Research Keyword: computational biology

Recent advances in natural polysaccharides for type 2 diabetes management: sources, structural characteristics, and mechanistic insights

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Natural polysaccharides from plants, mushrooms, and seaweed show promise as treatments for type 2 diabetes. These complex sugar molecules work through multiple mechanisms including improving how the body uses insulin, reducing inflammation and oxidative stress, and promoting beneficial gut bacteria. The effectiveness of these polysaccharides depends on their specific chemical structure, particularly their molecular weight and how their sugar units are linked together.

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The molecular mechanisms through which psilocybin prevents suicide: evidence from network pharmacology and molecular docking analyses

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Researchers used computer-based analysis to understand how psilocybin, a compound found in certain mushrooms, might help prevent suicide. They identified four key proteins that psilocybin interacts with and found that it works through serotonin and calcium signaling pathways in the brain, which are known to be involved in depression and suicidal behavior. While these findings are promising, more research is needed to confirm these effects in humans before psilocybin can be used clinically for suicide prevention.

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Unlocking the magic in mycelium: Using synthetic biology to optimize filamentous fungi for biomanufacturing and sustainability

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This comprehensive review explores how scientists can use modern genetic engineering tools to improve filamentous fungi (molds and mushrooms) for producing valuable products like antibiotics, enzymes, and sustainable food and materials. The authors explain that while these fungi naturally excel at breaking down plant material and producing useful compounds, they haven’t received as much attention from genetic engineers as other microorganisms. By applying techniques like CRISPR gene editing, computational modeling, and directed evolution, researchers can make fungal strains grow faster, produce higher yields, and use cheaper feedstocks, making industrial production more efficient and environmentally friendly.

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Synergistic target network construction and dynamic simulation analysis based on a prospective systems pharmacology strategy

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Researchers used computer-based methods to study how Sang Huang, a traditional medicinal fungus, might help treat type 2 diabetes. They identified 17 active compounds in the fungus and found that a key component called estradiol dipropionate could improve insulin sensitivity and glucose control by activating specific protein pathways. The study suggests Sang Huang could be a promising natural treatment for diabetes, though more laboratory and animal testing is needed.

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