Vancomycin Induced Ferroptosis in Renal Injury Through the Inactivation of Recombinant Glutathione Peroxidase 4 and the Accumulation of Peroxides

Therapeutic effects of natural compounds against diabetic complications via targeted modulation of ferroptosis

Diabetes mellitus, a chronic metabolic disorder, can result in serious tissue and organ damage due to long-term metabolic dysfunction, leading to various complications. Therefore, exploring the pathogenesis of diabetic complications and developing effective prevention and treatment drugs is crucial. The role of ferroptosis in diabetic complications has emerged as a significant area of research in recent years. Ferroptosis, a recently discovered form of regulated cell death closely linked to iron metabolism imbalance and lipid peroxidation, has garnered increasing attention in studies exploring the potential role of natural products in its regulation. This review provides an overview of the mechanisms underlying ferroptosis, outlines detection methods, and synthesizes information from natural product databases. It also summarizes current research on how natural products may regulate ferroptosis in diabetic complications. Studies have shown that these products can modulate the ferroptosis process by influencing iron ion balance and combating oxidative stress. This highlights the potential of natural products in treating diabetic complications by regulating ferroptosis, offering a new strategy for managing such complications.

The multifaceted mechanisms of Dihydrotanshinone I in the treatment of tumors

The morbidity and mortality of malignant tumors are progressively rising on an annual basis. Traditional Chinese Medicine (TCM) holds promise as a possible therapeutic agent for the avoidance or therapy of malignant tumors. Salvia miltiorrhiza Bunge (Danshen), a traditional Asian functional food, has therapeutic characteristics in application for the treatment of malignant tumors. Dihydrotanshinone I (DHTS) is the principal lipophilic phenanthraquinone compound found in Salvia miltiorrhiza Bunge, whose anti-tumor effect has attracted widespread attention. The anti-tumor effects include inhibiting cancer cell proliferation, triggering apoptosis of tumor cells, inducing ferroptosis in tumor cells, inhibiting tumor cell invasion and metastasis, and improving drug resistance of tumor cells. In this paper, we summarized and analyzed the mechanisms and targets of anti-tumor effect of DHTS, providing new ideas and establishing a solid theoretical basis for the future advancement and clinical treatment of DHTS.

Leonurine alleviates vancomycin nephrotoxicity via activating PPARγ and inhibiting the TLR4/NF-κB/TNF-α pathway

Vancomycin (VCM) is the first-line antibiotic for severe infections, but nephrotoxicity limits its use. Leonurine (Leo) has shown protective effects against kidney damage. However, the effect and mechanism of Leo on VCM nephrotoxicity remain unclear. In this study, mice and HK-2 cells exposed to VCM were treated with Leo. Biochemical and pathological analysis and fluorescence probe methods were performed to examine the role of Leo in VCM nephrotoxicity. Immunohistochemistry, q-PCR, western blot, FACS, and Autodock software were used to verify the mechanism. The present results indicate that Leo significantly alleviates VCM-induced renal injury, morphological damage, and oxidative stress. Increased intracellular and mitochondrial ROS in HK-2 cells and decreased mitochondrial numbers in mouse renal tubular epithelial cells were reversed in Leo-administrated groups. In addition, molecular docking analysis using Autodock software revealed that Leo binds to the PPARγ protein with high affinity. Mechanistic exploration indicated that Leo inhibited VCM nephrotoxicity via activating PPARγ and inhibiting the TLR4/NF-κB/TNF-α inflammation pathway. Taken together, our results indicate that the PPARγ inhibition and inflammation reactions were implicated in the VCM nephrotoxicity and provide a promising therapeutic strategy for renal injury.

Perioperative acute kidney injury: The renoprotective effect and mechanism of dexmedetomidine

Dexmedetomidine (DEX) is a highly selective and potent α2-adrenoceptor (α2-AR) agonist that is widely used as a clinical anesthetic to induce anxiolytic, sedative, and analgesic effects. In recent years, a growing body of evidence has demonstrated that DEX protects against acute kidney injury (AKI) caused by sepsis, drugs, surgery, and ischemia-reperfusion (I/R) in organs or tissues, indicating its potential role in the prevention and treatment of AKI. In this review, we summarized the evidence of the renoprotective effects of DEX on different models of AKI and explored the mechanism. We found that the renoprotective effects of DEX mainly involved antisympathetic effects, reducing inflammatory reactions and oxidative stress, reducing apoptosis, increasing autophagy, reducing ferroptosis, protecting renal tubular epithelial cells (RTECs), and inhibiting renal fibrosis. Thus, the use of DEX is a promising strategy for the management and treatment of perioperative AKI. The aim of this review is to further clarify the renoprotective mechanism of DEX to provide a theoretical basis for its use in basic research in various AKI models, clinical management, and the treatment of perioperative AKI.

Prediction of Acute Kidney Injury in Intracerebral Hemorrhage Patients Using Machine Learning

Background

Acute kidney injury (AKI) is prevalent in patients with intracerebral hemorrhage (ICH) and is associated with mortality. This study aimed to verify the predictive accuracy of different machine learning algorithms for AKI in patients with ICH using a large dataset.

Methods

A total of 1366 ICH patients received treatments between 2001 and 2012 from the Medical Information Mart for Intensive Care-III (MIMIC-III) database were identified based on the ICD-9 code: 431. The main outcome of AKI during hospitalizations was confirmed based on the KDIGO criteria. Overall, ICH patients were randomly divided into the training cohort and validation cohort with the ratio of 7:3. Six machine learning algorithms including extreme gradient boosting, logistic, light gradient boosting machine, random forest, adaptive boosting, support vector machine were trained in the training cohort with the 5-fold cross-validation method to predict the AKI. The predictive accuracy of those algorithms was compared by area under the receiver operating characteristics curve (AUC).

Results

A total of 1213 ICH patients were included with the incidence of AKI being 29.3%. The incidence of AKI was 29.3% among the 1213 patients with ICH. The AKI group had higher 30-day mortality (p<0.001), longer ICU stay (p<0.001), and longer hospital stay (p<0.001). Among the six machine learning algorithms, the random forest performed the best in predicting AKI in both the training cohort (AUC=1.000) and the validation cohort (AUC=0.698). The top five features in the random forest algorithm-based model were platelets, serum creatinine, vancomycin, hemoglobin, and hematocrit.

Conclusion

The random forest algorithm-based predictive model we developed incorporating important features, including platelet count, serum creatinine level, vancomycin level, hemoglobin level, and hematocrit level, performed the best in predicting AKI among patients with ICH.

The Emerging Roles of Ferroptosis in Neonatal Diseases

Ferroptosis is a novel type of programmed cell death involved in many diseases' pathological processes. Ferroptosis is characterized by lipid peroxidation, reactive oxygen species accumulation, and iron metabolism disorder. Newborns are susceptible to ferroptosis due to their special physiological state, which is prone to abnormal iron metabolism and the accumulation of reactive oxygen species. Recent studies have linked ferroptosis to a variety of diseases in the neonatal period (including hypoxic-ischemic encephalopathy, bronchopulmonary dysplasia, and necrotizing enterocolitis). Ferroptosis may become an effective target for the treatment of neonatal-related diseases. In this review, the ferroptosis molecular mechanism, metabolism characteristics of iron and reactive oxygen species in infants, the relationship between ferroptosis and common infant disorders, and the treatment of infant diseases targeted for ferroptosis are systematically summarized.