Application of natural products in regulating ferroptosis in human diseases.

BACKGROUND: Ferroptosis is a type of cell death caused by excessive iron-induced peroxidation. It has been found to be involved in a variety of diseases, and natural products can be used to target ferroptosis in treatments. Natural products are biologically active compounds extracted or synthesized from nature. It is an important resource for the discovery of skeletons with a high degree of structural diversity and a wide range of bioactivities, which can be developed directly or used as a starting point for the optimization of new drugs. PURPOSE: In this review, we aim to discuss the interactions between natural products and ferroptosis in the treatment of human diseases. METHODS: Literature was searched in Pubmed, Science Direct, and Web of Science databases for the 11-year period from 2012 to 2023 using the search terms "natural products", "ferroptosis", "human disease", "neurodegenerative disease", "cardiovascular disease", and "cancer". RESULTS: In this research, the roles of natural products and ferroptosis were investigated. We suggest that natural products, such as terpenoids, flavonoids, polyphenols, alkaloids, and saponins, can be used in therapeutic applications for human diseases, as well as in ferroptosis. Additionally, the main mechanisms of ferroptosis were summarized and discussed. Furthermore, we propose that natural products can be utilized to enhance the sensitivity of cancer cells to ferroptosis, thus helping to overcome drug resistance and inhibit metastasis. Moreover, natural products have the potential to modulate the expression levels of ferroptosis-related factors. Finally, the future directions of this field were highlighted. CONCLUSION: The potential of natural products which focus on ferroptosis to treat human illnesses, particularly cancer, is very encouraging for human wellbeing.

Exploring the ferroptosis-related gene lipocalin 2 as a potential biomarker for sepsis-induced acute respiratory distress syndrome based on machine learning.

BACKGROUND: Sepsis is a major cause of mortality in patients, and ARDS is one of the most common outcomes. The pathophysiology of acute respiratory distress syndrome (ARDS) caused by sepsis is significantly impacted by genes related to ferroptosis. METHODS: In this study, Weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI) networks, functional enrichment analysis, and machine learning were employed to identify characterized genes and to construct receiver operating characteristic (ROC) curves. Additionally, DNA methylation levels were quantified and single-cell analysis was conducted. To validate the alterations in the expression of Lipocalin-2 (LCN2) and ferroptosis-related proteins in the in vitro model, Western blotting was carried out, and the changes in intracellular ROS and Fe2+ levels were detected. RESULTS: A combination of eight machine learning algorithms, including RFE, LASSO, RandomForest, SVM-RFE, GBDT, Bagging, XGBoost, and Boruta, were used with a machine learning model to highlight the significance of LCN2 as a key gene in sepsis-induced ARDS. Analysis of immune cell infiltration showed a positive correlation between neutrophils and LCN2. In a cell model induced by LPS, it was found that Ferrostatin-1 (Fer-1), a ferroptosis inhibitor, was able to reverse the expression of LCN2. Knocking down LCN2 in BEAS-2B cells reversed the LPS-induced lipid peroxidation, Fe2+ levels, ACSL4, and GPX4 levels, indicating that LCN2, a ferroptosis-related gene (FRG), plays a crucial role in mediating ferroptosis. CONCLUSION: Upon establishing an FRG model for individuals with sepsis-induced ARDS, we determined that LCN2 could be a dependable marker for predicting survival in these patients. This finding provides a basis for more accurate ARDS diagnosis and the exploration of innovative treatment options.

Identification of RRM2 as a key ferroptosis-related gene in sepsis.

