Exploring the Potential Toxicological Mechanisms of Vine Tea on the Liver Based on Network Toxicology and Transcriptomics

Arecoline-Induced Hepatotoxicity in Rats: Screening of Abnormal Metabolic Markers and Potential Mechanisms

Arecoline is a pyridine alkaloid derived from areca nut in the Arecaceae family. It has extensive medicinal activity, such as analgesic, anti-inflammatory, and anti-allergic. However, the toxicity of Arecoline limits its application. Most current studies on its toxicity mainly focus on immunotoxicity, carcinogenesis, and cancer promotion. However, there are few systematic studies on its hepatotoxicity and mechanisms. Therefore, this research explored the mechanism of hepatotoxicity induced by Arecoline in rats and analyzed endogenous metabolite changes in rat plasma by combining network toxicology with metabolomics. The differential metabolites after Arecoline exposure, such as D-Lysine, N4-Acetylaminobutanal, and L-Arginine, were obtained by metabolomics study, and these differential metabolites were involved in the regulation of lipid metabolism, amino acid metabolism, and vitamin metabolism. Based on the strategy of network toxicology, Arecoline can affect the HIF-1 signaling pathway, MAPK signaling pathway, PI3K-Akt signaling pathway, and other concerning pathways by regulating critical targets, such as ALB, CASP3, EGFR, and MMP9. Integration of metabolomics and network toxicology results were further analyzed, and it was concluded that Arecoline may induce hepatotoxicity by mediating oxidative stress, inflammatory response, energy and lipid metabolism, and cell apoptosis.

Exploring the Mechanism of Action of Trachelospermi Caulis et Folium for Depression Based on Experiments: Combining Network Pharmacology and Molecular Docking

Objective

To reveal the safety, efficacy, and mechanism of action of Trachelospermi Caulis et Folium (TCEF) for treating depression.

Methods

The maximum dose method was employed to evaluate the safety of TCEF, and its antidepressant activity was assessed using the tail suspension and sugar water depletion tests. The main components of TCEF were determined using ultrahigh performance liquid chromatography coupled with quadrupole exactive orbitrap mass spectrometer (UHPLC-Q-EOMS). The active ingredients and their action targets were obtained using network pharmacology with SwissADME and SwissTargetPrediction screening, and the targets of depression were obtained using GeneCards, DrugBank, etc. The drug and depression-related targets were intersected and analyzed via PPI network, GO, and KEGG. Subsequently, the binding ability of the core components of TCEF to the core targets was validated via molecular docking and simulation.

Results

No statistically significant difference was observed between the normal and TCEF groups in terms of body weight, visceral index, and biochemical parameters (P > 0.05). Compared with the model group, all dose groups of TCEF had reduced the immobility time of tail suspension (P < 0.05) and increased the rate of sugar water consumption (P < 0.05). UHPLC-Q-EOMS was employed to identify 59 major components of TCEF, and network pharmacology analysis was used to screen 48 active components of TCEF for treating depression, corresponding to 139 relevant targets, including ALB, AKT1, TNF, ESR1, and CTNNB1. The involved pathways include neuroactive ligand-receptor interaction. The molecular docking results indicated that the core components have a good binding activity to the core targets.

Conclusions

TCEF is a relatively safe antidepressant medicine that exerts therapeutic effects through multiple components, targets, and pathways, providing a new idea and theoretical basis for future use of TCEF to treat depression.

Study on the Mechanism of Mesaconitine-Induced Hepatotoxicity in Rats Based on Metabonomics and Toxicology Network

Mesaconitine (MA), one of the main diterpenoid alkaloids in Aconitum, has a variety of pharmacological effects, such as analgesia, anti-inflammation and relaxation of rat aorta. However, MA is a highly toxic ingredient. At present, studies on its toxicity are mainly focused on the heart and central nervous system, and there are few reports on the hepatotoxic mechanism of MA. Therefore, we evaluated the effects of MA administration on liver. SD rats were randomly divided into a normal saline (NS) group, a low-dose MA group (0.8 mg/kg/day) and a high-dose MA group (1.2 mg/kg/day). After 6 days of administration, the toxicity of MA on the liver was observed. Metabolomic and network toxicology methods were combined to explore the effect of MA on the liver of SD rats and the mechanism of hepatotoxicity in this study. Through metabonomics study, the differential metabolites of MA, such as L-phenylalanine, retinyl ester, L-proline and 5-hydroxyindole acetaldehyde, were obtained, which involved amino acid metabolism, vitamin metabolism, glucose metabolism and lipid metabolism. Based on network toxicological analysis, MA can affect HIF-1 signal pathway, MAPK signal pathway, PI3K-Akt signal pathway and FoxO signal pathway by regulating ALB, AKT1, CASP3, IL2 and other targets. Western blot results showed that protein expression of HMOX1, IL2 and caspase-3 in liver significantly increased after MA administration (p < 0.05). Combined with the results of metabonomics and network toxicology, it is suggested that MA may induce hepatotoxicity by activating oxidative stress, initiating inflammatory reaction and inducing apoptosis.

Study on the Potential Mechanism of Tonifying Kidney and Removing Dampness Formula in the Treatment of Postmenopausal Dyslipidemia Based on Network Pharmacology, Molecular Docking and Experimental Evidence

BACKGROUND

Management of menopausal dyslipidemia is the main measure to reduce the incidence of cardiovascular disease in postmenopausal women. Tonifying Kidney and Removing Dampness Formula (TKRDF) is a traditional Chinese medicine (TCM) formula that ameliorates dyslipidemia in postmenopausal women. This study applied network pharmacology, molecular docking, and in vitro and in vitro experiments to investigate the underlying mechanism of TKRDF against postmenopausal dyslipidemia.

METHODS

Network pharmacology research was first conducted, and the active compounds and targets of TKRDF, as well as the targets of postmenopausal dyslipidemia, were extracted from public databases. Protein-protein interaction (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to identify the potential targets and signaling pathways of TKRDF in postmenopausal dyslipidemia. Molecular docking was then performed to evaluate the combination of active compounds with principal targets. Finally, an ovariectomized rat model was used for the in vivo experiment and alpha mouse liver 12 (AML12) cells treated with palmitic acid were used for the in vitro experiments to provide further evidence for the research.

RESULTS

Based on network pharmacology analysis, we obtained 78 active compounds from TKRDF that acted on 222 targets of postmenopausal dyslipidemia. The analysis results indicated that IL6, TNF, VEGFA, AKT1, MAPK3, MAPK1, PPARG and PIK3CA, etc., were the potentially key targets, and the PI3K/AKT signaling pathway was the possibly crucial pathway for TKRDF to treat postmenopausal dyslipidemia. Molecular docking suggested that the active compounds have good binding activity with the core targets. The in vivo and in vitro experiments demonstrated that TKRDF ameliorates postmenopausal dyslipidemia by regulating hormone levels, inhibiting inflammation, promoting angiogenesis and inhibiting lipid synthesis, which appear to be related to TKRDF's regulation of the ERK1/2 and PI3K/AKT signaling pathways.

CONCLUSION

This study clarified the active ingredients, potential targets, and molecular mechanisms of TKRDF for treating postmenopausal dyslipidemia. It also provided a feasible method to uncover the scientific basis and therapeutic mechanism for prescribing TCM in the treatment of diseases.