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Tripterygium Glycosides Tablets (TGT) has shown obvious anti-rheumatoid arthritis (RA) effects accompanied by hepatotoxicity. Despite that many studies looked at TGT's anti-RA or hepatotoxic mechanism and substance basis, the results were still insufficient. Furthermore, the anti-RA and hepatotoxicity investigations of TGT were undertaken separately, neglecting the relationship between efficacy and toxicity. Herein, an integrated approach combining metabolomics, network pharmacology, serum pharmacochemistry, and molecular docking was adopted to elucidate the mechanism and substance basis of Tripterygium Glycosides Tablets (TGT) on anti-rheumatoid arthritis and hepatotoxicity simultaneously. The results showed that 33 components in TGT were absorbed into rat serum. Two toxic targets (PRKCA, FASN), three effective targets (PLA2G10, PTGES, PLA2G1B), and four effective and toxic targets (PTGS1, PTGS2, PLA2G2A, ALOX5) were obtained by metabolomics combined with network analysis and network pharmacology. A component-target-RA-hepatotoxicity network was constructed and five hepatotoxic components (1-desacetylwilforgine, wilfordconine, wilforgine, wilformine, wilfornine D), eight effective-toxic components (14-oxo-19-(4 → 3) abeo-abieta-3,8,12-tetraen-19,18-olide, 7-oxo-18(4 → 3) abeo-abieta-3,8,11,13-tetraen-18-oic acid, hypoglaulide, triptotriterpenic acid A, wilforol F, wilforlide B, triptoquinone B, wilforlide A); and 23 non-effective and non-toxic components were acquired and validated by molecular docking. In addition, our research revealed that glycerophospholipid metabolism and ether lipid metabolism were correlated to both hepatotoxicity and anti-RA of TGT. While in sphingolipid metabolism, ceramidases regulated ceramide-sphingosine and phytoceramide-phytosphingosine reaction were found to be correlated to hepatotoxicity, sphinganine-1-phosphate lyase (SPL) regulated sphingosine 1-phosphate (S1P)-phosphoethanolamine and sphinganine 1-phosphate-phosphoethanolamine were found to be attributed to anti-RA effects.

Background Surgical resection remains the only potentially curative treatment for pancreatic ductal adenocarcinoma (PDAC). However, a number of patients get disease recurred in a short time post-operation. Few studies have focused on the predictors of different recurrence patterns of PDAC. Objective To try to establish and verify a nomogram to predict recurrence free survival (RFS) in PDAC patients, and to distinguish the risk factors of local recurrence first and distant metastasis first via competing risk model. Methods Patients who underwent radical pancreatectomy for PDAC in our center from 2010 to 2018 were reviewed retrospectively. Kaplan-Meier methods and multivariate Cox regression analyses were used to identify the clinicopathological predictors of recurrence post-operation. And then, a nomogram was constructed and validated. Competing risk regression model was used to compare the predictors between local recurrence group and distant metastasis group. Results A total of 200 patients were included into the final analysis, and 153 patients got disease relapsed post-operation. CA19-9 level, vascular resection, tumor differentiation, lymph node ratio (LNR) and adjuvant chemotherapy were identified as independent risk factors for recurrence free survival (RFS) and incorporated into the nomogram. The C-index of the nomogram was 0.650. Competing risk model indicated that the status of lymph-node metastasis was significantly associated the patterns of first relapse. Conclusions Nomogram and competing risk model were constructed to quantify the risk of recurrence following surgery for PDAC. Our findings may be useful for predicting RFS and recurrence pattern in clinical work.