OBJECTIVE: Sepsis and sepsis-associated organ failure are devastating conditions for which there are no effective therapeutic agent. Several studies have demonstrated the significance of ferroptosis in sepsis. The study aimed to identify ferroptosis-related genes (FRGs) in sepsis, providing potential therapeutic targets. METHODS: The weighted gene co-expression network analysis (WGCNA) was utilized to screen sepsis-associated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to explore gene functions. Three machine learning methods were employed to identify sepsis-related hub genes. Survival and multivariate Cox regression analysis allowed further screening for the key gene RRM2 associated with prognosis. The immune infiltration analysis of the screened sepsis key genes was performed. Additionally, a cecum ligation and puncture (CLP)-induced mouse sepsis model was constructed to validate the expression of key gene in the sepsis. RESULTS: Six sepsis-associated differentially expressed FRGs (RRM2, RPL7A, HNRNPA1, PEBP1, MYL8B and TXNIP) were screened by WGCNA and three machine learning methods analysis. Survival analysis and multivariate Cox regression analysis showed that RRM2 was a key gene in sepsis and an independent prognostic factor associated with clinicopathological and molecular features of sepsis. Immune cell infiltration analysis demonstrated that RRM2 had a connection to various immune cells, such as CD4 T cells and neutrophils. Furthermore, animal experiment demonstrated that RRM2 was highly expressed in CLP-induced septic mice, and the use of Fer-1 significantly inhibited RRM2 expression, inhibited serum inflammatory factor TNF-α, IL-6 and IL-1ß expression, ameliorated intestinal injury and improved survival in septic mice. CONCLUSION: RRM2 plays an important role in sepsis and may contribute to sepsis through the ferroptosis pathway. This study provides potential therapeutic targets for sepsis.

Extracellular vesicles as a novel mediator of interkingdom communication.

Extracellular vesicles (EVs) are nanosized lipid bilayer-delimited particles secreted from almost all types of cells including bacteria, mammals and plants, and are presumed to be mediators of intercellular communication. Bacterial extracellular vesicles (BEVs) are nanoparticles with diverse diameters, ranging from 20 to 400 nm. BEVs are composed of soluble microbial metabolites, including nucleic acid, proteins, lipoglycans, and short-chain fatty acids (SCFAs). In addition, EVs may contain quorum sensing peptides that are endowed with the ability to protect bacteria against bacteriophages, form and maintain bacterial communities, and modulate the host immune system. BEVs are potentially promising therapeutic modalities for use in vaccine development, cancer immunotherapy regimens, and drug delivery cargos. Plant-derived EVs (PEVs), such as EVs derived from herbal medicines, can be absorbed by the gut microbiota and influence the composition and homeostasis of gut microbiota. This review highlights the roles of BEVs and PEVs in bacterial and plant physiology and discusses crosstalk among gut bacteria, host metabolism and herbal medicine. In summary, EVs represent crucial communication messengers in the gut microbiota, with potential therapeutic value in the delivery of herbal medicines.

The destiny of microplastics in one typical petrochemical wastewater treatment plant.

Microplastic (MP) is a type of emerging contaminant that is verified to be threatening to some organisms. Controlling MP emission from the source is preferred for its refractory characteristic. The petrochemical industry is a possible contributor, responsible for the most plastic production, and wastewater is the most possible sink of MP. This study applied the Agilent 8700 Laser infrared imaging spectrometer (LDIR) to detect MPs in one typical petrochemical wastewater treatment plant (PWWTP). It was determined that the abundances of MPs in the influent and effluent of the target PWWTP were as high as 7706 and 608 particles/L. The primary treatment removed most MPs (87.5 %) with a final removal efficiency of 92.1 %. 23 types of MPs were identified, and Polyethylene (PE), Polypropylene (PP), Silicone resin prevailed in the effluent. All the MPs were smaller than 483.9 µm. All in all, this study preliminarily unveiled the ignorable status of the petrochemical industry in releasing MPs into the water environment for the first time.

Identification of Lipocalin 2 as a Potential Ferroptosis-related Gene in Ulcerative Colitis.

