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To solve the problem of inaccurate prediction caused by the lack of representativeness of samples due to the small sample size of the collected clinical data when using machine learning methods to predict drug concentration in plasma and describe the hysteresis phenomenon of drug effect lagging behind plasma drug concentration, this paper proposes a pharmacokinetic-pharmacodynamic (PK-PD) model based on the SSA-1DCNN-Attention network and the semicompartment method. First, a one-dimensional convolutional neural network (1DCNN) is established, and the attention mechanism is introduced to determine the importance of each physiological and biochemical parameter. The sparrow search algorithm (SSA) is used to optimize the parameters of the network to improve the prediction accuracy after data enhancement through the synthetic minority oversampling technique (SMOTE) method. After constructing the time-concentration relationship of the drug through the SSA-1DCNN-Attention network, the concentration-effect relationship of the drug is established by using the semicompartment method to synchronize the drug effect with the concentration. At last, the phenobarbital (PHB) combined with Cynanchum otophyllum saponins to treat epilepsy was taken as an example to validate the proposed method.

From the Cynanchum wilfordii roots, 32 compounds, including 5 previously undescribed (1, 4-6, 12) and 27 known (2, 3, 7-11, 13-32) compounds, were isolated, and their structures were elucidated using NMR spectroscopic data and MS data aided by ECD calculations or the modified Mosher's reaction. All isolates were tested for their inhibitory effects on proprotein convertase subtilisin/kexin type 9 (PCSK9) secretion. Among the isolates, compound 4, a methyl cholesterol analog, exhibited the most potent effect in reducing PCSK9 secretion, along with PCSK9 downregulation at the mRNA and protein levels via FOXO1/3 upregulation. Moreover, compound 4 attenuated statin-induced PCSK9 expression and enhanced the uptake of DiI-LDL low-density lipoprotein. Thus, compound 4 is suggested to be a potential candidate for controlling cholesterol levels., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Objective: To explore the targets and pathways of Cynanchum wilfordii for treatment of ulcerative colitis (UC)., Methods: UPLC-QE-MS was used to identify the components of Cynanchum wilfordii ethanol extract, and their targets were screened using public databases for construction of the core protein-protein interaction (PPI) network and GO and KEGG enrichment analyses. Forty male C57 mice were randomized into normal control group, model group, mesalazine group and Cynanchum wilfordii group ( n =10), and in the latter 3 groups, mouse UC models were established by treatment with 2.5% DSS and the latter 2 groups drug interventions by gavage. The therapeutic effect was evaluated by recording body weight changes and DAI score. Pathological changes of the colon tissue were observed with HE and AB-PAS staining, and JAK2 and STAT3 protein expressions were detected with Western blotting. The metabolites and metabolic pathways were identified by metabonomics analysis., Results: We identified 240 chemical components in Cynanchum wilfordii alcoholic extracts, including 19 steroids. A total of 177 Cynanchum wilfordii targets, 5406 UC genes, and 117 intersection genes were obtained. JAK2 and STAT3 were the core targets and significantly enriched in lipid and atherosclerosis pathways. Cynanchum wilfordii treatment significantly increased the body weight and decreased DAI score of UC mice ( P < 0.05), alleviated intestinal pathologies, and decreased JAK2 and STAT3 protein expressions in the colon tissues. Most of the 83 intersecting differential metabolites between the control, model and Cynanchum wilfordii groups were identified as glycerophospholipids, arachidonic acid, and amino acids involving glycerophospholipid metabolism and other pathways. Correlation analysis suggested that the core targets of Cynanchum wilfordii for UC participated in regulation of the metabolites., Conclusion: Cynanchum wilfordii alleviates lipid and amino acid metabolism disorders to lessen UC in mice by regulating the core targets including JAK2 and STAT3 and the levels of endogenous metabolites.