Background. Lung metastasis of malignant tumor signifies worse prognosis and immensely deteriorates patients’ life quality. Spatholobi Caulis (SC) has been reported to reduce lung metastasis, but the mechanism remains elusive. Methods. The active components and corresponding targets of SC were obtained from the Traditional Chinese Medicine Database and Analysis Platform (TCMSP) database and the SwissTargetPrediction database. The disease targets were acquired from DisGeNET and GeneCards databases. Venn map was composed to figure out intersection targets by using R. The PPI network was constructed through STRING and Cytoscape, and MCODE plug-in was used to sift hub targets. Gene Ontology (GO)-Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was carried out by utilizing clusterProfiler package (R3.6.1) with adjusted value <0.05. Network of SC-active components-intersection targets-KEGG pathway was accomplished with Cytoscape. Molecular docking between hub targets and active components was performed, analyzed, and visualized by AutoDockTools, AutoDock Vina, PLIP Web tool, and PYMOL. Results. 24 active components and 123 corresponding targets were screened, and the number of disease targets and intersection targets was 1074 and 47, respectively. RELA, JUN, MAPK1, MAPK14, STAT3, IL-4, ESR1, and TP53 were the 8 hub targets. GO analysis and KEGG analysis elucidated that SC could ameliorate lung metastasis mainly by intervening oxidative stress, AGE-RAGE signaling pathway, and microRNAs in cancer. All 8 hub targets were proven to combine successfully with active components of SC. Conclusion. Inflammation is the core factor that integrates all these targets, biological process, and signaling pathways, which indicates that SC prevents or reduces lung metastasis mainly by dispelling inflammation.

Background: Acute kidney injury (AKI) is a serious disease with a high incidence and easy induction. The search for innovative biomarkers and treatment methods is of great significance for improving the prognosis of patients. Autophagy is closely related to the occurrence and development of AKI. This study aims to explore the role of autophagy-related genes (ARGs) as potential biomarkers and therapeutic targets in AKI. Methods: In this study, the gene microarray data of the GEO dataset were used to explore the molecular profile of AKI, and three machine learning algorithms were used to screen autophagy-related feature genes. To further validate the reliability of the screening results, we constructed a cisplatin-induced AKI rat model to validate potential biomarkers of machine learning screening. Results: Machine learning analysis identified 17 differentially expressed ARGs and selected the core genes FIZ1 and FBXO21, with area under curve (AUC) values both exceeding 0.7 (95% CI [0.706–0.899]). Immune analysis revealed that the number of Mast cells resting significantly decreased in AKI samples compared to normal samples ( P < 0.05). Electron microscopy observations of the cisplatin-induced AKI rat model indicated thickening of the basement membrane, fusion of foot processes, and swelling and rupture of mitochondria in the model group, suggesting a correlation between AKI and mitochondrial autophagy; Western blot results indicated a significant increase in the expression of FIZ1 and a significant decrease in FBXO21 in the AKI group ( P < 0.01). The results of IHC staining were also consistent with those of Western blot results. Conclusion: This study highlights the significant role of ARGs in AKI and identifies FIZ1 and FBXO21 as promising biomarkers with high diagnostic potential, offering new insights into the molecular mechanisms underlying AKI.

Context: The mechanism of Yiqi–Wenyang–Tiaoshen decoction (YWT) in treating cisplatin‐induced acute kidney injury (AKI) remains unknown. Objective: This study identifies the key components of YWT and explores its therapeutic potential and mechanisms in a cisplatin‐induced AKI rat model. Materials and Methods: UPLC‐ESI‐MS/MS was utilized for the identification of compounds present in both the aqueous extract of YWT and serum samples. The overlapping components were recognized as active constituents, followed by a network pharmacological analysis. A rat model of cisplatin‐induced AKI was established, and comprehensive pathological analyses including HE, PAS, and electron microscopy, as well as biochemical assessments of serum Cre, BUN, IL‐6, and TNF‐α levels, were conducted. Western blotting was utilized to evaluate the expression levels of Caspase‐3, Caspase‐9, BAX, Bcl‐2, and LC3 Ⅱ/Ⅰ. Results: Using UPLC‐ESI‐MS/MS, we identified 182 compounds in the aqueous extract of YWT, 34 of which are confirmed to be absorbable into the bloodstream. Network pharmacological analysis suggests that YWT primarily acts by inhibiting apoptosis and activating autophagy. In the rat model, YWT significantly ameliorated renal pathology and electron microscopic features. Additionally, YWT mitigated body weight loss and renal hypertrophy while lowering serum creatinine and blood urea nitrogen levels. YWT alleviates AKI by suppressing apoptosis‐related proteins such as Caspase‐3, Caspase‐9, and BAX, enhancing Bcl‐2 expression, increasing the LC3 Ⅱ/Ⅰ ratio, and reducing p62, a marker of autophagy. Discussion and Conclusion: This study confirms the therapeutic efficacy of YWT in cisplatin‐induced AKI, potentially linked to its ability to inhibit apoptosis, activate autophagy, and mitigate mitochondrial damage.