BACKGROUND: Ulcerative colitis (UC) is a chronic nonspecific inflammatory disease generally limited to the mucosa and submucosa of the colon. Recent studies suggest that ferroptosis is a novel programmed cell death that may be involved in the process of UC. However, the mechanism of ferroptosis in UC remains to be further investigated. METHODS: The genes associated with UC and ferroptosis were screened by bioinformatics methods, and a random forest model was constructed to identify the core genes of UC and validated with external data sets. Establishment of dextran sodium sulfate (DSS) induced UC in an animal model in vivo. Interferon (IFN)-γ primed immortalized bone marrow-derived macrophages cells stimulated with Lipopolysaccharides (LPS) inflammation model and LPS-stimulated Caco-2 cells colitis model in vitro were constructed. The potential link between Lipocalin-2 (LCN2) and UC ferroptosis was explored by flow cytometry, Fe2+ assay, Western Blot, gene knockdown, hematoxylin and eosin staining, and immunohistochemistry staining. RESULTS: Analysis of differentially expressed genes (DEGs) showed that LCN2 was highly expressed in UC. The protein-protein interaction (PPI) networks showed that ferroptosis-associated DEGs were highly correlated with the immune gene LCN2. The most important gene in the random forest model, LCN2, was identified as a core gene in UC. In the LPS/IFN-γ-induced inflammation model, LCN2 expression was elevated, lipid peroxidation, Fe2+, ACSL4 and COX-2 levels increased, whereas GPX4 and FTH1 expression decreased. Similarly, in the DSS-induced UC mouse model, Occludin, ZO-1, Claudin-1, and GPX4 expression were significantly decreased, but ACSL4 and LCN2 expression were elevated. In addition, the use of Ferrostatin-1 (Fer-1) can significantly reverse its trend. More importantly, silencing of LCN2 suppressed ferroptosis events in both the LPS/IFN-γ-induced inflammation model and the LPS-stimulated colitis model. CONCLUSION: In conclusion, our study demonstrates that LCN2 is a key factor in the regulation of ferroptosis in UC and provides additional evidence for the important role of ferroptosis in UC.

Is the petrochemical industry an overlooked critical source of environmental microplastics?

Microplastics (MPs) are ubiquitous in the environment and have been verified to be harmful to organisms. The petrochemical industry is a possible contributor, for it is the primary plastic producer but is not focused on. In this background, MPs in the influent, effluent, activated sludge, and expatriate sludge of a typical petrochemical wastewater treatment plant (PWWTP) were identified by the laser infrared imaging spectrometer (LDIR). It revealed that the abundances of MPs in the influent and effluent were as high as 10310 and 1280 items/L with a removal efficiency of 87.6%. The removed MPs accumulated in the sludge, and the MP abundances in activated and expatriate sludge reached 4328 and 10767 items/g, respectively. It is estimated that 1440,000 billion MPs might be released into the environment by the petrochemical industry in 2021 globally. For the specific PWWTP, 25 types of MPs were identified, among which Polypropylene (PP), Polyethylene (PE), and Silicone resin were dominant. All of the detected MPs were smaller than 350 µm, and those smaller than 100 µm prevailed. As for the shape, the fragment was dominant. The study confirmed the critical status of the petrochemical industry in releasing MPs for the first time.

99mTc-dextran lymphoscintigraphy can detect sentinel lymph node in breast cancer patients.

The aim of this study was to retrospectively determine the accuracy and feasibility of using 99mTc-dextran (DX) lymphoscintigraphy for the localization of sentinel lymph nodes (SLNs) in breast cancer patients. The relevant factors affecting lymphoscintigraphy were also investigated. In this study, 235 breast cancer patients underwent 99mTc-DX lymphoscintigraphic imaging and examination by a γ-probe method in combination with blue dye staining to detect SLNs. The detection results were considered in combination with rapid frozen pathology results to determine whether SLN metastasis was positive or negative. SLNs were identified in 191 patients by γ-probe detection among the 202 patients that tested positive by lymphoscintigraphic imaging, a coincidence rate of 94.6%. This suggested that lymph node metastasis had occurred and could be detected using lymphoscintigraphy. The axillary status of the breast cancer patients was also predicted using lymphoscintigraphy and the false-negative rate, sensitivity, specificity and positive predictive value were 13.3% (4/30), 90.7% (39/43), 23.4% (45/192) and 13.5% (21/155), respectively. The age of the patient, menstrual status, tumor location, tumor size, pathological type, preoperative biopsy and neoadjuvant chemotherapy were unrelated to the success of lymphoscintigraphy (P>0.05). 99mTc-DX lymphoscintigraphy is able to exactly determine the location of SLN in breast cancer patients, and can be used for guiding γ-probe methods and sentinel lymph node biopsy.