With increasing requirements of replacing the high-cost and unstable natural enzymes, the rational design of highly efficient inorganic mimetic enzymes (nanozymes), as one of the most important bioactive materials, has attracted more and more attention in recent years. In our work, using the solvent evaporation induced co-assembly strategy with high-molecular weight poly(ethylene oxide)-block-polystyrene (PEO-b-PS) diblock copolymer as the template and two metal salts as the co-precursors in one-pot system, we synthesized ordered mesoporous heteroatom-doped CeO2 with high surface area, bimodal pore sizes and highly crystallized walls. The composite materials were then constructed as the mimetic enzymes to investigate their peroxidase-like catalytic performance and detect H2O2 and glucose as bioactive materials in diverse systems including complex biological samples. It was demonstrated that mesoporous 5%CoO/CeO2 catalyst was the best peroxidase mimic, following the typical Michaelis–Menten kinetics and exhibiting the excellent peroxidase-like catalytic performance toward 3,3′,5,5′-tetramethylbenzidine (TMB) with comparable Km and Vm values to horseradish peroxidase (HRP) enzyme. A highly sensitive and selective colorimetric assay was developed to detect H2O2 and glucose with detection limits of 0.88 and 19.6 μM, respectively. The promising catalytic behavior of mesoporous 5%CoO/CeO2 as the peroxidase-like bioactive catalyst could be ascribed to its interconnected large mesopores, rich exposed surface defects and oxygen vacancies introduced by the heterojunction interface of ultrasmall CeO2 and CoO nanocrystals within pore walls.

As a classical formula of traditional Chinese medicine (TCM), Lingguizhugan Decoction (LGZGD) has been used for treating heart failure (HF) because it has an efficiency of yang-warming and fluid-dispersing. However, the pharmacodynamic material basis of LGZGD responsible for the therapeutic benefits is not well understood.The aim of this study was to elucidate the pharmacodynamic material basis of LGZGD by an integrated approach.Following oral administration of LGZGD in mice, ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS/MS) was used to identify prototype substances. A heart failure (HF) model was established, followed by an untargeted metabolomics study to determine potential targets of LGZGD. The network pharmacology method was performed to screen substances that interacted with potential targets of LGZGD treating HF. Molecular docking technology was applied to further screen substances based on binding energy. Cell viability assays were conducted to verify pharmacodynamic effects of selected substances.In all, forty-two prototype substances were identified in the blood, urine, and fecal samples of mice. A total of fifty-five differential metabolites were identified using heart tissue untargeted metabolomics. Twenty-five substances of LGZGD were screened relating to thirty-three targets treating HF. Twenty-two substances were filtered according to their binding energy using molecular docking technology. Cell experiments revealed cinnamaldehyde, glycyrrhetinic acid, kaempferol, daidzein, caffeic acid, and catechin could significantly improve the survival rate of H9c2 cells, which might be the pharmacodynamic material basis of LGZGD.A scientific approach that integrated in vivo substances identification, metabolomics, network pharmacology, molecular docking, and cell pharmacodynamic assay has been developed to study the pharmacodynamic material basis of LGZGD in the treatment of HF.

Background Surgical resection is the only potentially curative treatment for pancreatic ductal adenocarcinoma (PDAC). However, most of patients lose the chance of surgery due to the unresectable disease at the time of diagnosis. Despite the improvement of radiological imaging, a portion of patients intended for radical resection were proven to be unresectable at surgical exploration due to occult metastasis. Methods Patients who were aimed to undergo radical pancreatectomy for PDAC from 2010 to 2019 were reviewed retrospectively. All patients included underwent diagnostic laparoscopic exploration. Patients were divided into two groups depending on whether distant metastasis were encountered during exploration. Univariate and multivariate logistic regression analyses were used to identify risk factors for occult metastasis. A nomogram to predict occult metastasis of PDAC on exploration was developed and evaluated. Results A total of 273 patients who underwent diagnostic laparoscopic exploration were included in this study. Nineteen (7.0%) patients were found with distant metastasis during exploration. Multivariate logistic regression analysis showed that ALT>40U/L, CA19-9, CA125 and regional nodes enlargement were independent predictors for occult metastasis. Incorporating these four factors, the nomogram achieved concordance index of 0.799, with a well-fitted calibration curve. Conclusions Occult metastasis is not unusual during surgical exploration in patients with resectable or borderline resectable PDAC. The nomogram could achieve a personal prediction of unexpected distant metastasis on exploration. It may help to sift through patients with PDAC who would benefit from laparoscopic exploration.