributing to 70-85% of strokes, one of the leading causes of mortality and long-term disability. Despite advancement in preventive measures, the total number of strokes is set to rise in the future due to increasing numbers of aging populations across the world. Diabetes as a risk factor for stroke has been well established. There are also emerging evidence to suggest glucose level management in acute stroke phase as a therapeutic target may be beneficial, albeit remains controversial. One of the issues in difficulty in interpreting study findings is their heterogeneity. In this article, we provide epidemiological, basic science, clinical observational and trial evidence leading to the current practice of regarding blood glucose as the therapeutic target in acute ischaemic stroke setting.
Call for Papers in Thematic Issues
Adaptogens—History and Future Perspectives
Adaptogens are pharmacologically active compounds or plant extracts that are associated with the ability to enhance the body’s stability against stress. The intake of adaptogens is associated not only with a better ability to adapt to stress and maintain or normalise metabolic functions but also with better mental and physical ...read more
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The most common causes of death in the world are cardiovascular disease (CVD) and cancer. These are perhaps best addressed by reducing lipodystrophy and blockages with niacin and inositol polyphosphates (e.g., IP6+inositol) respectively when addressing CVD. Niacin serves as a vitamin by virtue of its role as a skeletal precursor ...read more
AlphaFold in Medicinal Chemistry: Opportunities and Challenges
AlphaFold, a groundbreaking AI tool for protein structure prediction, is revolutionizing drug discovery. Its near-atomic accuracy unlocks new avenues for designing targeted drugs and performing efficient virtual screening. However, AlphaFold's static predictions lack the dynamic nature of proteins, crucial for understanding drug action. This is especially true for multi-domain proteins, ...read more
Artificial intelligence for Natural Products Discovery and Development
Our approach involves using computational methods to predict the potential therapeutic benefits of natural products by considering factors such as drug structure, targets, and interactions. We also employ multitarget analysis to understand the role of drug targets in disease pathways. We advocate for the use of artificial intelligence in predicting ...read more
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