The advancement of polysaccharides in disease modulation: Multifaceted regulation of programmed cell death.

Programmed cell death (PCD), also known as regulatory cell death (RCD), is a process that occurs in all organisms and is closely linked to both normal physiological processes and disease states. Various signaling pathways, such as TP53, KRAS, NOTCH, hypoxia, and metabolic reprogramming, have been found to regulate RCD. Polysaccharides, which are essential natural products, have been the subject of extensive research in the fields of food, nutrition, and medicine due to their wide range of pharmacological effects. Studies have shown that polysaccharides have biological activities and the potential to target signal transduction pathways for the treatment of diseases. This paper provides a review of the mechanisms through which polysaccharides exert their therapeutic effects at different levels and explores the relationship between different types of RCD and human diseases. The aim of this review is to provide a theoretical basis for the further clinical use and application of polysaccharide bioactivities.

Mitochondria-mediated Ferroptosis in Diseases Therapy: From Molecular Mechanisms to Implications.

Ferroptosis, a type of cell death involving iron and lipid peroxidation, has been found to be closely associated with the development of many diseases. Mitochondria are vital components of eukaryotic cells, serving important functions in energy production, cellular metabolism, and apoptosis regulation. Presently, the precise relationship between mitochondria and ferroptosis remains unclear. In this study, we aim to systematically elucidate the mechanisms via which mitochondria regulate ferroptosis from multiple perspectives to provide novel insights into mitochondrial functions in ferroptosis. Additionally, we present a comprehensive overview of how mitochondria contribute to ferroptosis in different conditions, including cancer, cardiovascular disease, inflammatory disease, mitochondrial DNA depletion syndrome, and novel coronavirus pneumonia. Gaining a comprehensive understanding of the involvement of mitochondria in ferroptosis could lead to more effective approaches for both basic cell biology studies and medical treatments.

The combination of machine learning and untargeted metabolomics identifies the lipid metabolism -related gene CH25H as a potential biomarker in asthma.

BACKGROUND: Lipids, significant signaling molecules, regulate a multitude of cellular responses and biological pathways in asthma which are closely associated with disease onset and progression. However, the characteristic lipid genes and metabolites in asthma remain to be explored. It is also necessary to further investigate the role of lipid molecules in asthma based on high-throughput data. OBJECTIVE: To explore the biomarkers and molecular mechanisms associated with lipid metabolism in asthma. METHODS: In this study, we selected three mouse-derived datasets and one human dataset (GSE41665, GSE41667, GSE3184 and GSE67472) from the GEO database. Five machine learning algorithms, LASSO, SVM-RFE, Boruta, XGBoost and RF, were used to identify core gene. Additionally, we used non-negative matrix breakdown (NMF) clustering to identify two lipid molecular subgroups and constructed a lipid metabolism score by principal component analysis (PCA) to differentiate the subtypes. Finally, Western blot confirmed the altered expression levels of core genes in OVA (ovalbumin) and HDM+LPS (house dust mite+lipopolysaccharide) stimulated and challenged BALB/c mice, respectively. Results of non-targeted metabolomics revealed multiple differentially expressed metabolites in the plasma of OVA-induced asthmatic mice. RESULTS: Cholesterol 25-hydroxylase (CH25H) was finally localized as a core lipid metabolism gene in asthma and was verified to be highly expressed in two mouse models of asthma. Five-gene lipid metabolism constructed from CYP2E1, CH25H, PTGES, ALOX15 and ME1 was able to distinguish the subtypes effectively. The results of non-targeted metabolomics showed that most of the aberrantly expressed metabolites in the plasma of asthmatic mice were lipids, such as LPC 16:0, LPC 18:1 and LPA 18:1. CONCLUSION: Our findings imply that the lipid-related gene CH25H may be a useful biomarker in the diagnosis of asthma.