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Stroke is a severe neurological disease and a major worldwide issue, mostly manifesting as ischemic stroke (IS). In order to create effective treatments for IS, it is imperative to fully understand the underlying pathologies, as the existing therapeutic choices are inadequate. Recent investigations have shown the complex relationships between several programmed cell death (PCD) pathways, including necroptosis, ferroptosis, and pyroptosis, and their correlation with immune responses during IS. However, this relationship is still unclear. To address this gap, this review study explored the cellular interactions in the immune microenvironment of IS. Then, to validate prior findings and uncover biomarkers, the study investigated bioinformatics studies. Several pathways, including nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), Toll-like receptor 4 (TLR4), and receptor-interacting protein kinase (RIPK), were involved in PCD-immune interactions. The bioinformatics studies reported key biomarkers such as glutathione peroxidase 4 (GPX4), NOD-like receptor family pyrin domain containing 3 (NLRP3), gasdermin D (GSDMD), and TLR4, which have important implications in ferroptosis, cuproptosis, pyroptosis, and necroptosis respectively. These biomarkers were associated with PCD mechanisms such as oxidative stress and inflammatory reactions. The immune infiltration analysis consistently revealed a significant correlation between PCD pathways and detrimental immune cells, such as neutrophils and γδ T cells. Conversely, M2 macrophages and T helper cells showed protective effects. In conclusion, considering the intricate network of interactions between immune responses and PCD pathways, this study emphasized the necessity of a paradigm shift in therapeutic approaches to address the injuries that are related to this complex network.
Stroke is a severe neurological disease and a major worldwide issue, mostly manifesting as ischemic stroke (IS). In order to create effective treatments for IS, it is imperative to fully understand the underlying pathologies, as the existing therapeutic choices are inadequate. Recent investigations have shown the complex relationships between several programmed cell death (PCD) pathways, including necroptosis, ferroptosis, and pyroptosis, and their correlation with immune responses during IS. However, this relationship is still unclear. To address this gap, this review study explored the cellular interactions in the immune microenvironment of IS. Then, to validate prior findings and uncover biomarkers, the study investigated bioinformatics studies. Several pathways, including nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), Toll-like receptor 4 (TLR4), and receptor-interacting protein kinase (RIPK), were involved in PCD-immune interactions. The bioinformatics studies reported key biomarkers such as glutathione peroxidase 4 (GPX4), NOD-like receptor family pyrin domain containing 3 (NLRP3), gasdermin D (GSDMD), and TLR4, which have important implications in ferroptosis, cuproptosis, pyroptosis, and necroptosis respectively. These biomarkers were associated with PCD mechanisms such as oxidative stress and inflammatory reactions. The immune infiltration analysis consistently revealed a significant correlation between PCD pathways and detrimental immune cells, such as neutrophils and γδ T cells. Conversely, M2 macrophages and T helper cells showed protective effects. In conclusion, considering the intricate network of interactions between immune responses and PCD pathways, this study emphasized the necessity of a paradigm shift in therapeutic approaches to address the injuries that are related to this complex network.
Uncertainty in biology refers to situations in which information is imperfect or unknown. Variability, on the other hand, is measured by the frequency distribution of observed data. Biological variability adds to the uncertainty. The Constrained Disorder Principle (CDP) defines all systems in the universe by their inherent variability. According to the CDP, systems exhibit a degree of variability necessary for their proper function, allowing them to adapt to changes in their environments. Per the CDP, while variability differs from uncertainty, it can be viewed as a regulated mechanism for efficient functionality rather than uncertainty. This paper explores the various aspects of un-certainties in biology. It focuses on using CDP-based platforms for refining fuzzy algorithms to address some of the challenges associated with biological and medical uncertainties. Developing a fuzzy decision tree that considers the natural variability of systems can help minimize uncertainty. This method can reveal previously unidentified classes, reduce the number of unknowns, improve the accuracy of modeling results, and generate algorithm outputs that are more biologically and clinically relevant.
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