The root bark of Dictamnus dasycarpus Turcz is a traditional Chinese medicine, Dictamni Cortex (DC), which is mainly used in the clinical treatment of skin inflammation, eczema, rubella, rheumatism, and gynecological inflammation. Unexpectedly, there are some cases of liver injury after the administration of DC. However, the mechanism of hepatotoxicity remains ambiguous. The aim of this study was to explore the mechanism and substance bases of DC hepatotoxicity based on network pharmacology and molecular docking, verified through pharmacological experiments. Partial prototype components and metabolites in vivo of quinoline alkaloids from DC were selected as candidate compounds, whose targets were collected from databases. Network pharmacology was applied to study the potential hepatotoxic mechanism after correlating the targets of candidate compounds with the targets of hepatotoxicity. Molecular docking was simulated to uncover the molecular mechanism. Furthermore, the hepatotoxicity of the extract and its constituents from DC was evaluated in vivo and in vitro. We constructed the “potential toxic components-toxic target-toxic pathway” network. Our results showed that the targets of DC included CYP1A2 and GSR, participating in heterologous steroid metabolism, REDOX metabolism, drug metabolism, heterocyclic metabolic processes, the synthesis of steroid hormone, cytochrome P450 metabolism, chemical carcinogens and bile secretion pathways. In vitro and in vivo experiments displayed that DC could result in a decrease in GSH-Px and oxidative stress, simultaneously inhibiting the expression of CYP1A2 and inducing hepatotoxicity. These results further indicated the mechanism of hepatotoxicity induced by Dictamnus dasycarpus, providing a basic theory to explore and prevent hepatotoxicity in the clinical usage of Dictamnus dasycarpus.

The gut microbiota plays a vital role in the progression of heart failure (HF), making it a potential strategy for treating HF. The Bacteroides genus has shown promising potential for treating HF. However, further research is needed to identify specific beneficial Bacteroides strains for treating HF and elucidate their potential mechanisms. This study aimed to elucidate the therapeutic effect and mechanism of Bacteroides strain on HF. This study comprehensively used pharmacological evaluation, 16S rRNA genetic sequencing, short-chain fatty acid (SCFA) targeted metabolomics, transcriptome, and molecular biology methods to investigate the efficacy and mechanism of Bacteroides vulgatus (B. vulgatus) in the treatment of HF. We observed a significant decrease in the abundance of B. vulgatus in both HF patients and mice, and dysbiosis of the gut microbiota could cause cardiac dysfunction in mice. The administration of B. vulgatus to mice with HF significantly improved their cardiac function and significantly increased the levels of SCFAs, especially butyric acid. Meanwhile, we also observed a significant reduction in the level of butyric acid in the serum of HF patients, and the cardiac function of HF mice improved after the administration of butyric acid. Compared to patients with higher butyric acid level, patients with lower butyric acid level had a significantly increased incidence of endpoint events. Moreover, the transcriptome results revealed that B. vulgatus significantly regulated the mitogen-activated protein kinase (MAPK) pathway. After further molecular biology verification, B. vulgatus was confirmed to regulate the transforming growth factor-β1 (TGF-β1)/MAPK pathway in the heart through butyric acid, thereby exerting anti-HF effects. This study provides evidence that B. vulgatus improves heart function by regulating SCFA metabolism and subsequently modulating the TGF-β1/MAPK pathway in myocardial tissue, confirming the potential therapeutic role of B. vulgatus in HF.

Polyunsaturated fatty acid‐derived oxylipins regulate systemic inflammation and exert cardiovascular effects, yet their role in ST‐segment elevation myocardial infarction (STEMI) remains unclear. Herein, we used targeted metabolomics and machine learning algorithms to develop an oxylipin‐based risk model to accurately predict recurrent major adverse cardiovascular events (MACE) after STEMI in two independent prospective cohorts with 2 years of follow‐up. The in vivo effects of significant oxylipin predictors were explored via a murine myocardial ischemia‒reperfusion model and functional metabolomics. Among the 130 plasma oxylipins detected in discovery cohort (n = 645), patients with and without recurrent MACE exhibited significant differences in a variety of oxylipin subclasses. We constructed an oxylipin‐based prediction model that showed powerful performance in predicting recurrent MACE in the discovery cohort (predictive accuracy: 91.5%). The predictive value of the oxylipin marker panel was confirmed in an independent external validation cohort (predictive accuracy: 89.9%; n = 401). Furthermore, we found that the anti‐inflammatory/pro‐resolving oxylipin (ARO) predictor panel showed better prognostic performance than the pro‐inflammatory oxylipin predictor panel in both cohorts. Compared with the treatment of pro‐inflammatory oxylipin predictor panel, combined treatment of six ARO predictors, including 14,15 epoxy‐eicosatrienoic acid, 14(15)‐epoxy‐eicosatetraenoic acid, 12,13‐epoxy‐octadecenoic acid, lipoxin A4, resolving D1, and 6 keto‐prostaglandin F1 showed significant cardiac activities and synergistic metabolic actions in myocardial infarction‒reperfusion model mice. We also mechanistically identified an important role of ARO predictors in restraining ceramide/lysophosphatidylcholine synthesis and inhibiting inflammatory responses. Overall, the present study depicted the landscape of oxylipin profiles in the largest panel of STEMI patients worldwide. Our results also highlight the great potential of bioactive oxylipins in prognostic prediction and therapeutics after STEMI.

A rapid and real-time method was established based on the combination of rapid evaporative ionization mass spectrometry (REIMS) and two-dimensional liquid chromatography mass spectrometry (2DLC-MS) for identification of wild Astragali Radix (WAR) and cultivated AR (CAR). The samples were analyzed under ambient ionization without time-consuming sample preparation. The phenotypic data of WAR and CAR were used to develop a real-time recognition model. Subsequently, the compounds in these two species were comprehensively characterized based on 2DLC-MS, and 45 different compounds were screened out by multivariate statistical analysis. A semi-quantitative method for 45 different compounds was established based on ultrahigh-performance liquid chromatography/quadrupole-linear ion trap mass spectrometry (UHPLC-QTRAP-MS). The results showed that the relative content of most compounds in WAR was higher than in CAR. In summary, the method has demonstrated remarkable performance in distinguishing between WAR and CAR, providing a reference in the field of traditional Chinese medicine (TCM) analysis and identification.